微观交通仿真及其应用初连禹lchu@berkeley.edu加州创新交通研究中心加州交通管理实验室

长春， 2006 年 8 月 26日

Introduction

Microscopic simulation a software tool to model traffic system, including roads,

drivers, and vehicles, in fine details. models: AIMSUN, CORSIM, MITSIM, PARAMICS,

VISSIM… Why simulation?

Can capture detailed traffic flow dynamics Can be calibrated to reproduce real world scenarios Can provide a visualization tool to evaluate traffic

management and operational strategies answer “what if” questions

Applications

Online/off-line applications

Evaluate traffic management and operational improvements

Model and Evaluate ITSCalibrate / optimize operational parameters

of ITS strategiesDevelop / test new models, algorithms,

control strategies

Paramics model

PARAMICS: PARAllel MICroscopic Simulation a suite of software tools for micro traffic simulation, including:

Modeller, Analyzer, Processor, Estimator, Programmer developer: Quadstone, Scotland

Features large network simulation capability modeling the emerging ITS infrastructures OD estimation tool Application Programming Interfaces (API)

access core models of the micro-simulator customize and extend many features of Paramics model complex ITS strategies complement missing functionalities of the current model

How to model ITS:Application Programming Interfaces

User

Developer

Output Interface

Input Interface

GUI Tools

Professional Community Oversight

Core Model API

function calls:vehicle related..

link related..and others

user-definedprograms

Main simulation loop PluginsAPI

data

Other applications

/APIs

functions

PARAMICS API

Provided API Library

Developed API Library

Advanced Algorithms

Adaptive Signal Control

Adaptive Ramp Metering

Dynamic Network Loading

ATMIS Modules

Data Handling

Routing

Ramp

Signal

CORBA

Databases

Demand

XML

PARAMICS Plug-in Development

Vissim vs Paramics

Paramics is better in following aspects: Large-scale network modeling Faster simulation speed API OD estimation tool Conversion tool

Vissim excels in Car-following model Easy learning Vissum, as planning model

Data needs

CoverageAccuracyData processing

Model Calibration

Model needs to be calibrated before applications Capacity calibration OD Estimation Route choice calibration Bottleneck calibration

Proposed calibration targets

Flow Within 25%-75% percentile Due to traffic congestion, variation

Speed contours Three levels of targets

Visual assessment Match Bottleneck Area Detailed Bottleneck Calibration

6:30

6:40

6:50

7:00

7:10

7:20

7:30

7:40

7:50

8:00

8:10

8:20

8:30

8:40

8:50

9:00

9:10

9:20

0.05

3.47

4.66

6.22

7.13

8.83

9.9

10.49

11.66

12.3

13.78

14.69

15.54

16.06

16.45

17.11

17.82

18.48

19.04

19.68

20.42

22.13

23.35

24.65

25.51

26.84

28.07

28.88

29.75

32.1

33.15

65-7555-6545-5535-4525-3515-255-15

6:30

6:40

6:50

7:00

7:10

7:20

7:30

7:40

7:50

8:00

8:10

8:20

8:30

8:40

8:50

9:00

9:10

9:20

0.05

3.47

4.66

6.22

7.13

8.83

9.9

10.49

11.66

12.3

13.78

14.69

15.54

16.06

16.45

17.11

17.82

18.48

19.04

19.68

20.42

22.13

23.35

24.65

25.52

26.84

28.07

28.88

29.75

32.1

33.15

65-7555-6545-5535-4525-3515-255-15

Sample applications

Signal control

Signal Hardware-in-loop, testing 170 controller Adaptive signal control based on real-time delay

estimation

Evaluation of Adaptive Ramp Metering Algorithms

Algorithms ALINEA, BOTTLENECK, ZONE

Morning peak hour (6:30-10:00) High Demand Low Demand

Scenarios Recurrent congestion Non-recurrent congestion

Incidents: block the rightmost lane for 10 minute at the beginning of congestion at the end of congestion

Traffic direction 1 2 3 7 6 5 4

Evaluation of Adaptive Ramp Metering Algorithms (cont.)

Optimization of parameters of ALINEA

ALINEA, A local feedback

ramp-metering strategy

Optimization method: Hybrid method:

simulation + GA

))(*()(~)( tOOKttrtr R

Downstream detectorOn-ramp detector

Queue detector

Optimization of parameters of ALINEA (Cont.)

