@article{ref1,
title="Automated road safety analysis using computer vision techniques",
journal="Proceedings of the Road Safety on Four Continents Conference",
year="2010",
author="Saunier, Nicolas and Sayed, Tarek and Ismail, Karim",
volume="15",
number="",
pages="507-518",
abstract="Traffic safety analysis has often been undertaken using historical collision  data. However, there are well-recognized availability and quality problems associated with collision data. In addition, the use of collision records for safety analysis is reactive: a significant number of collisions has to be recorded before action is taken. Therefore, the observation of traffic conflicts  has been advocated as a complementary approach to analyze traffic safety. However, incomplete conceptualization, and the cost of training observers and collecting conflict data have been factors inhibiting extensive application of the technique. Therefore, the successful automation of extracting conflicts from  video sensors data using computer vision techniques can have practical benefits  for traffic safety analysis. This paper describes a comprehensive system for automated road safety analysis using video sensors. The system automatically detects traffic conflicts in video data and calculates several conflict indicators. The paper describes two applications of the automated system. The first deals with detecting pedestrian/vehicle conflicts in downtown Vancouver. The second application introduces a probabilistic framework for the analysis of road user interactions. The framework provides computational definitions of the probability of collision for road users involved in interactions.<p />",
language="",
issn="",
doi="",
url="http://dx.doi.org/"
}