Car-following model and optimization strategy for connected and automated vehicles under mixed traffic environment

PENG Jia-li; SHANGGUAN Wei; CHAI Lin-guo; QIU Wei-zhi

doi:10.19818/j.cnki.1671-1637.2023.03.018

Volume 23 Issue 3

Jun. 2023

Turn off MathJax

Article Contents

Article Navigation > Journal of Traffic and Transportation Engineering > 2023 > 23(3): 232-247

Next Previous

PENG Jia-li, SHANGGUAN Wei, CHAI Lin-guo, QIU Wei-zhi. Car-following model and optimization strategy for connected and automated vehicles under mixed traffic environment[J]. Journal of Traffic and Transportation Engineering, 2023, 23(3): 232-247. doi: 10.19818/j.cnki.1671-1637.2023.03.018

Citation:

PENG Jia-li, SHANGGUAN Wei, CHAI Lin-guo, QIU Wei-zhi. Car-following model and optimization strategy for connected and automated vehicles under mixed traffic environment[J]. Journal of Traffic and Transportation Engineering, 2023, 23(3): 232-247. doi: 10.19818/j.cnki.1671-1637.2023.03.018

Citation:

PENG Jia-li, SHANGGUAN Wei, CHAI Lin-guo, QIU Wei-zhi. Car-following model and optimization strategy for connected and automated vehicles under mixed traffic environment[J]. Journal of Traffic and Transportation Engineering, 2023, 23(3): 232-247. doi: 10.19818/j.cnki.1671-1637.2023.03.018

PDF( 25318 KB)

Car-following model and optimization strategy for connected and automated vehicles under mixed traffic environment

doi: 10.19818/j.cnki.1671-1637.2023.03.018

1.
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
2.
State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China

Funds:

National Natural Science Foundation of China 52272328

Joint Fund of the Ministry of Education for Equipment Preresearch 8091B022238

Natural Science Foundation of Beijing L211022

More Information

Author Bio:
PENG Jia-li(1997-), male, doctoral student, jialipeng@bjtu.edu.cn

SHANGGUAN Wei(1979-), male, professor, PhD, wshg@bjtu.edu.cn
Received Date: 2022-11-30
Available Online: 2023-07-07
Publish Date: 2023-06-25

Abstract

Abstract

To improve the driving efficiency and traffic flow stability of vehicles in the mixed traffic environment, the informations such as the velocities and accelerations of multiple vehicles in front were fused, and an exponential smoothing approach was adopted to build a car-following model of connected and automated vehicles (CAVs) based on the backward-looking effect. Then the effects of number of vehicles in front and behind and the completeness of state information on the model stability were studied. The linear stability analysis was carried out and the optimal parameters of the model were determined by combining the Lyapunov's first method and linear harmonic perturbation method. Combined with the characteristics of mixed traffic environments, the car-following strategies of CAVs in different positions and states were proposed in the condition of communication information loss. The numerical simulations were carried out in three typical scenarios with different CAV penetration rates, including vehicle starting, vehicle braking to stop, and circular road. Research results show that in the scenario of vehicle braking to stop, the maximum stopping wave speed of all vehicles increases by 26.1%. In the scenario of vehicle starting, the maximum starting wave speed increases by 15.5%, and the accelerations and speeds of vehicles change more smoothly. In the circular road scenario, when the CAV penetration rate in the mixed traffic flow increases from 40% to 100%, the fluctuation time of average speed of vehicles in the larger disturbance scenario decreases by 44.8%, the wave peak decreases by 5.7%, and the wave trough increases by 19.4%, compared to the low CAV penetration rate scenarios. However, the proposed optimization strategy does not significantly improve the mixed traffic flow at a lower CAV penetration rate. Thus, in the current situation where it is difficult to construct an actual mixed traffic environment and conduct CAV real vehicle tests, the model and strategies can be employed for the car-following simulation and test verification in specific scenarios to effectively guarantee the absorption of traffic flow disturbance and stable driving vehicles in the mixed traffic environment.
- traffic information engineering,
- car-following model,
- numerical simulation,
- mixed traffic environment,
- connected and automated vehicle

FullText(HTML)

References(36)

