Automated traffic incident detection using GPS-based transit probe vehicles
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AbstractThe recent advancements in electronics, communication and information processing and the application of such technologies to transportation through Intelligent Transportation Systems (ITS) have resulted in safer, faster and more efficient surface transportation systems. ITS have contributed significantly to the current state of technology in automated traffic monitoring, and probe vehicle-based traffic monitoring is one of these techniques. Although the potential of probe vehicle-based traffic monitoring was well understood, its wider application was severely restricted by the state of vehicle positioning system capabilities and associated cost considerations. This thesis presents the devolvement and performance analysis of a probe vehicle-based automated traffic incident detection system that uses transit vehicles equipped with GPS as a passive probe vehicle fleet. Since these vehicles serve primary purposes other than providing vehicle-tracking data, such vehicles are more likely to be equipped with systems such as GPS, thus providing multiple benefits. However, passive probe vehiclebased traffic incident detection has its own challenges over dedicated probe vehicles. These challenges are addressed and solutions are developed in two stages in this thesis. Firstly, the need for a GPS positioning technique that provides better performance in urban environments is addressed with an outline of advantages of High Sensitivity GPS (HSGPS). HSGPS error mitigation techniques are discussed with the emphasis on mapmatching augmentations; a major advantage being their independence from vehicle sensors. A discussion of HSGPS map-matching issues, pros and cons of using internally filtered HSGPS positions, and alternative filtering techniques are also presented. Secondly, probe-based incident detection algorithms and their performances are analyzed. Instead of conducting a complex field data collection for probe and traffic incident data collection, a traffic microsimulation model was developed to simulate transit probe vehicles with and without simulated incidents. The simulation model is calibrated using actual transit vehicle and non-transit vehicle data collected over several days. Incidents detection performance was analyzed with respect to three indicators: Detection Rate (DR), Time to Detect (TTD) and False Alarm Rate (FAR). Performance under varying incident characteristics and GPS performance levels were investigated and the results show over a 90 % DR and a TTD of under 5 minutes for all simulated scenarios.
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