Providing Real-Time Traffic Advisory and Route Guidance to Manage Borman Incidents On-Line Using the Hoosier Helper Program

Abstract

Prepared in cooperation with the Indiana Department of Transportation and Federal Highway Administration. AbstractThis study addresses the issue of whether the message content of variable message signs (VMS) can be used as a control variable to favorably influence traffic conditions in real-time. The focus is on the level of detail of information displayed on the VMS, and not human factor issues. It implies an understanding of driver sensitivity to information content. Also, for real-time implementation, the displayed information should be consistent, timely, and reliable. A framework is developed for optimizing system performance under incidents using the VMS message content as the primary control parameter. It consists of: (i) an efficient control strategy to enhance system performance using the VMS and information on current traffic conditions received from on-line sensors; (ii) a driver response model to supplied information that addresses the effect of the message content on drivers' en-route switching decisions; and (iii) an incident clearance time prediction model which predicts the expected delay due to an incident. Key Wordsvariable message signs, real-time incident management, advanced traffic management systems, simulation-based optimization, consistent route diversion models, internet-based driver survey, incident clearance time prediction model. Distribution StatementNo restrictions. This document is available to the public through the National Technical Information Service, Springfield, VA 22161 as part of information-based real-time advanced traffic management systems (ATMS) to enable travelers to make more informed pretrip and en-route route choice decisions. The effectiveness of the VMS strategy in enhancing travel conditions, especially under incidents, depends on driver attitudes and response behavior under the messages displayed. This highlights the importance of the content of the VMS messages displayed and the need for coordinated and consistent control strategies by the system controller. The primary focus of this study is to develop a mechanism to determine the VMS messages to be displayed that enhance system performance and are consistent with driver response behavior.To enable effective VMS-based incident management, a framework for optimizing system performance was developed using the VMS message content as the control variable. It consists of simulation-based algorithms to determine the optimal VMS messages to be displayed, driver response behavior models under the displayed VMS messages, and an incident clearance time prediction model to estimate the incident duration. The driver behavior models were classified into freight truck and non-truck categories to differentiate between the response attitudes of freight truck drivers and other travelers vis-a-vis en-route route diversion.The Borman Expressway corridor in northwest Indiana was used as a case study to develop the driver response behavior models and the incident clearance time prediction model. Simulation-based off-line testin...

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“…• ℓ 2 Regulized Linear Regression (Ridge) [23]. Ridge regression is an extension for linear regression.…”

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Traffic Incident Clearance Time Prediction and Influencing Factor Analysis Using Extreme Gradient Boosting Model

“…Statistical methods have their own model assumptions and predefined underlying relationships between dependent and independent variables [6] which provide the explainable ability to statistical methods. e widely used statistical methods are summarized as follows: probabilistic distribution analyses method [7,8], regression method [9][10][11][12][13], discrete choice method [14], structure equation method [15], hazard-based duration method [16], Cox proportional hazards regression method [17][18][19], and accelerated failure time method [20][21][22][23]. Unlike statistical methods, machine learning methods are based on a more flexible mapping process that requires no or less prior hypothesis.…”

An Improved Automatic Traffic Incident Detection Technique Using a Vehicle to Infrastructure Communication

“…e presented method produced better results as compared to other predictive models. Peeta et al [28] also proposed a variable message sign (VMS) Journal of Advanced Transportation scheme that only focused on the prediction of incident clearance time because of the delay caused by an accident.…”