Skip to contentUnited States Department of Transportation - Federal Highway Administration FHWA Home
Research Home
Report
This report is an archived publication and may contain dated technical, contact, and link information
Publication Number: FHWA-HRT-04-131
Date: September 2004

Identifying and Assessing Key Weather-Related Parameters and Their Impacts on Traffic Operations Using Simulation

View PDF Version (340 KB)

PDF files can be viewed with the Acrobat® Reader®

View Table of Contents

FOREWORD

Adverse weather conditions can have a dramatic impact on the quality of traffic flow. Traffic analysts need adequate traffic analysis tools to design better for the impacts of adverse weather. One available type of analysis tools is microscopic traffic simulation, which allows analysts to model and evaluate complex roadway geometries, traffic control devices, and Intelligent Transportation Systems (ITS).

The objectives of this effort, as captured in the report, Identifying and Assessing Key Weather-Related Parameters and Their Impacts on Traffic Operations Using Simulation, are to identify how adverse weather affects traffic operations, to assess the sensitivity of weather-related traffic parameters in a microscopic traffic simulation package (CORSIM), and to develop guidelines for using the CORSIM simulation model to account for the affects of adverse weather.

The intended audiences for this report are transportation professionals who use traffic analysis tools, in particular microscopic traffic simulation, to plan, evaluate, or design roadway or traffic control improvements and are interested in incorporating the impacts of adverse weather into their analysis.

Toni Wilbur
Director, Office of Operations Research and Development

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document. This report does not constitute a standard, specification, or regulation.

The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers' names appear in this report only because they are considered essential to the objective of the document.

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information to serve Government, industry, and the public in a manner that promotes public understanding. Standards and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its information. FHWA periodically reviews quality issues and adjusts its programs and processes to ensure continuous quality improvement.

Technical Report Documentation Page

1. Report No. FHWA-HRT-04-131

2. Government Accession No.

     

3. Recipient's Catalog No.

4. Title and Subtitle
Identifying and Assessing Key Weather-Related Parameters and Their Impacts on Traffic Operations Using Simulation

5. Report Date
September 2004

6. Performing Organization Code

7. Author(s)
Li Zhang, Peter Holm, and James Colyar

8. Performing Organization Report No.

9. Performing Organization Name and Address
ITT Industries Inc.
Systems Division
P.O. Box 15012
Colorado Springs, CO 80935-15012

10. Work Unit No.

     

11. Contract or Grant No.

12. Sponsoring Agency Name and Address
Office of Operations Research and Development
Federal Highway Administration
6300 Georgetown Pike
McLean, VA 22101-2296

13. Type of Report and Period Covered
Final Report

September 2002–December 2003

14. Sponsoring Agency Code

15. Supplementary Notes
The Contracting Officer's Technical Representative was John Halkias.

16. Abstract

The objectives of this study were to identify how weather events affect traffic operations, to assess the sensitivity of weather-related traffic parameters in the CORridor SIMulation (CORSIM) traffic microsimulation model, and to develop guidelines for using the CORSIM model to account for the affects of adverse weather conditions on traffic operations.

This report summarizes the methodologies, findings, and conclusions for each of these study objectives. A high-level conclusion from this project is that CORSIM can be used adequately to model the affects of weather events on traffic operations. This conclusion is based on the fact that a majority of the generic weather-related parameters identified are currently available in CORSIM, and that the key weather-related parameters are adequately sensitive in producing model outputs inline with that expected from adverse weather.

17. Key Words
traffic simulation, traffic operations, CORSIM, adverse weather, weather responsive traffic management, highway capacity      

18. Distribution Statement
No restrictions. This document is available to the public through the National Technical Information Service, Springfield, VA 22161.

19. Security Classif. (of this report)

20. Security Classif. (of this page)

21. No of Pages 77

22. Price

     

Form DOT F 1700.7  (8-72)                                               Reproduction of completed pages authorized


