نوع مقاله : علمی - پژوهشی
نویسندگان
1 دانشکده عمران، دانشگاه علم وصنعت ایران
2 دانشگاه علم و صنعت ایران
3 دانشکده عمران ، دانشگاه علم و صنعت ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
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
کلیدواژهها [English]
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