High-resolution detector and signal data to support crash identification and reconstruction

Indrajit Chatterjee, Gary A Davis

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


Traffic crashes may not always result in severe or fatal injuries, but they can have a nontrivial impact on system performance, particularly during heavy traffic conditions. One way to reduce the frequency of such incidents is first to identify the necessary circumstances that resulted in the collision. However, road accidents, particularly intersection-related crashes, are complex phenomena and may result from various combinations of causal factors. Recently, methods for recording high-resolution arterial traffic data have been developed. Traffic safety engineers should explore such high-resolution data to understand the causes of crashes. A study was done to illustrate, for a particular intersection crash resulting from a signal violation, how high-resolution event-based data obtained from loop detectors could be used to identify the incident and the vehicles involved in the crash. How high-resolution data could support a traditional reconstruction of this crash was also illustrated. A Monte Carlo simulation technique was used to estimate the most probable combination of driver behaviors that resulted in the collision. Excessive speed of the vehicle that violated the red light was the most critical factor contributing to the crash.

Original languageEnglish (US)
Pages (from-to)126-133
Number of pages8
JournalTransportation Research Record
Issue number2237
StatePublished - Dec 1 2011


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