Travel Patterns Analysis of Urban Residents Using Automated Fare Collection System

WANG Ya; DU Bowen; RONG Qiannan; LIN Xia

doi:10.1049/cje.2016.01.007

Volume 25 Issue 1

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WANG Ya, DU Bowen, RONG Qiannan, et al., “Travel Patterns Analysis of Urban Residents Using Automated Fare Collection System,” Chinese Journal of Electronics, vol. 25, no. 1, pp. 40-47, 2016, doi: 10.1049/cje.2016.01.007

Citation:

WANG Ya, DU Bowen, RONG Qiannan, et al., “Travel Patterns Analysis of Urban Residents Using Automated Fare Collection System,” Chinese Journal of Electronics, vol. 25, no. 1, pp. 40-47, 2016, doi: 10.1049/cje.2016.01.007

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Travel Patterns Analysis of Urban Residents Using Automated Fare Collection System

doi: 10.1049/cje.2016.01.007

WANG Ya^1,3,
DU Bowen^{1,2
,},
RONG Qiannan¹,
LIN Xia¹

1.
State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China;
2.
School of Software, Beihang University, Beijing 100191, China;
3.
Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing, 210096, China

Funds: This research is supported by the National Natural Science Foundation of China (No.51408018).

More Information

Corresponding author: DU Bowen (corresponding author) was born in 1982, he received the Ph.D. degree in Computer Science and Engineering from Beihang University. He is currently an associate professor with the State Key Laboratory of Software Development Environment, Beihang University. His research interests include smart city technology, multi-source data fusion and data mining. (Email: dubowen@buaa.edu.cn)
Received Date: 2014-11-14
Rev Recd Date: 2015-01-12
Publish Date: 2016-01-10

Abstract

Abstract

As one of the essential information, passenger Origin-destination (OD) matrix is crucial for transit system planning. Automated fare collection (AFC) system is widely used in big cities all around the world, OD data not only can be collected in dynamic way but also through citywide. It is only a byproduct of AFC and have the imperfection. This paper proposes a novel method to infer trip chain information of each commuter's OD matrix based on travel pattern identify, and then the relationship between lines which have the character of the geographical proximity is used to calibrate the result of inferring. A serious of experiment results based on the real data show that the method has relatively high accuracy and can be use to practical application.
- Smart card,
- Public transportation,
- Tra-vel patterns

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References(17)

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