Issues in Expanding the Denver Regional Activity-Based Model for Statewide Modeling in Colorado

Author(s):  
David Kurth ◽  
Erik Sabina ◽  
Jason Lemp ◽  
Jeffrey Newman ◽  
Thomas Rossi

This paper discusses the activity- and tour-based model developed for the Denver Regional Council of Governments in Colorado with respect to two major issues that underlie its expansion to a statewide travel model: managing short- and long-distance travel within a single model and accounting for overnight travel. In a statewide model, the issues are interconnected to the modeling of closed and nonclosed tours. Closed tours are those that begin and end at the same location during the travel day (i.e., home). Although nonclosed tours typically are not modeled in regional activity- and tour-based models, or they are modeled with relatively simple procedures, they are more important in statewide models to accommodate overnight travel. Some long-distance travel involves an overnight stay at a location other than the traveler’s home. Such nonclosed tours, which begin or end the day at a location other than home, must be modeled explicitly in a statewide model. In this paper, required adjustments are identified for key activity- and tour-based model components, and the impacts of the explicit modeling of nonclosed tours for the tour mode choice model are presented.

Author(s):  
Carlos Llorca ◽  
Joseph Molloy ◽  
Joanna Ji ◽  
Rolf Moeckel

Long-distance trips are less frequent than short-distance urban trips, but contribute significantly to the total distance traveled, and thus to congestion and transport-related emissions. This paper develops a long-distance travel demand model for the province of Ontario, Canada. In this paper, long-distance demand includes non-recurrent overnight trips and daytrips longer than 40 km, as defined by the Travel Survey for Residents in Canada (TSRC). We developed a microscopic discrete choice model including trip generation, destination choice, and mode choice. The model was estimated using travel surveys, which did not provide data about destination attractiveness and modal level of service. Therefore, a data collection method was designed to obtain publicly available data from the location-based social network Foursquare and from the online trip planning service Rome2rio. In the first case, Foursquare data characterized land uses and predominant activities of the destination alternatives, by the number of user check-ins at different venue types (i.e., ski areas, outdoor or medical activities, etc.). In the second case, the use of Rome2rio data described the modal alternatives for each observed trip. Combining data from travel surveys, Foursquare, and Rome2rio, coefficients of the model were estimated econometrically. It was found that the Foursquare data on number of check-ins at destinations was statistically significant, especially for leisure trips, and improved the goodness of fit compared with models that only used population and employment. Additionally, Rome2rio mode-specific variables were found to be significant for mode choice selection, making the resulting model sensitive to changes in travel time, transit fares, or service frequencies.


2021 ◽  
pp. 100337
Author(s):  
Angelica Andersson ◽  
Leonid Engelson ◽  
Maria Börjesson ◽  
Andrew Daly ◽  
Ida Kristoffersson

2014 ◽  
Vol 7 (1) ◽  
pp. 35-46 ◽  
Author(s):  
Rolf Moeckel ◽  
Rhett Fussell ◽  
Rick Donnelly

2021 ◽  
Author(s):  
Virginia A. Fonner ◽  
David Geurkink ◽  
Faraja Chiwanga ◽  
Ismail Amiri ◽  
Samuel Likindikoki

2008 ◽  
Vol 42 (2) ◽  
pp. 208-219 ◽  
Author(s):  
Marcela Munizaga ◽  
Sergio Jara-Díaz ◽  
Paulina Greeven ◽  
Chandra Bhat

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