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A car-following model accounting for the driving habits

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  • Liao, Peng
  • Tang, Tie-Qiao
  • Wang, Tao
  • Zhang, Jian

Abstract

In this paper, we propose a car-following model to ensure the car-following safety, stability, comfort and fuel-optimal with consideration of the driver’s different driving habits under different headways. During the car-following state, the following vehicle’s acceleration is determined by its driving strategy in different headways to fit the driving habits. When the headway is overlong, the following vehicle will shorten the headway by a comfort and fuel-optimal acceleration–uniform motion–deceleration process to ensure the stable car-following behavior. When the headway is too short, the following vehicle take emergency brake to ensure the car-following safety. When the headway is within the desired range, the following vehicle can run at a relatively steady speed since the comfort driving is an important reason for drivers to adopt a new driving behavior. The numerical results show that the proposed model can ensure the safety, stability, comfort, fuel-optimal and the consistency with the driver’s driving habits under the car-following state.

Suggested Citation

  • Liao, Peng & Tang, Tie-Qiao & Wang, Tao & Zhang, Jian, 2019. "A car-following model accounting for the driving habits," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 108-118.
    • Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:108-118
    DOI: 10.1016/j.physa.2019.03.027
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    Cited by:

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    2. Chen, Can & Ge, Hongxia & Cheng, Rongjun, 2019. "Self-stabilizing analysis of an extended car-following model with consideration of expected effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    3. Chen, Dong & Zhao, Min & Sun, Dihua & Zheng, Linjiang & Jin, Shuang & Chen, Jin, 2020. "Robust H∞ control of cooperative driving system with external disturbances and communication delays in the vicinity of traffic signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    4. Kaur, Daljeet & Sharma, Sapna, 2020. "A new two-lane lattice model by considering predictive effect in traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    5. Shuaiyang Jiao & Shengrui Zhang & Bei Zhou & Zixuan Zhang & Liyuan Xue, 2020. "An Extended Car-Following Model Considering the Drivers’ Characteristics under a V2V Communication Environment," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    6. Wang, Xiaoning & Liu, Minzhuang & Ci, Yusheng & Wu, Lina, 2022. "Effect of front two adjacent vehicles’ velocity information on car-following model construction and stability analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 607(C).
    7. Verma, Muskan & Sharma, Sapna, 2022. "Chaotic jam and phase transitions in a lattice model with density dependent passing," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    8. Song, Tao & Zhu, Wen-Xing, 2020. "Study on state feedback control strategy for car-following system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 558(C).
    9. Verma, Muskan & Sharma, Sapna, 2023. "Modeling heterogeneity in an open percolation backbone fractal traffic network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 619(C).

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