Chapter
Jul 2, 2019
Research on Transportation Mode Split Based on Random Forest
Authors: Zhenbo Lu [email protected], Zhen Long, Zuguang Wang, Juan Liu, and Gai ZhangAuthor Affiliations
Publication: CICTP 2019
Abstract
Transportation mode split is the core part of the four-stage method and its characteristics are constantly changing. However, most transportation mode split methods adopted in traffic planning assumed that each area had the same traffic patterns, which is not correct. This paper used random forest to split the transportation mode. First, several features were extracted from resident trip survey data and mobile phone signaling data. Then, the model accuracy was adjusted using a variety of methods. Next, the mode split model was built on the random forest. Finally, mobile phone data was used to verify its accuracy. The results show that the random forest performs well in the transportation mode split with 85% accuracy and it could be used for mobile phone signaling data to identity the transportation mode.
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© 2019 American Society of Civil Engineers.
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Published online: Jul 2, 2019
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Intelligent Transportation System Research Center, Southeast Univ., Nanjing 210096, China. E-mail: [email protected]
Zhen Long
Intelligent Transportation System Research Center, Southeast Univ., Nanjing 210096, China.
Zuguang Wang
Intelligent Transportation System Research Center, Southeast Univ., Nanjing 210096, China.
Juan Liu
Intelligent Transportation System Research Center, Southeast Univ., Nanjing 210096, China.
Gai Zhang
Intelligent Transportation System Research Center, Southeast Univ., Nanjing 210096, China.
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Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.