DocumentCode :
262309
Title :
Congestion Score Computation of Big Traffic Data
Author :
Jiwan Lee ; Bonghee Hong
Author_Institution :
Dept. of Electr. & Comput. Eng., Pusan Nat. Univ., Busan, South Korea
fYear :
2014
fDate :
3-5 Dec. 2014
Firstpage :
189
Lastpage :
196
Abstract :
Because of the increasing number of vehicles, traffic congestion has become a significant problem for many big cities. Numeric representations of traffic congestion cause deep concern in the population, and existing indices of traffic congestion are difficult to understand. In this paper, we propose a new concept of a traffic congestion score (TCS) that is computed by using an approximation of the speed limit. To aggregate the spatiotemporal TCS, we suggest a chained computation framework that is composed of two type of Mapreduce algorithms in Hadoop.
Keywords :
Big Data; data handling; parallel processing; road traffic; traffic engineering computing; Hadoop; Map Reduce algorithm; TCS; big traffic data; speed limit approximation; traffic congestion; Approximation methods; Equations; Indexes; Roads; Spatiotemporal phenomena; Traffic control; Vehicles; Big traffic data; Computing congestion score; Spatiotemporal aggregation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on
Conference_Location :
Sydney, NSW
Type :
conf
DOI :
10.1109/BDCloud.2014.64
Filename :
7034785
Link To Document :
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