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1

Pace Transit

Signal Priority (TSP)

Initiative

Evaluation Report

for the

Harvey Area TSP Demonstration

Project

Prepared for

Prepared by

March, 2012

i

Table of Contents

EVALUATION HIGHLIGHTS ..……………………………………………………………....ii

SUMMARY ................................................................................................................................... ii

What is the purpose of this document? .................................................................................. iii

TSP 101: What is TSP and how does it work? ...................................................................... iii

What is the Pace Transit Signal Priority (TSP) Initiative?................................................ viii

What are the Goals and Objectives of the Harvey Area TSP Demonstration Project? .... ix

How do the Pace TSP Initiative and the Harvey Area TSP Demonstration Project align

with efforts to improve transit service throughout the Chicago metropolitan area? ........ xi

What do I need to know about the Harvey Area TSP Demonstration Project? .............. xii

What have we learned from the Harvey Area TSP Demonstration Project, and what are

the key findings? ..................................................................................................................... xv

1.0 INTRODUCTION.......................................................................................................... - 1 -

1.1 Report Organization ...................................................................................................... - 1 -

1.2 Background .................................................................................................................... - 1 -

1.3 Task 2 Demonstration Project Area ............................................................................. - 3 -

1.4 Harvey Area TSP Demonstration Project – Traffic Signal Timing Improvements - 5 -

1.5 Goals and Objectives ..................................................................................................... - 5 -

2.0 QUANTITATIVE EVALUATION METHODOLOGY ............................................ - 9 -

2.1 Measures of Effectiveness.............................................................................................. - 9 -

2.2 Data Collection ............................................................................................................. - 10 -

2.3 Analysis Methods ......................................................................................................... - 15 -

3.0 QUANTITATIVE EVALUATION RESULTS ......................................................... - 16 -

3.1 Comparison of Before (Existing) and After (TSP On) Conditions.......................... - 16 -

3.1.1 Transit Mobility ...................................................................................................... - 16 -

3.1.2 Transit Reliability ................................................................................................... - 16 -

3.2 Signal Optimization Results ........................................................................................ - 19 -


3.2.2 Transit Reliability ................................................................................................... - 20 -

3.2.3 General Traffic Mobility ......................................................................................... - 21 -

3.3 TSP Implementation Results ...................................................................................... - 22 -


4.0 QUALITATIVE EVALUATION MEASURES ........................................................ - 40 -

4.1 Experiences and Lessons Learned in TSP System Deployment .............................. - 40 -

4.1.1 TSP System Planning and Design........................................................................... - 40 -

4.1.2 TSP System Deployment ........................................................................................ - 42 -

4.2 Institutional Considerations ........................................................................................ - 42 -

4.3 Other Factors that Impact TSP Benefits ................................................................... - 44 -

5.0 KEY FINDINGS and NEXT STEPS.......................................................................... - 47 -

5.1 Key Findings ................................................................................................................. - 47 -

5.2 Next Steps ..................................................................................................................... - 47 -

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Harvey Area TSP Demonstration Project Evaluation

Highlights

The Harvey Area TSP Demonstration Project (Phase 1) was successfully implemented and tested

in 2010 along Pace bus routes 350, 352 and 364, operating on Sibley Boulevard, Halsted Street,

and 159th

Street, respectively, realized significant benefits as detailed below. Not only did Pace

reduce its costs by reducing delays, but Pace riders saw a reduction in travel time and were more

often on time. Pace equipped 20 intersections and 55 buses with TSP equipment, and a TSP

Central Management System was established at Pace headquarters.

The following are some key benefits found during the Harvey TSP Demonstration Project

Deployment:

• Bus Travel times were reduced up to 15% (by a range of 25 seconds to 3.3 minutes).

• Cumulative Daily Delay for buses was reduced by 27 minutes at TSP- equipped

intersections during AM and PM Peak Periods.

• Average travel time for all traffic was reduced by as much as 6 minutes during peak

hours.

• The number of stops made by buses at signalized intersections with TSP at a

corridor level was reduced by a range of 3 to a maximum of 13 on a directional basis

by route.

In conclusion, Harvey TSP Demonstration Project was successful both in terms of benefits to

Pace riders and technology implementation. Pace plans to start Phase 2 deployment of the project

by mid-year 2012 and begin subsequent region wide TSP deployment along major Arterial Rapid

Transit (ART) corridors.

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SUMMARY

What is the purpose of this document?

This document presents an evaluation of the Harvey Area Transit Signal Priority (TSP)

Demonstration Project, a component of the Pace TSP Initiative. The evaluation report includes

both qualitative and quantitative findings and emphasizes both the invaluable experience gained

by Pace during the process of planning, procuring, constructing, testing, and operating the TSP

system that has been deployed as part of the demonstration project as well as the measurable

benefits of improved schedule adherence and travel time savings.

TSP 101: What is TSP and how does it work?

TSP gives transit vehicles a little extra green time or a little less red time at signalized

intersections to reduce the time they are slowed down by traffic signals.

“TSP is an operational strategy that facilitates the movement of in-service transit vehicles, either

buses or streetcars, through traffic signal controlled intersections. [S]ignal priority modifies the

normal signal operation process to better accommodate transit vehicles…. [O]bjectives of TSP

include improved schedule adherence, improved transit efficiency, contribution to enhanced

transit information, and increased road network efficiency.1”

By reducing the time that transit vehicles spend delayed at intersection queues, TSP can reduce

transit delay and travel time and improve transit service reliability, thereby increasing transit

quality of service. It also has the potential for reducing overall delay at the intersection on a per-

person basis. At the same time, TSP attempts to provide these benefits with a minimum of

impact on other facility users, including cross-traffic and pedestrians.2”

Objectives of TSP

The objectives of TSP include3:

• Improved schedule adherence

• Reduced delay

• Improved transit efficiency

• Contribution to enhanced transit information

• Increased road network efficiency

Improving schedule adherence can reduce waiting time and passenger anxiety by lessening the

extent to which riders need to add additional time as a contingency (e.g., catching an earlier bus,

leaving for bus stop early) in order to arrive on time at their destination. Reduced delay—but not

iv

elimination of delay -- to transit vehicles can enhance transit efficiency as well as potentially

improve schedule adherence. TSP may also facilitate the provision of enhanced rider information

by enabling real-time detection information to be used for other purposes. Any resulting

increases in ridership and the higher occupancies on transit vehicles can also contribute to the

significance of reductions in transit vehicle delay. Since transit service is typically much more

frequent than rail or emergency vehicle service, use of priority rather than preemption allows the

system to maintain a higher level of performance.

Key Components of a TSP System4

The basic components of a TSP system are described in the following section. See Figure ES-1

for a simplified representation of how TSP works.

• Vehicle detection system – The vehicle detection system provides vehicle data (location,

arrival time, approach, etc.) to a Priority Request Generator (PRG). For the Pace Harvey

Area TSP Demonstration Project, satellite (GPS)-based vehicle detection is utilized; a

GPS antenna on board the bus provides location data to the PRG.

• Priority Request Generator (PRG) – Generates the request for TSP. The PRG is located

in the transit vehicle and communicates with the Priority Request Server (PRS) at the

local TSP-equipped intersections. Once a vehicle has been detected within a specified

vicinity of a TSP-equipped intersection, the PRG initiates requests for TSP based on

predefined criteria; in the case of the Pace TSP System, transit vehicles will only request

TSP when running behind schedule by more than 1 minute.

• Priority Request Server (PRS) – Receives request(s) for TSP from the PRG. Prioritizes

and processes the request(s) for TSP at the intersection based on predefined TSP criteria.

The PRS is located inside the traffic signal controller cabinet.

• Communications System – The communication system links the PRG, PRS, and other

components with one another. In the case of the Pace Harvey Area TSP Demonstration

Project, the PRGs on the buses and the PRSs at the TSP intersections communicate with

one another via a hardened (i.e. outdoor) Wi-Fi network, which was installed as part of

the project.

• TSP Traffic Signal Controller Strategies – A traffic signal controller software

enhancement that allows for “a little extra green time or a little less red time” while still

operating within requirements of the agency that has jurisdiction of the intersection.

• TSP Management System (optional) – Can configure settings, log events, and provide

reporting capabilities on the TSP system either locally or remotely via the

communications system.

v

Figure ES-1: TSP at Traffic Signals – A Simplified Representation5

The general steps involved in providing TSP are as follows:

1. The bus approaching the intersection is detected (“check-in”) at some point Pd upstream

of the intersection (various detection methods exist).

2. The Priority Request Generator (PRG) on board the bus notifies the Priority Request

Server (PRS) installed in traffic signal controller cabinet that the approaching bus would

like to receive TSP.

3. The PRS processes the request and decides whether to grant TSP based on defined

conditions.

4. If those conditions are met, the PRS will communicate with the traffic signal controller,

C, to then initiate action to provide TSP based on defined TSP control strategies.

Typically, if the intersection signals are already displaying a green light for the approach

being used by the bus, the controller will extend the length of the green phase (i.e. “green

extension”) to enable the bus to pass through the intersection on that phase. If the

intersection signals are displaying a red light on the bus approach, the controller will

shorten the green phase on the cross street (i.e. truncate the red phase or “red truncation”)

to provide an earlier green phase for the bus approach.

5. When the bus passes through the intersection, clearance is detected (“check-out”) by the

vehicle detection system at Pc and a communication is sent to the controller C that the

bus has cleared the intersection.

6. On being notified that the bus has cleared the intersection, the controller, C, restores the

normal traffic signal timing through a predetermined logic.

Transit Signal Priority Examples6:

The following examples provide a general explanation of what happens at an intersection when

TSP is triggered. These examples are consistent with the TSP control strategies that are

implemented as part of the Pace Harvey Area TSP Demonstration project, known as “red

truncation” and “green extension.”

Typically, if the intersection signals are displaying a red light on the bus approach, the controller

will shorten the green phase on the cross street to provide an earlier green phase (i.e. truncate the

PRS

PRG

vi

red phase or “red truncation”) for the bus approach. If the intersection signals are already

displaying a green light for the approach being used by the bus, the controller will extend the

length of the green phase (i.e. “green extension”) to enable the bus to pass through the

intersection on that phase.

The following figure, Figure ES-2, shows how red truncation and green extension work.

Figure ES-2: Transit Signal Priority Examples

TSP Bus

TSP Bus

TSP Bus

TSP Bus

TSP Bus TSP Bus

vii

Traffic Signal Timing Operation for TSP7

Figure ES-3: Normal Traffic Signal Timing Operation

Red Truncation: The intersection signals are displaying a red light on the bus approach; the

controller will shorten the green phase on the cross street to provide an earlier green phase (i.e.

truncate the red phase or “red truncation”) for the bus approach.

Figure ES-4: Traffic Signal Timing Operation with Red Truncation (i.e. Early Green)

Green Extension: The intersection signals are displaying a green light on the bus approach; the

green light on the bus approach is lengthened up to a maximum permitted time. This proves

helpful when the transit vehicle is detected near the end of the green and no near side bus stop is

present. By extending the green a few seconds, the transit vehicle avoids stopping at the signal.

Main Street maintains coordination with adjacent traffic signals in a

coordinated signal system.

viii

Figure ES-5: Traffic Signal Timing Operation with Green Extension

Example: Green Extension – Bus traveling on Main Street arrives late during Main Street green

and wants phase extension.

What is the Pace Transit Signal Priority (TSP) Initiative?

Identified in the “Vision 2020” plan, Pace’s blueprint for the future of suburban transit, as one of

several key service improvements intended to help enhance bus speed and thus improve travel

times and on-time performance, TSP is envisioned as an integral part of Pace’s Intelligent Bus

System (IBS) and a key component of future Arterial Rapid Transit (ART) service as Pace

reshapes it system by using new methods and technologies.

It is anticipated that implementing TSP throughout the Pace service area at strategically-selected

signalized intersections along Pace bus routes will improve bus mobility and reliability, and

therefore, as a result, will help Pace provide enhanced transit services to better meet current and

future demands, attract additional ridership, and increase the satisfaction of transit users.

In order to investigate how to best implement a region-wide TSP program, determine where TSP

should be deployed, and assess how TSP would benefit Pace transit operations, Pace began work

on the planning, design, demonstration, testing, and evaluation of a TSP system through the Pace

TSP Initiative. The Pace TSP Initiative included the development of a comprehensive Regional

TSP Deployment Plan and the execution of a TSP demonstration project.

• Regional TSP Deployment Plan – This plan is being used by Pace to help guide the future

deployment of TSP throughout Pace’s service area. The Regional TSP Deployment Plan,

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completed in June 2008, identified and prioritized corridors in Pace’s service area that

could benefit from the deployment of TSP in short-, medium-, and long-term timeframes.

• Harvey Area TSP Demonstration Project – The purpose of the Harvey Area TSP

Demonstration Project is to help educate and inform Pace on the following:

o how to best implement a TSP program

o the benefits that can be realized from the deployment of TSP in coordination with

other transit technologies

o to provide a roadmap for future TSP deployments

What are the Goals and Objectives of the Harvey Area TSP Demonstration

Project?

Quantitative Goals and Objectives:

The quantitative goals and objectives were identified to assess the potential improvements in

mobility and reliability for buses and general traffic after TSP implementation.

Goal 1: Improve Transit Mobility – TSP implementation will improve mobility for Pace buses.

Objective 1-1: To reduce bus travel time

Objective 1-2: To reduce bus delay at TSP intersections

Objective 1-3: To reduce bus delay at the corridor level (i.e. to reduce bus delay for each

bus within the segment of the bus route where TSP is deployed)

Goal 2: Improve Transit Reliability – TSP implementation will improve schedule adherence

for Pace buses.

Objective 2-1: To reduce bus travel time variance

Objective 2-2: To reduce the amount of time that arrival/departure times deviate from the

schedule

Goal 3: Improve General Traffic Mobility – Signal optimization and TSP implementation will

improve mobility for general traffic.

