DocumentCode :
245867
Title :
Discovering Regional Taxicab Demand Based on Distribution Modeling from Trajectory Data
Author :
Qi Zhou ; Junming Zhang ; Jinglin Li ; Shangguang Wang
Author_Institution :
State Key Lab. of Networking & Switching Technol., Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2014
fDate :
19-21 Dec. 2014
Firstpage :
1605
Lastpage :
1610
Abstract :
Taxicab demand discovering is one of the most fundamental issues of taxicab services. Most of the regions in one city suffer the demand and supply disequilibrium problem. It causes the difficulty in scheduling taxicabs for taxicab companies. It will be solved by modeling the regional demand of taxicabs by using trajectory data. In this paper, we propose a method to model regional taxicab demand. Firstly, the method uses the KS measures to test the distribution of taxicab service rate. Then, it uses the Parzen window to estimate the probability density function of the rate. We have implemented our method with experiments based on real trajectory data. The results show the effectiveness of our method.
Keywords :
probability; public transport; scheduling; supply and demand; Parzen window; demand and supply disequilibrium problem; distribution modeling; probability density function; regional taxicab demand; scheduling; taxicab services; trajectory data; Estimation; Gaussian distribution; Global Positioning System; Kernel; Probability density function; Testing; Trajectory; Distribution modeling; Taxicab demand; Trajectory data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Science and Engineering (CSE), 2014 IEEE 17th International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4799-7980-6
Type :
conf
DOI :
10.1109/CSE.2014.296
Filename :
7023807
Link To Document :
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