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Abstract
Increasing the proportion of commuters travelling by public transportation can effectively ease urban traffic congestion. This paper addresses the application of Advanced Public Transportation Systems (APTS) data to analyze transit commuters travel demand. This study involved collection of APTS data and boarding stops information by combining smart card data and intelligent dispatching data. Transit commuters were judged according to travel frequency of morning and evening traffic peaks. The residences and work places were identified by spatial-temporal characteristics of commuters travel. Based on this idea, an estimation algorithm was proposed. The algorithm was tested and analyzed using large-scale APTS data. Finally, the method's accuracy was analyzed by comparison with the “Trip-chain” method. The proposed method provides some advantages including, high accuracy and strong operability. The study provides a fast and economic new approach to acquiring transit commuters Origin-Destination (OD) distribution.
Published Version
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