Prediction of Individual Social-Demographic Role Based on Travel Behavior Variability Using Long-Term GPS Data
Abstract
With the development of and advances in smartphones and global positioning system (GPS) devices, travelers’ long-term travel behaviors are not impossible to obtain. This study investigates the pattern of individual travel behavior and its correlation with social-demographic features. For different social-demographic groups (e.g., full-time employees and students), the individual travel behavior may have specific temporal-spatial-mobile constraints. The study first extracts the home-based tours, including Home-to-Home and Home-to-Non-Home, from long-term raw GPS data. The travel behavior pattern is then delineated by home-based tour features, such as departure time, destination location entropy, travel time, and driving time ratio. The travel behavior variability describes the variances of travelers’ activity behavior features for an extended period. After that, the variability pattern of an individual’s travel behavior is used for estimating the individual’s social-demographic information, such as social-demographic role, by a supervised learning approach, support vector machine. In this study, a long-term (18-month) recorded GPS data set from Puget Sound Regional Council is used. The experiment’s result is very promising. In conclusion, the sensitivity analysis shows that as the number of tours thresholds increases, the variability of most travel behavior features converges, while the prediction performance may not change for the fixed test data.
- Authors:
-
[1];
- Transportation and Hydrogen Systems Center, National Renewable Energy Laboratory (NREL), 15013 Denver West Parkway, Golden, CO 80401, USA
- Department of Civil, Structural and Environmental Engineering, University at Buffalo, Buffalo, NY 14260, USA
- Publication Date:
- Research Org.:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Org.:
- USDOE; U.S. Department of Transportation (DOT), Federal Highway Administration (FHWA)
- OSTI Identifier:
- 1375278
- Alternate Identifier(s):
- OSTI ID: 1376048
- Report Number(s):
- NREL/JA-5400-68857
Journal ID: ISSN 0197-6729; PII: 7290248; 7290248
- Grant/Contract Number:
- AC36-08GO28308
- Resource Type:
- Published Article
- Journal Name:
- Journal of Advanced Transportation
- Additional Journal Information:
- Journal Name: Journal of Advanced Transportation Journal Volume: 2017; Journal ID: ISSN 0197-6729
- Country of Publication:
- Egypt
- Language:
- English
- Subject:
- 29 ENERGY PLANNING, POLICY, AND ECONOMY; travel behavior; GPS; travel pattern; sensitivity analysis; Puget Sound Regional Council
Citation Formats
Zhu, Lei, Gonder, Jeffrey, and Lin, Lei. Prediction of Individual Social-Demographic Role Based on Travel Behavior Variability Using Long-Term GPS Data. Egypt: N. p., 2017.
Web. doi:10.1155/2017/7290248.
Zhu, Lei, Gonder, Jeffrey, & Lin, Lei. Prediction of Individual Social-Demographic Role Based on Travel Behavior Variability Using Long-Term GPS Data. Egypt. https://doi.org/10.1155/2017/7290248
Zhu, Lei, Gonder, Jeffrey, and Lin, Lei. Wed .
"Prediction of Individual Social-Demographic Role Based on Travel Behavior Variability Using Long-Term GPS Data". Egypt. https://doi.org/10.1155/2017/7290248.
@article{osti_1375278,
title = {Prediction of Individual Social-Demographic Role Based on Travel Behavior Variability Using Long-Term GPS Data},
author = {Zhu, Lei and Gonder, Jeffrey and Lin, Lei},
abstractNote = {With the development of and advances in smartphones and global positioning system (GPS) devices, travelers’ long-term travel behaviors are not impossible to obtain. This study investigates the pattern of individual travel behavior and its correlation with social-demographic features. For different social-demographic groups (e.g., full-time employees and students), the individual travel behavior may have specific temporal-spatial-mobile constraints. The study first extracts the home-based tours, including Home-to-Home and Home-to-Non-Home, from long-term raw GPS data. The travel behavior pattern is then delineated by home-based tour features, such as departure time, destination location entropy, travel time, and driving time ratio. The travel behavior variability describes the variances of travelers’ activity behavior features for an extended period. After that, the variability pattern of an individual’s travel behavior is used for estimating the individual’s social-demographic information, such as social-demographic role, by a supervised learning approach, support vector machine. In this study, a long-term (18-month) recorded GPS data set from Puget Sound Regional Council is used. The experiment’s result is very promising. In conclusion, the sensitivity analysis shows that as the number of tours thresholds increases, the variability of most travel behavior features converges, while the prediction performance may not change for the fixed test data.},
doi = {10.1155/2017/7290248},
journal = {Journal of Advanced Transportation},
number = ,
volume = 2017,
place = {Egypt},
year = {Wed Aug 16 00:00:00 EDT 2017},
month = {Wed Aug 16 00:00:00 EDT 2017}
}
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Works referenced in this record:
The promises of big data and small data for travel behavior (aka human mobility) analysis
journal, July 2016
- Chen, Cynthia; Ma, Jingtao; Susilo, Yusak
- Transportation Research Part C: Emerging Technologies, Vol. 68
Changing commuters’ behavior using rewards: A study of rush-hour avoidance
journal, September 2011
- Ben-Elia, Eran; Ettema, Dick
- Transportation Research Part F: Traffic Psychology and Behaviour, Vol. 14, Issue 5
Dynamic Ride Sharing Service: Are Users Ready to Adopt it?
journal, January 2015
- Gargiulo, Eleonora; Giannantonio, Roberta; Guercio, Elena
- Procedia Manufacturing, Vol. 3
An examination of the determinants of day-to-day variability in individuals' urban travel behavior
journal, January 1986
- Pas, Eric I.; Koppelman, Frank S.