Objective 3-1: To reduce general traffic travel time (i.e. all other traffic besides Pace

buses)

Please refer to Section 2, which describes the methodology used for the quantitative evaluation

including descriptions of measures of effectiveness (MOE), data collection, and analysis

methods. Section 3 presents the quantitative evaluation analysis results.

x

Qualitative Goals and Objectives:

While not Pace’s first foray into TSP, the Harvey Area TSP Demonstration Project represents a

considerable advancement in project scope, the capabilities of the available TSP technology and

related equipment, and the project’s goals and objectives when compared to the Cermak Road

Bus Preemption Study and demonstration project completed in 1998.

As indicated in the previous section, the Harvey Area TSP Demonstration Project aims to help

Pace learn how to best implement and reap the benefits from TSP, which will provide invaluable

experience for upcoming TSP deployments. The qualitative goals and objectives were

developed to assess the areas of the project that cannot be measured in hard numbers.

Goal 1: Address Institutional Concerns – Address institutional concerns related to deploying

TSP in the demonstration project area and throughout the Pace service area

Objective 1-1: Coordinate with local jurisdictions, such as Illinois DOT, City of

Harvey, and Village of Riverdale.

Goal 2: Address Needs for Deploying TSP on Buses

Objective 2-1: Integrate TSP system with Pace’s IBS, the existing Automated Vehicle

Location (AVL) system

Objective 2-2: Implement conditional priority where the buses only request TSP when

behind schedule

Objective 2-3: Cancel TSP calls when entrance/exit doors are open and when the next

stop pull cords are activated

Objective 2-4: Distinguish the locations of near-side and far-side bus stops at TSP

intersections

Goal 3: Address Needs for Deploying TSP at Intersections

Objective 3-1: Implement “green extension” and “red truncation” TSP strategies

Objective 3-2: Implement TSP on the various locally-approved traffic signal

controllers, mainly the Econolite ASC/2 and ASC/3 controllers and

Siemens EAGLE EPAC300 M40 and M50 controllers.

Objective 3-3: Maintain coordination for traffic signals that are part of interconnected

signal systems

Objective 3-4: Maintain pedestrian clearance intervals

Objective 3-5:Maintain functionality of existing Emergency Vehicle Preemption (EVP)

systems

Goal 4: Address Requirements for Deploying TSP Central Management System

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Objective 3-6: Remotely monitor, collect data from, and configure the TSP system

from Pace Headquarters in Arlington Heights.

Please refer to Section 4, which presents qualitative evaluation measures and results, including

project experiences that will benefit Pace in future deployments of TSP systems in the region.

How do the Pace TSP Initiative and the Harvey Area TSP Demonstration

Project align with efforts to improve transit service throughout the Chicago

metropolitan area?

The following section describes how the TSP Initiative and the Harvey Area TSP Demonstration

Project align with, and help to achieve, the goals and objectives of other efforts to improve

transit service and regional mobility by Pace and its sister agencies.

Chicago Metropolitan Agency for Planning (CMAP)

CMAP is the federally designated Metropolitan Planning

Organization (MPO) for the northeastern Illinois counties

of Cook, DuPage, Kane, Kendall, Lake, McHenry, and

Will. CMAP developed and now guides the

implementation of GO TO 2040, metropolitan Chicago's first comprehensive regional plan in

more than 100 years. To address anticipated population growth of more than 2 million new

residents, GO TO 2040 establishes coordinated strategies that help the region's 284 communities

address transportation, housing, economic development, open space, the environment, and other

quality-of-life issues. GO TO 2040 includes specific recommendations on improvements related

to public transit, Intelligent Transportation Systems (ITS), and TSP. The following two

paragraphs are direct quotes from the GO TO 2040 plan.

“GO TO 2040 recommends that the region prioritize investments toward strategic enhancements

and modernization of the transportation system. If carefully targeted, these types of projects will

improve access, mobility, and the overall experience for all users.8”

“Improvements related to Intelligent Transportation Systems (ITS) are also considered strategic

enhancements and modernization. These include the use of real-time traveler information for

both highway and transit, signal improvements such as interconnects or Transit Signal Priority

(TSP) systems, traffic management centers, and many others. (…) GO TO 2040 supports

continuing to advance ITS projects of all types, and recommends a continued role for CMAP in

coordinating these efforts regionally.9”

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Pace’s Vision 2020 Plan

Unveiled in 2002, Pace continues to use its Vision 2020 plan as a

guide into the future. The Pace TSP Initiative and the Harvey

Area TSP Demonstration Project will help Pace realize many of

the expected benefits of implementing the Vision 2020 plan, which are as follows10

. (A check

mark indicates an identified benefit of implementing the Vision 2020 plan that TSP can have a

positive influence on.)

The key reasons to implement Vision 2020 are:

Customers

� Higher level of suburban mobility

� Faster service

� More flexible service

o Pedestrian and bicycle access

o Improved passenger facilities

o Greater public safety

� Improved connections

o Better access to jobs and community

facilities

� Reduced reliance on the automobile

Region

o Positive effect on new development

� Less congestion

� Infrastructure improvements

o Strong economic development

� Strong regional public transportation

system

Environment

� Improved Air Quality

� Better connected communities

Serves Everyone

� Transit dependent

� Work commuters

� Riders with strollers

� People with disabilities

� Seniors

Full Suburban Access

� Convenient

o Affordable

o Easy to use

� Faster

o Direct

Pace’s 2012 Budget, Appendix E: Planning Initiatives

Pace is meeting the goals of Vision 2020 in a variety of ways,

including through several continued efforts aimed at increasing

network speed as noted in the 2012 Pace Budget11

. Those

network speed enhancements include the following strategies:

• implementing TSP on designated corridors as part of the 5-year Traffic Corridor

Optimization and Traffic Signal Priority Program

• improving on-time performance of Pace fixed routes

• converting routes from “flag stop” service to “posted stop” service

xii

The Harvey Area TSP Demonstration project included two (2) bus routes that were converted

from flag stop service to posted stop service during the course of the project, and Pace Service

Planning is currently using data from the Harvey Area TSP Demonstration project system to help

improve on-time performance as part of its ongoing program to make transit work better for

existing riders and to encourage non-users to try public transit.

What do I need to know about the Harvey Area TSP Demonstration Project?

The Harvey Area TSP Demonstration project included the following activities:

• Pace equipped 20 signalized intersections in the area surrounding the Harvey

Transportation Center (HTC) with TSP equipment (PRS units)

• Three diverse and strategically-selected Pace bus routes that serve the HTC, Route 350

(Sibley), Route 352 (Halsted), and Route 364 (159th Street), travel through the

TSP-equipped intersections.

• Pace outfitted 55 buses that operate out of the South Division Garage with TSP

equipment (PRG units).

• Pace installed a TSP Central Management System at the Arlington Heights

headquarters so that Pace could monitor, evaluate, and configure the TSP system

remotely.

• Pace installed a robust communications system that connects the various elements of

the TSP system, from the wayside (on-street) equipment to the bus-mounted equipment

to the Central Management System at Pace Headquarters.

The TSP system provides Pace buses with the technology to either extend green lights (green

extension) or shorten red lights (red truncation) in the direction that the bus is traveling at the 20

TSP-equipped intersections when the buses are running behind schedule by more than one

(1) minute. The TSP system can be managed from anywhere with access to the internet by

anyone that has the required security clearance for the Central Management System’s servers

that reside at Pace Headquarters.

A key objective of the Pace TSP system is to improve the schedule adherence of Pace fixed-

route service. This is aided by integrating the TSP System with the bus Automated Vehicle

Location (AVL) system, Pace’s on-board Intelligent Bus System (IBS). When the Pace IBS

determines that a bus is more than one minute behind schedule, the bus will request TSP until the

deviation from the route’s schedule has been corrected. Improving the schedule adherence will

indirectly lead to operational cost savings through a decrease in fuel consumption, emissions,

and wear-and-tear on the buses as a result of fewer stops and starts at red lights afforded by TSP.

Customer satisfaction with Pace transit can also be improved as passengers notice an increase in

on-time performance and a decrease in transit travel times, which could potentially increase

ridership along TSP Corridors.

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Table ES-1 provides a table listing of the 20 signalized intersections that were equipped with

TSP equipment.

Table ES-1: Pace Harvey Area TSP Demonstration Project – TSP Intersections

147th St Corridor (7 Signals) 159th St Corridor (7 Signals)

147th St @ LaSalle St 159th St @ Vincennes Rd

147th St @ Indiana Ave/State St 159th St @ Indiana Ave/State St

147th St @ Chicago Rd/South Park Ave 159th St @ Wausau Ave

147th St @ Cottage Grove Ave 159th St @ Chicago Rd/South Park Ave

147th St @ Greenwood Rd 159th St @ Cottage Grove Ave

147th St @ Woodlawn Ave 159th St @ Ellis Ave

147th St @ Lincoln Ave/Michigan City Rd 159th St @ Woodlawn Ave

Halsted St Corridor (3 Signals) Park Ave Corridor (3 Signals)

Halsted St @ 138th St Park Ave @ 154th St



Figure ES-2 on the following page provides a graphic of the project area featuring the three Pace

bus routes and the 20 TSP-equipped intersections in the project area.

xiv

Figure ES-6: Pace Harvey Area TSP Demonstration Project Area

to

95th

/Dan Ryan

to

Hammond TC

to

Hammond TC

to Chicago Hts

Dalton

South Holland

Harvey

Riverdale

xv

What have we learned from the Harvey Area TSP Demonstration Project, and

what are the key findings?

The evaluation results are presented in this document in both quantitative and qualitative terms.

Quantitative results are presented at a high level in Tables ES-2 through ES-5 and Figures ES-7

through ES-9 found in the following pages. Transit and traffic data have been collected from

three major sources, including the Pace Intelligent Bus System (IBS data) as well as more

detailed data collected by URS staff traveling through the TSP project area on Pace buses (Bus

Ride Along Data) and in passenger vehicles (Floating Car Data).

Transit and traffic data collection was conducted for AM and PM peak periods over the course of

the demonstration project to study the conditions at specific stages of the project.

• Before (Existing) Conditions – Data collected during this stage of the project represents

Pace operations before any work was done on the project.

• Optimized (TSP Off) – Data collected during this stage of the project represents Pace

operations after traffic signal timings were optimized to best accommodate current traffic

patterns and conditions but before TSP was deployed.

• After (TSP On) – Data collected during this stage of the project, the final configuration of

the demonstration project, represents Pace operations after the traffic signal timings were

optimized and the TSP System was deployed.

The evaluation focused on transit mobility and reliability and was performed by comparing the

Measures of Effectiveness (MOEs) for travel time, delay, time deviated from schedule, and

number of delayed buses before and after TSP implementation. Direct value change and

percentage change were both used to quantify the improvements for these MOEs.

The tables and figures summarize the major MOEs (travel time and travel time variation)

discussed in this document for Pace Routes 350, 352, and 364 respectively. The improvements

to Pace transit operations for the AM and PM peak periods are displayed by comparing the

Existing state (Before) vs. the TSP state (After). Improvements are all highlighted in blue in the

tables.

Overall, the travel time was reduced by a range from 2% (25 sec) to 15% (3.3 min). The travel

time variation was reduced by a range of 14% (12 sec) to 66% (4 min). Route 364 WB received

the most improvements during the PM peak period.

There were some instances where the TSP system did not improve transit operations as expected.

Some reasons for this include various changes made to transit operations between the rounds of

data collection. These are discussed in more detail within this document. In addition, different

traffic levels during the before and after phases when the evaluation data was collected may also

xvi

impact the evaluation results. If more travel runs were collected during the peak hour out of the

three-hour peak periods, the higher likelihood is to obtain higher travel time and delay which

may cause the results to vary.

While TSP can improve schedule adherence and transit travel times, TSP alone can only reduce

the delays to transit vehicles caused by traffic signals, specifically the delay from red lights. For

the TSP Demonstration evaluation, signal delay was objectively defined as the time between

when a transit vehicle stops at the end of a queue at a red light while waiting for a green light and

when that light first turns green.

Delay can occur at that same intersection for other reasons as well. Slow-moving traffic can

prevent the transit vehicle from clearing the intersection, thus causing it to be delayed through an

additional red signal cycle. Delay can also be caused by other factors on the roadway, such as

train crossings, which may be creating lengthy vehicle queues beyond the intersection which the

transit vehicle is waiting to clear. Thus, the green extension or red truncation of TSP cannot be

guaranteed to eliminate all of the delay that can potentially occur at a signalized intersection.

TSP can only reduce the amount of time that a transit vehicle is stopped at a red light.

xvii

Table ES-2: Comparison of Total Daily Travel Time (hh:mm:ss) for Each Route and All

Routes Combined During AM and PM Peak Periods

Route

Route

Direction From To

Before

(Existing)

After

(TSP On) Change

%

Change

350

EB HTC 147

th St (Sibley Blvd)

@ I-94 5:52:32 5:32:36 -0:19:56 -5.7%

WB 147

th St (Sibley Blvd)

@ I-94 HTC 5:29:27 5:49:24 0:19:56 6.1%

352

NB HTC

Halsted St

@ Blue Island-

Riverdale Rd.

5:17:06 5:03:03 -0:14:03 -4.4%

SB

Halsted St

@ Blue Island-

Riverdale Rd.

