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原文传递 How Many Trajectories Should Be Collected to Evaluate Signal Coordination Performance? Cluster Analysis Using Connected Vehicle Data

题名：	How Many Trajectories Should Be Collected to Evaluate Signal Coordination Performance? Cluster Analysis Using Connected Vehicle Data
正文语种：	eng
作者：	ERICKA MORA CAMPOS;AOBO WANG;ZONG TIAN
作者单位：	University of Nevada Reno;Department of Civil & Environmental Engineering University of Nevada Reno;Center for Advanced Transportation Education and Research (CATER) at the University of Nevada Reno
摘要：	Practitioners can usually conduct floating car investigations to collect trajectory data to assess signal timing and coordination. Vehicle trajectories can provide several measures of effectiveness (MOEs) to evaluate the quality of signal timing. Travel time, arrivals on green per arrivals on red, and stops per mile are the most commonly used MOEs to intuitively characterize the performance of progressed traffic operations. Such floating-car investigations do not require additional infrastructure investment, but the data collection is typically performed manually, which can be costly and time-consuming. Consequently, it can be challenging to implement the trajectory-based signal performance measurement to achieve a representative sample size through a minimum effort of doing travel runs. Field data collection can provide the most accurate performance measurement but can often be costly or resource-prohibitive.
出版年：	2023
期刊名称：	ITE journal
卷：	93
期：	12
页码：	39-46