An Assessment of Arterial Network Using Macro and Micro Simulation Models

Presentation

bySabbir Saiyed, P.Eng.

Principal Transportation Planner

Regional Municipality of Peel

Brampton, Ontario

17th Annual International EMME/2 Users’ ConferenceCalgary, Alberta

Overview Introduction Macro and micro-simulation models Background

Region of Peel Region of Peel Travel Demand Forecasting Model Transportation Tomorrow Survey

Traffic simulation packages EMME/2 INTEGRATION Synchro & Sim-Traffic

Experimental design and methodology Experimental results and discussions Conclusions and recommendations

Introduction Transportation systems provide vital service to our

community by moving people and goods Operation of transportation systems is an important

concern for elected officials and engineers Many cities are experiencing tremendous growth in traffic Several municipalities do not have sufficient funds to meet

growing travel demands The emphasis is to improve performance of traffic systems One of the solutions is to improve performance of traffic

systems by integrating planning and operational analysis This presentation describes the process of integrating

Regional travel demand model with micro-simulation models such as INTEGRATION, Synchro and Sim-Traffic

Macro Simulation Models Macro simulation models such as Regional Travel

Demand (RTM) models are used by most municipalities to forecast current and future travel demands

These models are used for transportation and land use planning

Generally, they involve 4-step approach involving trip generation, trip distribution, modal choice and trip assignment

Micro-simulation models

Micro-simulation models– an important tool in transportation planning

Micro Simulation Models e.g. INTEGRATION, Synchro, Sim-Traffic, VISSIM, PARAMICS, etc.

Micro simulation models simulate car following and lane change behavior of drivers on a second by second basis

Displays output in the form of animation that shows individual cars, buses, trucks, etc.

These models work at an incredibly detailed level and requires equally detailed data

Provides data on speeds, delays and emissions

Macro and Micro Simulation Models at other Municipalities

Several municipalities are employing macro and micro simulation models

City of Calgary is currently supplementing Regional Transportation Demand (RTM) model by using micro-simulation models developed using Vissim

City of Edmonton is also employing micro-simulation models to analyze and design LRT expansion project

City of Toronto is using PARAMICS to evaluate and test ITS initiatives

Region of Peel is using micro-simulation models for analyzing arterials and freeways in addition to RTM

Region of Peel is strategically located…

Region of Peel Region of Peel is 2nd largest municipality in Ontario, 5th

largest in Canada and it is growing rapidly Serves over 1 million residents It covers City of Mississauga, City of Brampton and

Town of Caledon Provides services such as health, regional planning,

housing, transportation, water, sewers, and other municipal services

Rapid population growth and commercial development have transformed what was primarily a rural area of farms and villages into a dynamic blend of urban, industrial and residential areas.

Images of Peel

Region of Peel Model - Background

Regional staff developed the Peel Region’s first travel demand model in 1978

Model was being run on mainframe computer using modeling software developed by MTO and United States DOT (UTPS package)

Acquired emme/2 software in 1989 and Regional staff developed the simplified version of model

Model was calibrated/validated using 1986 TTS and Cordon Count data

Since then model is updated on continuous basis

Region of Peel Model

Four staged model consisting of Trip generation Trip distribution Modal split Trip assignment

Model simulates a.m. peak hour trips Model uses land use and transportation data from

Transportation Tomorrow Survey (TTS) and Census It is validated using Cordon Count data and counts

obtained from traffic and transit departments Several scenarios has been developed for existing and

horizon years such as 1996, 2001, 2011, 2021 and 2031

Structure of Region of Peel model

Trip Generation External Trips Airport Trips

Trip Distribution Apply Growth Factors Apply Growth Factors

Modal Split

Auto Occupancy

Trip Assignment

Peel Traffic Zone System

Traffic zone system used by Peel’s Model is based on Greater Toronto Area (GTA) zone system

