X. (Ximing) Chang

Profile

Ximing Chang is a Ph.D. candidate in Beijing Jiaotong University (BJTU) in China. His research interests include Travel Behaviour Analysis, Urban Mobility based on Traffic (Big) Data, and Sustainable Transportation. During the last three years, he worked together with Prof. Jianjun Wu in BJTU on modeling and optimizing the transportation system through a data-driven approach.

Research

His first work shed some light on the analysis of the factors affecting the travel mode choice behaviour and modeling travel mode choice using machine learning algorithms. Other researches focused on the station-free shared bike usage data. Some topics have been completed or in progress, like understanding user’s travel behaviour and city region functions from station-free shared bike usage data, short-term forecasting of shared bike demand with a spatio-temporal deep learning approach, dynamic shared bike rebalancing problem by considering the collection of bikes in need of repair etc.

Ximing Chang, Jianjun Wu, Hao Liu, Xiaoyong Yan, Huijun Sun, Yunchao Qu. 2019. Travel mode choice: a data fusion model using machine learning methods and evidence from travel diary survey data. Transportmetrica A: Transport Science. 15 (2): 1587–1612. https://doi.org/10.1080/23249935.2019.1620380

Ximing Chang

PhD Researcher


Additional information

X. (Ximing) Chang PhD

profiel

Biografie

Ximing chang is a Ph.D. candidate in Beijing Jiaotong University (BJTU) in China. His research interests include Travel Behavior Analysis, Urban Mobility based on Traffic (Big) Data, and Sustainable Transportation.

Here at the TU Delft, His  daily supervisor is Dr.ir. G. (Gonçalo) Correia. The current status and progress is about car sharing or bike sharing system especially the user's travel behavior, charging and rebalancing problem etc. Combined with academic discussion, the research framework and prospect will be constructed. 

Expertise

During the research period in BJTU, he worked together with Prof. Jianjun Wu and  Xiaoyong Yan in Beijing Jiaotong University on Modeling and optimizing the transportation system through a data-driven approach.

His first work shed some light on the analysis of the factors affecting the choice behavior and the prediction of travel mode choice. Based on the travel diary survey data, he established a data fusion model using machine learning method model to predict the travel mode choice and to analyze the internal influencing factors that affect travel mode choice behavior.

His other researches focus on the station-free sharing bike usage data. Some topics have been completed or is in progress, like Understanding user's travel behavior and city region functions from station-free shared bike usage data, Short-term forecasting of station-free shared bike demand: a spatio-temporal deep learning approach, dynamic station-free shared bike rebalancing by considering the collection of bicycles in need of repair etc.

Prijzen

  1. Ximing Chang, Jianjun Wu*, Zhengbin He, Daqing Li, Huijun Sun, Kangli Zhu. Outstanding paper award. Understanding user's travel behavior and city region functions from station-free sharing bike usage data. The 7th International Workshop on Transportation and Space-time Economics (TSTE-2019), October 11-13, 2019, Beijing, China.
  2. Ximing Chang, Jianjun Wu*, Huijun Sun. Best paper award. Short-term forecasting of station-free shared bike demand: a spatio-temporal deep learning approach. The 11th international workshop on Computational Transportation Science (CTS 2019), June 29-30, 2019, Tianjin, China.