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摘要
This paper addresses the automated analysis of pedestrians' conformance behavior and data collection in an intersection with a perceived high rate of traffic conflicts involving pedestrians. The intersection is located in the Downtown Eastside of Vancouver, British Columbia, Canada. Despite implementation of countermeasures such as reducing the speed limit, safety issues linger at the intersection. The intersection is characterized by a high pedestrian volume and considerable crossing violations by pedestrians, which elevate the safety risk and disrupt vehicle traffic flow. A challenge in performing pedestrian road safety analysis is the shortfall of reliable data. Recent advances in automated detection of pedestrians through the use of computer vision expanded the range of applications in traffic safety. In this study, an automated system for identifying pedestrian crossing nonconformance to traffic regulations by using pattern matching was developed and tested. The results show satisfactory accuracy in detecting both spatial and temporal violations, with the detection rate for violations being more than 84% correct. The automated collection of pedestrian data on crossing speed and counts is also demonstrated with high accuracy. The availability of these data is important for diagnosing the safety issues at the intersection and for justifying capital for implementing pedestrian safety countermeasures.
- 出版日期2014
