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21st Century Operations Using 21st Century Technologies
Table of Contents

Analysis, Modeling, and Simulation for Traffic Incident Management Applications

Introduction

Purpose of This Document

Traffic incidents are a major source of congestion in both urban and rural areas. Nationally, roughly 25 percent of total congestion is due to traffic incidents (Figure 1). Further, traffic incidents create unexpected congestion – congestion that occurs in times and places where travelers don’t expect to be delayed – and are therefore a major source of frustration for our customers.

Figure 1. Relative Sources of Congestion

Figure 1 is a pie chart showing the relative sources of congestion with Bottlenecks at 40 percent, Traffic Incidents at 25 percent, Work Zones at 10 percent, Weather at 15 percent, Poor Signal Timing at 5 percent, and Nonrecurring at 5 percent.

(Source: Chin et al., Temporary Losses of Highway Capacity and Impacts on Performance, prepared for FHWA, 2004.)

In addition to contributing to total congestion, disruptions such as traffic incidents, work zones, and inclement weather also define travel time reliability, which is the variability in congestion that occurs from day-to-day. This variability, and the uncertainty in travel conditions it causes, has been shown to have significant costs to travelers beyond “typical” or “average” congestion. It is therefore critical that the reliability component of congestion be captured when performing evaluations and economic analyses of transportation investments.

Implementing Traffic Incident Management (TIM) strategies has proven to be a highly cost-effective way of treating congestion problems. However, a strong need exists to be able to predict what the impacts of TIM strategies will be at the planning stage of project development and to monitor the effects of TIM programs.

To these ends, this document provides a synthesis of analysis, modeling, and simulation (AMS) methods for incident impacts. The focus is on incidents effects on congestion and reliability as well as secondary incidents, for the purpose of estimating TIM benefits and evaluating programs and proposed strategies.

The research and examples presented in this document will significantly assist practitioners in the planning and development of TIM and the evaluation of the performance of TIM strategies. By estimating the expected impacts and evaluating the performance of TIM projects, practitioners can demonstrate the value of TIM. Specifically, the research and examples can be linked with best practices in TIM in a number of ways (FHWA, Best Practices in Traffic Incident Management, Report FHWA-HOP-100-50, September 2010.):

  1. Methods for measuring incident impacts from field data: these can be used to establish performance monitoring procedures based on field data. Collection of incident data characteristics and the sensitivity of the estimates to the accuracy of incident data reporting also are covered. Travel time reliability metrics can be readily derived from field measurements of performance under incident conditions.
  2. Methods for predicting impacts of a single incident: practitioners can choose the most appropriate tool for the analysis of the problem in hand, from simple queuing models for isolated incidents to complex simulation tools on traffic corridors with multiple bottlenecks where the incident location within the system is of great importance.
  3. Methods for predicting cumulative incident impacts: systemwide impacts of incidents that can be used as a decision support tool in a TMC to trigger actions for the management of the adverse impacts of incidents is covered. These include control of ramps or signals, and rerouting of traffic.
  4. Methods for predicting incident duration: given a set of incident characteristics, what is the expected duration so more accurate information can be provided in a timely manner and response and clearance activities can be deployed. These can be used in conjunction with methods for predicting cumulative impacts (#3 above) for possible corridor management and rerouting to parallel facilities.
  5. Methods for predicting secondary incidents: better understanding of the occurrence of secondary incidents based on the characteristics of primary incidents, the operating conditions of the facility, and the TIM in place; guidance in developing and implementing TIM measures to reduce the occurrence of secondary incidents.

Uses for TIM AMS Methods

A wide variety of applications require TIM AMS methods for incidents. These applications can include:

  • Development and evaluation of TIM plans – What is the expected impact of TIM strategies on congestion and secondary crashes as a basis for a TIM plan?
  • Analysis and evaluation of TIM strategies such as use of service patrols – What effect have TIM strategies had after they were implemented?
  • Decision support systems used for incident management – What is the expected duration of an incident that has just occurred, what will be its impacts on congestion, and what strategies should be deployed to manage incidents.
  • Congestion/operations performance measurement – What are the trends in incident characteristics, how have they been affected by TIM programs, and what role do incidents play in total congestion and travel time reliability?
  • Benefit-cost analysis of TIM programs/strategies – What congestion and safety benefits result from TIM programs?
  • Integrated Corridor Management – How can the response of other corridor management methods be integrated with TIM strategies?

How We Developed This Document

In developing the material presented in this document, we reviewed the relevant technical literature as a starting point. We then conducted a survey of practitioners and researchers to identify the current state of the practice in AMS for incidents. The progress of the work was monitored by an independent three-person review panel.

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