There are over 500 traffic zones in Peel and GTA Level of details vary over GTA Zone system is fairly detailed within Peel, with

diminishing level of details away from boundary City of Toronto contains large number of zones due

to its size and trips to and from downtown Oakville has been coded in fine detail Mode split model has been aggregated in 27 zone

groups and occupancy model in 47 zone groups

PeelPeel

HaltonHalton

YorkYork

TorontoToronto

DurhamDurham

Transportation Tomorrow Survey Transportation Tomorrow Survey is an important O-D Survey

conducted by Regional Municipality of Peel, the Province of Ontario, 15 other municipalities in Southern Ontario, GO Transit and Toronto Transit Commission

The most recent survey was completed in 2001, with the previous ones carried out in 1986, 1991 and 1996

The trip data contains information about the household and trips made by each person in the household including trip origin, trip destination, trip purpose, start time and mode of travel

This data is geo-coded and data is available for input into Emme/2 and other models

The O-D matrix developed for the analysis in this paper is based on the data collected from TTS survey and is used as input both for Emme/2 and INTEGRATION software

Traffic simulation packages

Traffic simulation packages used in this study are: Emme/2 Synchro and Sim-Traffic INTEGRATION

The transportation network was created using Emme/2 transportation planning software

Synchro and Sim-Traffic were used to model pre-timed and actuated signal control

INTEGRATION was used to simulate adaptive signal controls

Emme/2 Software

Emme/2 is an interactive multi-modal transportation planning software used worldwide for over 20 years

It offers a complete and comprehensive set of tools for demand modeling, multi-modal network modeling and analysis for implementing evaluation procedures for transportation planning

Its data bank is structured to permit simultaneous descriptions, analysis and comparison of several transportation planning scenarios

In this study, emme/2 is used to develop and code transportation network and to generate O-D matrix for input in INTEGRATION model

Synchro

Synchro is a complete software package for modeling and optimizing traffic signal timings

It optimises cycle lengths, splits, offsets and phase orders

Synchro also optimises multiple cycle lengths and performs coordination analysis

Synchro can analyse pre-timed and actuated signal control systems

It can optimise the entire network or group of arterials and intersections in a single run

Synchro has colourful, informative time-space diagrams It provides more than 17 reports on several measures of

effectiveness of signalized intersection

Sim-Traffic

Sim-Traffic is companion traffic model that comes with Synchro and it is a microscopic simulation model

It is designed to model networks of signalized and unsignalized intersections

It can be used to check and fine tune traffic signal operations and is useful for analyzing complex situations such as closely spaced intersections and intersections under heavy congestion

It can model pre-timed and actuated signal controls Each vehicle in the traffic network is individually tracked

through the model and comprehensive measures of effectiveness are recorded during simulation

INTEGRATION Model

Developed in late 1980s by late Dr. M. Van Aerde with extensive support of MTO

INTEGRATION model is an attempt to provide a single model that could consider both freeways and arterials as well as traffic assignment and simulation

This ability is intended to bridge a gap between the planning models as well as traffic operational models/tools

INTEGRATION model can also model Intelligent Transportation Systems such as ATMS and ATIS.

It can also be used for evaluating TDM (HOV) policies, goods movement (truck sub network), toll roads, intersection improvements, etc.

INTEGRATION Model It models the interactions of individual vehicles with

freeways, arterials, traffic signals and ITS, while preserving macroscopic properties of each link in the network

The model uses Dynamic Traffic Assignment (DTA) in addition to Static Traffic Assignment

DTA allows vehicles to reroute according to current traffic conditions of the network

INTEGRATION does not require the user to collect input data at the individual vehicle level

It uses O-D traffic demands and therefore EMME/2 data can be used effectively

The model uses internal logic to determine microscopic measures such as free speeds and densities

Experimental Design Transportation network was created in emme/2 software

based on real network of Region of Peel with minor modifications to number of lanes and capacities

