sjcog fhwa reliability cmp workshop presentation spring2016

Incorporating Reliability into the Congestion Management Process

Training Workshop

May 17, 2016

San Joaquin Council of Governments

Stockton CA

Incorporating Travel-Time Reliability into the CMP2


• Presenters• Steven Gayle, PTP, Senior Consultant, RSG Inc.

• Richard Dowling, P.E., Senior Principal Engineer, Kittelson & Associates, Inc.

• Attendees


Morning

8:30 Welcome and Introductions

8:45 Background and Workshop outcomes

9:00 Incorporating Reliability in the CMP: Part 1 - Reliability-Related

Goals, Objectives, and Performance Measures

10:00 Break

10:15 Incorporating Reliability in the CMP: Part 2 - Data for reliability

analysis and diagnosing reliability problems

11:45 Lunch

Afternoon

12:30 Feedback opportunity - questions from the morning sessions

12:45 Facilitated discussion on incorporating reliability into broader

planning efforts

1:15 Interactive session: Travel time reliability and planning in the San

Jaoquin region

2:00 Peer presentation: CMP State of the Practice

2:30 Moving forward: Developing an action agenda

3:00 Concluding remarks/adjourn


We expect that the material and activities developed for this workshop will:

• Introduce the FHWA Primer on Incorporating Reliability in the Congestion Management Process

• Facilitate discussion about reliability and enumerate how SJCOG, Caltrans, and other planning partners might fully integrate reliability into planning efforts

• Discuss the relationship to Performance Based Planning and Programming


• Background

• Introduction to Travel-Time Reliability

• How to Incorporate Reliability into the CMP


Timeline of Key Events

FEDERAL LEGISLATION

ISTEA SAFETEA-LU MAP-21 FAST ACT

CONGESTION MANAGEMENT APPROACH

Congestion Management System Congestion Management Process

RELIABILITY RESEARCH

PERFORMANCE BASED PLANNING

1991 2005 2012 2015

CMS CMP

SHRP2 Extended Completed

National Goals Rules


The Second Strategic Highway Research Program (SHRP 2)

Applied research

Focus on the most-pressing needs of highway system

Capacity

Renewal

Safety

Reliability

Systematic approach to provide tools for improving reliability of travel Defining objectives

Analytical techniques

Design procedures

Institutional approaches


Federal Legislation - MAP-21

Introduces paradigm of performance-based planning and programming

States and MPOs are expected to select investments to achieve best outcomes for system users

Performance measurement

Target setting

Reporting on outcomes

System reliability is one of seven national goals

Proposed System Performance rule published April 20


FAST Act (Fixing America’s Surface

Transportation)

• Retains the requirement for the CMP

• Makes no changes in the State and MPO requirements

for performance based planning

• Creates an optional Congestion Management Plan that

focuses on access to employment


Implementation of Reliability

Congestion Management Process is a natural implementation tool

Familiar process for many regions

Updated periodically

Focused on congestion

Implementing regional goals and objectives

Monitoring

Establishing performance measures

Developing strategies

Evaluating strategies

… but most CMPs focus only on recurring congestion


Incorporating Reliability into the CMP

Part of Planning for Operations effort

Transportation system management and operations (TSM&O) strategies

A primer to assist states and MPOs with:

Developing regional objectives

Developing performance measures

Analyzing congestion problems and needs

Identifying and assessing strategies

Evaluating strategy effectiveness


02 TOPIC INTRODUCTIONTravel-Time Reliability


• The MPO Long Range Transportation Plan is foundational.

• The LRTP states MPO priorities for transportation investments through goals and objectives.

• The Transportation Improvement Program (TIP) and Congestion Management Process (CMP) are tools for implementing the LRTP

• The TIP and CMP must reflect the goals and objectives of the LRTP.


• Goal: What does the MPO intend to achieve over the long term to mitigate congestion and/or improve travel time reliability?

