With the development of information technology and connected vehicles technology, vehicle trajectories acquisition in a crowdsourcing way are becoming more prevalent. The detailed vehicle trajectory data provide a new means of signal offset optimization on urban arterial. One critical factor associated is the sampling frequency (SF) of probe vehicles, which is supposed to significantly impact the communication cost and the effect of signal offset optimization. Thus, in this study such issue was scrutinized by using field DiDi vehicle trajectory data collected in one arterial of Shenzhen, China. Given an average penetration rate of DiDi vehicles of 7.4%, four SFs, i.e., 1/3, 1/6, 1/9 and 1/12 HZ are set. Signal offset was optimized by examining the average vehicle delay at each intersection. It was generally found that the performance of offset optimization gets enhanced with the increasing of SF, however, become less insensitive when SF is below 1/6 HZ.

CICTP