United States Department of Transportation
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Improving Rush Hour Traffic Flow by Computer-Vision-Based Parking Detection and Regulations
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2020-01-01
[PDF-2.32 MB]
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Edition:Final Report
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Abstract:To optimize the transportation network through a detailed analysis of all the traffic flows one needs to have two main ingredients. First it is necessary to have a holistic modeling framework that can manage the complexity of this multi-modal system. Second is comprehensive data for all the traffic statistics. In this project the authors want to demonstrate with an example how parking information can be incorporated into a multi-modal dynamic user equilibrium (MMDUE) model and develop a computer vision tool that can provide street parking data. This project allows the authors to collect time-varying parking data that could be used, in addition to existing traffic data, to understand travel behavior among various travel modes, such as driving (including solo-driving and carpooling), public transit, and park-and-ride. The travel behavior of all travelers in the network is then simulated to assess system performance and features of passenger/vehicular flow.
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