An online approach for intersection navigation of autonomous vehicle

Yang Bai, Zhuang Jie Chong, Marcelo H. Ang, Xueshan Gao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

Navigation through an intersection is a fundamental task that will enable an autonomous car to operate in a real traffic environment. Previous studies about intersection navigation generally assume vehicle to vehicle communication ability for all of the vehicles. Since this is unattainable in the near future, we focus on the scenario that vehicles on the road cannot communicate with each other. A new model is presented for this kind of intersection navigation as a Partially Observable Markov Decision Process problem. The proposed model can handle multiple numbers of cars in a dynamic environment. To validate the feasibility of the model, experiments are carried out with an autonomous golf cart in the university campus.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2127-2132
Number of pages6
ISBN (Electronic)9781479973965
DOIs
Publication statusPublished - 20 Apr 2014
Event2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014 - Bali, Indonesia
Duration: 5 Dec 201410 Dec 2014

Publication series

Name2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014

Conference

Conference2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014
Country/TerritoryIndonesia
CityBali
Period5/12/1410/12/14

Keywords

  • intention
  • intersection
  • navigation
  • online planning

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