Integrated Decision Making and Planning Based on Feasible Region Construction for Autonomous Vehicles Considering Prediction Uncertainty

For autonomous vehicles, scene understanding is still one of the major challenges, which needs to be well handled to avoid jittery decisions and unsmooth trajectories. Furthermore, uncertainty in trajectory prediction of traffic participants directly affects decision results, and thus contributes to safety, comfort and efficiency. This article proposwes an integrated decision-making and planning (DNP) framework considering the uncertainty in trajectory prediction based on Partially Observable Markov Decision Process (POMDP). A multivariate Gaussian distribution is utilized to model the propagation of uncertainty in trajectory prediction process. To plan smooth trajectories, a feasible region construction is proposed based on fine-grained decision results to bridge the gap between decision-making and planning. Simulation and experimental results confirm that the proposed framework leads to a safer and smoother trajectory compared to command-type decision outputs by increasing the safety distance by 1.27 m and reducing the curvature fluctuations by 2.08.

• Record URL:
  http://dx.doi.org/10.1109/TIV.2023.3299845
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23798858
• Supplemental Notes:
  • Copyright © 2024, IEEE.
• Authors:
  • Xiong, Lu
  • Zhang, Yixuan
  • Liu, Yuanzhi
  • Xiao, Hongyu
  • Tang, Chen
• Publication Date: 2023-11

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References;
• Pagination: pp 4515-4523
• Serial:
  • IEEE Transactions on Intelligent Vehicles
  • Volume: 8
  • Issue Number: 11
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 2379-8858
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7274857

Subject/Index Terms

• TRT Terms: Autonomous vehicles; Decision making; Markov processes; Trajectory control; Uncertainty; Vehicle safety
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01905976
• Record Type: Publication
• Files: TRIS
• Created Date: Jan 26 2024 10:02AM