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Creating Valuable User Information When Complex Incidents Occur In Transportation Management Centers

In Transportation Management Centers, incident information is acquired sequentially and this progression should be reflected in operational prediction models. For instance, initially we may know that there is an incident on a particular roadway and we will know only a few parameters that can be used to model and predict incident duration (typically location and time of day). So initially, analysts can make a prediction based on the limited information available about the incident (and may be able to disseminate the information to users). Then more information about the incident often arrives, e.g., the incident might be a crash and with a large truck involved and multiple injuries. The incident duration can be updated in the light of this new information, e.g., the incident will last longer due to truck-involvement and multiple injuries. To develop such time sequential operational models (for future use in TMSs), there is a need to identify distinct stages of the incident duration based on the availability of incident information.

Then statistical techniques known as truncated regression can be used to predict incident duration, as more information about the incident arrives in a TMC. Each stage can have a separate truncated regression model, and the models can progressively add more variables. The models can be developed to allow us to predict the chances of a secondary incident and provide insights into how resources might be allocated in case the chances of secondary incidents increase beyond a threshold.

These time sequential models can be tested and validated in a study by using different samples for estimation and prediction. Thus the study should develop models to forecast future incident durations and secondary crash occurrence in real-time. The information can be disseminated to users who can use it to make more informed travel choices.

Sponsoring Committee:ACH40, Human Factors of Infrastructure Design and Operations
Date Posted:11/19/2007
Date Modified:11/20/2007
Index Terms:Traffic incidents, Incident detection, Incident management, Multiple vehicle accidents, Truck accidents, Injury severity, Injuries, Traffic control centers,
Cosponsoring Committees: 
Data and Information Technology
Operations and Traffic Management
Safety and Human Factors
Terminals and Facilities

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