• Reduce peak period freeway congestion through improved operations

• Objectives: More specific statements of proposed accomplishments that are “SMART” [Specific, Measurable, Agreed on, Realistic, Timebound]

• Reduce elapsed time of freeway incident detection to clearance by 15% in the next 5 years

• Performance Measures: What metrics will be used to determine progress on objectives?

• Total incident time averaged over a one year period.


How is congestion mitigation and reliability improvement enabled

by evolving technology? How is this likely to change by 2020?

2040?


Forecasting non-recurring congestion

• Do we have adequate tools?

Implementing the CMP: projects, strategies, actions

• Where does congestion mitigation fit among other MPO priorities?

• Where does reliability fit among congestion mitigation priorities?

• Geographic context: regionwide, corridors, subareas,

• Modal context: auto, truck/freight, transit

• Time of day context: peak v. off-peak


What is travel-time reliability?

Consistent travel times for the same trip


How is travel-time reliability assessed?

Longitudinal look at continuous data

Expands the single-day review of travel times

Variation in travel time day-to-day, holding all else equal

Same trip (point A to point B)

Same mode (vehicle, transit type)

Same time of day (AM peak, mid-day, PM peak, off-peak)

Same type of day (mid-weekday, shoulder weekday, weekend)


An example

… and adds the “Reliability Dimension” for day-to-day analysis

Source: Highway Capacity Manual, Chapter 37 – Travel Time Reliability: Supplemental, Exhibit 37-21


Why is reliability important?

Non-recurring congestion causes greater total delay than recurring congestion

Particularly in less urban areas

Public sentiment

Traveling public

Freight and trucking companies

Constraints on new roadway capacity

Federal legislation


• What drives the conversation?

• Public expectations

• Business needs

• Reporting of performance measures


Public Sentiment

Knowledge of technological advances

Experience travel in different regions

Heightened expectations

Dissemination of real-time information

Efficient management of incidents

Opinion polls (1)

63% of Americans feel that nation can no longer build its way out of traffic congestion

71% of drivers would be willing to pay a higher toll fare to save travel time


4.5 million riders33 Metro bus routes

How does reliability affect ridership?


Frei

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Ton

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in t

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1,0

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0s)

Growth in Freight Tonnage 1990 to 2012

Data Source: American Trucking Associations

Year


Freight Carriers and Shippers

Reliability paramount for profitable operations

Equipped vehicles for data collection

Just in time delivery imposes narrow windows on drivers

Automated reporting of hours of service

Cities restrict peak period deliveries


Costs of Unreliable Travel to Shippers and Carriers

Delays increase cost of transporting goods by 50% to 250% (USDOT FHWA 2006) Buffer Time Index for Trucks on Major Freight Corridors in 2005

Image Source: Freight Performance Measurement: Travel time in Freight-Significant Corridors, FHWA


Value of Incorporating Reliability Into the CMP

Systematic method to address issues is already in place

Monitoring

Problem identification

Generation of strategies

Evaluation of strategies

Provides a robust understanding of regional transportation

Recurrent congestion

Non-recurrent congestion


Value of Incorporating Reliability Into CMP

Expands the toolbox of strategies to address congestion

Cost-saving management and operations strategies

Minimize impacts


Technological Advances for Continuous

Data Collection

Permanent detectors (spot speeds)

Loop

Video

Wireless communications (point-to-point)

In-vehicle personal navigation devices

In-vehicle commercial navigation devices

Bluetooth readers

Electronic toll tags

Automatic vehicle locators (for transit)Image Source: Kittelson & Associates, Inc., FlickR


Dissemination of Devices That

Can Track Mobility

Mobile phones

2013 data indicates 10% more subscriptions than population (1)

Bluetooth

90% of all 2014 mobile phones are equipped (2)

Electronic toll tags

70% to 90% of drivers on many tolled roads

Intelligent Transportation Systems

Infrastructure

In-vehicle

Communication between them

Source: Michigan Department of Transportation, Connected Vehicle Update, October 2011, Vol. 4, No. 1, Courtesy of the U.S. Department of Transportation


Data Availability

Private vendors analyze travel times

Resellers: results available for a fee Proprietary use: trucking and delivery companies

National Performance Monitoring Research Data Set (NPMRDS)

Average travel time in 5-minute segments Data from National Highway System

From October 2011 on Interstate From July 2013 for other roads

Local sources

Traffic management centers Transit agencies Previous studies

Original data collection

Source: Kittelson & Associates, Inc.