MOE

GA

Time-dependentTravel demands

PARAMICSsimulation

ALINEAramp-metering algorithm

PerformanceMeasure

Ramp MeteringController

Loop DataAggregator

ParameterValues

Ramp Metering Evaluation Platform What is it?

A simple platform to guide Caltrans personnel on how to successfully manipulate the various aspects of the ramp-metering systems, including initializing parameters, fine tuning of parameters, performance analyses, and hypothetical "what if" simulated testing.

What does it consist of? A library of metering algorithms either

currently or potentially applied in California is included in this platform. The platform has intuitive graphical interfaces in order to facilitate Caltrans practitioners.

How has it been used? Not yet deployed.

How can it be used? provides a quick and cost-effective way

to conduct ramp-metering studies.

Design Evaluation

ALINEA SJRMS

SDRMS

SATMS SWARM Override Strategies

MOE Loop Ramp

PARAMICS Simulation

Loop data Network Traffic control

Graphical Interfaces (GUI)

URMS

Work zone Noticeable source of accidents and congestion

AWIS: Automated Workzone Information Systems Components:

Sensors Portable CMS Central controller

Benefits: Provide traffic information Potentially

• Improve safety• Enhance traffic system efficiency

Evaluation of Traffic Delay Reduction from AWIS

Evaluation of Traffic Delay Reduction from AWIS (cont.)

Calibration for the before model

Calibration for the after model

Data collection

Network OD Table OD Table Network

Simulation Simulation

Evaluation

ATMIS components Scena-

rio Scenario description Ramp Metering Signal Control Traveler Information

Incident Management

0 BASELINE 2000 Fixed time Coordinated N/A N/A

1 Non-incident management Fixed time Coordinated N/A 33 mins

2 Existing incident management Fixed time Coordinated N/A 26 mins

3 Improved incident management Fixed time Coordinated N/A 22 mins

4 Local adaptive ramp metering ALINEA Coordinated N/A 26 mins

5 Coordinated ramp metering BOTTLENECK Coordinated N/A 26 mins

6 Traveler information Fixed time Coordinated 5% compliance 26 mins

7 Combination-1 Fixed time Synchro-Adaptive 5% compliance 26 mins

8 Combination-2 ALINEA Synchro-Adaptive 5% compliance 26 mins

Caltrans’ Traffic Management System master plan

Caltrans’ Traffic Management System master plan (cont.)

Corridor management Plan Demo

Goal: to incorporate detailed multi-modal performance

measurement and operational analysis into the traditional corridor planning efforts.

Major Tool: Microscopic Traffic Simulation (Paramics)

Outcome: A template for Caltrans to use in corridor planning

efforts that will integrate both planning and operations To help to address the problem of lost system

productivity during congestion, thereby improving mobility in the most cost effective manner.

I-880 corridor simulation

I-880 improvement projects Interchange improvement

SR-92 Davis Marina Mission Blvd

Freeway mainline improvement Extend HOV lanes Add one more lane to both NB and SB SR-238

Construct auxiliary lanes Add an aux lane along SB 880 from SR-238 to A St. Add an aux lane along NB 880 from Tennyson to SR-92

Arterial improvement Widen Stevenson from 4 to 8 lanes

…

Current I-880/SR92 Interchange

SR92 I-880

I-880 improvement projects

A: Add 3- lane facility on SR92 EB which continues until I-880 interchange

B: Remove a diagonal ramp to Hesperian NB and add two left turn lanes on loop ramp to Hesperian SB

A

B

Proposed Improvements A & B

C: Remove SR92 to 880NB loop and add 3 lane flyover ramp(1 lane for HOV only).