HTC 4:55:32 4:09:00 -0:46:32 -15.7%

364

EB HTC 159th St(US 6)

@ I-94 4:03:25 4:20:36 0:17:10 7.1%

WB 159th St(US 6)

@ I-94 HTC 4:19:10 3:53:00 -0:26:10 -10.1%

All

Routes All - - 29:57:13 28:47:39 -1:09:34 -3.9%

Note: AM Peak Period: 6:00 am – 9:00 am; PM Peak Period: 3:30 pm – 6:30 pm

Figure ES-7: Percentage Change in Daily Travel Time Between Before and After

Conditions

-5.7%

6.1%

-4.4%

-15.7%

7.1%

-10.1%

-20.0%

-15.0%

-10.0%

-5.0%

0.0%

5.0%

10.0%

350 EB 350 WB 352 NB 352 SB 364 EB 364 WB

Pe

rce

nta

ge

Ch

an

ge

(%

)

Bus Route

Percentage Change in Daily Travel Time Between

Before and After Conditions

% Diff

xviii

Table ES-3: Comparison of Daily Travel Time Variation (mm:ss) for Each Route and All

Routes Combined During AM and PM Peak Periods

Route

Route

Direction From To

Before

(Existing)

After

(TSP On) Change

%

Change

350

EB HTC 147

th St (Sibley Blvd)

@ I-94 03:43 01:59 -01:43 -46%

WB 147

th St (Sibley Blvd)

@ I-94 HTC 01:31 01:26 -00:05 -6%

352

NB HTC

Halsted St

@ Blue Island-

Riverdale Rd.

01:40 02:06 00:26 26%

SB

Halsted St

@ Blue Island-

Riverdale Rd.

HTC 01:40 00:59 -00:40 -41%

364

EB HTC 159th St(US 6)

@ I-94 04:10 01:26 -02:43 -65%

WB 159th St(US 6)

@ I-94 HTC 05:21 02:25 -02:55 -55%

All

Routes All Average Travel Time Variations 03:01 01:44 -01:17 -43%


Figure ES-8: Percentage of Daily Travel Time Variation Between Before and After

Conditions

-46%

-6%

26%

-41%

-65%

-55%

-80%

-60%

-40%

-20%

0%

20%

40%

350 EB 350 WB 352 NB 352 SB 364 EB 364 WB

Pe

rce

nta

ge

Ch

ag

ne

(%

)

Bus Route

Percentage Change in Travel Time Variation

Between Before and After

% Diff

xix

Table ES-4: Comparison of Daily TSP Intersection Delay (mm:ss) for each TSP

Intersection and All TSP Intersections Combined During AM and PM Peak Periods

TSP Intersection

Optimized

(TSP Off)

After

(TSP On) Change

147th St @ Halsted St 26:26 16:42 -09:44

147th St @ LaSalle St 00:08 00:23 00:15

147th St @ Indiana Ave/State St 04:05 00:37 -03:28

147th St @ Chicago Rd/South Park Ave 05:00 03:41 -01:19

147th St @ Cottage Grove Ave 00:48 00:18 -00:30

147th St @ Greenwood Rd 01:50 03:29 01:39

147th St @ Woodlawn Ave 01:53 01:47 -00:06

147th St @ Lincoln Ave/Michigan City Rd 02:42 03:57 01:15

Halsted St @ 144th St 02:35 01:22 -01:13

Halsted St @ 138th St 03:24 02:04 -01:20

Park Ave @ 154th St 01:44 01:41 -00:03

Park Ave @ 155th St 08:22 08:21 -00:01

Park Ave @ 157th St 06:24 03:32 -02:52

159th St @ Vincennes Rd 12:55 06:24 -06:31

159th St @ Indiana Ave/State St 22:21 19:58 -02:23

159th St @ Wausau Ave 01:07 02:14 01:07

159th St @ Chicago Rd/South Park Ave 03:34 03:01 -00:33

159th St @ Cottage Grove Ave 01:38 01:32 -00:06

159th St @ Ellis Ave 03:07 02:08 -00:59

159th St @ Woodlawn Ave 02:01 01:19 -00:42

All Intersections 1:52:04 1:24:30 -27:34


xx

Table ES-5: Comparison of Daily TSP Intersection Delay (mm:ss) for Each Route and for

All Routes Combined

Route

Number Of

TSP Intersections

Optimized

(TSP Off)

After

(TSP On) Change % Change

350EB 8 16:23 10:29 -05:54 -36%

350WB 8 11:06 10:22 -00:44 -7%

352NB 3 11:30 09:02 -02:28 -21%

352SB 3 09:52 04:27 -05:25 -55%

364EB 10 34:13 28:55 -05:18 -15%

364WB 10 29:00 21:15 -07:45 -27%

All

Routes

Total Delay for All

Intersections* 1:52:04 1:24:30 -27:34 -25%

* Note: The total number of intersections is 20. Routes 350 and 352 both travel through the TSP intersection at

147th St at Halsted St.

Figure ES-12: Percentage Change in Intersection Delay Between TSP Off and TSP On

Conditions

-36%

-7%

-21%

-55%

-15%

-27%

-60%

-50%

-40%

-30%

-20%

-10%

0%

350 EB 350 WB 352 NB 352 SB 364 EB 364 WB

Pe

rce

nta

ge

Ch

an

ge

(%

)

Bus Route

Percentage Change in Intersection Delay

Between TSP OFF and TSP ON

% Diff.

- 1 -

1.0 INTRODUCTION

1.1 Report Organization

• Section 2 describes the methodology used for the quantitative evaluation including

descriptions of measures of effectiveness (MOE), data collection, and analysis methods.

• Section 3 presents the quantitative evaluation analysis results.

• Section 4 presents qualitative evaluation measures, including project experiences that will

benefit Pace in future deployments of TSP systems in the region.

• Section 5 summarizes key finds learned from the deployment of the TSP system and the

evaluation analysis and lists the items that the project teams need to be aware of for

future TSP deployment.

1.2 Background

Pace, the suburban bus division of the Regional Transportation Authority (RTA), provides

suburban fixed bus route, ADA Paratransit, vanpools, and Dial-a-Ride public transportation

services to six-counties (Cook, DuPage, Will, Kane, McHenry, and Lake) in northeastern Illinois.

It is the intent of Pace to implement methods that can improve and maximize the usage of all

transit services in the six-county service area. As Pace’s service area continues to expand and

develop from population growth and employment opportunities, the demand for a faster, more

efficient and effective transit system becomes an increased concern.

Pace has been a leader in the application of technology to improve transit operations, enhance the

travel experience of its customers, and meet the stated goals of its “Vision 2020” long-range plan.

TSP technology is widely used to improve transit operational efficiency by reducing bus delay at

signalized intersections, maintaining bus speed, and enhancing bus schedule adherence. It is

anticipated that implementing a TSP system throughout the region at signalized intersections

along Pace bus routes will improve Pace bus mobility and reliability, and as a result, help Pace

provide better transit services to meet current and future demands, attract additional ridership,

and increase the satisfaction of transit users.

In order to investigate how to best implement a TSP system, determine where TSP should be

deployed, and assess how the TSP system would benefit Pace transit operations, Pace began

work on the planning, design, demonstration, testing, and evaluation of a TSP system through the

Pace TSP Initiative. The Pace TSP Initiative included the development of a comprehensive

Regional TSP Deployment Plan and the execution of a TSP Demonstration project.

The Pace TSP Initiative includes a total of five tasks that cover both the Regional TSP

Deployment Plan and the TSP Demonstration project. The tasks and associated milestones for

each task of the project are listed below:

- 2 -

Task 1: Coordinate with Public Agencies (for both the Regional TSP Deployment Plan and

TSP Demonstration)

- Kickoff Meeting

- Outreach Plan

- Project Management

TSP Demonstration Project

Task 2: Harvey Area TSP Demonstration Project

- Subtask 1: Perform Needs Assessment

- Subtask 2: Develop High-Level System Requirements

- Subtask 3: Complete Signal Timing Optimization, Field Operations Test

Plan and Specifications

- Subtask 4: Complete Pre-Deployment Impact Analysis

- Subtask 5: Perform TSP Deployment, Demonstration, and Evaluation

Regional TSP Deployment Plan

Task 3: Collection of Transit and Traffic Characteristics Data for TSP Implementation

- Establish Study Corridors

- Develop Data Gathering Plan and Costs

- Assemble Data

Task 4: Prioritization of Pace Routes/Corridors for TSP Implementation Based on Cost-

Benefit Analysis and Return on Investments

- Develop/Apply Locational Delay Rating Algorithm

- Develop Menu of Route Improvement Techniques

- Evaluate Corridors for Applying TSP Techniques

Task 5: Design and Evaluation Strategy

- System Architecture and Hardware / Software

- TSP Implementation / Deployment Plan

- TSP Deployment Costs

This document presents the results of an evaluation of the Harvey Area TSP Demonstration

Project in Task 2. The results consists of both qualitative and quantitative sections to emphasize

both the measurable benefits of travel time savings as well as the invaluable experience gained

by Pace personnel in the process of planning, deploying, and operating the TSP System around

the HTC.

- 3 -

Tasks 3, 4, and 5 listed above were completed in June 2008 and resulted in the development of a

Regional TSP Deployment Plan that identified several Pace corridors that could benefit from the

deployment of TSP technologies in short, medium, and long term timeframes.

1.3 Task 2 Demonstration Project Area

Three Pace bus routes serving the Harvey Transportation Center were chosen to be part of the

Demonstration. These are routes 350 (Sibley / 147th

Ave.), 352 (Halsted St.), and 364 (159th

St.).

Together, these three bus routes travel through a total of 20 signalized intersections that have

been equipped with TSP equipment that receives requests from Pace buses for transit signal

priority.

Table 1-1 provides a table listing of the 20 signalized intersections with TSP equipment. Figure

1-2 on the following page provides a graphic of the project area, the three Pace bus routes, and

the 20 TSP-equipped intersections in the project area.

Table 1-1: Traffic Signal Intersection in Pace TSP Demonstration

147th St Corridor (7 Signals) 159th St Corridor (7 Signals)

147th St @ LaSalle St 159th St @ Vincennes Rd

147th St @ Indiana Ave/State St 159th St @ Indiana Ave/State St

147th St @ Chicago Rd/South Park Ave 159th St @ Wausau Ave

147th St @ Cottage Grove Ave 159th St @ Chicago Rd/South Park Ave

147th St @ Greenwood Rd 159th St @ Cottage Grove Ave

147th St @ Woodlawn Ave 159th St @ Ellis Ave

147th St @ Lincoln Ave/Michigan City Rd 159th St @ Woodlawn Ave

Halsted St Corridor (3 Signals) Park Ave Corridor (3 Signals)




- 4 -

Figure 1-2: Harvey Area TSP Demonstration Project Area

to 95

th/Dan Ryan

to Hammond TC

to Hammond TC

to Chicago Hts

Dalton

South Holland

Harvey

Riverdale

- 5 -

1.4 Harvey Area TSP Demonstration Project – Traffic Signal Timing

Improvements

Prior to the deployment of TSP equipment at the traffic signals identified in Figure 1-1, Pace

conducted an effort as part of Task 2 of this project to improve the overall traffic signal timing

operations in the project area. This evaluation report presents data measured before these signal

timing improvements, after the improvements (but before TSP equipment was installed), and

after TSP equipment was installed and operational at all intersections. A separate evaluation

report was prepared detailing travel time savings to general traffic as a result of the traffic signal

timing improvements made in Phase 2.

1.5 Goals and Objectives

Quantitative Goals and Objectives:

The quantitative goals and objectives were identified to assess the potential improvements in

mobility and reliability for buses and general traffic after TSP implementation.

Goal 1: Improve Transit Mobility – TSP implementation will improve mobility for Pace buses.

Objective 1-1: To reduce bus travel time

Objective 1-2: To reduce bus delay at TSP intersections

Objective 1-3: To reduce bus delay at the corridor level (i.e. to reduce bus delay for each

bus within the segment of the bus route where TSP is deployed)

Goal 2: Improve Transit Reliability – TSP implementation will improve schedule adherence

for Pace buses.

Objective 2-1: To reduce bus travel time variance

Objective 2-2: To reduce the amount of time that arrival/departure times deviate from the

schedule

Goal 3: Improve General Traffic Mobility – Signal optimization and TSP implementation will

improve mobility for general traffic.

Objective 3-1: To reduce general traffic travel time (i.e. all other traffic besides Pace

buses)

Please refer to Section 2, which describes the methodology used for the quantitative evaluation

including descriptions of measures of effectiveness (MOE), data collection, and analysis

methods. Section 3 presents the quantitative evaluation analysis results.

- 6 -

Qualitative Goals and Objectives:

While not Pace’s first foray into TSP, the Harvey Area TSP Demonstration Project represents a

considerable advancement in project scope, the capabilities of the available TSP technology and

related equipment, and the project’s goals and objectives when compared to the Cermak Road

Bus Preemption Study and demonstration project completed in 1998.

As indicated in the previous section, the Harvey Area TSP Demonstration Project aims to help

Pace learn how to best implement and reap the benefits from TSP, which will provide invaluable

experience for upcoming TSP deployments. The qualitative goals and objectives were

developed to assess the areas of the project that cannot be measured in hard numbers.

Goal 1: Address Institutional Concerns – Address institutional concerns related to deploying

TSP in the demonstration project area and throughout the Pace service area

Objective 1-1: Coordinate with local jurisdictions, such as Illinois DOT, City of

Harvey, and Village of Riverdale.

Goal 2: Address Requirements for Deploying TSP on Buses

Objective 2-1: Integrate TSP system with Pace’s IBS, the existing Automated Vehicle

Location (AVL) system

Objective 2-2: Implement conditional priority where the buses only request TSP when

behind schedule

Objective 2-3: Cancel TSP calls when entrance/exit doors are open and when the next

stop pull cords are activated

Objective 2-4: Distinguish the locations of near-side and far-side bus stops at TSP

intersections

Goal 3: Address Requirements for Deploying TSP at Intersections

Objective 3-1: Implement “green extension” and “red truncation” TSP strategies

Objective 3-2: Implement TSP on the various locally-approved traffic signal

controllers, mainly the Econolite ASC/2 and ASC/3 controllers and

Siemens EAGLE EPAC300 M40 and M50 controllers.

