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A Trajectory Planning Method of Automatic Lane Change Based on Dynamic Safety Domain

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Abstract

Traditional research on automatic lane change has primarily focused on high-speed scenarios and has not considered the dynamic state changes of surrounding vehicles. This paper addresses this problem by proposing a trajectory planning method to enable automatic lane change at medium and low speeds. The method is based on a dynamic safety domain model, which takes into account the actual state change of surrounding vehicles, as well as the upper boundary of the safety domain for collision avoidance and the lower boundary of comfort for vehicle stability. The proposed method involves the quantification of the safety and comfort boundaries through parametric modeling of the vehicle. A quintic polynomial trajectory planning method is proposed and evaluated through simulation and testing, resulting in improved safety and comfort for automatic lane change.

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Abbreviations

SV:

Self-vehicle

VFS:

Front vehicle in the same lane

VFT:

Front vehicle in the target lane

VRT:

Rear vehicle in the target lane

References

  1. Zhuo, G., Wu, C., Zhang, F.: Model predictive control for feasible region of active collision avoidance. In: WCX 17: SAE World Congress Experience, pp. 4–6. Detriot (2017)

  2. Yang, D., Zheng, S., Wen, C., et al.: A dynamic lane-changing trajectory planning model for automated vehicles. Transp. Res. Part C Emerg. Technol. 95, 228–247 (2018)

    Article  Google Scholar 

  3. Guo, H., Shen, C., Zhang, H., et al.: Simultaneous trajectory planning and tracking using an MPC method for cyber-physical systems: a case study of obstacle avoidance for an intelligent vehicle. IEEE Trans. Industr. Inf. 14, 4273–4283 (2018)

    Article  Google Scholar 

  4. You, F., Zhang, R., Lie, G., et al.: Trajectory planning and tracking control for autonomous lane change maneuver based on the cooperative vehicle infrastructure system. Expert Syst. Appl. 42, 5932–5946 (2015)

    Article  Google Scholar 

  5. Bai, H., Shen, J., Wei, L., et al.: Accelerated lane-changing trajectory planning of automated vehicles with vehicle-to-vehicle collaboration. J. Adv. Transp. 2017, 1–11 (2017)

    Article  Google Scholar 

  6. Xu, G., Liu, L., Ou, Y., et al.: Dynamic modeling of driver control strategy of lane-change behavior and trajectory planning for collision prediction. IEEE Trans. Intell. Transp. Syst. 13, 1138–1155 (2012)

    Article  Google Scholar 

  7. Sazgar, H., Azadi, S., Kazemi, R.: Trajectory planning and combined control design for critical high-speed lane change manoeuvres. Proc. Inst. Mech. Eng. Part D J. Automob. Eng. (2019). https://doi.org/10.1177/0954407019845253

    Article  Google Scholar 

  8. Karlsson, J., Murgovski, N., Sjoberg., J.: Optimal trajectory planning and decision making in lane change maneuvers near a highway exit. In: 2019 18th European Control Conference (ECC), pp. 25–28 (2019)

  9. Mehmood, A., Liaquat, M., Bhatti, A.I., et al.: Trajectory planning and control for lane-change of autonomous vehicle. In: 2019 5th International Conference on Control, Automation and Robotics (ICCAR), pp. 19–22 (2019)

  10. Patel, M., Khatun, M., Jung, R., et al.: Simulation-based analysis of highway trajectory planning using high-order polynomial for highly automated driving function. In: 2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), pp. 7–8. Mauritius (2021)

  11. Ghariblu, H., Moghaddam, H.B.: Trajectory planning of autonomous vehicle in freeway driving. Trans. Telecommun. J. 22(3), 278–286 (2021)

    Google Scholar 

  12. Zhou, P., Zhu, X., Liu, X., et al.: Research on driver’s lane change intention detection method based on natural driving working condition. Shanghai Automob. 6, 36–42 (2016)

    Google Scholar 

  13. Huang, J., Tan, H.S., Bu, F., et al.: An investigation on driver trajectory planning behaviors based on double lane change vehicle test data. In: 2011 14th International IEEE Conference on Intelligent Transportation Systems, pp. 1231–1236. Washington DC (2011)

  14. Wang, X.: Automotive Chassis Design. Tsinghua University Press, Beijing (2010)

    Google Scholar 

  15. Bian, M.: A vehicle safety distance model for collision avoidance system based on emergency lane change motion. J. Chongqing Univ. Technol. (Nat. Sci.) 26, 1–4 (2016)

    MathSciNet  Google Scholar 

  16. Wang, Y., Wang, X.: The assessment of bus comfort. Railw. Locomot. Veh. 3, 1–4 (2000)

    Google Scholar 

  17. Wu, D.: Study on anti-collision control strategy of automatic emergency braking system. Dissertation, Liaoning University of Technology (2018).

  18. Zhao, D., Guo, H.: A trajectory planning method for polishing optical elements based on a non-uniform rational b-spline curve. Appl. Sci. 8(8), 1355 (2018)

    Article  Google Scholar 

  19. Wang, C., Zheng, C.: Lane change trajectory planning and simulation for intelligent vehicle. AMR 671–674, 2843–2846 (2013)

    Article  Google Scholar 

  20. Ren, D., Zhang, G., Wu, H.: Symbol reference model of desired yaw angle for automated lane changing behavior of vehicle. J. Harbin Inst. Technol. (New Ser.) 23, 23–33 (2016)

    Google Scholar 

  21. Abbas, M.A., Milman, R., Eklund, J.M.: Obstacle avoidance in real time with nonlinear model predictive control of autonomous vehicles. Can. J. Electr. Comput. Eng. 40, 12–22 (2017)

    Article  Google Scholar 

  22. Li, H., Luo, Y.: Study on steering angle input during the automated lane change of electric vehicle. In: SAE 2017 Intelligent and Connected Vehicles Symposium, pp. 26–27. Jiangsu (2017)

  23. Wang, Y., Pan, D., Liu, Z., et al.: Study on lane change trajectory planning considering of driver characteristics. In: SAE 2018 Intelligent and Connected Vehicles Symposium, pp. 14–15. Jiangsu (2018)

  24. Wang, Z., Deng, W., Zhang, S., et al.: Vehicle automatic lane changing based on model predictive control. SAE Int. J. Passeng. Cars Electron. Electr. Syst. 9, 231–236 (2016)

    Article  Google Scholar 

  25. Wang, Y., Liu, Z., Deng, H., et al.: Automatic lane change environment perception system of electric vehicle. J. Tongji Univ. (Nat. Sci.) 47, 1201–1206 (2019)

    Google Scholar 

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Correspondence to Yangyang Wang.

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The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Academic Editor: Quan Zhou

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Wang, Y., Cao, X. & Hu, Y. A Trajectory Planning Method of Automatic Lane Change Based on Dynamic Safety Domain. Automot. Innov. 6, 466–480 (2023). https://doi.org/10.1007/s42154-023-00224-5

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