MATEC Web Conf.
Volume 81, 20162016 5th International Conference on Transportation and Traffic Engineering (ICTTE 2016)
|Number of page(s)||5|
|Published online||25 October 2016|
Travel Mode Detection Exploiting Cellular Network Data
Sharif University of Technology, Department of Civil Engineering, Tehran, Iran
There has been growing interest in exploiting cellular network data for transportation planning purposes in recent years. In this paper, we utilize these data for determining mode of travel in the city of Shiraz, Iran. Cellular data records -including location updates in 5minute time intervals- of 300,000 users from the city of Shiraz has been collected for 40 hours in three consecutive days in a cooperation with the major telecommunications service provider of the country. Depending on the density of mobile BTS’s in different zones of the city, the user location can be located within an average of 200 meters. Considering data filtering and smoothing, data preparation and converting them to comprehensible traces is a large portion of the work. A novel approach to identify stay locations is proposed and implemented in this paper. Origin-Destination matrices are then created based on trips detected, which shows acceptable consistency with current O-D matrices. Finally, Travel times for all trips of a user is estimated as the main attribute for clustering. Trips between same origin and destination zones are combined together in a group. Using K-means algorithm, records within each group are the portioned in two or three clusters, based on their travel speeds. Each cluster represents a certain mode of travel; walking, public transportation or driving a private car.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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