Analyzing Multiday Route Choice Behavior using GPS Data

Wenyun Tang and Lin Cheng
Additional contact information
Lin Cheng: Nexus (Networks, Economics, and Urban Systems) Research Group, Department of Civil Engineering, University of Minnesota
Authors registered in the RePEc Author Service: David Matthew Levinson

No 135, Working Papers from University of Minnesota: Nexus Research Group

Abstract: Understanding variability in daily behavior is one of the most important missions in travel behavior modeling. In traditional method, in order to find the differences, respondents were asked to list the used multiday paths. The quality of results is sensitive to the accuracy of respondents’ memories. However, few empirical studies of revealed route characteristics, chosen by the travelers day-to-day, have been reported in the literature. In this study, accurate Global Position Systems (GPS) and Geographic Information System (GIS) data were employed to reveal multiday routes people used, to study multiday route choice behavior for the same origin-destination (OD) trips. Travelers are classified into three kinds based on their route types. A two-stage route choice process is proposed. After analyzing the characteristics of different types of travelers, a neural network was adopted to classify travelers and model route choice behavior. An empirical study using GPS data collected in Minneapolis-St. Paul metropolitan area was carried out in the following part. It finds that most travelers follow the same route during commute trips on successive days. The results indicate that neural network framework can classify travelers and model route choice well.

Keywords: multiday travel behavior; day-to-day modeling; route choice behavior; GPS data; neural networks (search for similar items in EconPapers)
JEL-codes: C45 R41 R42 (search for similar items in EconPapers)
Date: 2015
New Economics Papers: this item is included in nep-cmp, nep-geo, nep-tre and nep-ure
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in Advances in Mechanical Engineering 2016, Vol. 8(2) 1–11

Downloads: (external link)
http://nexus.umn.edu/Papers/Multiday.pdf First version, 2015 (application/pdf)
Our link check indicates that this URL is bad, the error code is: 500 Can't connect to nexus.umn.edu:80 (No such host is known. )

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nex:wpaper:multiday

Access Statistics for this paper

More papers in Working Papers from University of Minnesota: Nexus Research Group Contact information at EDIRC.
Bibliographic data for series maintained by David Levinson ( this e-mail address is bad, please contact ).