Prediction of Commuter’s Daily Time Allocation
This paper presents a model system to predict the time allocation in commuters’ daily activity-travel pattern. The departure time and the arrival time are estimated with Ordered Probit model and Support Vector Regression is introduced for travel time and activity duration prediction. Applied in a real-world time allocation prediction experiment, the model system shows a satisfactory level of prediction accuracy. This study provides useful insights into commuters’ activity-travel time allocation decision by identifying the important influences, and the results are readily applied to a wide range of transportation practice, such as travel information system, by providing reliable forecast for variations in travel demand over time. By introducing the Support Vector Regression, it also makes a methodological contribution in enhancing prediction accuracy of travel time and activity duration prediction.
- Record URL:
-
Availability:
- Find a library where document is available. Order URL: http://worldcat.org/issn/1848406903535320
-
Supplemental Notes:
- © 2013 Zong, F. et al.
-
Authors:
- Zong, Fang
- Publication Date: 2013
Language
- English
Media Info
- Media Type: Print
- Features: Figures; References; Tables;
- Pagination: pp 445-455
-
Serial:
- PROMET-Traffic & Transportation
- Volume: 25
- Issue Number: 5
- Publisher: University of Zagreb
- ISSN: 0353-5320
- EISSN: 1848-4069
- Serial URL: https://traffic2.fpz.hr/index.php/PROMTT
-
Publication flags:
Open Access (libre)
Subject/Index Terms
- TRT Terms: Commuting; Departure time; Mathematical prediction; Probits; Regression analysis; Travel patterns; Travel time
- Uncontrolled Terms: Arrival time; Support vector regression; Time allocation
- Subject Areas: Highways; Planning and Forecasting; Public Transportation; I72: Traffic and Transport Planning;
Filing Info
- Accession Number: 01502223
- Record Type: Publication
- Files: TRIS
- Created Date: Dec 23 2013 11:06AM