New Model for Predicting Freeway Incidents and Incident Delays

Abstract

This paper presents a new model that predicts the number of freeway incidents and associated delays based on general freeway segment characteristics, traffic volumes, and incident management procedures. The model is intended to be used in planning capacity-enhancing freeway improvements and incident management programs. Estimates of incident frequencies, severity, durations, and delays are provided for seven standard incident types, each of which represents a significant fraction of total unplanned incidents and has severity and/or duration characteristics substantially different from the others. In addition to describing the incident prediction model, the paper addresses the need for a coordinated national strategy for collecting incident data, with particular attention to urban freeways. It concludes that the incident data systems that have evolved in several urban areas, often in connection with freeway service patrols and incident response team activities, already provide a valuable nationwide data resource for understanding incident patterns and their variations. However, better national coordination of locally collected incident data would be helpful for addressing issues beyond the scope of the local concerns for which virtually all current systems were originally designed. Specific areas for improvement include the definitions of incident types, descriptions of incident locations (relative to both the length and breadth of the highway), and data recording the critical times during incidents such as when detection, response, and clearing occur.