Reliability Research and Analysis Tools

Planning for Operations

The Second Strategic Highway Research Program (SHRP 2)

Highway Capacity Manual


Five (5) Key CMP

Actions Into Which

Reliability Can Be

Incorporated

Action 8

Action 6

Action 5

Action 3

Action 1


National Resources


Where does an agency start when it comes to

incorporating reliability into the Process?


Action 1Develop objectives to

guide you through the Process.


CMP Action 1 – Develop

Regional Objectives

Resources

Incorporating Reliability Performance Measures into the Transportation Planning and Programming Processes: A Guide (SHRP 2 L05)

Congestion Management Process: A Guidebook

Advancing Metropolitan Planning for Operations: The Building Blocks of a Model Transportation Plan Incorporating Operations – A Desk Reference


CMP Action 1 – Develop Regional Objectives


Encourages examining current reliability performance before setting goals

Identifies data and types of info useful for establishing goals



Congestion Management Process: A Guidebook

Reliability goal and objective ideas

Ideal objectives are SMART

Specific

Measurable

Agreed (stakeholders from wide range of backgrounds)

Realistic

Time-bound (“by 2015”).



Sample Objectives Reduce hours of delay per capita by 15%

percent by year 2030

Reduce mean incident clearance time per incident by 20% percent over 8 years

Improve average on-time performance for specified transit routes/facilities by 25% within 5 years

Passenger loads on transit routes at each route's busiest point should not exceed 50 passengers on any vehicle (or on average) during the hour during peak/off-peak periods




Reliability objective ideas



Category Operations Objective

Non-Recurring

Delay

Reduce total person hours of delay (or travel-time delay per capita) by

time period (peak, off-peak) caused by:

• (Option 1) scheduled events, work zones, or system maintenance by

X hours in Y years.

• (Option 2) unscheduled disruptions to travel by X hours in Y years.

• (Option 3) all transient events such as traffic incidents, special events,

and work zones by X hours in Y years.

Travel Time Buffer

Index

Decrease the buffer index for (specific travel routes) by X percent over

the next Y years.

Decrease the average buffer index for (multiple routes or trips) by X

percent over Y years.

Reduce the average buffer time needed to arrive on-time for 95 percent

of trips on (specified routes) by X minutes over Y years.



Category Operations Objective

Planning Time

Index

Reduce the average planning time index for (specific routes in region)

by X (no units) over the next Y years.

Reduce the average planning time for (specific routes in region) by X

minutes over the next Y years.

Travel Time

Reduce the average of the 90th (or 95th) percentile travel times for (a

group of specific travel routes or trips in the region) by X minutes in Y

years.

Reduce the 90th (or 95th) percentile travel time for each route selected

by X percent over Y years.

VariabilityReduce the variability of travel time on specified routes by X percent

during peak and off-peak periods by year Y.

Transit On-Time

Performance

Improve average on-time performance for specified transit

routes/facilities by X percent within Y years.


How does an agency track and assess if the reliability-related

objectives are achieved?


