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作 者:WANG Ya DU Bowen RONG Qiannan LIN Xia
机构地区:[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
出 处:《Chinese Journal of Electronics》2016年第1期40-47,共8页电子学报(英文版)
基 金:supported by the National Natural Science Foundation of China(No.51408018)
摘 要: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.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.
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