Trip-detection method with smartphone-assisted collection of travel data

Safi, Hamid, Assemi, Behrang, Mesbah, Mahmoud and Ferreira, Luis (2016) Trip-detection method with smartphone-assisted collection of travel data. Transportation Research Record: Journal of the Transportation Research Board, 2594 2594: 18-26. doi:10.3141/2594-03


Author Safi, Hamid
Assemi, Behrang
Mesbah, Mahmoud
Ferreira, Luis
Title Trip-detection method with smartphone-assisted collection of travel data
Journal name Transportation Research Record: Journal of the Transportation Research Board   Check publisher's open access policy
ISSN 0361-1981
2169-4052
Publication date 2016
Year available 2016
Sub-type Article (original research)
DOI 10.3141/2594-03
Open Access Status Not Open Access
Volume 2594
Issue 2594
Start page 18
End page 26
Total pages 9
Place of publication Washington, DC, United States
Publisher U.S. National Research Council * Transportation Research Board
Collection year 2017
Language eng
Abstract This paper puts forward a method that automatically detects trips and trip segments with data on the instantaneous movement attributes of individuals that can be collected automatically by smartphone sensors. The goal is to enhance the accuracy of the data collected through the better identification of single-mode trips and trip segments while minimizing the participant's involvement and preserving battery life. The proposed method works independently of data from external sources and can be implemented in smartphone applications to enhance the accuracy of the data that are collected and minimize the amount of data that need to be transferred. The method consists of a combination of real-time processing and postprocessing of the data and incorporates a series of rules to clean, split, and merge trips and trip segments, if required. The performance of the model was evaluated in a real-world experiment, in which it achieved an overall accuracy of 97% for the detection of trips from records of daily tracks. The analysis of the results shows that the implementation of the trip detection model increased the proportion of nonmotorized trips detected by 6%. In addition, the implementation of the model increased the accuracy of the data on the duration and the length of the recorded trips.
Keyword Trip detection
Travel data
Single-mode trips
Trip segments
Smartphone assisted collection
Smartphone sensors
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ
Additional Notes http://trrjournalonline.trb.org/doi/abs/10.3141/2594-03

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Civil Engineering Publications
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Created: Fri, 18 Mar 2016, 18:33:56 EST by Behrang Assemi on behalf of School of Civil Engineering