Traffic & Transportation Engineering

Effect of the Tunnel Warning System on Traffic Capacity Based on Aggregated Spatiotemporal Characteristics of Vehicles

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  • 1. Beijing Key Laboratory of Traffic Engineering,Beijing University of Technology,Beijing 100124,China;2. Traffic Operations & Safety Laboratory,University of Wisconsin-Madison,Madison 53706,USA
常鑫 (1991-),男,博士生,主要从事智能交通、交通流理论、交通安全研究。E-mail: changxin@ emails.bjut. edu. cn

Received date: 2020-02-23

  Revised date: 2020-04-10

  Online published: 2020-04-17

Supported by

Supported by the National Natural Science Foundation of China (51608017) and the Beijing Natural Science Foundation of China (9202001)

Abstract

To explore spatiotemporal characteristics of vehicles in a long tunnel road under the vehicle-road coopera-tive environment,the human-machine interface of tunnel warning system based on the connected vehicle technology was designed and a driving simulation experiment was carried out. 35 drivers' spatiotemporal characteristics of vehi-cle were studied by taking the group without warning system as the control group. The results reveal that when the system was on,the slowdown trigger points of vehicle was earlier,and the curvature values and number of inflection points of the spatiotemporal graph decreased. Moreover,the coefficient of variation of vehicle speed near the entrance and inside tunnel and the degree of overspeed in tunnel decreased obviously when the system was on. In conclusion,with the warning system,the driving pattern was changed from a visual stimulation-based response be-havior to a psychological expectation-based proactive behavior,which was easy to form the stable spatiotemporal characteristics. Further research shows that,assuming that the minimum headway of the following distance is 1. 5s,and based on the best converging patterns from 35 drivers' spatiotemporal trajectories,the overall traffic capacity was 21. 27% higher than that without the warning system.

Cite this article

CHANG Xin, LI Haijian, RONG Jian, et al . Effect of the Tunnel Warning System on Traffic Capacity Based on Aggregated Spatiotemporal Characteristics of Vehicles[J]. Journal of South China University of Technology(Natural Science), 2020 , 48(9) : 107 -115,123 . DOI: 10.12141/j.issn.1000-565X.200080

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