Objective 3-3: Maintain coordination for traffic signals that are part of interconnected

signal systems

Objective 3-4: Maintain pedestrian clearance intervals

Objective 3-5:Maintain functionality of existing Emergency Vehicle Preemption (EVP)

systems

- 8 -

Goal 4: Address Requirements for Deploying TSP Central Management System

Objective 3-6: Remotely monitor, collect data from, and configure the TSP system

from Pace Headquarters in Arlington Heights.

Please refer to Section 4, which presents qualitative evaluation measures and results, including

project experiences that will benefit Pace in future deployments of TSP systems in the region.

- 9 -

2.0 QUANTITATIVE EVALUATION METHODOLOGY

This section presents the quantitative evaluation methodology of the Harvey Area TSP

Demonstration, including the specific measures of effectiveness (MOEs), data, and analyses that

will be employed.

2.1 Measures of Effectiveness

MOEs are identified to quantify the effect of traffic signal optimization and TSP implementation

on transit and general traffic. The MOE’s are defined as follows to help evaluate the goals and

objectives listed in the following sub-sections.

2.1.1 Transit Mobility

Average Bus Travel Time: Bus travel time is defined as the total time that a bus commutes

between passing a starting data collection point (an intersection or a bus stop) and passing an

ending data collection point (an intersection or a bus stop) along the studied segment. The travel

time includes running time, stop time, and dwell time for a bus. Average bus travel time was

calculated by averaging the observed travel time for multiple bus runs. Bus travel time data were

collected by field bus travel time runs and data from IBS bus database.

Bus Intersection Delay: Bus delay is defined as the bus stop time that a bus experiences at each

intersection. Bus intersection delay for each bus run was derived by subtracting the point in time

when buses began moving at a stopped position from the point in time when buses stopped at an

intersection under a red light. Total bus delay was calculated by adding the derived bus

intersection delays for multiple bus runs based on field bus travel time run data.

Bus Corridor Delay: Bus corridor delay is defined as the sum of the bus intersection delay

experienced by each bus route along a corridor. Bus corridor delay for each bus run was derived

by adding the intersection bus delays for each bus run. Average bus corridor delay was

calculated by averaging the derived bus corridor delays for multiple bus runs based on field bus

travel time run data.

Number of Stops: Number of stops is defined as the total number of buses that stopped at each

intersection. Number of bus stops was derived by counting all buses that stopped at each

intersection for each bus route during the peak period based on field bus travel time run data.

2.1.2 Transit Reliability

Bus Travel Time Variance: Bus travel time variance is defined as one standard deviation for

observed Pace bus travel time based on field bus data. Pace bus travel time is defined as the total

time that a bus commutes between passing an identified starting Pace bus time-point and passing

- 10 -

an ending Pace bus time-point for selected routes along the studied segments. The bus travel

time variance is calculated by determining one standard deviation for the observed Pace bus

travel time during A.M. and P.M. peak periods based on field bus run data and IBS bus database.

Average Bus Schedule Deviation Time: Bus schedule deviation time is defined as the offset

between the scheduled bus arrival time and actual field bus arrival time at a selected bus stop.

The average bus schedule deviation time was calculated by averaging the absolute value of the

time deviated (including both early arrival and late arrival) from the schedule for multiple buses

during the peak periods. The bus schedule deviation times will be collected by Pace IBS bus

database.

2.1.3 General Traffic Mobility

Average Car Travel Time: Car travel time is defined as the travel time that a probe vehicle

commutes among the traffic flow between passing a starting data collection point (intersection)

and passing an ending data collection point (intersection) along the studied segment. Average

car travel time was calculated by averaging the observed car travel time for all probe vehicle runs.

Car travel time data were collected by the field probe vehicle travel time runs.

2.2 Data Collection

Evaluation data were collected during three phases in time:

• Before (Existing): Before traffic signal timing optimization

• Optimized (TSP Off): After traffic signal timing optimization, but before TSP System

implementation

• After (TSP On): After TSP System implementation

Traffic signal timing optimization throughout the project area was a task required prior to TSP

System deployment to ensure that signal timings were optimized to accommodate the current

traffic volumes and travel patterns.

Data on transit and traffic characteristics were also obtained from three key data sources: 1) Pace

Intelligent Bus System (IBS), which provides transit vehicle data from the Automated Vehicle

Locator technology on buses, 2) Bus ride-along travel time runs, which provides additional

details on transit vehicle delays along TSP bus routes and at individual TSP intersections., and 3)

floating car travel time runs, which provides data on general traffic conditions along TSP bus

routes and at individual TSP intersections.

- 11 -

Transit and traffic data collection was performed before traffic signal optimization by gathering

IBS data on the TSP bus routes, Routes 350, 352, and 364. Bus ride-along and floating car travel

time data collection was also performed prior to traffic signal optimization.

While traffic signal timings were optimized in May 2007, transit and traffic data were not

collected for Phase 2 until after the TSP System was deployed and operational. Transit and

traffic data for Phases 2 and 3 were collected in consecutive weeks, which more accurately

revealed how the TSP System affects both transit and traffic operations while minimizing the

potential for road construction, changes in traffic volumes and travel patterns, or other factors to

influence transit and traffic operations between these two intervals.

The TSP System was de-activated to allow for Phase 2 data collection to occur during the weeks

of August 8th

and August 15th

, 2011. Phase 3 data collection was completed during the weeks of

July 25th

and August 1st.

Table 2-1 below displays the timeline of data collection activities.

Table 2-1: Types of Data Collection during Harvey Area TSP Demonstration

Data Type Route Before

(Existing) Optimized

(TSP Off) After

(TSP) Pace IBS 350, 352, 364 February 2006 August 2011 Jul/Aug 2011 Bus Ride Along Data 350, 352, 364 May 2006 August 2011 Jul/Aug 2011 Floating Car Travel Time

Runs 159

th St (US 6),

147th St (IL 83)

November 2006 August 2011 Jul/Aug 2011

2.2.1 Pace IBS Bus Data

Pace uses Automatic Vehicle Location (AVL) systems installed on selected bus routes to collect

real time bus data. The Pace bus data includes trip information, timestamps (both arrival and

departure times), bus headways, schedule deviations, bus identification numbers, and bus

position coordinates at each time point along the bus route. Bus travel time and schedule

deviation were derived from the Pace bus data to assess bus operational performance and

schedule adherence improvement after the signal timing optimization and TSP implementation.

- 12 -

Table 2-2: Timeline for IBS Bus Data Collection

Route Direction Peak Period

Optimized

(TSP Off)

After

(TSP)

350

EB AM

August 2011 August 2011 PM

WB AM

PM

352

NB AM


SB AM

PM

364

EB AM

August 2011 July 2011 PM

WB AM

PM

It should be noted that there were significant changes in Pace transit operations between 2006

and 2011 in the TSP Demonstration Project area (including the three TSP bus routes), such as

route re-structuring, moving bus stops from the near side to the far side of intersections where

feasible, and changing from flag stop operation to posted stops operation. The scheduled travel

times on Pace bus routes 350, 352, and 364 between key time points that are affected by TSP

System operations have changed only slightly. The scheduled travel times vary based on type of

day (weekday vs. weekend), time of day, and direction of travel. Adjustments to scheduled

travel times were also made based on AVL data on actual travel times between time points.

Table 2-3: Scheduled Travel Times between Time points along Pace Bus Routes

Route 350 Route 352 Route 364 Year # of TSP Signals on Route 9 6 10

2006 Time point #7 (HTC) Time point #3 (Torrence) 17 to 19

minutes -- --

2011 Time point #1 (HTC) Time point #4 (Torrence) 18 to 23

minutes -- --

2006 Time point #4 (HTC) Time point #5 (127th) -- 10 to 16

minutes --

2011 Time point #6 (HTC) Time point #7 (127th) -- 10 to 14

minutes --

2006 Time point #6 (HTC) Time point #9

(River Oaks Shopping Center) -- --

25 to 30

minutes

2011 Time point #6 (HTC) Time point #9

(River Oaks Shopping Center) -- --

23 to 28

minutes

2.2.2 Bus Ride-Along Data

Bus ride along travel time and delay data was collected for the three TSP bus routes. The data

collection was performed by collecting data on a bus among the general traffic flow between the

- 13 -

selected starting and ending points during A.M. and P.M. peak periods along the three TSP bus

routes. The data collection personnel used travel time data collection software installed on a

laptop computer and a Global Positioning System (GPS) antenna to collect travel time, running

time, and delay for buses. The field travel time and delay data were used to assess mobility and

reliability improvements for buses. See Table 2-4 for the dates when the field bus ride along

data collection was performed during the three stages. Table 2-5 lists the start and end

intersections for the field travel time runs data analysis.

Table 2-4: Timeline for Bus Ride Along Data Collection

Route Direction

Peak

Period

Before

(Existing)

Optimized

(TSP Off)

After

(TSP)

350

EB AM

May 2006 August 2011 August 2011 PM

WB AM

PM

352

NB AM

May 2006 August 2011 August 2011 PM

SB AM

PM

364

EB AM

May 2006 August 2011 July 2011 PM

WB AM

PM

Table 2-5: Start and End Points for Bus Ride Along Data Collection

Route Direction From To

350 EB Harvey Center/Halsted Sibley/I-94

WB Sibley/I-94 Harvey Center/Halsted

352 NB Harvey Center/Halsted Halsted/Blue Island-Riverdale Road

SB Halsted/ Blue Island-Riverdale Road Harvey Center/Halsted

364 EB Harvey Center/Halsted 159

th St. (US 6)/I-94

WB 159th St. (US 6)/I-94 Harvey Center/Halsted

2.2.3 Floating Car Travel Time Runs

Floating car travel time runs were conducted to collect travel time and delay data for general

traffic by using “floating car” method. This method was performed by driving a probe vehicle

among the general traffic flow (floating car) between the selected starting and ending points

during A.M. and P.M. peak periods along selected routes. The data collection personnel used

travel time data collection software installed on a laptop computer and a Global Positioning

System (GPS) antenna to collect travel time, running time, and delay for cars. The floating car

- 14 -

car travel time and delay data were used to assess mobility improvements to general traffic along

the selected routes. Table 2-6 lists the dates when the field floating car data collection was

performed during the various data collection periods. Table 2-7 lists the start and end

intersections for the field floating car travel time data collection runs.

Table 2-6: Dates for Floating Car Data Collection

Route Direction PeakPeriod

Optimized

(TSP Off)

After

(TSP)

159th St

(US 6)

EB AM


WB AM

PM

147th St

(IL 83/

(Sibley Blvd)

EB AM


WB AM

PM

Table 2-7: Start and End Points for Floating Car Data Analysis

Route Direction From To

159th St

(US 6)

EB Carse Ave. Woodlawn Ave.

WB Woodlawn Ave. Carse Ave.

147th St

(IL 83/

(Sibley Blvd)

EB Dixie Highway Michigan City Rd

WB Michigan City Rd Dixie Highway

Table 2-8 summarizes the evaluation data used to assess each goal and objective in the analysis

as previously discussed in Section 1.

Table 2-8: Data Used for Analysis

Goal Objective Evaluation Data 1: Improve Transit

Mobility

1-1: To reduce bus travel time Field bus ride along runs data and

IBS data

1-2: To reduce bus delay at an

intersection level

Field bus ride along runs data and

IBS Data

1-3: To reduce bus delay at a

corridor level

2: Improve Transit

Reliability

2-1: To reduce bus travel time

variance

Field bus ride along runs data and

IBS Data

2-2: To reduce time deviated

from the schedule

3: Improve General

Traffic Mobility

3-1: To reduce car travel time Field floating car travel time runs data

3-2: To reduce car delay Field floating car travel time runs data

- 15 -

2.3 Analysis Methods

The evaluation analysis was conducted by comparing the MOEs between Before (Existing) and

Optimized (TSP Off) and between Optimized (TSP Off) and After (TSP On). The comparison

between Before (Existing) and Optimized (TSP Off) was performed to identify the mobility and

reliability improvements for transit and general traffic after signal timing optimization. The

comparison between Optimized (TSP Off) and After (TSP On) was performed to identify the

mobility and reliability improvements for transit and general traffic after the TSP implementation.

Percentage change in the values of the MOEs was used as the measurement to quantify the

comparison results. For signal optimization analysis, the percentage difference is defined as the

ratio of the difference between aggregated MOEs under Optimized conditions and aggregated

MOEs under Existing conditions over aggregated MOEs under Existing conditions. For TSP

analysis, the percentage difference is defined as the ratio of the difference between aggregated

MOEs under TSP condition and aggregated MOEs under Optimized condition over aggregated

MOEs under Optimized conditions.

The MOEs for assessing the traffic signal optimization impact were aggregated based on the

field travel time runs data and Pace bus data. The MOEs for assessing TSP implementation

impact were aggregated based on both field travel time runs data, Pace bus data and TSP data for

the TSP intersections along the studied segment.

- 16 -

3.0 QUANTITATIVE EVALUATION RESULTS

This section presents the quantitative evaluation analysis results for the traffic signal timing

optimization and TSP implementation conditions according to the identified goals and objectives

listed in Section 1.4. The qualitative evaluation results are documented in Section 4.0 of this

document.

3.1 Comparison of Before (Existing) and After (TSP On) Conditions

This section presents the analysis results in terms of percentage change in the MOEs between

Before (existing conditions) and After (after TSP implementation) conditions. The analysis

results indicate that traffic operations were improved for both transit and general traffic during

the A.M. (6-9 A.M.) and P.M. (3:30-6:30 P.M.) peak periods after TSP implementation.


Travel Times -- Bus Ride Along Data

Average Bus Travel Time: The analysis results show that the average bus travel times only

improved for routes 352 and 364 in the AM peak period, but improved for all routes and

directions in the PM peak period except for westbound Route 350. Tables 3-1 and 3-2

summarize the change in travel time between Before and After TSP conditions in the AM and

PM peak periods, respectively. The greatest decreases in travel times during the AM and PM

peak periods were observed for Route 352 in the southbound direction, where the travel times

decreased by 12.4% and 18%, respectively.


