Skip to main content
SpringerLink
Log in

Structured trajectory planning of collision-free lane change using the vehicle-driver integration data

  • Article
  • Published:
Science China Technological Sciences Aims and scope Submit manuscript

Abstract

In this paper, the structured trajectory planning of lane change in collision-free road environment is studied and validated using the vehicle-driver integration data, and a new trajectory planning model for lane change is proposed based on linear offset and sine function to balance driver comfort and vehicle dynamics. The trajectory curvature of the proposed model is continuous without mutation, and the zero-based curvature at the starting and end points during lane change assures the motion direction of end points in parallel with the lane line. The field experiment are designed to collect the vehicle-driver integration data, such as steering angle, brake pedal angel and accelerator pedal angel. The correction Correlation analysis of lane-changing maneuver and influencing variables is conducted to obtain the significant variables that can be used to calibrate and test the proposed model. The results demonstrate that vehicle velocity and Y-axis acceleration have significant effects on the lane-changing maneuver, so that the model recalibrated by the samples of different velocity ranges and Y-axis accelerations has better fitted performance compared with the model calibrated by the sample trajectory. In addition, the proposed model presents a decreasing tendency of the lane change trajectory fitted MAE with the increase of time span of calibrating samples at the starting stage.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Zhang A M H, Gao Z Y, Ren H L. Incident-based traffic congestion control strategy. Sci China Tech Sci, 2011, 54: 1338–1344

    Article  MATH  Google Scholar 

  2. Xiong Z, Sheng H, Rong W G, et al. Intelligent transportation systems for smart cities: a progress review. Sci China Inf Sci, 2012, 55: 2908–2914

    Article  Google Scholar 

  3. Moritz W, Julius Z, Soeren K. Optimal trajectory generation for dynamic street scenarios in a frenet frame. In: Proceedings of the 2010 IEEE International Conference on Robotics and Automation, Anchorage: IEEE, 2010. 987–993

    Google Scholar 

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

    Article  Google Scholar 

  5. Feng J X, Ruan J H, Li Y B. Study on intelligent vehicle lane change path planning and control simulation. In: Proceedings of the 2006 IEEE International Conference on Information Acquisition, Weihai, 2006. 683–688

    Chapter  Google Scholar 

  6. You F, Wang R B, Zhang R H. Research on lane changing and overtaking for intelligent vehicle based on vision navigation. In: Proceedings of the 2008 IEEE International Conference on Industrial Technology, Chengdu: IEEE, 2008. 1–6

    Chapter  Google Scholar 

  7. Yang Z G, Qi Z J, Huang Y. Trajectory planning of lane changing for intelligent vehicles. J Chongqing Jiaotong Univ, 2013, 32: 520–524

    Google Scholar 

  8. Ren D B, Zhang J Y, Zhang J M, et al. Trajectory planning and yaw rate tracking control for lane changing of intelligent vehicle on curved road. Sci China Tech Sci, 2011, 54: 630–642

    Article  MathSciNet  MATH  Google Scholar 

  9. Damoon S, Azim E, David C. Vehicle collision avoidance maneuver with limited lateral acceleration using optimal trajectory control. J Dyn Sys Meas Control, 2013, 135: 1–12

    Google Scholar 

  10. Kim S, Oh H, Suk J, et al. Coordinated trajectory planning for efficient communication relay using multiple UAVs. Control Engn Pract, 2014, 29: 42–49

    Article  Google Scholar 

  11. Butakov V, Ioannou P. Personalized driver/vehicle lane change models for ADAS. IEEE T Veh Tech, 2015, 64: 4422–31

    Article  Google Scholar 

  12. Soudbakhsh D, Eskandarian A, Chichka D. Vehicle collision avoidance maneuvers with limited lateral acceleration using optimal trajectory control. J Dyn Sys Meas Control, 2013,135: 1–12

    Article  Google Scholar 

  13. Zhang Z H, Yu X C, Jin Z J, et al. Trajectory planning and optimal lateral stability control under multiple barriers for intelligent vehicle. World J Eng Tech, 2015, 3: 100–105

    Article  Google Scholar 

  14. Rossi C, Savino S. Robot trajectory planning by assigning positions and tangential velocities. Robot Com-Int Manuf, 2013, 29: 139–156

    Article  Google Scholar 

  15. Vale A, Fonte D, Valente F, et al. Trajectory optimization for autonomous mobile robots in ITER. Robot Auton Syst, 2014, 62, 871–888

    Article  Google Scholar 

  16. Li A J, Li S M, Shen H, et al. Motion trajectory planning method of lane changing for intelligent vehicle. J Theory App Inf Tech, 2012, 45: 297–302

    Google Scholar 

  17. Hidalgo-Martínez M, Sanmiguel-Rojas E, Burgos M. A. Design of cams with negative radius follower using Bézier curves. Mech Mach Theory, 2014, 82, 87–96

    Article  Google Scholar 

  18. Guo L, Ge P, Yue M, et al. Lane changing trajectory planning and tracking controller design for intelligent vehicle running on curved road. Math Probl Eng, 2014, 2014: 1–9

    MathSciNet  Google Scholar 

  19. Behere S, Törngren M, Chen D. A reference architecture for cooperative driving. J Syst Architect, 2013, 59: 1095–1112

    Article  Google Scholar 

  20. Pérez J, Milanés V, Godoy J, et al. Cooperative controllers for highways based on human experience. Expert Syst Appl, 2013, 40: 1024–1033

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing, 100044, China

    JiangFeng Wang, Qian Zhang, ZhiQi Zhang & XueDong Yan

Authors
  1. JiangFeng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qian Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. ZhiQi Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. XueDong Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to JiangFeng Wang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, J., Zhang, Q., Zhang, Z. et al. Structured trajectory planning of collision-free lane change using the vehicle-driver integration data. Sci. China Technol. Sci. 59, 825–831 (2016). https://doi.org/10.1007/s11431-016-6041-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11431-016-6041-2

Keywords

Search

Navigation