Chapter
Aug 12, 2020
Analysis of the Spatiotemporal Evolution Characteristics of Travel Demand
Authors: Yilong Ren, Han Jiang, Runkun Liu, Fei Wang, Le Zhang, and Haiyang Yu [email protected]Author Affiliations
Publication: CICTP 2020
ABSTRACT
Due to the great diversity and complexity of travel demand, the analysis of spatiotemporal evolution characteristics of travel demand is of significance to the planning and management of urban traffic systems. To investigate the spatiotemporal evolution characteristics of travel demand, this research obtains massive order data from Didi Platform in Haikou, including longitude and latitude of departure and destination points of order as well as time stamps. Based on these data, characteristics that affect travel demand from may to october and the main factors are analyzed. A model is established to describe the relationship between travel demand and the service level of public bus in Haikou. The conclusions of this research can contribute to the planning of public transportation networks and provide effective reference to citizens’ travel choices under special weather conditions.
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Published In
CICTP 2020
Pages: 436 - 447
Copyright
© 2020 American Society of Civil Engineers.
History
Published online: Aug 12, 2020
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Authors
Affiliations
Yilong Ren
1National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology, Beijing 100191, China; School of Transportation Science and Engineering, Beihang Univ., Beijing 100191, China; Beijing Advanced Innovation Center for Big Data and Brain Computing, Beijing 100191, China.
Han Jiang
2National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology, Beijing 100191, China; School of Transportation Science and Engineering, Beihang Univ., Beijing 100191, China; Hefei Innovation Research Institute, Beihang Univ., Xinzhan Hi-Tech District, Anhui 230013, China.
Runkun Liu
3National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology, Beijing 100191, China; School of Transportation Science and Engineering, Beihang Univ., Beijing 100191, China.
Fei Wang
4National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology, Beijing 100191, China; School of Transportation Science and Engineering, Beihang Univ., Beijing 100191, China.
Le Zhang
5National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology, Beijing 100191, China; School of Transportation Science and Engineering, Beihang Univ., Beijing 100191, China.
6National Engineering Laboratory for Comprehensive Transportation Big Data Application Technology, Beijing 100191, China; School of Transportation Science and Engineering, Beihang Univ., Beijing 100191, China; Beijing Advanced Innovation Center for Big Data and Brain Computing, Beijing 100191, China. Email: [email protected]
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