ISBN: 978-981-11-3671-9 DOI: 10.18178/wcse.2017.06.219
Urban Taxi Resource Optimization Using Probability Model and Cellular Automata
Abstract— This study explores the supply-demand relationship in urban taxi service and provide the means
to optimize taxi distribution. Flaws can be observed in current configurations of taxi resource, hindering the
efficiency of public transport. We use principal component evaluation to summarize supply-demand
relationship on a macro scale. A probability model based on cellular automaton is established to study the
effects of existing subsidy programs, with regard to which we propose a new bounty-based subsidy scheme
as the tool for optimization. The results of this study are consistent and can adapt to solve taxi distribution
problems under different configurations.
Index Terms— probability model; cellular automaton; taxi resource distribution
Shaocong Mo, Xiaotian Jin, Tao Zheng, Jia Shuai, Yuntao Yang
School of Computer Science and Technology, Wuhan University of Technology, CHINA
ISBN: 978-981-11-3671-9 DOI: 10.18178/wcse.2017.06.17Xsrc="http://www.wcse.org/uploadfile/2019/0823/20190823055609629.png" style="width: 120px; height: 68px;" />[Download]
Cite: Shaocong Mo, Xiaotian Jin, Tao Zheng, Jia Shuai, Yuntao Yang, "Urban Taxi Resource Optimization Using Probability Model and Cellular Automata," Proceedings of 2017 the 7th International Workshop on Computer Science and Engineering, pp. 1257-1262, Beijing, 25-27 June, 2017.