The zone centroids represents the traffic zones of Peel Region

A traversal matrix was developed for the study area based on actual O-D survey data

There are 26 nodes, 58 links and 77 O-D demand loadings The saturation flow rate was set to regional standards,

which is 1900 vehicles/hour, consistent with typical high grade urban network

The inter-green time was set to 4 seconds of Amber and 2 seconds for all Red

Experimental Methodology

The arterial network and a traversal matrix was developed using Emme/2

This network was batched out from Emme/2 and was entered in INTEGRATION software

Additionally, the data could be imported into Excel spreadsheet for further changes

All the essential files were created for the INTEGRATION model and it was run to simulate traffic demands

The turning movement generated using INTGRATION were entered into Synchro to simulate pre-timed and actuated traffic demands

Arterial Network

Types of Signal Control Traffic engineers can maximise performance of traffic signal

by varying cycle time, green splits, offsets and phase types as well as sequencing

There are three types of signal control Pre-timed Actuated Adaptive

In pre-timed signal controls , there are fixed time plans and time of day plans

In actuated signal controls, controller operates on traffic demands based on actuation of vehicles and pedestrians

In adaptive signal controls, no preset plans are developed; new signal timing plans are computed dynamically based on prevailing traffic demands

Network Totals before Optimisation

 Pre-timed Actuated Adaptive

Total Signal Delay (hr) 90 42 42

Stops/Veh 0.79 0.3 0.45

Total Stops 13049 5045 7698

Average Speed (km/hr) 47 52 50

Total Travel Time (hr) 450 403 425

Distance Travelled (km) 21050 21050 21050

Fuel Consumed (litre) 2509 2123 2019

CO Emissions (kg) 46.66 39.48 66.55

NOx Emissions (kg) 9.01 7.62 3.72

 Pre-timed Actuated Adaptive

Total Signal Delay (hr) 32 27 24

Stops/Veh 0.46 0.45 0.26

Total Stops 7678 7545 4612

Average Speed (km/hr) 54 54 54

Total Travel Time (hr) 392 387 416

Distance Travelled (km) 21050 21050 21050

Fuel Consumed (litre) 2171 2156 1900

CO Emissions (kg) 40.38 40.11 56.26

NOx Emissions (kg) 7.79 7.74 3.22

Network Totals – Cycle/Offsets Optimisation

Total Signal Delays

Total Signal Delay

0

20

40

60

80

100

Pre-timed Actuated Adaptive

Signal Control Types

To

tal

Sig

na

l D

ela

y (

hr)

Before Optimisation

After Cycle Optimisation

After Offset Optimisation

After Cycle/OffsetOptimisation

Conclusions and Recommendations

Emme/2 could be effectively utilized to develop a regional travel demand model

Transportation network could be easily developed using Emme/2 for input into micro-simulation model

Emme/2 could be used to develop sub-area model and also for developing traversal matrix

Emme/2 could be easily integrated with micro-simulation models such as INTEGRATION, Synchro and Sim-Traffic to provide additional measures of effectiveness for arterial network for transportation planning and operational analysis

Conclusions and Recommendations

INTEGRATION offers Dynamic Traffic Assignment method in addition to traditional methods of assignment

Sim-Traffic and the INTEGRATION models produce an on-line simulation display that can be efficiently used to visualize traffic flow and to analyze the measures of effectiveness of the network

Sim-Traffic could be used to simulate and animate to determine operational level traffic problems

Synchro could be effectively used to determine macro level LOS and delays

Conclusions and Recommendations

The experiment also demonstrates that Synchro, Sim-Traffic and INTEGRATION could be used to analyze pre-timed, actuated and adaptive traffic signal controls

It is shown that optimization improves the performance of the arterial network

It is recommended that further work should be carried out to examine medium and large network using above methodology

The results of the experiment would provide additional information and a better understanding of several measures of effectiveness for effective transportation planning and operation analysis

Thank you