References

[1]	YANG Long-hai, ZHANG Chun, QIU Xiao-yun, et al. Research progress on car-following models[J]. Journal of Traffic and Transportation Engineering, 2019, 19(5): 125-138. (in Chinese) doi: 10.3969/j.issn.1671-1637.2019.05.014
[2]	TIAN Ye, PEI Hua-xin, YAN Song, et al. Extended driving risk field model for i-VICS and its application[J]. Journal of Tsinghua University (Science and Technology), 2022, 62(3): 447-457. (in Chinese) doi: 10.16511/j.cnki.qhdxxb.2021.22.034
[3]	CHEN Dan-jue, SRIVASTAVA A, AHN S, et al. Traffic dynamics under speed disturbance in mixed traffic with automated and non-automated vehicles[J]. Transportation Research Part C: Emerging Technologies, 2020, 113: 293-313. doi: 10.1016/j.trc.2019.03.017
[4]	NEWELL G F. Nonlinear effects in the dynamics of car following[J]. Operations Research, 1961, 9(2): 209-229. doi: 10.1287/opre.9.2.209
[5]	BANDO M, HASEBE K, NAKAYAMA A, et al. Dynamical model of traffic congestion and numerical simulation[J]. Physical Review E, 1995, 51(2): 1035-1042. doi: 10.1103/PhysRevE.51.1035
[6]	HELBING D, TILCH B. Generalized force model of traffic dynamics[J]. Physical Review E, 1998, 58(1): 133-138. doi: 10.1103/PhysRevE.58.133
[7]	JIANG Rui, WU Qing-song, ZHU Zuo-jin. Full velocity difference model for a car-following theory[J]. Physical Review E, 2001, 64(1): 017101. doi: 10.1103/PhysRevE.64.017101
[8]	SUN Di-hua, ZHANG Jian-chang, LIAO Xiao-yong, et al. Optimal velocity difference model of non-neighboring vehicles[J]. Journal of Traffic and Transportation Engineering, 2011, 11(6): 114-118. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2011.06.018
[9]	TANG Yi, LIU Wei-ning, SUN Di-hua, et al. A new car following model with considering the synergy effect of ahead-backward vehicles and its stability analysis[J]. Journal of Harbin Institute of Technology, 2014, 46(2): 115-120. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-HEBX201402021.htm
[10]	PENG Guang-han, LU Wei-zhen, HE Hong-di, et al. Nonlinear analysis of a new car-following model accounting for the optimal velocity changes with memory[J]. Communications in Nonlinear Science and Numerical Simulation, 2016, 40: 197-205. doi: 10.1016/j.cnsns.2016.04.024
[11]	JI Yi, SHI Xin, ZHAO Xiang-mo. Car-following model for intelligent connected vehicles based on multiple headway information fusion[J]. Journal of Computer Applications, 2019, 39(12): 3685-3690. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-JSJY201912044.htm
[12]	WANG Shu-yi, YU Bin, WU Mi-yi. MVCM car-following model for connected vehicles and simulation-based traffic analysis in mixed traffic flow[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(6): 5267-5274. doi: 10.1109/TITS.2021.3052818
[13]	WU Bing, WANG Wen-xuan, LI Lin-bo, et al. Longitudinal control model for connected autonomous vehicles influenced by multiple preceding vehicles[J]. Journal of Traffic and Transportation Engineering, 2020, 20(2): 184-194. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2020.02.015
[14]	ZONG Fang, SHI Pei-xin, WANG Meng, et al. Connected and automated vehicle mixed-traffic car-following model considering states of multiple front and rear vehicles[J]. China Journal of Highway and Transport, 2021, 34(7): 105-117. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL202107009.htm
[15]	ZHANG Yi, YAO Dan-ya, LI Li, et al. Technologies and applications for intelligent vehicle-infrastructure cooperation systems[J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(5): 40-51. (in Chinese) doi: 10.16097/j.cnki.1009-6744.2021.05.005
[16]	NGODUY D, LEE S, TREIBER M, et al. Langevin method for a continuous stochastic car-following model and its stability conditions[J]. Transportation Research Part C: Emerging Technologies, 2019, 105: 599-610. doi: 10.1016/j.trc.2019.06.005
[17]	YUAN Zi-jian, WANG Tao, ZHANG Jing, et al. Influences of dynamic safe headway on car-following behavior[J]. Physica A: Statistical Mechanics and its Applications, 2022, 591: 126697. doi: 10.1016/j.physa.2021.126697
[18]	ZHU Wen-xing, ZHANG Li-dong. A new car-following model for autonomous vehicles flow with mean expected velocity field[J]. Physica A: Statistical Mechanics and its Applications, 2018, 492: 2154-2165. doi: 10.1016/j.physa.2017.11.133
[19]	MA Guang-yi, MA Ming-hui, LIANG Shi-dong, et al. Nonlinear analysis of the car-following model considering headway changes with memory and backward looking effect[J]. Physica A: Statistical Mechanics and its Applications, 2021, 562: 125303. doi: 10.1016/j.physa.2020.125303
[20]	TANG Tie-qiao, GUI Yong, ZHANG Jian. ATAC-based car-following model for level 3 autonomous driving considering driver's acceptance[J]. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(8): 10309-10321. doi: 10.1109/TITS.2021.3090974