D: Improve the curvature of 880SB to SR92 WB

E: Improve the curvature of 880NB to SR92 EB

F: Remove SR92 to 880SB loop and add 1 lane flyover ramp

C

DE

F

Proposed Improvements C, D, E, & F

G: Add 1 aux lane on 880SB until Tennyson Rd

H: Add 1 aux lane on 880 NB from Tennyson Rd

G H

Proposed Improvements G & H

I: Add 1 aux lane on 880 NB until Winton Ave

J: Add 1 aux lane on 880 SB from Winton Ave

JI

Proposed Improvements I & J

I-880/SR92 Interchange Improvements

Add 3-lane facility on SR92

Add 1 aux lane on 880NBAdd 1 aux lane

on 880SB

Remove SR 92EB to 880NB loop and add 3-lane flyover ramp

Remove SR 92WB to 880SB loop and add 1-lane flyover ramp

Remove diagonal ramp to Hesperian and add 2 left turn lanes on loop ramp

Add 1 aux lane on 880SB

Add 1 aux lane on 880NB

I-880SR-92

Improve the curvature of 880SB to SR92WB diagonal ramp

Improve the curvature of 880NB to SR92EB diagonal ramp

Add 3-lane facility on SR92

Add 1 aux lane on 880NBAdd 1 aux lane

on 880SB

Remove SR 92EB to 880NB loop and add 3-lane flyover ramp

Remove SR 92WB to 880SB loop and add 1-lane flyover ramp

Remove diagonal ramp to Hesperian and add 2 left turn lanes on loop ramp

Add 1 aux lane on 880SB

Add 1 aux lane on 880NB

I-880SR-92

Improve the curvature of 880SB to SR92WB diagonal ramp

Improve the curvature of 880NB to SR92EB diagonal ramp

I-880/SR92 Interchange: After Improvement

Benefit Analysis of Selected Proposed Orange County Freeway Improvement Projects Project 1: Re-stripe left shoulder of I-5 between SR-55

interchange and SR-22/SR-57 interchange to add second HOV (High Occupancy Vehicle) lane.

Project 2: Re-stripe left shoulder on I-5 between Tustin Ranch Road and SR-133 interchange to add continuous auxiliary lane.

Project 3: Extend existing HOV lane on SR-55 from the I-405 to Victoria in both directions.

Project 4-1: Add one general purpose lane on I-5 between the Orange/San Diego County line and Camino Capistrano.

Project 4-2: Extend HOV lane on I-5 between the Orange/San Diego County line and Camino Capistrano.

MOE Comparison for Project 1 MOE Before After Percent Change

VMT (miles) 147995.6 150683.7 1.8 %

VHT (hrs) 4942.3 4049.9 -18.1 %

Average HOV lane speed (mph) 38.5 69.0 79.5 %

Total HOV lane throughput (veh/hr) 1854 1945 4.9%

Total vehicle throughput (veh/hr) 7416.3 7483.7 0.9 %

Total person throughput (persons/hr) 10371.8 11877.67 14.5 %

Re-stripe left shoulder of I-5 Re-stripe left shoulder of I-5 between SR-55 interchange between SR-55 interchange and SR-22/SR-57 interchange and SR-22/SR-57 interchange to add second HOV (High to add second HOV (High Occupancy Vehicle) laneOccupancy Vehicle) lane

MOE Comparison for Project 2 MOE Before After Percent Change

VMT (miles) 353406.3 361449.4 2.3%

VHT (hrs) 8884.5 7967.9 -10.3%

NB 39.6 49.6 25.2% Average mainline travel speed (mph) SB 53.0 57.4 8.4%

Re-stripe left shoulder on I-5 Re-stripe left shoulder on I-5 between Tustin Ranch Road between Tustin Ranch Road and SR-133 interchange to and SR-133 interchange to add continuous auxiliary add continuous auxiliary lanelane

MOE Comparison for Project 3 MOE Before After Percent Change

VMT (miles) 176910.66 184527.66 4.3%

VHT (hrs) 7689.43 4950.95 -35.6%

Mainline 38.8 59.1 52.5% NB average travel speed (mph) HOV 46.8 69.4 48.2%

Mainline 61.6 62.6 1.6% SB average travel speed (mph) HOV 68.0 68.8 1.2%

Extend existing HOV lane on Extend existing HOV lane on SR-55 from the I-405 to SR-55 from the I-405 to Victoria in both directionsVictoria in both directions

