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Determining Mode of Travel Using Cell Phone Data

Kalatian, Arash | 2016

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 49208 (09)
  4. University: Sharif University of Technology
  5. Department: Civil Engineering
  6. Advisor(s): Shafahi, Yousef
  7. Abstract:
  8. There has been growing interest in exploiting cellular network data for transportation planning purposes in recent years. In this thesis, 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. For the purpose of determining mode of travel, trips have been grouped together based on their departure time, origin and destination zones and feasibility of using public transport.Travel times for all trips of a user is estimated along with the density of bus stations in origin and destination of the trips as the attributes of clustering. Using K-means algorithm or classifying based on travel speed, records within each group are then portioned in two or three clusters. Each cluster represents a certain mode of travel; walking, public transportation or driving a private car. For validation purposes, an android app was developed to acquire spatio-temporal data of about 20 selected users. These users were asked to complete a daily report including their daily trips, travel times and mode of travel. Impleenting the proposed method, stay and activity locations of 81% of users and mode of travel for 64% of users were predicted correctly
  9. Keywords:
  10. Mode Choice ; Cellular Network ; Mobile Telephony ; Cellular Network Data ; Modal Split

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