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首页> 外文期刊>Promet-traffic & transportation >A REAL-TIME TRAFFIC SIGNAL CONTROL STRATEGY UNDER PARTIALLY CONNECTED VEHICLE ENVIRONMENT
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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：交通系统的性能趋于改善，因为随着总流量的百分比（CV）的百分比增加。然而，由于当前车辆市场的CV渗透率低，因此提高了交通信号操作仍然是一个具有挑战性的任务。为了以低渗透率提高CV应用的性能，作者开发了一种新方法来估计沿着信号交叉口的非连接车辆（NCV）的速度和位置。该算法使用来自环路检测器的CV信息和NCVS的初始速度和位置，并使用GIPPS'跟随模型估计NCV的前向移动。 GIPPS模型的校准参数使用求解器优化工具确定。估计算法应用于在两个不同隔离的交叉路口上的先前显影的车辆信号控制（CVSC）策略上。 Vissim中的模拟显示了与较少车道相交的估计精度。随着CV渗透率的降低，估计误差增加，随着交通需求的降低而降低。 CVSC策略具有40％和更高的CV渗透（用于交叉口1）和20％，更高的CV渗透（用于交叉口2）在减少旅行时间延迟和停止数而不是EPIC自适应控制的情况下表现出更好的性能。

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