DocumentCode :
173910
Title :
Cloud aided safety-based route planning
Author :
Zhaojian Li ; Kolmanovsky, Ilya ; Atkins, Ella ; Jianbo Lu ; Filev, Dimitar ; Michelini, John
Author_Institution :
Dept. of Aerosp. Eng., Univ. of Michigan, Ann Arbor, MI, USA
fYear :
2014
fDate :
5-8 Oct. 2014
Firstpage :
2495
Lastpage :
2500
Abstract :
This paper proposes a novel multi-objective route planning approach within the framework of a Vehicle-to-Cloud-to-Vehicle (V2C2V) architecture. Time and road risk index (RRI) are both considered as metrics. To evaluate road segment risk, an accident database from the Highway Safety Information System (HSIS) is processed to build a comprehensive road risk assessment model. Route planning is formulated as a multi-objective network flow problem and further reduced to a Mixed Integer Programming (MIP) problem. A real-world case study, route planning through the city of Columbus, Ohio, is presented. The Vehicle-to-Cloud-to-Vehicle (V2C2V) based implementation of our safety-based route planning approach is proposed to facilitate access to real-time information and computing resources.
Keywords :
cloud computing; integer programming; path planning; risk management; road safety; traffic information systems; Columbus; HSIS; MIP problem; Ohio; RRI; accident database; cloud aided safety-based route planning; highway safety information system; mixed integer programming problem; multiobjective route planning approach; road risk assessment model; road risk index; road segment risk; vehicle-to-cloud-to-vehicle architecture; Accidents; Indexes; Neural networks; Planning; Rail to rail inputs; Roads; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on
Conference_Location :
San Diego, CA
Type :
conf
DOI :
10.1109/SMC.2014.6974301
Filename :
6974301
Link To Document :
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