Improved STCA lane changing model for two-lane road based on driving guidance under CVIS

被引：0
|
作者：
Li X. [1 ,2 ]
Ma W. [1 ]
Zhao Z. [3 ]
Zhang K. [1 ]
Wang X. [1 ]
机构：
[1] School of Electronics and Information, Xi'an Polytechnic University, Xi'an
[2] Bernoulli Institute Faculty of Science and Engineering, University of Groningen, Groningen
[3] Fifth Institute of Electronics, Ministry of Industry and Information Technology, Guangzhou
来源：
Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition) | 2020年 / 50卷 / 06期
关键词：
Cellular automaton model; Cooperative vehicle infrastructure system (CVIS); Lane changing model; Microscopic traffic object; Traffic engineering;
D O I：
10.3969/j.issn.1001-0505.2020.06.021
中图分类号：
学科分类号：
摘要：
To provide an applicable lane change rule for cooperative vehicle infrastructure system (CVIS) environment, an improved symmetric two-lane cellular automata (STCA) lane changing model STCA-M for two-lane road based on driving guidance was proposed. First, the relationship between vehicles in the CVIS environment was analyzed, and the threat evaluation function was constructed according to the basic information of possible interaction, such as position, speed and acceleration. Secondly, according to the dynamic safety distance and the real-time congestion state of the road section, a two-lane vehicle driving guidance function was established to provide a speed guidance and a lane change guidance. Finally, in the numerical analysis, the average velocity, the average flow rate, the lane change frequency, and the spatial and temporal speckle patterns of STCA, STCA-I, STCA-S, and hybrid two-lane traffic flow models under different vehicle densities were compared. The results show that the channel change frequency of STCA-M model is about 6.91% higher than that of STCA-S model, and the maximum average flow rate is about 21.21% and 7.28% higher than that of STCA-I and STCA-S models, respectively. STCA-M under CVIS can effectively adjust the movement trend of micro-traffic objects in two-lane road section and improve the efficiency of the vehicle lane change and the road use. © 2020, Editorial Department of Journal of Southeast University. All right reserved.
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页码：1134 / 1142
页数：8
相关论文
共 17 条
  • [1] Zhang L, Zhu X T, Li J Y., Research on application of network slices in vehicle-road cooperative system, Application of Electronic Technique, 46, 1, pp. 12-16, (2020)
  • [2] Cui X W., The future of vehicle-road collaboration: Application of intelligent highway technology in vehicle-road collaboration, China ITS Journal, 12, pp. 22-26, (2018)
  • [3] Chen C, Lu Z Y, Fu S S, Et al., Overview of the development in cooperative vehicle-infrastructure system home and abroad, Journal of Transport Information and Safety, 29, 1, pp. 102-105, (2011)
  • [4] Tang T Q, Shi W F, Shang H Y, Et al., An extended car-following model with consideration of the reliability of inter-vehicle communication, Measurement, 58, pp. 286-293, (2014)
  • [5] Lee S, Ngoduy D, Keyvan-Ekbatani M., Integrated deep learning and stochastic car-following model for traffic dynamics on multi-lane freeways, Transportation Research Part C: Emerging Technologies, 106, pp. 360-377, (2019)
  • [6] Lombard A, Abbas-Turki A, El-Moudni A., V<sub>2</sub>V-based memetic optimization for improving traffic efficiency on multi-lane roads, IEEE Intelligent Transportation Systems Magazine, 12, 1, pp. 35-46, (2020)
  • [7] Li T T, Wu J P, Chan C Y, Et al., A cooperative lane change model for connected and automated vehicles, IEEE Access, 8, pp. 54940-54951, (2020)
  • [8] Chowdhury D, Wolf D E, Schreckenberg M., Particle hopping models for two-lane traffic with two kinds of vehicles: Effects of lane-changing rules, Physica A: Statistical Mechanics and Its Applications, 235, 3, pp. 417-439, (1997)
  • [9] Wang Y M, Zhou L S, Lu Y B., Lane changing rules based on cellular automaton traffic flow model, China Journal of Highway and Transport, 21, 1, pp. 89-93, (2008)
  • [10] Xu H X, Chu S F., A symmetric same direction two-lane traffic flow model based on safe lane changing distance rule, Journal of Shenyang University (Natural Science), 28, 2, pp. 118-121, (2016)
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