The aim of this paper is to contribute to describe the simultaneous choice of travel mode and 1 departure time by making use of a cross-nested logit structure that allows for the joint representation of 2 inter-alternative correlation along the both choice dimensions. Traditional multinomial logit model and 3 nested logit model are formulated respectively. The analysis uses the Revealed Prefere...

BACKGROUND Children who use active modes of travel (walking or cycling) to school are more physically active than those who use passive (motorised) modes. However, less is known on whether a change in mode of travel to school is associated with a change in children's physical activity levels. The purpose of this analysis was to investigate the association between change in mode of travel to sch...

This paper presents a multi-stage approach toward the robust classification of travel-modes from GPS traces. Due to the fact that GPS traces are often composed of more than one travel-mode, they are segmented to find sub-traces characterized as an individual travel-mode. This is conducted by finding individual movement segments by identifying stops. In the first stage of classification three ma...

Most travel behavior studies on route and mode choice focus only on an individual level. This paper adopts the concept of multi-state supernetworks to model the two-person joint travel problem (JTP). Travel is differentiated in terms of activity-vehiclejoint states, i.e. travel separately or jointly with which transport mode and with which activities conducted. In each state, route choice can b...

2 Xing Su 3 Computer Science Department, 4 Graduate Center, City University of New York 5 New York, NY 10016 6 [email protected] 7 +1-(347)784-4035 8 9 Hernan Caceres 10 Industrial and Systems Engineering (ISE) 11 University of Buffalo, The State University of New York 12 Buffalo, NY 14260 13 [email protected] 14 +1-(716)645-2357 15 16 Hanghang Tong 17 School of Computing, Informatics, and...

Travel mode identification is one of the essential steps in travel information detection with Global Positioning System (GPS) survey data. This paper presents a Support Vector Classification (SVC) model for travel mode identification with GPS data. Genetic algorithm (GA) is employed for optimizing the parameters in the model. The travel modes of walking, bicycle, subway, bus, and car are recogn...