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A REAL-TIME TRAFFIC SIGNAL CONTROL STRATEGY UNDER PARTIALLY CONNECTED VEHICLE ENVIRONMENT

机译:部分连接的车辆环境下的实时交通信号控制策略

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摘要

The performance of a traffic system tends to improve as the percentage of connected vehicles (CV) in total flow increases. However, due to low CV penetration in the current vehicle market, improving the traffic signal operation remains a challenging task. In an effort to improve the performance of CV applications at low penetration rates, the authors develop a new method to estimate the speeds and positions of non-connected vehicles (NCV) along a signalized intersection. The algorithm uses CV information and initial speeds and positions of the NCVs from loop detectors and estimates the forward movements of the NCVs using the Gipps' car-following model. Calibration parameters of the Gipps' model were determined using a solver optimization tool. The estimation algorithm was applied to a previously developed connected vehicle signal control (CVSC) strategy on two different isolated intersections. Simulations in VISSIM showed the estimation accuracy higher for the intersection with less lanes. Estimation error increased with the decrease in CV penetration and decreased with the decrease in traffic demand. The CVSC strategy with 40% and higher CV penetration (for Intersection 1) and with 20% and higher CV penetration (for Intersection 2) showed better performance in reducing travel time delay and number of stops than the EPICS adaptive control.
机译:随着联网车辆(CV)在总流量中所占百分比的增加,交通系统的性能趋于提高。但是,由于当前汽车市场的CV普及率低,改善交通信号灯的操作仍然是一项艰巨的任务。为了提高低穿透率CV应用程序的性能,作者开发了一种新方法来估计未连接车辆(NCV)沿信号交叉口的速度和位置。该算法使用CV信息以及来自回路检测器的NCV的初始速度和位置,并使用Gi​​pps的跟车模型估算NCV的向前运动。 Gipps模型的校准参数是使用求解器优化工具确定的。该估计算法已应用于两个不同的隔离路口上先前开发的连接车辆信号控制(CVSC)策略。 VISSIM中的仿真显示,对于较少车道的交叉路口,估算精度更高。估计误差随着CV渗透率的降低而增加,并随着交通需求的降低而降低。与EPICS自适应控制相比,CVSC策略具有40%和更高的CV渗透率(针对交叉路口1)以及CV渗透率更高和20%(针对交叉路口2),在减少行驶时间延迟和停车次数方面表现出更好的性能。

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