DocumentCode :
1943478
Title :
Self-defensive coordinated maneuvering of an intelligent vehicle platoon in mixed traffic
Author :
Guo, Chunzhao ; Wan, Nianfeng ; Mita, Seiichi ; Yang, Ming
Author_Institution :
Toyota Technol. Inst., Nagoya, Japan
fYear :
2012
fDate :
16-19 Sept. 2012
Firstpage :
1726
Lastpage :
1733
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.
Keywords :
air pollution; automated highways; cooperative systems; environmental factors; road accidents; road safety; road traffic; road vehicles; CO2 emission reduction; autonomous vehicles; communication system; cooperative driving; human-driven vehicles; intelligent vehicle platoon; interfering vehicle behavior; mixed traffic; nonautomated interfering vehicles; on-board sensors; platoon formations; self-defensive coordinated maneuvering strategy; traffic accident reduction; traffic jam reduction; Hidden Markov models; Humans; Mobile robots; Roads; Safety; Sensors; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2012 15th International IEEE Conference on
Conference_Location :
Anchorage, AK
ISSN :
2153-0009
Print_ISBN :
978-1-4673-3064-0
Electronic_ISBN :
2153-0009
Type :
conf
DOI :
10.1109/ITSC.2012.6338836
Filename :
6338836
Link To Document :
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