Travel Time Variance -- Bus Ride Along Data

Bus Travel Time Variance: The analysis results show that the bus travel time variances

decreased for Pace bus routes in most directions during the AM and PM peak periods. Tables

3-3 and 3-4 summarize the changes in travel time variation between the Before and After TSP

conditions during the AM and PM peak periods, respectively. The greatest decrease in travel

time variation during the AM peak period was observed for Route 352 in the southbound

direction (65%), while the greatest decrease in the PM peak period was observed for Route 350

in the westbound direction (66%).

- 17 -

Table 3-1: Comparison of Average Travel Time (in seconds) between Before (Existing) and

After (TSP On) Conditions – AM Peak Period

Route Direction Before After Change % Change

350 EB 736 792 56 7.6%

WB 849 876 27 3.1%

352 NB 545 575 30 5.5%

SB 592 519 -73 -12.4%

364 EB 1117 1314 197 17.6%

WB 1214 1164 -50 -4.1%

Table 3-2: Comparison of Average Travel Time (in seconds) between Before (Existing) and

After (TSP On) Conditions – PM Peak Period

Route Direction Before After Change % Change

350 EB 1027 871 -156 -15%

WB 798 897 99 12%

352 NB 603 531 -72 -12%

SB 590 484 -106 -18%

364 EB 1317 1292 -25 -2%

WB 1378 1166 -212 -15%

Table 3-3: Comparison of Average Travel Time Variation (in seconds) between Before

(Existing) and After (TSP On) Conditions – AM Peak Period

Route Direction Before After Change. % Change.

350 EB 108 125 17.1 16%

WB 72 117 44.6 62%

352 NB 132 110 -21.3 -16%

SB 135 47 -88.4 -65%

364 EB 84 72 -12.2 -14%

WB 259 169 -90.1 -35%

- 18 -

Table 3-4: Comparison of Average Travel Time Variation (in seconds) between Before

(Existing) and After (TSP On) Conditions – PM Peak Period

Route Direction Before After Change. % Change.

350 EB 217 110 -106.8 -49%

WB 104 51 -52.4 -51%

352 NB 81 146 64.7 79%

SB 89 70 -18.8 -21%

364 EB 270 109 -160.8 -60%

WB 388 132 -255.8 -66%

- 19 -

3.2 Signal Optimization Results


Existing (before traffic signal timing optimization) and Optimized (after traffic signal timing

optimization) conditions. The analysis results indicate that traffic operations were improved for

both transit and general traffic on a directional basis during A.M. and P.M. peak periods after

signal optimization.


3.2.1.1 Travel Times -- Bus Ride Along Data

Average Bus Travel Time: The analysis results show that the bus travel times improved for

routes 350 and 352 in both the AM and PM peak periods, while travel times improved only in

the westbound direction for Route 364. Table 3-5 displays the travel time savings and the

percentage difference between Existing and Optimized Phases in the AM peak, while Table 3-6

presents these measures for the PM peak. The largest decrease in travel times during the AM

peak was observed for Route 352 in the southbound direction, which decreased travel times by

9.1%. The largest decrease in travel times during the PM peak was also observed for Route 352

in the southbound direction, which decreased travel times by 22%.

Table 3-5: Comparison of Average Travel Time (in seconds) between Existing and

Optimized Phases – AM Peak Period

Route Direction Before


Change % Change

350 EB 736 685 -51 -6.9%

WB 849 822 -28 -3.2%

352 NB 545 525 -20 -3.7%

SB 592 538 -54 -9.1%

364 EB 1117 1139 22 2.0%

WB 1214 1185 -28 -2.3%

- 20 -


Optimized Phases – PM Peak Period

Route Direction Before


Change % Change

350 EB 1027 943 -84 -8%

WB 798 793 -5 -1%

352 NB 603 523 -80 -13%

SB 590 460 -130 -22%

364 EB 1317 1355 38 3%

WB 1378 1180 -198 -14%


3.2.2.1 Travel Time Variance -- Bus Ride Along Data


decreased for Pace bus routes in most directions during the AM and PM peak periods. Tables 3-

3 and 3-4 display the comparison of average travel time variation between the Existing and

Optimized phases during the AM and PM peaks, respectively. The largest decrease in travel

time variation during the AM peak was observed for Route 352 in the southbound direction

(37%), while the largest decrease in the PM peak was observed for Route 350 (70%).

Table 3-3: Comparison of Average Travel Time Variation (in seconds) between Existing

and Optimized Phases – AM Peak Period

Route Direction

Before

(Existing) Optimized Change % Change

350 EB 108 82 -25.8 -24%

WB 72 160 88.3 123%

352 NB 132 102 -29.2 -22%

SB 135 85 -50.4 -37%

364 EB 84 150 65.3 77%

WB 259 174 -84.7 -33%

- 21 -

Table 3-4: Comparison of Average Travel Time Variation (in seconds) between Existing

and Optimized Phases – PM Peak Period

Route Direction

Before

(Existing) Optimized Change % Change

350 EB 217 79 -138.1 -64%

WB 104 31 -72.8 -70%

352 NB 81 83 1.7 2%

SB 89 61 -28.0 -32%

364 EB 270 157 -112.8 -42%

WB 388 190 -197.4 -51%

3.2.3 General Traffic Mobility

3.2.3.1 Travel Times -- Field Floating Car Data

Average Car Travel Time: The analysis results show that the car travel times improved along

both of the east and west-bound corridors on which traffic signal timing optimization was

performed in the AM, midday (MD), and PM peak periods. Table 3-5 displays the travel time

savings to general traffic in absolute and percentage terms. In general, car travel time savings

along IL 83 (147th

Ave.) were greater than those savings experienced along US 6 (159th

St.).


Optimized Phases – AM, Midday, and PM Peak Periods

Route Direction From To Peak

Period Before

(Existing) Optimized (TSP Off) Change

%

Change

159th

St (US 6)

EB Carse Ave.

Woodlawn Ave

AM 405 366 -39 -10%

Midday 447 351 -96 -21%

PM 479 361 -118 -25%

WB Woodlaw

n Ave. Carse Ave.

AM 432 312 -120 -28%

Midday 449 330 -119 -27%

PM 513 366 -147 -29%

147th

St IL 83

EB Dixie

Highway Michigan City Rd

AM 885 566 -319 -36%

Midday 841 531 -310 -37%

PM 1060 641 -419 -40%

WB Michigan City Rd

Dixie Highway

AM 917 545 -371 -41%

Midday 825 556 -269 -33%

PM 1159 708 -451 -39%

- 22 -

3.3 TSP Implementation Results


Optimized (after traffic signal optimization) and TSP (after TSP implementation) conditions.


3.3.1.1 Travel Times -- Bus Ride Along Data

Average Bus Travel Time: The analysis results show that the bus travel times improved in some

directions during the AM and PM peak periods, but did not improve in all directions for all Pace

bus routes. Tables 3-6 and 3-7 display the percentage change in average bus travel times

between the Optimized (TSP Off) and TSP On conditions during the AM and PM peaks,

respectively. The largest decrease in travel times during the AM peak was observed for Route

352 in the southbound direction, which decreased travel times by 4%. The largest decrease in

travel times during the PM peak was observed for Route 350 in the eastbound direction, which

decreased travel times by 8%.

Table 3-6: Comparison of Average Travel Time (in seconds) between Optimized (TSP Off)

and TSP On Conditions – AM Peak Period

Route Direction TSP Off TSP Change % Change

350 EB 685 792 107 16%

WB 822 876 54 7%

352 NB 525 575 50 10%

SB 538 519 -19 -4%

364 EB 1139 1314 175 15%

WB 1185 1164 -21 -2%

Table 3-7: Comparison of Average Travel Time (in seconds) between Optimized (TSP Off)

and TSP On Conditions – PM Peak Period

Route Direction TSP Off TSP Change % Change

350 EB 943 871 -72 -8%

WB 793 897 104 13%

352 NB 523 531 9 2%

SB 460 484 24 5%

364 EB 1355 1292 -63 -5%

WB 1180 1166 -14 -1%

- 23 -

3.3.1.2 Intersection Stops -- Bus Ride Along Data

Number of Intersection Stops: The analysis results show that Pace buses stopped less at TSP-

equipped signalized intersections after TSP system was operational. Tables 3-10 through 3-15

display the number of stops that were experienced by Routes 350, 352, and 364, respectively, by

direction of travel. Decreases in the number of stops are highlighted in blue. The largest

decrease in the number of stops made by a Pace bus route was Route 350 in the eastbound

direction.

Table 3-10: Comparison of Number of Stops at TSP Intersection between Optimized (TSP

Off) and TSP On Conditions – Route 350 EB

TSP Intersection AM Peak Period PM Peak Period

TSP Off TSP On Change TSP Off TSP On Change

147th St @ Halsted St 4 3 -1 8 3 -5

147th St @ LaSalle St 0 1 1 1 0 -1

147th St @ Indiana Ave/State St 2 2 0 4 0 -4

147th St @ Chicago Rd/South Park

Ave 1 2 1 1 0 -1

147th St @ Cottage Grove Ave 1 2 1 2 0 -2

147th St @ Greenwood Rd 1 2 1 0 4 4

147th St @ Woodlawn Ave 0 0 0 3 0 -3

147th St @ Lincoln Ave/Michigan

City Rd 2 4 2 4 3 -1


Off) and TSP On Conditions – Route 350 WB

TSP Intersection

AM Peak Period PM Peak Period


147th St @ Halsted St 3 4 1 3 2 -1

147th St @ LaSalle St 0 0 0 0 1 1

147th St @ Indiana Ave/State St 2 1 -1 0 4 4

147th St @ Chicago Rd/South Park Ave 3 2 -1 5 3 -2

147th St @ Cottage Grove Ave 0 0 0 0 1 1

147th St @ Greenwood Rd 0 3 3 3 2 -1

147th St @ Woodlawn Ave 0 3 3 3 3 0

147th St @ Lincoln Ave/Michigan City

Rd 1 1 0 3 3 0

- 24 -


Off) and TSP On Conditions – Route 352 NB

TSP Intersection



Halsted St @ 147th St 6 4 -2 7 5 -2

Halsted St @ 144th St 2 0 -2 3 2 -1

Halsted St @ 138th St 2 1 -1 3 3 0


Off) and TSP On Conditions – Route 352 SB

TSP Intersection


TSP Off TSP On

Chang

e TSP Off TSP On

Chang

e

Halsted St @ 147th St 4 4 0 3 4 1

Halsted St @ 144th St 3 2 -1 4 1 -3

Halsted St @ 138th St 6 3 -3 3 0 -3


Off) and TSP On Conditions – Route 364 EB

TSP Intersection



Park Ave @ 154th St 1 3 2 2 1 -1

Park Ave @ 155th St 4 3 -1 3 3 0

Park Ave @ 157th St 5 2 -3 2 2 0

159th St @ Vincennes Rd 1 0 -1 5 1 -4


159th St @ Wausau Ave 3 2 -1 0 2 2

159th St @ Chicago Rd/South Park Ave 1 2 1 3 2 -1


159th St @ Ellis Ave 3 3 0 4 2 -2

159th St @ Woodlawn Ave 2 1 -1 1 3 2

- 25 -


Off) and TSP On Conditions – Route 364 WB

TSP Intersection



Park Ave @ 154th St 4 2 -2 3 3 0

Park Ave @ 155th St 2 3 1 4 4 0

Park Ave @ 157th St 2 2 0 4 2 -2



159th St @ Wausau Ave 1 1 0 1 0 -1

159th St @ Chicago Rd/South Park Ave 1 3 2 1 3 2


159th St @ Ellis Ave 1 1 0 3 1 -2


3.3.1.3 Intersection Delay -- Bus Ride Along Data

Average Bus Intersection Delay: The analysis results show that average bus intersection delays

decreased at TSP-equipped signalized intersections after TSP system was operational. Tables 3-

16 through 3-21 display the difference for intersection delays that were experienced by Routes

350, 352, and 364, respectively, by direction of travel. Decreases in the intersection delays are

highlighted in blue. The largest decrease in intersection delays experienced by a Pace bus route

was Route 350 in the eastbound direction. Route 364 also experienced large decreases in

intersection delays in both the eastbound and westbound directions.