SI* (Modern Metric) Conversion Factors


Table of Contents

Executive Summary

1. Introduction

Background

Study Objective

Study Approach

Report Outline

2. General Relationship Between Weather Events and Traffic Operations

Definition of Weather Event

Relationship Between Roadway Environment and Weather Event

Relationship Between Roadway Environment and Traffic Parameters

3. Literature Review

Free-Flow Speed

Startup Lost Time

Saturation Headway

Traffic Demand

4. Identifying Simulation Parameters Affected by Weather Events

Road Geometry Parameters

Traffic Control and Management Parameters

Vehicle Performance Parameters

Traffic Demand Parameters

Driver Behavior Parameters

5. CORSIM Sensitivity Analysis

FRESIM Analysis Methodology

NETSIM Analysis Methodology

Data Processing Procedure

FRESIM Sensitivity Analysis Results

Sensitivity of Car Following Parameters

Sensitivity of Lane Changing Parameters

Sensitivity of Free-Flow Speed Parameters

NETSIM Sensitivity Analysis Results

Sensitivity of Car Following Parameters

Sensitivity of Lane Changing Parameters

Sensitivity of Free-Flow Speed Parameters

Sensitivity of Discharge Headway Parameters

Sensitivity of Startup Delay Parameters

Sensitivity of Turning Speed Parameters

Summary of Sensitivity Analysis

6. Guidelines for Modeling Weather Events in CORSIM

Step 1—Scope Project

Step 2—Data Collection

Step 3—Base Model Development

Step 5—Model Calibration

7. Conclusions

Relationship Between Weather Events and Traffic Operations

Microsimulation Parameters Affected by Weather Events

CORSIM Sensitivity Analysis

Guidelines for Modeling Weather Events in CORSIM

Future Research Needs

References

Bibliography

List of Figures

Figure 1. Study Approach

Figure 2. Relationship Between Weather Events and Traffic Operations

Figure 3. NETSIM Suburban Intersection Network. PA

Figure 4. NETSIM Urban Intersection Network

Figure 5. Analysis Area Information for Sample Sensitivity Test

Figure 6. Vehicle-Kilometers Traveled Graph for Sample Sensitivity Test

Figure 7. Average Speed Graph for Sample Sensitivity Test

Figure 8. Average Delay Graph for Sample Sensitivity Test

Figure 9. Average Density Graph for Sample Sensitivity Test

Figure 10. Sensitivity of Pitt Car Following Constant on Freeway System Network— Example of "Expected" Sensitivity Group

Figure 11. Sensitivity of Maximum Emergency Deceleration on Freeway System Network—Example of "Inconsistent" Sensitivity Group

Figure 12. Sensitivity of Jerk Value on Freeway System Network—Example of "No Effect" Sensitivity Group

Figure 13. Microsimulation Model Development and Application Process

List of Tables

Table 1. Impacts of Weather Events on Roadway Environment

Table 2. Range of Generic Traffic Simulation Parameters

Table 3. Road Geometry Traffic Parameters Impacted by Weather Events

Table 4. Traffic Control and Management Parameters Impacted by Weather Events

Table 5. Vehicle Performance Traffic Parameters Impacted by Weather Events

Table 6. Traffic Demand Traffic Parameters Impacted by Weather Events

Table 7. Driver Behavior Traffic Parameters Impacted by Weather Events

Table 8. FRESIM Sensitivity Analysis Networks

Table 9. Congestion Levels for FRESIM Sensitivity Analysis

Table 10. FRESIM MOEs for Sensitivity Analysis

Table 11. FRESIM MOE Collection Areas

Table 12. Car Following FRESIM Parameters Included in Sensitivity Analysis

Table 13. Lane Changing FRESIM Parameters Included in Sensitivity Analysis

Table 14. Free-Flow Speed FRESIM Parameters Included in Sensitivity Analysis

Table 15. NETSIM Sensitivity Analysis Networks

Table 16. Congestion Levels for NETSIM Sensitivity Analysis

Table 17. NETSIM MOEs for Sensitivity Analysis

Table 18. NETSIM MOE Collection Areas

Table 19. Car Following NETSIM Parameter Included in Sensitivity Analysis

Table 20. Lane Changing NETSIM Parameters Included in Sensitivity Analysis

Table 21. Free-Flow Speed NETSIM Parameters Included in Sensitivity Analysis

Table 22. Discharge Headway NETSIM Parameters Included in Sensitivity Analysis

Table 23. Startup Lost Time NETSIM Parameters Included in Sensitivity Analysis

Table 24. Turning Speed NETSIM Parameters Included in Sensitivity Analysis

Table 25. General Information for Sample Sensitivity Test

Table 26. Vehicle-Kilometers Traveled Table for Sample Sensitivity Test

Table 27. Average Speed Table for Sample Sensitivity Test

Table 28. Average Delay Table for Sample Sensitivity Test

Table 29. Average Density Table for Sample Sensitivity Test

Table 30. CORSIM Parameter Sensitivity Groups

Table 31. General Sensitivity of FRESIM Car Following Parameters

Table 32. General Sensitivity of FRESIM Lane Changing Parameters

Table 33. General Sensitivity of FRESIM Free-Flow Speed Parameters

Table 34. General Sensitivity of NETSIM Car Following Parameters

Table 35. General Sensitivity of NETSIM Lane Changing Parameters

Table 36. General Sensitivity of NETSIM Free-Flow Speed Parameters

Table 37. General Sensitivity of NETSIM Discharge Headway Parameters

Table 38. General Sensitivity of NETSIM Startup Delay Parameters

Table 39. General Sensitivity of NETSIM Turning Speed Parameters

Table 40. Traffic Parameters with No Effect on MOEs

Table 41. Traffic Parameters with Expected and Medium-to-High Effect on MOEs

Table 42. CORSIM Parameters Impacted by Weather Events

 

Executive Summary

Adverse weather conditions can have a dramatic impact on the operations and quality of traffic flow. With the advent of advanced traffic management systems (ATMS), there is an opportunity to develop traffic management strategies that seek to minimize negative weather-related impacts on traffic operations. Although simulation models are used widely in evaluating various traffic management strategies, applying them to evaluate ATMS strategies under adverse weather conditions needs to be explored.

