论文标题
通过商业连接的车辆数据评估动脉信号协调:经验交通可视化和性能测量
Evaluation of Arterial Signal Coordination with Commercial Connected Vehicle Data: Empirical Traffic Flow Visualization and Performance Measurement
论文作者
论文摘要
新兴连接的车辆(CV)数据集最近已商业上可用。本文使用简历数据介绍了几种工具,以评估信号走廊沿信号的交通进程质量。这些都包括用于高级分析的性能度量以及可视化的可视化措施,以检查协调操作的细节。通过使用CV数据,不仅可以评估走廊上的流量运动,而且可以考虑其起源用途(OD)路径。列出了八截面信号动脉的实际操作的结果。一系列高级绩效指标用于按一天中的时间评估整体绩效,并通过度量差异。接下来,使用两个可视化工具(循环时空图(TSD)和经验排进程图(PPD))检查操作的细节。比较与不同的OD路径开发的流量可视化揭示了几个特征。另外,生成了速度热图,从而提供了沿着走廊的速度性能。提出的可视化工具在整体上描绘了走廊性能,而不是结合单个信号性能指标。这项研究中所表现出的技术令人信服,可以识别需要工程解决方案的位置。无基础架构的最新进展显着提高了基于CV数据的流量管理系统的范围。该研究证明了CV轨迹数据的实用性,以获取走廊性能的高级细节并钻入微小的细节。
Emerging connected vehicle (CV) data sets have recently become commercially available. This paper presents several tools using CV data to evaluate traffic progression quality along a signalized corridor. These include both performance measures for high-level analysis as well as visualizations to examine details of the coordinated operation. With the use of CV data, it is possible to assess not only the movement of traffic on the corridor but also to consider its origin-destination (OD) path through the corridor. Results for the real-world operation of an eight-intersection signalized arterial are presented. A series of high-level performance measures are used to evaluate overall performance by time of day, with differing results by metric. Next, the details of the operation are examined with the use of two visualization tools: a cyclic time-space diagram (TSD) and an empirical platoon progression diagram (PPD). Comparing flow visualizations developed with different included OD paths reveals several features. In addition, speed heat maps are generated, providing both speed performance along the corridor. The proposed visualization tools portray the corridor performance holistically instead of combining individual signal performance metrics. The techniques exhibited in this study are compelling for identifying locations where engineering solutions are required. The recent progress in infrastructure-free sensing technology has significantly increased the scope of CV data-based traffic management systems. The study demonstrates the utility of CV trajectory data for obtaining high-level details of the corridor performance and drilling down into the minute specifics.