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Examining traffic conflicts of up stream toll plaza area using vehicles' trajectory data

机译:使用车辆的轨迹数据检查上游收费广场区域的交通冲突

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摘要

Despite the recognized benefits of electronic toll collection (ETC) system as an important part of toll plaza area, the mixed traffic of electronic toll collection (ETC) vehicles and manual toll collection (MTC) vehicles in the toll plaza diverging area are considered risky to vehicles, in which complex diverging and crossing behavior of vehicles would increase the collision risks. Therefore, it is vitally important to investigate the vehicle collision risk in the up stream toll plaza area. Video data are collected from a typical toll plaza in Nanjing, China, and vehicle trajectory data are extracted using an automated analysis system based on OpenCV. An extended Time-To-Collision (TTC) is proposed to evaluate the vehicle collision risk. Subsequently, the different effects on vehicle collision risk of vehicles with different toll collection types, target lanes and locations are compared. Furthermore, the random parameters logistic model is developed to investigate the effects of explanatory factors on the collision risk of vehicles diverging or adjusting their lane position. The results suggested that the MTC vehicles have the highest collision risk in the toll plaza diverging area and there are significant different effects on collision risk among vehicles with different target toll collection lanes. Further, more dangerous situations could be found for a vehicle if it is closer to the toll collection lanes and surrounded by heavy traffic. It is also confirmed that mixed traffic with MTC and ETC vehicles could increase the crash risk in the toll plaza diverging area. It is expected that the findings could help engineers and operators select the appropriate engineering and traffic control solutions to enhance the safety at the toll plaza diverging area.
机译:尽管电子收费系统(ETC)作为收费广场区域的重要组成部分已获得公认的好处,但在收费广场分流区域,电子收费(ETC)车辆和手动收费(MTC)车辆的混合交通仍被认为存在风险车辆,其中复杂的车辆分叉和交叉行为会增加碰撞风险。因此,调查上游收费广场区域的车辆碰撞风险至关重要。从中国南京典型的收费广场收集视频数据,并使用基于OpenCV的自动分析系统提取车辆轨迹数据。提出了延长碰撞时间(TTC)来评估车辆碰撞风险。随后,比较了具有不同收费类型,目标车道和位置的车辆对车辆碰撞风险的不同影响。此外,建立了随机参数逻辑模型,以研究解释性因素对车辆偏离或调整车道位置的碰撞风险的影响。结果表明,MTC车辆在通行费广场分散区域的碰撞风险最高,并且在具有不同目标收费车道的车辆之间对碰撞风险的影响差异显着。此外,如果车辆靠近收费通道并被繁忙的交通包围,则可能会发现更危险的情况。还可以确定的是,与MTC和ETC车辆混合行驶会增加收费广场分叉区域的撞车风险。预期这些发现将有助于工程师和操作人员选择适当的工程和交通控制解决方案,以提高收费广场分叉区域的安全性。

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