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A New Stochastic Discrete-Event Micro Simulation Model for Evaluating Traffic Operations at Electronic Toll Collection Plazas

机译:一种新的随机离散事件微观仿真模型,用于评估电子收费站的交通运营

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摘要

This article presents a discrete-event stochastic microscopic simulation model specifically developed to evaluate the operational performance of toll plazas. The model has been calibrated, validated, and applied to toll plazas equipped with Electronic Toll Collection (ETC) in Orlando, Florida. Traffic behavior is represented using a set of mathematical and logic algorithms that control the conflicts among vehicles within the toll plaza area. Modified versions of Car-Following and Lane-Changing Algorithms and a new Toll-Lane Selection Algorithm are integrated into this new model to simulate traffic operation at toll plazas. The model output includes Measures of Effectiveness that can be used to evaluate the performance of existing and future individual toll lanes and the entire toll plaza system. Real-life data collected at the busiest toll plaza in the Orlando-Orange County Expressway Authority (OOCEA) system was compared with the model output to validate the developed model. Statistical tests indicated that there is no significant difference at the 95% confidence level between Measures of Effectiveness obtained from the model and those collected in the real world.
机译:本文提出了一种离散事件随机微观仿真模型,该模型是专门为评估收费广场的运营性能而开发的。该模型已经过校准,验证,并已应用于佛罗里达州奥兰多市配备有电子收费站(ETC)的收费广场。交通行为使用一组数学和逻辑算法表示,这些算法控制收费广场区域内车辆之间的冲突。新的模型中集成了汽车跟随和车道变换算法的修改版本以及新的收费通道选择算法,以模拟收费站的交通运营。模型输出包括有效性度量,可用于评估现有和将来的单个收费通道和整个收费广场系统的性能。将在奥兰多-橙色县高速公路管理局(OOCEA)系统中最繁忙的收费站收集的真实数据与模型输出进行比较,以验证开发的模型。统计测试表明,从模型获得的有效性度量与在现实世界中收集的有效性度量之间,在95%的置信度水平上没有显着差异。

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