- Transportation, Vol. 13, Issue 2
On-line prediction of border crossing traffic using an enhanced Spinning Network method
journal, June 2014
- Lin, Lei; Wang, Qian; Huang, Shan
- Transportation Research Part C: Emerging Technologies, Vol. 43
Behavior Insights for an Incentive-Based Active Demand Management Platform
journal, June 2015
- Hu, Xianbiao; Chiu, Yi-Chang; Zhu, Lei
- International Journal of Transportation Science and Technology, Vol. 4, Issue 2
Daily activity pattern recognition by using support vector machines with multiple classes
journal, December 2013
- Allahviranloo, Mahdieh; Recker, Will
- Transportation Research Part B: Methodological, Vol. 58
Choice of Travel Mode in the Theory of Planned Behavior: The Roles of Past Behavior, Habit, and Reasoned Action
journal, September 2003
- Bamberg, Sebastian; Ajzen, Icek; Schmidt, Peter
- Basic and Applied Social Psychology, Vol. 25, Issue 3
Behavioural data mining of transit smart card data: A data fusion approach
journal, September 2014
- Kusakabe, Takahiko; Asakura, Yasuo
- Transportation Research Part C: Emerging Technologies, Vol. 46
Repetition and Variability in Urban Travel
journal, April 1986
- Huff, James O.; Hanson, Susan
- Geographical Analysis, Vol. 18, Issue 2
Use of an activity-based diary to collect household travel data
journal, May 1992
- Stopher, Peter R.
- Transportation, Vol. 19, Issue 2
Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel
journal, July 2003
- Keerthi, S. Sathiya; Lin, Chih-Jen
- Neural Computation, Vol. 15, Issue 7
Studying Driving Risk Factors using Multi-Source Mobile Computing Data
journal, September 2015
- Hu, Xianbiao; Chiu, Yi-Chang; Ma, Yu-Luen
- International Journal of Transportation Science and Technology, Vol. 4, Issue 3
The effectiveness of soft transport policy measures: A critical assessment and meta-analysis of empirical evidence
journal, March 2008
- Möser, Guido; Bamberg, Sebastian
- Journal of Environmental Psychology, Vol. 28, Issue 1
Intrapersonal variability in daily urban travel behavior: Some additional evidence
journal, May 1995
- Pas, Eric I.; Sundar, Subramanian
- Transportation, Vol. 22, Issue 2
From traces to trajectories: How well can we guess activity locations from mobile phone traces?
journal, September 2014
- Chen, Cynthia; Bian, Ling; Ma, Jingtao
- Transportation Research Part C: Emerging Technologies, Vol. 46
Application of Variable Tolls on Congested Toll Road
journal, July 2003
- Burris, Mark W.
- Journal of Transportation Engineering, Vol. 129, Issue 4
An analysis of soft transport policy measures implemented in Sweden to reduce private car use
journal, May 2012
- Friman, Margareta; Larhult, Lina; Gärling, Tommy
- Transportation, Vol. 40, Issue 1
Estimation of behavioural change of railway passengers using smart card data
journal, January 2012
- Asakura, Yasuo; Iryo, Takamasa; Nakajima, Yoshiki
- Public Transport, Vol. 4, Issue 1
Getting the Prices Right: An Evaluation of Pricing Parking by Demand in San Francisco
journal, January 2013
- Pierce, Gregory; Shoup, Donald
- Journal of the American Planning Association, Vol. 79, Issue 1
Discrete choice models of traveler participation in differential time of day pricing programs
journal, July 2002
- Burris, Mark W.; Pendyala, Ram M.
- Transport Policy, Vol. 9, Issue 3
Estimation method for railway passengers’ train choice behavior with smart card transaction data
journal, June 2010
- Kusakabe, Takahiko; Iryo, Takamasa; Asakura, Yasuo
- Transportation, Vol. 37, Issue 5
Urban activity pattern classification using topic models from online geo-location data
journal, July 2014
- Hasan, Samiul; Ukkusuri, Satish V.
- Transportation Research Part C: Emerging Technologies, Vol. 44
Exploring spatial variety in patterns of activity-travel behaviour: initial results from the Toronto Travel-Activity Panel Survey (TTAPS)
journal, August 2008
- Buliung, Ron N.; Roorda, Matthew J.; Remmel, Tarmo K.
- Transportation, Vol. 35, Issue 6
A mathematical theory of communication
journal, January 2001
- Shannon, C. E.
- ACM SIGMOBILE Mobile Computing and Communications Review, Vol. 5, Issue 1