Action 3

Develop performance measures


CMP Action 3 – Develop Multimodal

Performance Measures

Resources


Highway Capacity Manual Chapter 36 (Volume 4)



CMP Action 3 – Develop Multimodal Performance Measures

Examples

Travel Time Index

Planning Time Index

Others

Source: SHRP 2 Report L05, Incorporating Reliability Performance Measures into the Transportation Planning and Programming Process: A Guide



Partnerships for objectives and performance measures

Other Potential Partners

Major employers and universities

Major venue operators

Freight and delivery companies

Local weather experts

Public Agencies

State Departments of Transportation

Transit agencies

Toll authorities

City and county DPW

Local traffic signal operators and technicians

Local and state public safety agencies

Police

Fire

Emergency responders



Checklist self-assessment exercise

X

X

X


Please return in 15 minutes


How does an agency analyze the causes of non-recurring

congestion?


Action 5


Reliability analysis differs from typical studies:

More data

More resources

More staff effort

… But the upsides are:

Addressing concerns of the traveling public and freight industry

Opening doors to cost-effective solutions

Alignment with the national system reliability goal Source: Kittelson & Associates

http://librarian.kittelson.com/system/photos/1968/original/Family_Fest_018.jpg

http://librarian.kittelson.com/system/photos/1968/original/Family_Fest_018.jpg


Establishing Monitoring Programs for Travel Time Reliability: A Guidebook (SHRP 2 L02)

Design Guide for Addressing Nonrecurrent Congestion (SHRP 2 L07)

Incorporation of Travel Time Reliability into the HCM (SHRP 2 L08)


Step 1: Choose the facilities and study periods for analysis

Step 2: Collect data

Step 3: Estimate reliability from other data sources if direct

measures are not available

Step 4: Investigate and diagnose causes of reliability

problems


Focus on facilities, days of the week, and times of the day where reliability is likely to be a significant issue

Including times of day and days of year where there are few reliability problems will tend to “wash out” results

Selection of facilities for analysis should include occurrences of:

Regular peak period congestion

Crashes

Special events

Work zones

Weather-related incidents

Source: Kittelson & Associates

http://images.kittelson.com/system/photos/3251/original/FTL-crash.JPG

http://images.kittelson.com/system/photos/3251/original/FTL-crash.JPG


Original data – Minimum of one-year duration, such as:

Incident logs

Archived weather conditions

Road work logs

24-hour traffic counts and speeds

Other sources

National Performance Management Research Data Set (NPMRDS)

http://www.ops.fhwa.dot.gov/perf_measurement/index.htm

Private sector

Traffic management centers


http://images.kittelson.com/system/photos/3462/original/photo.JPG

http://images.kittelson.com/system/photos/3462/original/photo.JPG


Identification and Evaluation of Cost-Effectiveness of

Highway Design Features to Reduce Nonrecurrent

Congestion (SHRP 2 L07 Design Guide)

Spreadsheet tool to predict reliability distributions using these inputs:

Average annual demand/capacity ratio

Annual lane-hours lost due to incidents and work zones



Highway Capacity Manual Reliability Models (SHRP 2 L08)

Inputs required for freeways and arterials

Geometric

Intersection control

Demand and its variability

Weather events

Incident data

Methodologies provide default variability factors , but…

Local, site-specific data is best whenever feasible


If travel time archives are available…

Establishing Monitoring Programs for Travel Time Reliability Guidebook (SHRP 2 L02)

Group facility into 5-minute segments

Determine “congested” verses “uncongested” time periods

Analyst scans time period for incidents

Additional details at http://www.trb.org/StrategicHighwayResearchProgram2SHRP2/DataandAnalysisfor.aspx

http://www.trb.org/StrategicHighwayResearchProgram2SHRP2/DataandAnalysisfor.aspx


If travel time reliability was estimated…

Return to the tools used for diagnosing causes

Design Guide for Addressing NonrecurrentCongestion (SHRP 2 L07)

Incorporation of Travel Time Reliability into the HCM (SHRP 2 L08)


How does an agency analyze the reliability of their

transportation system?


