16th Road Safety on Four Continents Conference Beijing, China 15-17 May 2013 A NOVEL APPROACH FOR DIAGNOSING ROAD SAFETY ISSUES USING AUTOMATED COMPUTER VISION TECHNIQUES Tarek Sayed, Ph.D., P.Eng. Professor, Department of Civil Engineering, University of British Columbia 6250 Applied Science Lane, Vancouver, BC, Canada V6T 1Z4 E-mail:
[email protected] Mohamed H. Zaki, Ph.D. Post-Doctoral Fellow, Department of Civil Engineering, University of British Columbia 6250 Applied Science Lane, Vancouver, BC, Canada V6T 1Z4 E-mail:
[email protected] Jarvis Autey, MSc. Research Assistant, Department of Civil Engineering, University of British Columbia, 6250 Applied Science Lane, Vancouver, BC, Canada V6T 1Z4 E-mail:
[email protected] ABSTRACT The use of traffic conflicts for safety diagnosis has been gaining acceptance as a surrogate for collision data analysis. The traffic conflicts approach provided better understanding of collision contributing factors and the failure mechanism that leads to road collisions. This paper demonstrates an automated proactive safety diagnosis approach for vehicles, pedestrian and cyclists using video-based computer vision techniques. Traffic conflicts are automatically detected and several conflict indicators such as Time to collision (TTC) are calculated based on the analysis of the road-user positions in space and time. Additionally, spatial violations are detected based on the non-conformance of road users to travel regulations. Several case studies are described. The first case study deals of the safety analysis of a newly installed bike lane at the southern approach of a heavy volume Bridge in Vancouver, British Columbia. The results showed a high exposure of cyclists to traffic conflicts.