Table 3-16: Comparison of Intersection Delay (in seconds) at TSP Intersections between

Optimized (TSP Off) and TSP On Conditions – Route 350 EB

TSP Intersection



147th St @ Halsted St 47 50 3 478 177 -301

147th St @ LaSalle St 0 5 5 8 0 -8

147th St @ Indiana Ave/State St 80 20 -60 120 0 -120

147th St @ Chicago Rd/South

Park Ave 7 29 22 35 0 -35

147th St @ Cottage Grove Ave 20 6 -14 28 0 -28

147th St @ Greenwood Rd 14 36 22 0 99 99


147th St @ Lincoln Ave/Michigan

City Rd 47 124 77 45 83 38

- 26 -


Optimized (TSP Off) and TSP On Conditions – Route 350 WB

TSP Intersection


TSP Off TSP On

Chang

e TSP Off TSP On

Chang

e

147th St @ Halsted St 77 86 9 61 86 25

147th St @ LaSalle St 0 0 0 0 18 18

147th St @ Indiana Ave/State St 45 2 -43 0 15 15

147th St @ Chicago Rd/South Park Ave 100 81 -19 158 111 -47


147th St @ Greenwood Rd 0 24 24 96 50 -46

147th St @ Woodlawn Ave 0 34 34 59 73 14

147th St @ Lincoln Ave/Michigan City

Rd 30 3 -27 40 27 -13


Optimized (TSP Off) and TSP On Conditions – Route 352 NB

TSP Intersection



Halsted St @ 147th St 259 176 -83 292 262 -30

Halsted St @ 144th St 26 0 -26 23 46 23

Halsted St @ 138th St 35 18 -17 55 40 -15


Optimized (TSP Off) and TSP On Conditions – Route 352 SB

TSP Intersection



Halsted St @ 147th St 257 18 -239 115 147 32

Halsted St @ 144th St 32 30 -2 74 6 -68

Halsted St @ 138th St 82 66 -16 32 0 -32

- 27 -


Optimized (TSP Off) and TSP On Conditions – Route 364 EB

TSP Intersection


TSP Off TSP On

Chang

e TSP Off TSP On

Chang

e

Park Ave @ 154th St 2 34 32 3 15 12

Park Ave @ 155th St 220 135 -85 115 98 -17

Park Ave @ 157th St 207 39 -168 78 83 5



159th St @ Wausau Ave 34 41 7 0 66 66

159th St @ Chicago Rd/South Park Ave 46 48 2 117 21 -96


159th St @ Ellis Ave 35 50 15 82 41 -41

159th St @ Woodlawn Ave 50 20 -30 39 59 20


Optimized (TSP Off) and TSP On Conditions – Route 364 WB

TSP Intersection


TSP Off TSP On

Chang

e TSP Off TSP On

Chang

e

Park Ave @ 154th St 71 25 -46 28 27 -1

Park Ave @ 155th St 48 114 66 119 154 35

Park Ave @ 157th St 33 75 42 66 15 -51


159th St @ Indiana Ave/State St 141 100 -41 398 186 -212

159th St @ Wausau Ave 30 27 -3 3 0 -3

159th St @ Chicago Rd/South Park Ave 5 42 37 46 70 24

159th St @ Cottage Grove Ave 28 20 -8 10 12 2

159th St @ Ellis Ave 18 12 -6 52 25 -27


3.3.1.4 Number of Stops at Corridor Level -- Bus Ride Along Data

Number of Intersection Stops on a Corridor: The analysis results show that the number of stops

experienced on a corridor level decreased for all Pace bus routes in most directions of travel.

Table 3-22 displays the number of stops experienced on a corridor level for Routes 350, 352, and

364 during both the AM and PM peak periods. The PM peak period witnessed a greater decrease

in the number of stops made by Pace bus routes.

- 28 -

Table 3-22: Comparison of Number of Stops at Corridor Level between Optimized (TSP

Off) and TSP On Conditions

Route

Number of

Stops


TSP Off TSP On

Chang

e TSP Off TSP On

Chang

e

350EB 8 11 16 5 23 10 -13

350WB 8 9 14 5 17 19 2

352NB 3 10 5 -5 13 10 -3

352SB 3 13 9 -4 10 5 -5

364EB 10 27 27 0 33 24 -9

364WB 10 24 21 -3 35 22 -13

Bus Corridor Delay -- Bus Ride Along Data

Average Bus Corridor Delay: The analysis results show that intersection delays experienced on a

corridor level decreased for all Pace bus routes in most directions. Table 3-23 displays this

measure for Routes 350, 352, and 364 during the AM and PM peak periods. The PM peak

period witnessed a greater decrease in the average bus corridor delays experienced by Pace bus

routes.

Table 3-23: Comparison of Bus Corridor Delay (in seconds) between Optimized (TSP Off)

and TSP On Conditions

Route TSP Intersection



350EB 8 215 270 55 768 359 -409

350WB 8 252 230 -22 414 392 -22

352NB 3 320 194 -126 370 348 -22

352SB 3 371 114 -257 221 153 -68

364EB 10 962 996 34 1091 739 -352

364WB 10 694 522 -172 1046 753 -293

Travel Time -- Pace IBS Bus Data

Average Bus Travel Time: The analysis results show that the bus travel times (measured by Pace

IBS) improved in some directions during the AM and PM peak periods, but did not improve in

all directions for all Pace bus routes. Tables 3-24 and 3-25 display the percentage change in

average bus travel times between the Optimized (TSP Off) and TSP On conditions during the

AM and PM peaks, respectively. The largest decrease in travel times during the AM peak was

- 29 -

observed for Route 364 in the westbound direction, which decreased travel times by 3.5%. The

largest decrease in travel times during the PM peak was observed for Route 352 in the

northbound direction, which decreased travel times by 11.2%.

Table 3-24: Comparison of Travel Time (in seconds) between Optimized (TSP Off) and

TSP On Conditions – AM Peak Period

Route From To TSP Off TSP

Change

(Sec)

%

Change

350 EB HTC Torrence Ave 965 1042 76 7.9%

350 WB Torrence Ave HTC 1047 1108 61 5.8%

352 NB HTC 127th St 647 689 43 6.6%

352 SB 127th St HTC 826 883 57 6.9%

364 EB HTC River Oaks Center 1681 1678 -3 -0.2%

364 WB River Oaks Center HTC 2093 2021 -73 -3.5%

Table 3-25: Comparison of Travel Time (in seconds) between Optimized (TSP Off) and

TSP On Conditions – PM Peak Period

Route From To TSP Off TSP

Change

(Sec)

%

Change


350 WB Torrence Ave HTC 1203 1090 -113 -9.4%

352 NB HTC 127th St 823 731 -92 -11.2%

352 SB 127th St HTC 866 821 -45 -5.2%

364 EB HTC River Oaks Center 1850 1804 -46 -2.5%

364 WB River Oaks Center HTC 2034 2062 28 1.4%

Travel Time Delay -- Pace IBS Bus Data

Average Bus Travel Time Delay: The analysis results show that the bus travel time delays (the

difference between the field-observed bus travel time and scheduled bus travel time) decreased

in some directions during the AM and PM peak periods, but did not decrease in all directions for

all Pace bus routes. Tables 3-26 and 3-27 display the percentage change in travel time delays

between the Optimized (TSP Off) and TSP On conditions during the AM and PM peaks,

respectively. The largest decrease in travel time delays during the AM peak was observed for

Route 364 in the westbound direction, which decreased travel time delays by 14.7%. The largest

decrease in travel time delays during the PM peak was observed for Route 352 in the northbound

direction, which decreased travel time delays by 79.3%.

- 30 -

Table 3-26: Comparison of Travel Time Delay (in seconds) between Optimized (TSP Off)


Route From To TSP Off TSP Change

%

Change

350 EB HTC Torrence Ave 29 56 27 93%

350 WB Torrence Ave HTC 15 58 44 292%

352 NB HTC 127th St 1 29 28 2240%

352 SB 127th St HTC 168 183 15 8.9%

364 EB HTC River Oaks Center 63 124 61 96.3%


Table 3-27: Comparison of Travel Time Delay (in seconds) between Optimized (TSP Off)



%

Change



352 NB HTC 127th St 102 21 -81 -79.3%

352 SB 127th St HTC 127 86 -42 -32.8%



Transit Reliability

Travel Time Variation -- Bus Ride Along Data


decreased in some directions during the AM and PM peak periods, but did not decrease in all

directions for all Pace bus routes. Tables 3-8 and 3-9 display the comparison of average travel

time variation between the Optimized (TSP Off) and TSP On conditions during the AM and PM

peaks, respectively. The largest decrease in travel time variation during the AM peak was

observed for Route 364 in the eastbound direction (52%), while the largest decrease in the PM

peak was also observed for Route 364 in both the east and westbound directions (31%).

Table 3-8: Comparison of Average Travel Time Variation (in seconds) between Optimized

(TSP Off) and TSP On Conditions – AM Peak Period

Route TSP Off TSP Change % Change

350 EB 82 125 42.9 52%

350 WB 160 117 -43.7 -27%

352 NB 102 110 7.9 8%

- 31 -

352 SB 85 47 -38.0 -45%

364 EB 150 72 -77.5 -52%

364 WB 174 169 -5.4 -3%

Table 3-9: Comparison of Average Travel Time Variation (in seconds) between Optimized

(TSP Off) and TSP On Conditions – PM Peak Period

Route TSP Off TSP Change % Change

350 EB 79 110 31.3 40%

350 WB 31 51 20.4 66%

352 NB 83 146 62.9 76%

352 SB 61 70 9.2 15%

364 EB 157 109 -48.0 -31%

364 WB 190 132 -58.5 -31%

Travel Time Variation -- Pace IBS Bus Data

Bus Travel Time Variation: The analysis results show that the bus travel time variations

(measured by Pace IBS data) decreased in some directions during the AM and PM peak periods,

but did not decrease in all directions for all Pace bus routes. Tables 3-28 and 3-29 display the

percentage change in travel time variations between the Optimized (TSP Off) and TSP On

conditions during the AM and PM peaks, respectively. The largest decrease in travel time

variation during the AM peak was observed for Route 364 in the westbound direction, which

decreased travel time variation by 63.5%. The largest decrease in travel time variation during

the PM peak was observed for Route 350 in the westbound direction, which decreased travel

time delays by 78.6%.

- 32 -

Table 3-28: Comparison of Travel Time Variation (in seconds) between Optimized (TSP

Off) and TSP On Conditions – AM Peak Period


%

Change


350 WB Torrence Ave HTC 72 147 76 105.5%

352 NB HTC 127th St 57 147 90 156.9%

352 SB 127th St HTC 225 217 -8 -3.4%



Table 3-29: Comparison of Travel Time Variation (in seconds) between Optimized (TSP

Off) and TSP On Conditions – PM Peak Period


%

Change



352 NB HTC 127th St 198 83 -115 -58.3%

352 SB 127th St HTC 267 252 -15 -5.5%



Arrival Time Deviation -- Pace IBS Bus Data

Bus Arrival Time Deviation: The analysis results show that the bus arrival travel time variations



percentage change in arrival time deviations between the Optimized (TSP Off) and TSP On

conditions during the AM and PM peaks, respectively. The largest decreases in an arrival time

deviations during the AM peak were observed for Route 364 in the westbound direction. The

largest decrease in arrival time deviations during the PM peak was observed for Route 350 in the

eastbound direction.

- 33 -

Table 3-30: Comparison of Arrival Time Deviation (in seconds) between Optimized (TSP

Off) and TSP On Conditions – AM Peak Period

Route Crossing Street TSP Off TSP Change % Change

350 EB Halsted / Sibley / 147th 153 152 -1 -1%

Sibley / Chicago Rd. 114 140 25 22%

Sibley / Torrence 63 138 75 119%

350 WB Sibley / Torrence 105 65 -40 -38%

Halsted / Sibley / 147th 87 55 -32 -36%

Harvey Transportation Center 68 104 36 54%

352 NB Halsted / 127th St 72 215 143 198%

352 SB Harvey Transportation Center 262 298 36 14%

364 EB South Suburban 166 284 117 71%

Hwy 6 Cottage Grove 220 287 66 30%

River Oaks Center 295 332 37 12%

364 WB Hwy 6 Cottage Grove 247 121 -126 -51%

South Suburban 284 184 -101 -35%

Harvey Transportation Center 542 449 -93 -17%

Table 3-31: Comparison of Arrival Time Deviation (in seconds) between Optimized (TSP

Off) and TSP On Conditions – PM Peak Period

Route Crossing Street TSP Off TSP Change % Change

350 EB Halsted / Sibley / 147th 295 148 -147 -50%

Sibley / Chicago Rd. 263 121 -142 -54%

Sibley / Torrence 221 111 -110 -50%

350 WB Sibley / Torrence 197 274 78 40%

Halsted / Sibley / 147th 170 277 107 63%

Harvey Transportation Center 343 266 -77 -22%

352 NB Halsted / 127th St 378 300 -78 -21%

352 SB Harvey Transportation Center 314 357 43 14%

364 EB South Suburban 298 411 112 38%

Hwy 6 Cottage Grove 329 413 85 26%

River Oaks Center 363 463 100 27%

364 WB Hwy 6 Cottage Grove 354 861 507 143%

South Suburban 392 913 521 133%

Harvey Transportation Center 468 1106 639 137%

- 34 -

Number of Delayed Buses -- Pace IBS Bus Data

Number of Delayed Buses: The analysis results show that the number of delayed buses



differences in the number of delayed buses between the Optimized (TSP Off) and TSP On

conditions during the AM and PM peaks, respectively. The largest decreases in delayed buses

during the AM peak were observed for Route 350 in the eastbound direction. The largest

decrease in the number of delayed buses during the PM peak was also observed for Route 350 in

the eastbound direction.

Table 3-32: Comparison of the Number of Delayed Buses between Optimized (TSP Off)


Route Crossing Street TSP Off TSP Number

350 EB Halsted / Sibley / 147th 10 9 -1

Sibley / Chicago Rd. 7 6 -2

Sibley / Torrence 4 3 -1

350 WB Sibley / Torrence 5 5 0

Halsted / Sibley / 147th 5 5 0

Harvey Transportation Center 3 6 3

352 NB Halsted / 127th St 1 3 2

352 SB Harvey Transportation Center 5 5 0

364 EB South Suburban 2 3 1

Hwy 6 Cottage Grove 3 2 -1

River Oaks Center 4 2 -2

364 WB Hwy 6 Cottage Grove 3 2 0

South Suburban 3 3 0


- 35 -

Table 3-33: Comparison of the Number of Delayed Buses between Optimized (TSP Off)


Route Crossing Street Phase 2 Phase 3 Number

350 EB Halsted / Sibley / 147th 7 6 -1

Sibley / Chicago Rd. 7 5 -3

Sibley / Torrence 5 5 0

350 WB Sibley / Torrence 6 6 0

Halsted / Sibley / 147th 4 5 1


352 NB Halsted / 127th St 8 8 0

352 SB Harvey Transportation Center 9 10 1

364 EB South Suburban 5 6 1

Hwy 6 Cottage Grove 5 5 0

River Oaks Center 5 4 -1

364 WB Hwy 6 Cottage Grove 6 5 -1

South Suburban 4 5 1


General Traffic Mobility

Car Travel Time at Corridor Level

Average Car Travel Time: The analysis results show that the car travel times improved in some

directions during the AM, midday (MD), and PM peak periods, but not in all directions. Tables

3-34, 3-35, and 3-36 display the car travel times on a corridor level in absolute and percentage

terms. In general, car travel time savings were greater during the off peak period than they were

during the AM and PM peak periods.