MOE Comparison for Project 4-1 MOE Before After 1 Percent change

VMT (miles) 337771 348091 3.1%

VHT (hrs) 7290.13 5642.42 -22.6%

NB average travel speed (mph) 47.1 63.2 34.3%

SB average travel speed (mph) 58.8 63.2 7.5%

Add one general purpose Add one general purpose lane on I-5 between the lane on I-5 between the Orange/San Diego County Orange/San Diego County line and Camino Capistranoline and Camino Capistrano

MOE Comparison for Project 4-2 MOE Before After 2 Percent change

VMT (miles) 337771 341567 1.1%

VHT (hrs) 7290.13 6043.63 -17.1%

Mainline 47.1 61.7 31.0% NB average travel speed (mph) HOV 47.1 70.2 49.1%

Mainline 58.8 62.5 6.3% SB average travel speed (mph) HOV 58.8 70.4 19.8%

Extend HOV lane on I-5 Extend HOV lane on I-5 between the Orange/San between the Orange/San Diego County line and Diego County line and Camino CapistranoCamino Capistrano

ATMS Training and Development System What is it?

A high-end simulator for use in Caltrans operator training efforts as well as a true testing facility for ATMS upgrades and enhancements within an environment with the full functionality of a Caltrans TMC.

What does it consist of? An ITS Test Center and TMC Simulator that

provides connectivity to the Testbed’s real-time data streams (field and simulated). Provides both “live”and “virtual” connections to Caltrans field traffic control systems. An adjoining “classroom” has capacity for fifteen Caltrans trainees.

How has it been used? Provides Caltrans TMC operator training.

How can it be used? Test and evaluate upgrades/enhancements to

TMC operations in a secure environment that exactly duplicates actual TMC software systems and data feeds.

loop data

1 2 3

incident ramp metering, CMS messages

ATMS Training and Development System

Objective: Evaluate the impacts of allowing use of High Occupancy Vehicle (HOV) lanes by single-occupant gasoline-electric hybrid vehicles

Three major components: microscopic simulation modeling, emission modeling for HOV/hybrid system, demand modeling for future hybrid vehicles.

Scenarios consideredScenario Description

Baseline Current: Only HOV 1 Current: HOV + Existing Hybrids 2 HOV + Limit of 50,000 Hybrid Permits 3 HOV + Limit of 75,000 Hybrid Permits 4 HOV + Virginia I-395 Experience (7%) 5 HOV + Virginia I-95 Experience (19%)

Effects by Allowing Single Occupant Hybrid Vehicles on HOV Lanes

Effects by Allowing Single Occupant Hybrid Vehicles on HOV Lanes (cont.)

Extension of Hybrid HOV Lane Micro-simulation Model Evaluation of the impacts of:

allowing single-occupant vehicles to pay a toll to use the HOV lanes (so-called HOT lanes)

the use of Caltrans District 12 HOV lanes as a part time system with no buffer separating the lanes (similar to the HOV system that exists in Caltrans District 4)

Investigate the impacts of: Priority-based HOV

operation

Priority level

Vehicle types

6 Bus5 HOV 4 plus (includes

van pools)4 HOV 33 HOV 22 Hybrids, Low Emission

Vehicles (LEV)1 SOV willing to pay toll0 SOV

Sub-network Simulation Components

CORBA middle ware

Network Monitoring

API

Vehicle Routing

API

Subnet Simulator 1

Other SupportingAPIs

Other SupportingAPIs

Other SupportingAPIs

Computer 1

Network Monitoring

API

Vehicle Routing

API

Subnet Simulator 2

Other SupportingAPIs

Other SupportingAPIs

Other SupportingAPIs

Computer 2

Network Monitoring

API

Vehicle Routing

API

Subnet Simulator 3

Other SupportingAPIs

Other SupportingAPIs

Other SupportingAPIs

Computer 3

Network Monitoring

API

Vehicle Routing

API

Subnet Simulator 4

Other SupportingAPIs

Other SupportingAPIs

Other SupportingAPIs

Computer 4

• Global Network Database• Global Network Monitoring • Global Path Calculation• Path Tree Storage

Global Path Controller

Distributed Paramics Modeling

On-line simulation

Loop data from Oracle database at ATMS Testbed

Traffic data at each cordon points

Demand loading

Forecast lead time

Traffic flow prediction

Consistency check

Dynamic OD estimation

Loop data at measurement points

Data aggregation

Reference OD pattern

Paramics simulation