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Title:

Calibrating a New Reinforcement Learning Mechanism for Modeling Dynamic Activity-Travel Behavior and Key Events

Accession Number:

01046100

Record Type:

Component

Availability:

Transportation Research Board Business Office

500 Fifth Street, NW
Washington, DC 20001 United States

Abstract:

Recent transportation modeling mainly focuses on activity-based modeling. However the majority of such models are still quite static. Therefore, the current research aims at incorporating dynamic components, such as short-term adaptation and long-term learning, into these activity-based models. In particular, this paper attempts at simulating the learning process underlying the development of activity-travel patterns. Furthermore, this study explores the impact of key events on generation of daily schedules. The learning algorithm implemented in this paper uses a reinforcement learning technique, for which the foundations were provided in previous research. The goal of the present study is to release the predefined activity-travel sequence assumption of this previous research and to allow the algorithm to determine the activity-travel sequence autonomously. To this end, the decision concerning transport mode needs to be revised as well, as this aspect was previously also set within the fixed schedule. In order to generate feasible activity-travel patterns, another alteration consists of incorporating time constraints, for example opening hours of shops. In addition, a key event, in this case “obtaining a driving license”, is introduced into the learning methodology by changing the available set of transport modes. The resulting patterns reveal more variation in the selected activities and respect the imposed time constraints. Moreover, the observed dissimilarities between activity-travel schedules before and after the key event prove to be significant based on a sequence alignment distance measure.

Monograph Accession #:

01042056

Report/Paper Numbers:

07-0545

Language:

English

Corporate Authors:

Transportation Research Board

500 Fifth Street, NW
Washington, DC 20001 United States

Authors:

Vanhulsel, Marlies
Janssens, Davy
Wets, Geert

Pagination:

17p

Publication Date:

2007

Conference:

Transportation Research Board 86th Annual Meeting

Location: Washington DC, United States
Date: 2007-1-21 to 2007-1-25
Sponsors: Transportation Research Board

Media Type:

CD-ROM

Features:

References (30) ; Tables (3)

Uncontrolled Terms:

Activity based modeling

Subject Areas:

Highways; Planning and Forecasting; Society; I72: Traffic and Transport Planning

Source Data:

Transportation Research Board Annual Meeting 2007 Paper #07-0545

Files:

TRIS, TRB

Created Date:

Feb 8 2007 5:08PM