The objectives of this study were to identify how weather events impact traffic operations, assess the sensitivity of weather-related traffic parameters in the CORridor SIMulation (CORSIM) traffic microsimulation model, and develop guidelines for using the CORSIM model to account for the impacts of adverse weather conditions on traffic operations.

This final report summarizes the methodologies, findings, and conclusions for each of these study objectives. A high-level conclusion from this project is that CORSIM can be used adequately to model the impacts of weather events on traffic operations. This conclusion is based on the fact that a majority of the generic weather-related parameters identified are currently available in CORSIM, and that the key weather-related parameters are adequately sensitive in producing model outputs inline with that expected from adverse weather.

This report is organized into seven major sections. A summary of each section is provided below.

Section 1Introduction

This section presents the background and motivation for completing this project.It also highlights the objectives of the study and work tasks for each phase of the study.

Section 2—General Relationship Between Weather Events and Traffic Operations

Conceptually, it is easy to understand that a major weather event, such as a snowstorm, will lead to lower average speeds and higher delays. However, it is important to know what this relationship is, or in other words, what causes a weather event to degrade traffic operations.

This section shows that a weather event impacts traffic operations through a chain reaction: a weather event causes a change in the roadway environment (e.g., reduced visibility and pavement friction), which causes a reduction in traffic parameters (e.g., lower free-flow speeds and capacities), thereby creating a degradation in traffic flow (e.g., higher delays and lower average speeds).

The qualitative impacts of weather events are seen easily through this relationship, but the quantitative impacts have been historically difficult to measure for a number of reasons. For example, there are many "shades" of the severity of a weather event, and the impacts are different regionally (i.e., a snowstorm in Florida will have more impact than the same storm in Minnesota) and by time of year (i.e., a snowstorm at the beginning of winter will likely have more impact than the same storm near the end of winter after drivers have acclimated to the adverse weather).

Section 3—Literature Review

This section summarizes past research regarding the impact of weather events on traffic parameters, or inputs to a traffic model. Past research has shown a quantitative link between various weather events and reduced free-flow speeds, saturation (discharge) headway, startup lost time, and traffic demand.

Section 4—Identifying Simulation Parameters Affected by Weather Events

This section identifies the range of simulation parameters likely impacted by weather events. First, researchers developed a list of generic microsimulation parameters that are included in most simulation models. Then, parameters that potentially are impacted by weather events through a change in the roadway environment were determined based on the literature review and engineering judgment (e.g., adverse weather generally causes more conservative driver behavior, which means car following behavior is likely impacted by adverse weather).

Section 5—CORSIM Sensitivity Analysis

The purpose of the sensitivity study was to identify the most sensitive weather-related parameters in CORSIM. Each test parameter was modeled on various geometric networks and congestion (volume) levels using the default value and then changing the value to represent incrementally more conservative driver behavior, as would occur under adverse weather. The measures of effectiveness (MOE) produced by the default value then were compared to the MOEs produced with the changed parameter values to determine the level of sensitivity the parameter has on the MOEs.

Due to the large number of roadway networks, congestion levels, and parameters tested, approximately 45,000 individual CORSIM runs were completed. As a result, a largely automated process of creating the CORSIM input files and summarizing the output files was created specifically for this project.

One interesting result of the sensitivity analysis was that a number of parameters tested (19 total) had little or no impact on the MOEs. The majority of these were lane changing parameters. This finding does not mean they have no sensitivity whatsoever, but that they showed no sensitivity to the aggregate-level MOEs used for this study.

A number of weather-related parameters had an expected effect on the MOEs and were categorized as either having a medium or high effect on the MOEs (relative to the other parameters). These parameters are important because they represent the key weather-related parameters that should be altered when trying to model weather events in CORSIM. These parameters included the car following sensitivity multiplier and mean free-flow speed for freeway facilities, and time to react to sudden deceleration of lead vehicle, mean free-flow speed, mean discharge headway, and mean startup delay for arterial streets.

Section 6—Guidelines for Modeling Weather Events in CORSIM

This section provides practical guidelines for modeling weather events in CORSIM. The guidelines are based on Traffic Analysis Toolbox Volume III: Guidelines for Applying Traffic Microsimulation Modeling Software, a Federal Highway Administration (FHWA) guidance document on the proper guidance in this section builds on the more general microsimulation guidance by providing additional considerations when modeling weather events in CORSIM. For example, the type, severity, extent, and time period of the weather event being modeled should be agreed on before coding the model.

This section also details specific CORSIM parameters to consider changing when modeling various weather events. Finally, this section describes an alternate method of calibrating a microscopic simulation model when field data collection during adverse weather is not possible.

Section 7—Conclusions

This section summarizes the findings and results of each phase of the study and also highlights four areas of future research: empirical data collection to improve base understanding of impact of weather events on traffic operations, CORSIM enhancements for modeling adverse weather events, further study of CORSIM parameters which showed no or little sensitivity, and real-world case study of modeling weather events using CORSIM.

Table of Contents | Next

ResearchFHWA
FHWA
United States Department of Transportation - Federal Highway Administration