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Title: Dynamic decision making in lane change: game theory with receding horizon
Authors: Meng, Fanlin
Su, Jinya
Liu, Cunjia
Chen, Wen-Hua
Issue Date: 2016
Publisher: © IEEE
Citation: MENG, F. ... et al, 2016. Dynamic decision making in lane change: game theory with receding horizon. IN: Proceedings of the 11th UKACC International Conference on Control, 31st August-2nd September 2016, Belfast.
Abstract: Decision making for lane change manoeuvre is of practical importance to guarantee a smooth, efficient and safe operation for autonomous driving. It is, however, challenging. On one hand, the behaviours of ego vehicle and adjacent vehicles are dependent and interactive. On the other hand, the decision should strictly guarantee safety during the whole process of lane change with uncertain and incomplete information in a dynamic and cluttered environment. To this end, the concept of Receding Horizon Control (RHC) is integrated into game theory in conjunction with reachability analysis tool, resulting in RHC based game theory. Specifically, the decision of each game relies on not only uncertain information at current step but also the future information calculated by reachability analysis. The decision is repeatedly made with the advent of new information using the concept of RHC. As a result, safety can be guaranteed during the whole process of lane change in a dynamic environment. Case study is conducted to demonstrate the advantages of the proposed approach. It is shown that the proposed RHC based game theory approach incorporating uncertain information can provide a safer and real-time decision.
Description: Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor: This work is jointly supported by the UK Engineering and Physical Sciences Research Council (EPSRC) Autonomous and Intelligent Systems programme under the grant number EP/J011525/1 with BAE Systems as the leading industrial partner.
Version: Accepted for publication
DOI: 10.1109/CONTROL.2016.7737643
URI: https://dspace.lboro.ac.uk/2134/21900
Publisher Link: https://dx.doi.org/10.1109/CONTROL.2016.7737643
ISBN: 9781467398916
Appears in Collections:Closed Access (Aeronautical and Automotive Engineering)

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