T J T L U http://jtlu.org V. 12 N. 1 [2019] pp. 201–220 Analysis of trip generation rates in residential commuting based on mobile phone signaling data Fei Shi Le Zhu Nanjing University Nanjing University
[email protected] [email protected] Abstract: In this paper, mobile phone signaling data are first processed Article history: to extract information such as the trip volume and spatial distribution Received: July 17, 2018 from the starting point to the termination point. This information is Received in revised form: then used to identify the residential and employment locations of users. August 31, 2018 Next, multiple Thiessen polygons based on cell towers are aggregated Accepted: November 27, 2018 into Traffic Analysis Zones (TAZs) to minimize differences between the Available online: March 28, actual cell tower coverage and the theoretical coverage. Then, based on 2019 TAZ cluster analysis involving transport accessibility and commuting population density, multiple stepwise regression is applied to obtain the commuting trip production rates and attraction rates for overall resi- dential land and each subdivided housing type during the peak morning hours. The obtained commuting trip generation rates can be directly applied to local transport analysis models. This paper suggests that as information and data sharing continue, mobile phone signaling data will become increasingly important for use in future trip rate research. Keywords: Trip rate, signaling data, commuting trip, trip generation, trip production, trip attraction 1 Introduction 1.1 About trip generation Trip generation is the first step in the conventional four-step transport forecasting process (followed by trip distribution, mode choice, and route assignment) and is widely used for forecasting travel demands.