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An extended car-following model considering driver’s memory and average speed of preceding vehicles with control strategy

Author

Listed:
  • Sun, Yuqing
  • Ge, Hongxia
  • Cheng, Rongjun

Abstract

Considering effect of driver’s memory and average speed effect of preceding vehicles, an extended car-following model is proposed in this paper. The control signal including the velocity difference between the considered vehicle’s velocity and its preceding cars’ average speed is considered. The stability conditions of the model are derived by control theory method. The extended model is also analyzed from the perspective of energy consumption. Numerical simulation results show that driver’s memory has negative impact on stability of traffic flow and increases the energy consumption. However, the control signal can enhance the stability of traffic system and depress the energy consumption.

Suggested Citation

  • Sun, Yuqing & Ge, Hongxia & Cheng, Rongjun, 2019. "An extended car-following model considering driver’s memory and average speed of preceding vehicles with control strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 752-761.
    • Handle: RePEc:eee:phsmap:v:521:y:2019:i:c:p:752-761
    DOI: 10.1016/j.physa.2019.01.092
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    as
    1. Jiang, Rui & Wu, Qing-Song & Zhu, Zuo-Jin, 2002. "A new continuum model for traffic flow and numerical tests," Transportation Research Part B: Methodological, Elsevier, vol. 36(5), pages 405-419, June.
    2. Li, Xiangchen & Luo, Xia & He, Mengchen & Chen, Siwei, 2018. "An improved car-following model considering the influence of space gap to the response," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 536-545.
    3. Ou, Hui & Tang, Tie-Qiao, 2018. "Impacts of moving bottlenecks on traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 131-138.
    4. Qin, Shunda & He, Zhiting & Cheng, Rongjun, 2018. "An extended lattice hydrodynamic model based on control theory considering the memory effect of flux difference," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 809-816.
    5. Peng, Guanghan & Kuang, Hua & Qing, Li, 2018. "Feedback control method in lattice hydrodynamic model under honk environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 651-656.
    6. Xin, Qi & Yang, Nan & Fu, Rui & Yu, Shaowei & Shi, Zhongke, 2018. "Impacts analysis of car following models considering variable vehicular gap policies," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 338-355.
    7. Ou, Hui & Tang, Tie-Qiao, 2018. "An extended two-lane car-following model accounting for inter-vehicle communication," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 495(C), pages 260-268.
    8. Li, Zhipeng & Li, Wenzhong & Xu, Shangzhi & Qian, Yeqing, 2015. "Stability analysis of an extended intelligent driver model and its simulations under open boundary condition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 526-536.
    9. Cao, Bao-gui, 2015. "A new car-following model considering driver’s sensory memory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 218-225.
    10. Zhao, Xiaomei & Gao, Ziyou, 2006. "A control method for congested traffic induced by bottlenecks in the coupled map car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 513-522.
    11. Sharma, Sapna, 2015. "Lattice hydrodynamic modeling of two-lane traffic flow with timid and aggressive driving behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 401-411.
    12. Tang, Tie-Qiao & Luo, Xiao-Feng & Zhang, Jian & Chen, Liang, 2018. "Modeling electric bicycle’s lane-changing and retrograde behaviors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1377-1386.
    13. Robert Herman & Elliott W. Montroll & Renfrey B. Potts & Richard W. Rothery, 1959. "Traffic Dynamics: Analysis of Stability in Car Following," Operations Research, INFORMS, vol. 7(1), pages 86-106, February.
    14. Nagatani, Takashi, 1997. "Kinetic segregation in a multilane highway traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 237(1), pages 67-74.
    15. Yang, Liang-Yi & Sun, Di-Hua & Zhao, Min & Cheng, Sen-Lin & Zhang, Geng & Liu, Hui, 2018. "The influence of continuous historical velocity difference information on micro-cooperative driving stability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 294-301.
    16. Helbing, Dirk, 1996. "Derivation and empirical validation of a refined traffic flow model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 233(1), pages 253-282.
    17. Sun, Dihua & Kang, Yirong & Yang, Shuhong, 2015. "A novel car following model considering average speed of preceding vehicles group," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 103-109.
    18. G. F. Newell, 1961. "Nonlinear Effects in the Dynamics of Car Following," Operations Research, INFORMS, vol. 9(2), pages 209-229, April.
    19. Zhu, Wen-Xing & Zhang, Li-Dong, 2014. "A speed feedback control strategy for car-following model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 343-351.
    20. Peng, Guanghan & Yang, Shuhong & Zhao, Hongzhuan, 2018. "A delayed-feedback control method for the lattice hydrodynamic model caused by the historic density difference effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 855-860.
    21. Peng, Guang-han & Cheng, Rong-jun, 2013. "A new car-following model with the consideration of anticipation optimal velocity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3563-3569.
    22. Tang, Tie-Qiao & Rui, Ying-Xu & Zhang, Jian & Shang, Hua-Yan, 2018. "A cellular automation model accounting for bicycle’s group behavior," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 492(C), pages 1782-1797.
    23. Yu, Shaowei & Zhao, Xiangmo & Xu, Zhigang & Zhang, Licheng, 2016. "The effects of velocity difference changes with memory on the dynamics characteristics and fuel economy of traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 613-628.
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