DocumentCode :
3661655
Title :
Shortest Driving Time Computation Based on Cloud Technologies and Genetic Algorithm
Author :
Chu-Hsing Lin;Jung-Chun Liu;Ming-Hong Liou;Wen-Chen Wu
Author_Institution :
Dept. of Comput. Sci., Tunghai Univ., Taichung, Taiwan
fYear :
2014
Firstpage :
658
Lastpage :
662
Abstract :
By gathering information of communications between people, vehicles, and roads, the Intelligent Transportation System (ITS) improves traffic service quality, safety, efficiency, and convenience of the conventional transportation system. The paper proposes a method based on cloud computing and the genetic algorithm to provide improvements of performance boost, accuracy, and efficiency of the current transportation system. Maps are partitioned into layers in order to improve reusability of data. For maps with large number of nodes, the required execution time of the genetic algorithm will increase; moreover, different chromosome initialization settings and/or different feedback mechanisms are required to avoid failure or premature convergence of the genetic algorithm. For applications with tremendous number of traffic nodes, the proposed approach is a feasible solution since it can offer approximate solutions without consuming too much of resources; besides, the results also show that the approach can obtain approximately optimal solutions much faster and better.
Keywords :
"Genetic algorithms","Biological cells","Cloud computing","Vehicles","Genetics","Roads"
Publisher :
ieee
Conference_Titel :
Intelligent Systems, Modelling and Simulation (ISMS), 2014 5th International Conference on
ISSN :
2166-0662
Type :
conf
DOI :
10.1109/ISMS.2014.118
Filename :
7280989
Link To Document :
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