Utilization of ITS Data to Calibrate Simulation Models

Transpo 2012

Mohammed Hadi, Yan Xiao, Ali Daroodi

Lehman Center for Transportation ResearchDepartment of Civil and Environmental Engineering

Florida International UniversityMiami, FL

October 30, 2012

Utilization of ITS Data to Calibrate Simulation Models

• Microscocopic traffic simulation models allow detailed analysis of traffic operations and alternative capacity improvements and traffic operation analysis

• The complexity of simulation modeling increases with the increase in congestion level and advanced strategy modeling

• Data from ITS combined with data from other sources allow:– More cost-effective simulation model development

– Better calibrated and validated models

2

Introduction

• “Investigation of ATDM Strategies to Reduce the Probability of Breakdown”

• Joint FIU/UF Project: M. Hadi, L. Elefteriadou, Y. Xiao, C. Letter, A. Darroudi– Investigate the implementation of the breakdown probability

to an existing real-world deployment of ramp metering.

– Investigate the use of speed harmonization by itself or in combination with the ramp metering implementation

– Examine how connected vehicle technologies can be used to support the strategies investigated

– Provide guidelines to agencies on how to use simulation models to assess and fine-tune ATDM strategies of the types investigated in the project

3

STRIDE Project

• Utilize detailed data to identify the variability of congestion between days– How similar are different days

• Identify day(s)/congestion levels for use in the analysis

• Examine variation in breakdown attributes between days and associate these attributes with congestion levels

• Examine the use of new attributes (based on breakdown and queuing) for calibrating simulation models for use in modeling advanced strategies

4

Objectives

• Guidelines have been produced for calibration and use of simulation models– FHWA Traffic Analysis Toolbox (TAT) Volumes 3 and 4 are

examples

• Calibration data has consisted of measures of capacity; traffic counts; and measures of system performance such as travel times; speeds, delays, and queues

• TAT specifies that system performance data (travel times, delays, queues, speeds) must be gathered simultaneously with the traffic counts

5

Simulation Model Calibration

• Multi-scenario analysis for “normal”, incidents, special events, weather has been proposed in recent years.

• Range of “normal” conditions considered – low, median, and heavy based on VMT

6

Multi-Scenario Modeling

Mean

Median

Speed Contour Plot (16 days)Based on Similarity

4/26/2011

11/11/2010

5/12/2010

Less Congestion

11/18/2010

More Congestion

10/6/2010

CORSIM Results

Similarity Based on Euclidean Distance:

16 Days Distance Results Based on Speed

Speed Contour Plot (7 days)Based on Similarity of Speed

Less Congestion

More Congestion

CORSIM Results

5/12/2010

6/17/2010

Mean

Median

4/26/2011

2/11/2011

11/30/2010

Similarity Based on Euclidean Distance:

7 Days Distance Results Based on Speed Only

Speed Contour Plot (7 days)Based on Similarity of Speed and Volume

Less Congestion 3/15/2011

More Congestion

2/11/2011

CORSIM ResultsMean

Median

4/26/2011

5/12/2010

6/17/2010

Similarity Based on Euclidean Distance:

7 Days Distance Results Based on Speed and Volume after Normalization

Speed Contour Plot (7 days)Based on Congestion Index

Less Congestion

More Congestion

CORSIM Results

5/12/2010

6/17/2010

4/26/2011

Median

Mean

2/11/2011

11/30/2010

Congestion Index (7 days):

Capacity, Breakdown Flow, and Queue Discharge

• Congestion Index• Speed before breakdown (mph)• Average Speed of breakdown (mph)• Speed Reduction due to beakdown (mph)• Starting time• Duration (hr:min)• Maximum pre-Breakdown Flow upstream and downstream of

ramp (veh/hr/lane)• Breakdown Flow (veh/hr/lane)• Queue Discharge (veh/hr/lane)• Recovery Flow (veh/hr/lane)• Queue Build-up Rate and Queue Dissipation Rate 16

Congestion/Breakdown Attributes

Breakdown Analysis Results:

Date Congestion Index

Speed before breakdown

(mph)

Average Speed of breakdown (mph)

Speed Reduction

(mph)Starting time Duration

(hr:min)

Maximum pre-Breakdown Flow

(veh/hr/lane)

Breakdown Flow (veh/hr/lane)

Queue Discharge

(veh/hr/lane)

Recovery Flow (veh/hr/lane)

2/11/2011 28.87% 57.33 30.36 26.97 14:40:00 4:35 1926 1629 1563 1533

11/30/2010 24.08% 55.56 30.75 24.81 15:05:00 4:00 1788 1788 1551 1482

1/18/2011 23.27% 57.3 34.17 23.13 14:50:00 3:45 1878 1704 1560 1587

3/15/2011 19.13% 56.58 33.07 23.51 15:30:00 2:55 1965 1725 1608 1587

4/26/2011 19.02% 56.34 31.17 25.17 15:25:00 3:00 1749 1716 1569 1587

6/17/2010 14.49% 62.23 37.95 24.28 16:05:00 2:25 1761 1731 1638 1398

5/12/2011 12.54% 59.48 37.14 22.34 15:25:00 2:30 1923 1767 1689 1584

18

Thank You