[21]	QIN Yan-yan, WANG Hao, WANG Wei, et al. Review of car-following models of adaptive cruise control[J]. Journal of Traffic and Transportation Engineering, 2017, 17(3): 121-130. (in Chinese) doi: 10.3969/j.issn.1671-1637.2017.03.013
[22]	MA Hua-qing, WU Hao, HU Yu-cong, et al. Multiple-factors aware car-following model for connected and autonomous vehicles[J]. Transportation Research Record, 2021, 2676(2): 649-662.
[23]	AN Shu-ke, XU Liang-jie, QIAN Liang-hui, et al. Car-following model with optimal velocity information of multiple-vehicle ahead[J]. Journal of Southeast University (Natural Science Edition), 2020, 50(6): 1156-1162. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DNDX202006024.htm
[24]	WEI Chong-feng, PASCHALIDIS E, MERAT N, et al. Human-like decision making and motion control for smooth and natural car following[J]. IEEE Transactions on Intelligent Vehicles, 2023, 8(1): 263-274. doi: 10.1109/TIV.2021.3098184
[25]	DU Yu, SHANGGUAN Wei, CHAI Lin-guo, et al. Departure time prediction based eco-driving method of signalized intersection[J]. China Journal of Highway and Transport, 2022, 35(6): 277-288. (in Chinese) doi: 10.19721/j.cnki.1001-7372.2022.06.023
[26]	ZHU Wen-xing, ZHANG H M. Analysis of mixed traffic flow with human-driving and autonomous cars based on car-following model[J]. Physica A: Statistical Mechanics and its Applications, 2018, 496: 274-285. doi: 10.1016/j.physa.2017.12.103
[27]	PENG Jia-li, SHANGGUAN Wei, CHAI Lin-guo. Strategy of lane-changing coupling process for connected and automated vehicles in mixed traffic environment[J]. Transportmetrica B: Transport Dynamics, 2023, 11(1): 979-995. doi: 10.1080/21680566.2022.2154288
[28]	QIN Yan-yan, ZHANG Jian, CHEN Ling-zhi, et al. Cell transmission model of mixed traffic flow of manual-automated driving[J]. Journal of Traffic and Transportation Engineering, 2020, 20(2): 229-238. (in Chinese) doi: 10.19818/j.cnki.1671-1637.2020.02.019
[29]	PENG Jia-li, SHANGGUAN Wei, ZHANG Lu, et al. An optimal scheduling method using multi-agent a for autonomous shuttle bus[C]//IEEE. 2021 40th Chinese Control Conference. New York: IEEE, 2021: 6040-6045.
[30]	LI Yong-fu, HE Chang-peng, ZHU Hao, et al. Nonlinear longitudinal control for heterogeneous connected vehicle platoon in the presence of communication delays[J]. Acta Automatica Sinica, 2021, 47(12): 2841-2856. (in Chinese) doi: 10.16383/j.aas.c190442
[31]	PENG Yong, SHA Xiao-yu, LIU Shi-jie, et al. Continuous cellular automaton traffic flow model based on PFV strategy[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(3): 75-80. (in Chinese) doi: 10.16097/j.cnki.1009-6744.2019.03.012
[32]	YAO Zhi-hong, JIN Yu-ting, WANG Si-chen, et al. Stability and safety analysis on traffic flow mixed with ICV[J]. China Safety Science Journal, 2021, 31(10): 136-143. (in Chinese) doi: 10.16265/j.cnki.issn1003-3033.2021.10.019
[33]	QIN Yan-yan, WANG Hao, WANG Wei. Analysis on stability and safety for mixed traffic flow with connected auxiliary driving[J]. Journal of Southeast University (Natural Science Edition), 2018, 48(1): 188-194. (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-DNDX201801029.htm
[34]	LI Xia, WANG Yi-ge, CUI Hong-jun, et al. Stability analysis of complex heterogeneous traffic flow under connected and autonomous environment[J]. Journal of Transportation Systems Engineering and Information Technology, 2020, 20(6): 114-120. (in Chinese) doi: 10.16097/j.cnki.1009-6744.2020.06.015
[35]	YU Hai-yang, JIANG Rui, HE Zheng-bing, et al. Automated vehicle-involved traffic flow studies: a survey of assumptions, models, speculations, and perspectives[J]. Transportation Research Part C: Emerging Technologies, 2021, 127: 103101. doi: 10.1016/j.trc.2021.103101
[36]	MIN Hai-gen, FANG Yu-kun, WU Xia, et al. On-ramp merging strategy for connected and automated vehicles based on complete information static game[J]. Journal of Traffic and Transportation Engineering (English Edition), 2021, 8(4): 582-595. doi: 10.1016/j.jtte.2021.07.003

Relative Articles

Supplements(0)

Cited By

Get Citation

PDF

XML

Article Metrics

Article views (1683) PDF downloads(340)

Car-following model and optimization strategy for connected and automated vehicles under mixed traffic environment

doi: 10.19818/j.cnki.1671-1637.2023.03.018

Abstract

References

Catalog

Article Metrics

Related

Car-following model and optimization strategy for connected and automated vehicles under mixed traffic environment

doi: 10.19818/j.cnki.1671-1637.2023.03.018

Abstract

References

Catalog

Article Metrics

Related

Export File

Citation

Format

Content