Exploiting Heterogeneous Human Mobility Patterns for Intelligent Bus Routing

Abstract

Optimal planning for public transportation is one of the keys to sustainable development and better quality of life in urban areas. Compared to private transportation, public transportation uses road space more efficiently and produces fewer accidents and emissions. In this paper, we focus on the identification and optimization of flawed bus routes to improve utilization efficiency of public transportation services, according to people's real demand for public transportation. To this end, we first provide an integrated mobility pattern analysis between the location traces of taxicabs and the mobility records in bus transactions. Based on mobility patterns, we propose a localized transportation mode choice model, with which we can dynamically predict the bus travel demand for different bus routing. This model is then used for bus routing optimization which aims to convert as many people from private transportation to public transportation as possible given budget constraints on the bus route modification. We also leverage the model to identify region pairs with flawed bus routes, which are effectively optimized using our approach. To validate the effectiveness of the proposed methods, extensive studies are performed on real world data collected in Beijing which contains 19 million taxi trips and 10 million bus trips.

Meeting Name

2014 IEEE International Conference on Data Mining, ICDM 2014 (2014: Dec. 14-17, Shenzhen, China)

Department(s)

Computer Science

Comments

This research was partially supported by the National High Technology Research and Development Program of China (863 Program) via grant number SS2014AA012303.

Keywords and Phrases

Budget control; Buses; Data mining; Planning; Taxicabs; Transportation; Transportation routes; Urban planning; Urban transportation; Budget constraint; Bus Routing; Human mobility; Private transportation; Public transportation; Public transportation services; Transportation mode; Utilization efficiency; Bus transportation; Bus routing; Human mobility pattern

International Standard Book Number (ISBN)

978-1-4799-4302-9

International Standard Serial Number (ISSN)

1550-4786; 2374-8486

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2014 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Dec 2014

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