International Conference on Transportation and Development 2020
Estimation of Trip Behaviors in Walking Areas Using Big Data
Publication: International Conference on Transportation and Development 2020
ABSTRACT
The paper introduces a method for acquiring trip behaviors within walking distance by means of multiple big data. First, an optimal set of big data is selected from possible sets of big data in the transport sector to estimate the trip behaviors. Second, the authors propose a method of estimating trip volume. Finally, the proposed method is applied to a case study that has been carried out at Tachikawa Station of the Japan Railway Central Line in Tokyo in order to validate the proposed method. A field test with the use of the Wi-Fi packet sensor was conducted at 11 locations including stores and traffic nodes on 1st of September 2018. Based on interviews with the managers of the shopping sites observed by the Wi-Fi packet sensors, it was confirmed that the estimated trips were nearly the same as the actual situations. The authors have demonstrated the possibility of using Wi-Fi packet sensor data and mobile phone location data to acquire trip behaviors within walking distance.
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Information & Authors
Information
Published In
International Conference on Transportation and Development 2020
Pages: 173 - 185
Editor: Guohui Zhang, Ph.D., University of Hawaii
ISBN (Online): 978-0-7844-8316-9
Copyright
© 2020 American Society of Civil Engineers.
History
Published online: Aug 31, 2020
Published in print: Aug 31, 2020
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