Field (Probe) Data Analytics

Requires continuous data from system detectors and/or probes

Limited to past/present conditions

Useful for before/after evaluations and trend analysis

Doesn’t explicitly explain “why” a condition occurred

Model Estimation

Field is less mature – several models currently being developed/tested/applied

Enables prediction of future conditions and ‘what if’ analysis

Multiple models developed out of the SHRP 2 program (L04, L07, and L08)


Source: SHRP 2 Report L05, Incorporating Reliability Performance Measures into the Transportation Planning and Programming Process: A Guide

Reliability

MeasureFormula

Travel Time Index

(TTI): The total time

required to arrive at a

destination on-time

X% of the time

compared to free flow

conditions.

𝑋 𝑃𝑒𝑟𝑐𝑒𝑛𝑡𝑖𝑙𝑒 𝑜𝑓 𝑇𝑇

𝐹𝑟𝑒𝑒 𝐹𝑙𝑜𝑤 𝑇𝑇

Planning Time Index

(PTI): The total time

required to arrive at a

destination on-time

95% of the time

compared to free flow

conditions.

95𝑡ℎ 𝑃𝑒𝑟𝑐𝑒𝑛𝑡𝑖𝑙𝑒 𝑜𝑓 𝑇𝑇

𝐹𝑟𝑒𝑒 𝐹𝑙𝑜𝑤 𝑇𝑇

TT = Travel Time


Multiple probe-based data sources available:

Inrix.com

Here.com

RITIS.com

NPMRDS (free to States and MPOs)

National Performance Management Research Data Set

(NPMRDS)

Observed mean passenger vehicle and truck travel times

Covers National Highway System

Data averaged by five-minute periods by direction

Historic data available for Interstate freeways back to October 2011

Historic data available for Arterials back to July 2013


NPMRDS Monthly Average Travel Times Data File

Traffic Message Channel (TMC) Code (a segment of road)

Date (MMDDYYYY)

Epoch (5 minute period of the day)

Travel Time – all vehicles (seconds)

Travel time – passenger vehicles (seconds)

Travel Time – Freight Vehicles (seconds)

FAQs:http://ops.fhwa.dot.gov/freight/freight_analysis/perform_meas/vpds/npmrdsfaqs.htm

http://ops.fhwa.dot.gov/freight/freight_analysis/perform_meas/vpds/npmrdsfaqs.htm

Source: http://www.fhwa.dot.gov/planning/national_highway_system/

http://www.fhwa.dot.gov/planning/national_highway_system/


Total archive is 5-6GB per month, saved as a text file

Overall archive to date is approximately 700GB (raw data)

Data are provided as travel times; should be converted (back) to

speeds for analysis

Data are in “raw” format for 5-minute epochs, without cleaning or

post-processing


Scoping the Study

• Define the study segment (spatial scope)

• Define necessary study duration (temporal scope)

• Identify comparison segments

Processing the Data

• Download and store the travel time data*

• Convert travel time data to speeds and format data*

• Error-check and filter erroneous data*

• Finalize tidied data tables*

Analyzing and Interpreting the Data

• Run before and after analysis*

• Quantify and visualize performance measures *

• Interpret performance impacts and differences

• Make inference about other locations

* Step can be partially or fully automated by computational engine or software


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# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## 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# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # 4# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # 3 # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # 8 # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #

8:00 PM

9:00 PM

10:00 PM

11:00 PM

2:00 PM

3:00 PM

4:00 PM

5:00 PM

6:00 PM

7:00 PM

8:00 AM

9:00 AM

10:00 AM

11:00 AM

12:00 PM

1:00 PM

2:00 AM

3:00 AM

4:00 AM

5:00 AM

6:00 AM

7:00 AM

23 24 25 26

12:00 AM

1:00 AM

17 18 19 20 21 2211 12 13 14 15 165 6 7 8 9 10Week # 1 2 3 4


StatisticsTravel Speed (Daily) in mi/h

Before Work Zone (2013) With Work Zone (2014)

min 0.62 0.62

max 90.48 87.36

average 64.77 60.85

Standard deviation (SD) 6.58 10.98

% data left of mean 41.16% 29.76%

% data right of mean 58.84% 70.24%

85 percentile 69.89 68.47



Skewness -2.78 -2.30

Kurtosis 19.95 9.54


Segment 1 I-40 (upstream)

