NDLI: Self-defensive coordinated maneuvering of an intelligent vehicle platoon in mixed traffic

Content Provider	IEEE Xplore Digital Library
Author	Chunzhao Guo Nianfeng Wan Mita, S. Ming Yang
Copyright Year	2012
Description	Author affiliation: Toyota Technological Inst itute, Nagoya, Aichi 468-8511 Japan (Mita, S.) \|\| Toyota Technological Institute, Nagoya, Aichi 468-8511 Japan (Chunzhao Guo) \|\| Shanghai Jiao Tong University, Minhan, 200240 China (Nianfeng Wan; Ming Yang)
Abstract	Cooperative driving is a promising technology for reducing traffic jams, limiting CO2 emissions and reducing traffic accidents. With the future mixed traffic, the current platooning concept comes to its limitations when human-driven vehicles interfere with the platoon between the autonomous vehicles without negotiation. In this interfering situation, most of them have to break down into two platoons, which may ensure the safety while lose the efficiency. In this paper, we introduce a self-defensive coordinated maneuvering strategy to generalize platooning to situations with non-automated interfering vehicles in mixed traffic. It allows the vehicles in the platoon to observe the interfering vehicles' behaviors, predict their intentions, and then react by changing their platoon formations so as to keep such vehicles always out of the platoon. In the proposed framework, the platoon can not only “talk” and “listen” for cooperative driving based on the communication system, but also “guessing” and “reacting” to actively defend the completeness based on the on-board sensors. Therefore, higher safety and efficiency can be expected. Simulation results in various typical but challenging interfering situations with mixed traffic show the effectiveness of the proposed approach.
Starting Page	1726
Ending Page	1733
File Size	1008850
Page Count	8
File Format	PDF
ISBN	9781467330640
ISSN	21530009
e-ISBN	9781467330633
e-ISBN	9781467330626
DOI	10.1109/ITSC.2012.6338836
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vehicles Hidden Markov models Mobile robots Roads Safety Humans Sensors
Content Type	Text
Resource Type	Article

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