| Summary: | Safety and sustainability are the two main themes of this thesis. They are also the two main pillars of a functional transportation system. Recent studies showed that the cost of road collisions in Canada exceeds the cost of traffic congestion by almost tenfold. The reliance on collision statistics alone to enhance road safety is challenged by qualitative and quantitative limitations of collision data. Traffic conflict techniques have been advocated as a proactive and supplementary approach to collision-based road safety analysis. However, the cost of field observation of traffic conflicts coupled with observer subjectivity have inhibited the widespread acceptance of these techniques. This thesis advocates the use of computer vision for conducting automated, resource-efficient, and objective traffic conflict analysis. Video data in this thesis was collected at several national and international locations. Real-world coordinates of road users' positions were extracted by tracking moving features visible on road users from a calibrated camera. Subsequently, road users were classified into pedestrians and non-pedestrians, not differentiating between other road users' classes. Classification was based on automatically-learned and manually-annotated motion patterns. Subsequent to road user tracking, various spatiotemporal proximity measures were implemented to measure the severity of traffic events. The following contributions were achieved in this thesis: i) co-development of a methodology for tracking and classifying road users, ii) development of a methodology for measuring real-world coordinates of road users' positions which appear in video sequences, iii) automated measurement of pedestrian walking speed, iv) investigation of the effect of different factors on pedestrian walking speed, v) development and validation of a methodology for automated detection of pedestrian-vehicle conflicts, vi) investigation of the application of the developed methodology in a before-and-after evaluation of a pedestrian scramble treatment, vii) development of a methodology for aggregating event-level severity measurements into a safety index, viii) development and validation of two methodologies for automated detection of spatial traffic violations. Another contribution of this thesis was the creation of a video library collected from several locations around the world which can significantly aid in future developments in this field.
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