Master of Science (MS)
First Committee Member
Number of Pages
My proposed approach to the automatic detection of traffic accidents in a signalized intersection is presented here. In this method, a digital camera is strategically placed to view the entire intersection. The images are captured, processed and analyzed for the presence of vehicles and pedestrians in the proposed detection zones. Those images are further processed to detect if an accident has occurred; The mathematical model presented is a Poisson distribution that predicts the number of accidents in an intersection per week, which can be used as approximations for modeling the crash process. We believe that the crash process can be modeled by using a two-state method, which implies that the intersection is in one of two states: clear (no accident) or obstructed (accident). We can then incorporate a rule-based AI system, which will help us in identifying that a crash has taken or will possibly take place; We have modeled the intersection as a service facility, which processes vehicles in a relatively small amount of time. A traffic accident is then perceived as an interruption of that service.
Car; Computer; Computerized; Crash; Detection; Mathematical; Model; Techniques; Vision
Computer science; Artificial intelligence; Automobiles--Design and construction
University of Nevada, Las Vegas
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Strianese, Dawn Marie, "A mathematical model for computerized car crash detection using computer vision techniques" (2008). UNLV Retrospective Theses & Dissertations. 2323.