Challenges in Perception and Decision Making for Intelligent Automotive Vehicles: A Case Study

This paper overviews challenges in perception and decision making for intelligent, or highly automated, automotive vehicles. The authors illustrate our development of a complete perception and decision making system which addresses various challenges and propose an action planning method for highly automated vehicles which can merge into a roundabout. The authors use learning from demonstration to construct a classifier for high-level decision making, and develop a novel set of formulations that is suited to this challenging situation: multiple agents in a highly dynamic environment with interdependencies between agents, partial observability, and a limited amount of training data. Having limited amount of labeled training data is highly constraining, but a very real issue in real-world applications. The authors believe that their formulations are also well suited to other automated driving scenarios.

• Record URL:
  https://doi.org/10.1109/TIV.2016.2551545
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/23798858
• Supplemental Notes:
  • Copyright © 2016, IEEE.
• Authors:
  • Okumura, Bunyo
  • James, Michael R
  • Kanzawa, Yusuke
  • Derry, Matthew
  • Sakai, Katsuhiro
  • Nishi, Tomoki
  • Prokhorov, Danil
• Publication Date: 2016-3

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 20-32
• Serial:
  • IEEE Transactions on Intelligent Vehicles
  • Volume: 1
  • Issue Number: 1
  • 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: Case studies; Decision making; Intelligent vehicles; Merging control; Perception; Roundabouts
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Vehicles and Equipment;

Filing Info

• Accession Number: 01612006
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 26 2016 5:13PM