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Development of Platform-Independent System for Cooperative Automated Driving Evaluated in GCDC 2016
KTH, School of Industrial Engineering and Management (ITM), Centres, Integrated Transport Research Lab, ITRL.
KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH Royal Inst Technol, Sch Elect Engn, Dept Automat Control, S-10044 Stockholm, Sweden..
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2018 (English)In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 19, no 4, p. 1277-1289Article in journal (Refereed) Published
Abstract [en]

Cooperative automated driving is a promising development in reducing energy consumption and emissions, increasing road safety, and improving traffic flow. The Grand Cooperative Driving Challenge (GCDC) 2016 was an implementation oriented project with the aim to accelerate research and development in the field. This paper describes the development of the two vehicle systems with which KTH participated in GCDC 2016. It presents a reference system architecture for collaborative automated driving as well as its instantiation on two conceptually different vehicles: a Scania truck and the research concept vehicle, built at KTH. We describe the common system architecture, as well as the implementation of a selection of shared and individual system functionalities, such as V2X communication, localization, state estimation, and longitudinal and lateral control. We also present a novel approach to trajectory tracking control for a four-wheel steering vehicle using model predictive control and a novel method for achieving fair data age distribution in vehicular communications.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. Vol. 19, no 4, p. 1277-1289
Keywords [en]
Automated vehicles, cooperative automated driving, cyber-physical system architecture, intelligent transportation systems, model predictive control, vehicular communication
National Category
Vehicle Engineering
Identifiers
URN: urn:nbn:se:kth:diva-226785DOI: 10.1109/TITS.2017.2684623ISI: 000429017300025Scopus ID: 2-s2.0-85017136485OAI: oai:DiVA.org:kth-226785DiVA, id: diva2:1203153
Funder
Swedish Transport Administration
Note

QC 20180502

Available from: 2018-05-02 Created: 2018-05-02 Last updated: 2018-05-02Bibliographically approved

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Zhang, XinhaiSong, XinwuMårtensson, Jonas

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Kokogias, StefanosSvensson, LarsPereira, Goncalo CollaresOliveira, RuiZhang, XinhaiSong, XinwuMårtensson, Jonas
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Integrated Transport Research Lab, ITRLMachine Design (Dept.)Automatic Control
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IEEE transactions on intelligent transportation systems (Print)
Vehicle Engineering

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