Table 3-34: Comparison of Average Travel Time between Optimized (TSP Off) and TSP

On Conditions – AM Peak Period


%

Change

147th EB 147th/Broadway 147th/I-94 377 410 33 9%

147th WB 147th/I-94 147th/I-94 373 407 35 9%

159th EB 159th/Carse 159th/Woodlawn 496 547 51 10%

159th WB 159th/Woodlawn 159th/Carse 540 542 2 0%

Halsted NB Halsted/160th Halsted/Blue Island 644 636 -9 -1%

Halsted SB Halsted/Blue Island Halsted/160th 663 668 4 1%

- 36 -


On Conditions – OFF Peak


%

Change

147 EB 147th/Broadway 147th/I-94 438 483 45 10%

147 WB 147th/I-94 147th/I-94 491 459 -32 -7%

Halsted NB Halsted/160th Halsted/Blue Island 678 579 -98 -15%

Halsted SB Halsted/Blue Island Halsted/160th 706 624 -83 -12%

159 EB 159th/Carse 159th/Woodlawn 544 549 6 1%

159 WB 159th/Woodlawn 159th/Carse 568 517 -51 -9%


On Conditions – PM Peak Period


%

Change

147 EB 147th/Broadway 147th/I-94 362 435 73 20%

147 WB 147th/I-94 147th/I-94 400 447 47 12%

Halsted NB Halsted/160th Halsted/Blue Island 624 631 7 1%

Halsted SB Halsted/Blue Island Halsted/160th 632 630 -3 0%

159 EB 159th/Carse 159th/Woodlawn 493 430 -64 -13%

159 WB 159th/Woodlawn 159th/Carse 527 457 -70 -13%

Tables 3-37, 3-38 and 3-39 summarize the percentage change to all the MOEs for each route.

These summary tables provide an overview for the overall analysis results.

- 37 -

Table 3-37: Route 350

Summary of MOEs: Comparison of Before (Existing) vs. Optimized (TSP Off)

and Optimized (TSP Off) vs. After (TSP On)

Case Category MOEs Data Sets

EB WB

AM PM AM PM

Before

(Existing)

vs. Optimized

(TSP Off)

Transit Mobility Average Travel Time Bus Ride Along Data -6.9% -8% -3.2% -1%

Transit Reliability Average Travel Time Variation Bus Ride Along Data -24% -64% 123% -70%

General Traffic Mobility Average Travel Time Floating Car Data 10% to 49%

Optimized

(TSP Off)

vs

After (TSP On)

Transit Mobility

Average Travel Time Bus Ride Along Data 16% -8% 7% 13%

Pace IBS Bus Data 8% 5% 6% -9%

No. of Stops at Corridor Level Bus Ride Along Data 45% -57% 56% 12%

Bus Corridor Delay Bus Ride Along Data 26% -53% -9% -5%

Transit Reliability

Average Travel Time Variation Bus Ride Along Data 52% 40% -27% 66%

Pace IBS Bus Data 27% 117% 105% -79%

Average Bus Arrival Time Deviation at Corridor Level Pace IBS Bus Data 30% -51% -14% 15%

Total Number of Delayed Buses at Corridor Level Pace IBS Bus Data -17% -18% 23% 31%

General Traffic Mobility Average Travel Time Floating Car Data 9% 10% 9% -7%

- 38 -





NB SB

AM PM AM PM

Before

(Existing)

vs. Optimized

(TSP Off)

Transit Mobility Average Travel Time Bus Ride Along Data -3.7% -13% -9.1% -22%

Transit Reliability Average Travel Time Variation Bus Ride Along Data -22% 2% -37% -32%

General Traffic Mobility Average Travel Time Floating Car Data N/A

Optimized

(TSP Off)

vs

After (TSP On)

Transit Mobility

Average Travel Time Bus Ride Along Data 10% 2% -4% 5%

Pace IBS Bus Data 7% -11% 7% -5%

No. of Stops at Corridor Level Bus Ride Along Data -50% -23% -31% -50%

Bus Corridor Delay Bus Ride Along Data -39% -6% -69% -31%

Transit Reliability

Average Travel Time Variation Bus Ride Along Data 8% 76% -45% 15%

Pace IBS Bus Data 157% -58% -3% -5%

Average Bus Arrival Time Deviation at Corridor Level Pace IBS Bus Data 198% -21% 14% 14%

Total Number of Delayed Buses at Corridor Level Pace IBS Bus Data 200% 0% 0% 11%

General Traffic Mobility Average Travel Time Floating Car Data -1% -15% 1% -12%

- 39 -





EB WB

AM PM AM PM

Before

(Existing)

vs. Optimized

(TSP Off)

Transit Mobility Average Travel Time Bus Ride Along Data 2.0% 3% -2.3% -14%

Transit Reliability Average Travel Time Variation Bus Ride Along Data 77% -42% -33% -51%

General Traffic Mobility Average Travel Time Floating Car Data 10% to 49%

Optimized

(TSP Off)

vs

After (TSP On)

Transit Mobility

Average Travel Time Bus Ride Along Data 15% -5% -2% -1%

Pace IBS Bus Data 0% -5% -3% -2%

No. of Stops at Corridor Level Bus Ride Along Data 0% -27% -13% -37%

Bus Corridor Delay Bus Ride Along Data 4% -32% -25% -28%

Transit Reliability

Average Travel Time Variation Bus Ride Along Data -52% -31% -3% -31%

Pace IBS Bus Data 53% 1% -64% 62%

Average Bus Arrival Time Deviation at Corridor Level Pace IBS Bus Data 32% 30% -30% 137%

Total Number of Delayed Buses at Corridor Level Pace IBS Bus Data -22% 0% -11% 0%

General Traffic Mobility Average Travel Time Floating Car Data 10% 1% 0% -9%

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4.0 QUALITATIVE EVALUATION MEASURES

The evaluation of the Harvey Area TSP Demonstration Project cannot be measured solely on the

results of the quantitative data analysis. The purpose of the demonstration project is to help

educate and inform Pace on how to best implement a TSP program, the benefits that can be

realized from the deployment of TSP in coordination with other transit technologies, and to

provide a roadmap for future TSP deployments. It is important to take note of the invaluable

experience and lessons learned that Pace has gained during the Harvey Area TSP Demonstration

Project that will help ensure that this and future TSP deployments are as successful as possible.

4.1 Experiences and Lessons Learned in TSP System Deployment

The Harvey Area TSP Demonstration Project was a strategically planned effort intended to

provide Pace with know-how on all aspects of implementing a TSP program. Following the

Systems Engineering process for Intelligent Transportation Systems (ITS), the project afforded

Pace the opportunity to develop a TSP system from the ground up and resulted in benefits that

cannot be quantified in hard numbers but that are equally as important to the future of the Pace

TSP Initiative.

4.1.1 TSP System Planning and Design

The planning and design of the TSP Demonstration began with stakeholder outreach and

culminated with the development of an RFP that lead to the construction of the TSP system. Key

planning and design components of the TSP Demonstration are outlined below.

4.1.1.1 Coordinate with Public Agencies A critical first step in the Harvey Area TSP Demonstration was the coordination with local

public agencies and stakeholders affected by TSP Deployment. In all, 17 stakeholder interviews

with over 40 agency participants were conducted for the Regional TSP Deployment Plan and

TSP Demonstration project, including representatives from the Illinois DOT and the local

communities that are affected by the TSP Demonstration project such as Harvey, South Holland,

and Phoenix. This stakeholder outreach provided Pace with an opportunity to build broad-based

support for the TSP Initiative.

4.1.1.2 Perform Traffic Signal Needs Assessment The purpose of the needs assessment was to select a subset of all signal controllers around the

HTC at which TSP would be deployed and studied in subsequent TSP Demonstration activities.

A survey of the existing traffic signal controllers in the Harvey Area TSP Demonstration Project

study area was performed to determine which controllers possessed internal capabilities for TSP

operations. The location of coordinated signal systems was also noted to understand where re-

optimization of traffic signal timings would need to occur. The needs assessment was crucial in

helping Pace to better understand the limitations of the existing traffic signal equipment that is

typically deployed by the Illinois DOT and other jurisdictions. The TSP Demonstration project

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included a large cross-section of the traffic signal equipment that Pace will encounter on future

TSP projects throughout the region.

4.1.1.3 Develop High-Level Requirements High-level requirements defined how the TSP system would operate – it defined how the

on-board TSP equipment would function and be integrated with the IBS, how TSP would assign

priority to buses and emergency vehicles, how TSP would function at near-side bus stops, etc.

These high-level requirements were necessary to define at an early stage so that team members

possessed a clear understanding of how TSP would function.

The TSP System operates on the conditional basis of schedule adherence, and, as a result,

integration of on-board TSP equipment with Pace’s IBS was an important feature that needed to

be incorporated into the requirements. Another requirement accounts for the presence of

emergency vehicles utilizing Emergency Vehicle Preemption (EVP) equipment at intersections

where TSP equipment is deployed. In the event of simultaneous requests for priority, emergency

vehicles will be granted signal preemption over transit vehicles requesting signal priority.

Developing these high-level requirements helped Pace to ensure that the TSP system was as

efficient as possible by addressing all aspects of bus and traffic signal operations and how they

affected the TSP system.

4.1.1.4 Traffic Signal Timing Optimization and TSP Signal Timing Strategies Utilizing the Illinois DOT District 1 Signal Coordination and Timing (SCAT) Study process and

standard traffic engineering practices for traffic signal timing optimization, the optimization of

coordinated traffic signal systems and isolated traffic signals helped to ensure that the traffic

signals along the TSP corridors were operating so as to provide efficient progression to all traffic.

The optimized traffic signal timings were then used to determine the TSP signal timing strategies

that were implemented at each TSP intersection.

4.1.1.5 TSP Technology Assessment A thorough evaluation of the available TSP technologies allowed Pace to weigh the advantages

and disadvantages of the various commercially available off the shelf (COTS) TSP systems

available at the time.

The TSP technology assessment process afforded Pace the opportunity to see each of the

available TSP systems in a live demonstration using the same traffic signal equipment that would

be encountered in the field for the TSP Demonstration project. The TSP technology assessment

then led to the development of a Request for Proposals (RFP) that would result in the selection of

a TSP System for the Harvey Area TSP Demonstration project. This RFP also contained the

requirements for the TSP field operations test plan and specifications, which the selected vendor

and construction contractor of the TSP System were required to adhere to.

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4.1.2 TSP System Deployment

The deployment of the TSP system provided Pace with many valuable experiences and lessons

that will go a long way to ensuring the success of the Pace TSP Initiative and extracting

maximum value from this and future TSP deployments.

4.1.2.1 On-board TSP System Installation As discussed previously, integration of the TSP system with the Pace IBS was a critical

component of the TSP Demonstration project. Pace Tech Services worked closely with the TSP

system contractor to ensure that the TSP equipment was installed properly to work with the

various components of the Pace IBS, including the status of the bus’s schedule adherence, which

is used to trigger TSP when a bus is 1 minute or more behind schedule. Additionally, it was

important that the TSP system reacted accordingly to the opening of the bus doors and the

activation of the next stop pull cords and push buttons at near-side bus stops so as to not actuate

TSP when the bus was not able to utilize it.

4.1.2.1 On-street TSP System Deployment The deployment of the TSP system on the street along and between the TSP corridors was a

multi-faceted undertaking that included installing the TSP system vendor’s equipment at the

selected TSP intersections and installing both wired (fiber-optic) and wireless (Wi-Fi)

communications equipment throughout the project area to connect the TSP-equipped buses and

intersections and to connect the TSP system to Pace Headquarters in Arlington Heights so that

Pace could monitor, configure, and maintain the TSP system remotely.

4.2 Institutional Considerations

4.2.1 Internal Time Points and Running Time Adjustments Combining the use of the many powerful transit technologies that Pace has at its disposal, Pace

Service Planning has begun the iterative process of using HASTUS ATP runtime analysis and

IBS data analysis to determine where Pace can realize efficiencies in their operations by taking

advantage of improved travel times and decreased schedule deviation afforded by the TSP

system. For example, if a bus enters a TSP segment 8 minutes down on its schedule, Pace will

be able to analyze its on-time performance within the TSP segment to determine if it is possible

to decrease the running time with the TSP segment.

The first step in this process was for Pace Service Planning to establish the location of internal

time points along the TSP routes to allow for more precise evaluation of the impact of TSP on

bus performance using IBS data. These new internal time points will ensure that there are data

points within the IBS data as close as possible to the beginning and end of the TSP segments

along the 350, 352, and 364 routes. The following internal time points were added to the TSP

bus routes:

• Route 350 – one new internal time point was added at Sibley/Madison (between the

Sibley/Chicago and Sibley/Torrence time points);

- 43 -

• Route 352 – two new internal time points were added at Halsted/Jackson-Forestview

(between 127th/Halsted and Harvey TC) and 159th/Halsted (between the Harvey TC and

167th/Halsted time points);

• Route 364 – one new internal time point was added at 159th/Park (between the Cottage

Grove/Route 6 and River Oaks time points)

Route 350 already has existing time points that have allowed Pace Service Planning to analyze

the effect of TSP on travel times and on time performance. The Service Planning staff have

already begun to analyze IBS data to determine how to best adjust running times within the TSP

segment of Route 350.

It is currently expected that Pace Service Planning will implement the first round of changes to

weekday eastbound Route 350 running times based on their analysis of TSP operations in

December, 2011.

Going forward, Pace Service Planning will establish a time point at the beginning and end of all

future TSP corridors so that Pace can more easily evaluate the performance of the bus relative to

the schedule within the segment of the bus route that is equipped for TSP.