Segment 3I-40 (alternate)

Segment 4US70 (alternate)

Segment 5 Capital Blvd(alternate)

Segment 2 I-440 (in WZ)


Segment 1 I-40 (upstream)



Incorporating Travel-Time Reliability into the CMP32Segment 1

I-40 (upstream)




Source: Indiana Mobility Report 2013-2014, Purdue University, http://docs.lib.purdue.edu/imr/6/

Radial Chart Spatial Histogram

Source: Kittelson & Associates, Inc.

http://docs.lib.purdue.edu/imr/6/


• Key considerations in selecting minimum sample size

include: AADT, Time of Day, and Segment Length

• Exercise caution when working with data that are

“smoothed” to fill gaps; “outliers” can be important in

describing facility performance

• Use of statistical distributions and visualization

techniques are essential for understanding the “full

picture” of facility performance


How does an agency identify and evaluate strategies to

improve reliability?


Action 6


Sample

Goal Reduce non-recurring delay

High-level Objective

Reduce unplanned/unexpected non-recurring delay

Targeted Objective

Improve incident management

SMART Goal Reduce average incident response time by 15 minutes and incident duration by 30 minutes in peak

Potential Supporting Strategies to Evaluate

Reduce time to post traveler alert on dynamic message signs

Increase number of corridors covered by incident response teams

Increase number of signals with transit priority and emergency pre-empt

Organize additional regional coordinated incident response teams


Four Strategy Areas:1. Demand Management2. Operational

Improvements3. Public Transportation

Improvements4. Road Capacity

Improvements

Adapted from Congestion Management Process: A Guidebook, Federal Highway Administration, FHWA-HEP-11-011.


Enhancing system performance by influencing:

Trip time

Mode(s) choice

Route(s) choice

Capacity availability

Lane use

Speed

Service rate

Source: FHWA ATDM Evaluation Guidebook Pilot Workshop (2011)


Temporary use of shoulder as a travel lane

Source: FHWA ATDM Evaluation Guidebook Pilot Workshop (2011)


Regulate the number of vehicles entering or leaving a freeway.

Traffic smoothing


Dynamic lane allocation for directional flow. On-ramp and Off-

ramp


Counter-flow lanes; Incident management


Dynamically adjusting speed limits in critical areas to maintain

flow rate and reduce risk of collision


Toll amount increases as traffic gets heavier and

decreases as congestion eases. Ensures free-

flow operation

Area-wide, Zone-based, Roadways, Lanes


Access Control

Intersection movements

Managed lane access

Ramp access

Dynamic truck restrictions


Casual carpooling

San Francisco

www.ridenow.org/carpool

Slugging

DC metro, VA

www.slug-lines.com/

Dynamic ridesharing

http://www.slug-lines.com/


Estimated travel times for

specific routes

Re-routing motorists to less

congested facilities


A facility that increases freeway efficiency by

packaging various operational and design actions.

Lane management operations may be adjusted at any

time to better match regional goals.


Source; NCHRP Synthesis 447


http://onlinepubs.trb.org/onlinepubs/shrp2/SHRP2_L31_PresentationGuide.pdf


How does an agency monitor and report reliability?


Action 8

Information Flow in a Travel-Time

Reliability Monitoring System


V/C

LOS

Delay

TTI

Buffer

PTI

PT

RI

Throughput

85th%

95th%

Source: Delaware Valley Regional Planning Council


Tell a story

Educate

Justify

Source: Delaware Valley Regional Planning Council. Available at: www.dvrpc.org/asp/pubs/publicationabstract.asp?pub_id=NL13011

http://www.dvrpc.org/asp/pubs/publicationabstract.asp?pub_id=NL13011

sjcog fhwa reliability cmp workshop presentation spring2016

Documents