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摘要
This study utilizes travel time data from a well-equipped Intelligent Transportation System corridor to integrate travel time and traffic signal data with the goal of developing a volume-delay relationship between a signal's volume-capacity ratio and travel time. Specifically, the traffic signal timings were retrieved from an advanced transportation management system, individual travel time data were extracted from a WiFi-based travel time measurement system, and traffic volumes and queues were obtained by observing closed-circuit television video recordings. The collected data were then integrated on a cycle-by-cycle basis by using a C#-automated data postprocessing interface. Several traditional volume-delay functions were calibrated to fit the field data. Also, a new volume-delay function, named So-Stevanovic Volume-Delay Function, was developed to account for exponential behavior of travel time near and beyond the traffic saturation point. The So-Stevanovic Volume-Delay Function satisfied the seven Spiess's requirements for a well-behaved congestion function and produced slightly better results than the best traditional volume-delay function. All of the functions were then tested again on a different road segment in order to validate the results. These tests confirmed the previous findings that the So-Stevanovic Volume-Delay Function was the best predictor of relationship between volume-capacity ratio and link travel time. Further research should be conducted to validate this function in a variety of field traffic conditions.
- 出版日期2017-4
- 单位西北大学