4.2.2 Crossing Routes Currently, when two buses arrive at a TSP intersection at approximately the same time, the TSP

system is configured to provide TSP to the first bus that arrives at that intersection; the second of

the two buses to arrive at the intersection will not receive TSP. This TSP operational strategy is

called “first in, first out” (FIFO). This applies to buses arriving from opposite directions (one

eastbound and one westbound) and buses arriving from crossing streets (one northbound and one

westbound), and it also applies to buses whether they are running on the same route (eastbound

and westbound 350) or running on routes that cross one another (westbound 350 and northbound

352).

Pace Service Planning has begun to look at these situations where buses are scheduled to cross

one another at approximately the same time. It is important to remember that the traffic signal

controllers are configured to not grant TSP at the same intersection in which TSP has just been

granted until signal goes through one additional cycle without TSP, regardless of the direction

that the bus is arriving from, so as to not negatively affect the performance of the intersection for

general traffic. Simply stated, TSP can only be granted at the same intersection every other

cycle. Typical cycle lengths are approximately 120 seconds in the Harvey Area TSP

Demonstration project area.

Example Scenario: If an eastbound 350 bus leaves the HTC and arrives at 147th

Street @

Halsted Street more than one minute behind schedule – because it is late leaving the HTC or

otherwise unexpectedly delayed – the eastbound 350 bus will request TSP upon arrival at the

intersection. A loaded westbound 350 bus and/or southbound 352 bus may also be scheduled to

arrive at 147th

Street @ Halsted Street at approximately the same time (or within 1 cycle length)

and may be running late to make connections to other routes at the HTC. If the intersection

grants TSP to the first bus to arrive (the eastbound 350 bus just leaving the HTC), the other two

- 44 -

bus routes will not receive TSP if they arrive during the next cycle thus further delaying those

buses. The preference would be to assure that either the westbound 350 or southbound 352 bus

receives TSP for the following reasons:

• the westbound 350 and southbound 352 routes are typically more heavily loaded and

running further behind schedule as they near the end of their runs than an eastbound 350

bus just leaving the HTC, and

• the westbound 350 and southbound 352 routes are trying to make connections at the HTC

Pace Service Planning is using IBS data to study crossing routes and to adjust running times for

specific runs to ensure that when those runs arrive at a particular TSP intersection they are not

behind schedule, do not request TSP, and thus do not deny TSP to a crossing route that has

greater need for TSP.

4.3 Other Factors that Impact TSP Benefits

It is important to understand the limitations on and the other factors that impact the quantitative

benefits that the TSP system has currently been shown to provide. There are several influences

that are beyond the control of the TSP system that either limit or are potentially detrimental to

the quantitative benefits derived from the TSP system as presented in Section 3.

Limited TSP Deployment at Intersections and on Buses While the needs assessment helped to determine the signalized intersections where TSP could

potentially benefit bus operations the most, it should be noted that the resultant TSP system only

covers a portion of the three TSP bus routes and thus limits the impact of TSP on bus operations.

The second phase of the TSP Demonstration project will see TSP deployed on signalized

intersections along Halsted Street from 159th

Street just south of the HTC to US Route 30 in

Chicago Heights. This addition to the TSP system will be a valuable test bed for studying the

effects of TSP on bus operations along a contiguous TSP corridor between two major hubs that

stretches from the Pace transfer center in Chicago Heights to the Harvey Transportation Center

in Harvey.

Similarly, only a portion of the fleet at the Pace South Division garage, 55 out of approximately

95-100 buses that service Routes, 350, 352, and 364, were outfitted with TSP system equipment

as part of the TSP Demonstration project because of budgetary limitations. Thus, during the data

collection process, great time and effort was required of the Pace South Division garage dispatch

supervisors and staff to ensure that only buses outfitted with TSP equipment were assigned to the

TSP bus routes so as not to skew the results of the evaluation.

Furthermore, while the Pace dispatch staff try their hardest to do so during the day to day

operation of the TSP system, it is not always possible to ensure that only the TSP-equipped buses

are always operating on the TSP bus routes because of various factors such as interlining and

buses being out of circulation for maintenance. These factors conspire to greatly limit the

effectiveness of the TSP system.

- 45 -

Pace Service Changes Between the time that the planning for this project started and the time that the TSP system was

deployed, tested, and ownership was taken by Pace, there have been numerous changes made to

the bus service of the three TSP bus routes, Route 350, Route 352, and Route 364.

Because these service changes happened at various times throughout the life of the TSP

Demonstration project, it is difficult to determine the positive or negative affect each of the

changes had on bus operations and how each change may have impacted the TSP system and the

potential benefits that could be realized by the system. The project budget did not allow for the

project team to collect and analyze data every time a service change was made. It was also not

possible to delay the implementation of these service changes because the service changes were

critical to Pace’s ongoing restructuring efforts and the Harvey Area TSP Demonstration project

was a complicated, multi-year effort, the first such project of its kind in the United States.

The following list summarizes project milestone dates and the various service changes that were

made during the life of the TSP Demonstration project as part of the South Cook County – Will

County Restructuring Initiative:

Jan 12, 2006 Pace TSP Initiative Project Kickoff Meeting

May 4-24, 2006 Routes 350, 352, 364 & 370 – TSP Demonstration project data collection to

establish baseline conditions before traffic signal timing optimization and TSP

deployment

Nov 20, 2006 Route 350 service change – Implement weekday schedule adjustments based

on HASTUS ATP analysis

Quarter 1, 2007 Traffic signal timing optimization implemented

Nov 23, 2008 Route 352 service change – Establish Posted Stops (Partial) operation on the

City of Chicago route segment between 95th

/Dan Ryan and 127th

/Halsted

Mar 22, 2009 Route 364 service change

� Implement weekday/weekend schedule adjustments based on HASTUS

ATP analysis

� convert to Posted Stops operation

Jun 7, 2009 Route 350 service change


ATP analysis

� convert route to Posted Stops operation

� discontinue variant trip segment serving South Suburban College (segment

transferred to Route 348)

Route 352 service change

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ATP analysis

� convert route to Posted Stops operation

� shift routing alignment from Wood St/Dixie Hwy (segments transferred to

Routes 356 & 372) to South Halsted St (segment transferred from Route

370)

Route 370 service change – Discontinue route (segment transferred to Route

352)

Aug 23, 2009 Route 352 service adjustment – Adjust last evening NB & SB trips to

operate on Halsted instead of serving Prairie State College

Jul – Aug, 2011 Routes 350, 352, 364 – TSP Demonstration project data Collection to

establish conditions after traffic signal timing optimization and TSP

deployment

Aug 21, 2011 Routes 350, 352 & 364 internal Time Point additions – To allow more

precise evaluation of the on-time performance impact of TSP:

� one new internal Time Point was added at Sibley/Madison (between

Sibley/Chicago and Sibley/Torrence) on Route 350

� two new internal Time Points were added at Halsted/Jackson-Forestview

(between 127th

/Halsted and Harvey TC) and 159th

/Halsted (between

Harvey TC and 167th

/Halsted) on Route 352

� and one new internal Time Point was added at 159th

/Park (between

Cottage Grove/Route 6 and River Oaks) on Route 364

Current Schedules Not Optimized for TSP The service changes of the South Cook County – Will County Restructuring Initiative as

previously summarized were implemented in an effort to optimize transit operations given the

current traffic conditions at the time but did not account for TSP because the TSP system was not

fully deployed. The current bus schedule was designed to accommodate the existing traffic

congestion and thus make the service more reliable by providing additional running time

between time points.

While the addition of TSP may make it possible to reduce travel times from one intersection to

the next and one time point to the next, the current schedule is designed to ensure that the bus is

running on time more often and thus minimizes the need for TSP in the first place. The bus

drivers are not allowed to run ahead of schedule and therefore cannot take advantage of the

reduced travel times that are possible with the aid of TSP. As discussed previously, Pace Service

Planning is currently analyzing how to best adjust running times while taking advantage of TSP

as much as possible in an iterative and systematic process.

- 47 -

5.0 KEY FINDINGS AND NEXT STEPS

5.1 Key Findings

The following lists some key finds based on the evaluation results:

• Overall, signal optimization improved general traffic mobility for all three routes on both

directions during both peak and off-peak periods. The average car travel times were reduced

by a range of 39 seconds to 6 minutes by route and directions during both AM, MD, and PM

peak periods. Meanwhile, transit mobility was also improved in most cases for all three

routes. Average bus travel times and variations were reduced by a range of 5 seconds to 3.3

minutes and a range of 25 sec to 3.3 minutes respectively by route during the AM and PM

peak periods along the three routes.

• Transit mobility was improved on a directional basis by peak period and route after TSP

implementation. Overall, the travel times were reduced by a range from 5 seconds to 1.2

minutes on top of the signal optimization benefits. Number of stops at a corridor level was

reduced by a range of 3 to a maximum of 13 on a directional basis by route. The bus corridor

delay was reduced by a range from 22 seconds to approximately 7 minutes by route, direction

and peak periods.

• It is observed that the PM peak periods received improvements than the AM peak. The bus

ride along data and IBS data indicate that the travel times were reduced by a range of 1% (14

sec) to 8% (1.2 min) during PM peak period on both directions for all three routes. The data

showed that delay and number of delayed buses are higher during PM peak than during AM

peak. It is anticipated that the TSP implementation would be more beneficial for buses that

experienced most delays.

• It is noted that traffic flow may be a factor that result in some areas where no improvement or

negative impact was observed. High traffic flow may cause longer travel time and high delay

for certain travel runs during the TSP implementation periods, which may reduce the

potential travel time or delay savings. In addition, variations on bus ridership, bus route and

service changes during the demonstration periods could also impact the TSP benefits.

5.2 Next Steps

Follow-up and on-going tasks need to be performed after this demonstration project is complete.

The following lists these tasks and associated details:

• Recognition of the Project: This demonstration project offers great experience and lessons

learned in TSP planning, designing, installation, testing and evaluation which provide

valuable reference for future TSP deployment. The evaluation results indicate the potential

TSP benefits that provide positive evidence in supporting future decision making. Pace

- 48 -

should share the project results with related stakeholders and technical committee members

to improve the awareness for the potential TSP benefits.

• Institutional Coordination:

o Since any TSP projects will involve at a minimum both transit agency and

traffic signal control agency, Pace should continue to coordinate and

collaborate with other involved stakeholders who operate the traffic signals

along Pace bus routes for future deployment. Agreements need to be

established as needed to avoid future institutional issues.

o Going forward, Pace Service Planning has established new internal Time

Points at the beginning and end of the TSP corridor so that Pace can more

easily evaluate the performance of the bus relative to the schedule exclusively

within the portion of the bus route that is equipped for TSP. These internal

Time Points are not included in the printed schedule and are for performance

evaluation purposes only. For instance, if a bus enters the portion of the route

that is equipped for TSP running eight minutes down on its schedule, the

Time Points at the beginning and end of the TSP portion of the route will

allow Pace to evaluate how that bus performed within that zone. Pace will be

able to easily determine if the bus continued to lose time on its schedule,

made up time on its schedule, or stayed the same.

o If buses are continually making up time on their schedule within the TSP

portion of the route when entering behind schedule, it will allow Pace to

determine how much the running time can possibly be reduced from the TSP

portion of the route to fully take advantage of TSP. That running time

removed from the TSP portion of the route could then be added to other

portions of the route where the bus is struggling to stay on schedule.

o As a policy going forward for additional planned TSP routes, adding these

internal Time Points upfront will also allow Pace to evaluate on a step-by-

step basis other changes to the route that might be planned either as part of or

within the same time-span as the TSP project. This could include such

changes as traffic signal timing optimization, route restructuring and schedule

adjustments based on Service Planning analysis, converting to Posted Stops

operation, and moving bus stops from the near-side to the far-side of a

signalized intersection. Having the internal Time Points in place before a

TSP project starts will allow Pace to isolate and evaluate the effect that each

change, including the implementation of TSP, has on the performance of the

route.

• Operations and Maintenance: Operations and maintenance are always an important and

on-going task after a TSP system is fully operational. The Pace should use vendor’s

technical support to maintain the installed system before the warranty is expired. Dedicated

technical team or staff should monitor and maintain the system operations for the long term.

An operations and maintenance plan may need to be developed to identify roles and

responsibilities for the maintenance team, and guide system operations, troubleshooting, and

preventative maintenance. Preventative maintenance should be performed for the major on-

bus and intersection TSP equipment. A maintenance budget should also be estimated to

- 49 -

cover potential coats for future system operations and maintenance, spare parts procurement,

system upgrade and necessary training.

• System Integration: The Pace should work with the vendor to integrate the installed TSP

system with existing communications links. The integration should allow the Pace to collect

TSP data, monitor and control the TSP system, and download data remotely without paying

field visit to each individual TSP intersections.

- 50 -

References Transit Signal Priority (TSP); A Planning and Implementation Handbook, ITS America, 2005.

1 An Overview of Transit Signal Priority, Intelligent Transportation Society of America (ITS America), 2004, pg ii.

2 An Overview of Transit Signal Priority, Intelligent Transportation Society of America (ITS America), 2004, pg 2.

3 An Overview of Transit Signal Priority, Intelligent Transportation Society of America (ITS America), 2004, pg 2.

4 Derived from “Transit Signal Priority (TSP); A Planning and Implementation Handbook,” ITS America, 2005, Part

III, Section 13.1. 5 Derived from “Transit Signal Priority (TSP); A Planning and Implementation Handbook,” ITS America, 2005,

pg 6. 6 Derived from “Transit Signal Priority (TSP); A Planning and Implementation Handbook,” ITS America, 2005,

Section 14.4. 7 Ibid

8 GOTO 2040 Comprehensive Regional Plan, Chicago Metropolitan Agency for Planning (CMAP), 2010, pg 272.

9 Ibid

10 Vision 2020: Blueprint for the Future, Pace, 2002.

11 Pace 2012 Proposed Budget, Pace, 2011, Appendix E, Planning Initiatives.

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