Estimation of intercity travel demand using mobile phone data: a case study of Tehran and Shahryar cities

Articles in Press

Document Type : Scientific - Research

Authors

Civil School , Iran University of Science and Technology

Abstract

Nowadays, various organizations and institutions are continuously recording and storing large amounts of data, which has led to the emergence of rich sources of big data. Utilizing big data in transportation planning has been becoming a popular trend among engineers. The continuity in time and space makes some of these data very appealing for trip extraction purposes. Meanwhile, the increasing penetration rate of mobile phones in recent years has provided valuable data sources on how people move. In this study, we developed a methodology to estimate the travel demand between the counties of Tehran and Shahriar for different purposes, using LU mobile phone data. Considering this goal, the methodology consists of utilizing spatio-temporal algorithms for determining the origin and destination of trips with relevant time windows for identifying the main activity locations of users. One main contribution of our study is the use of a two-step approach to expand trips based on the population of cities and mobile phone penetration rate. To evaluate the results, the movement patterns obtained from the estimated demand between two counties of Tehran province were compared with real traffic counts. As a result, Pearson coefficients with values more than 0.9 and P-values less than 0.05 were obtained, demonstrating a high value of correlation between the estimated matrix and real traffic counts. According to the obtained results, it is possible to use mobile phone data as an applicable source in transportation analysis, specifically the estimation of travel demand at macro levels with high reliability

Keywords

Main Subjects

Quarterly Journal of Transportation Engineering

Articles in Press, Accepted Manuscript
Available Online from 05 March 2024

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History

  • Receive Date: 07 November 2023
  • Revise Date: 04 February 2024
  • Accept Date: 17 February 2024

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