Day Pattern Generation System for Jointly Modeling Tours and Stops: Bi-Level Multiple Discrete Continuous Probit Model. Issue 1 (2017)

• Record Type: Journal Article
• Authors: Enam, Annesha; Konduri, Karthik C.
• Is Part Of: Transportation research record. Volume 2665:Issue 1(2017)
• Page Start: 69
• Page End: 79
• Publication Date: 2017
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.3141/2665-08
• Languages: English
• ISSNs: 0361-1981

Abstract

The primary objective of this study was to contribute to the literature on activity pattern generation. In this paper, a new framework is proposed for simultaneously modeling the following tour and stop-making decisions: the number and purpose of tours conducted in a day, time allocated to different tours, number and purpose of stops conducted within each tour, and time allocated to different stops. The framework represents time as a continuous entity and explicitly considers the time constraints within which an individual operates when generating tours and stops. In addition, the framework is capable of accounting for the interrelationships across different tour- and stop-level decisions. The model formulation that operationalizes the proposed framework imitates a bi-level structure in which the participation (whether to pursue) and time allocation (how much time) decisions for daily tours are modeled at the upper level. Within each tour, participation and time allocation decisions for different stops are modeled at the lower level. The model formulation for the bi-level structure builds on the utility theoretic multiple discrete continuous probit modeling approach. The proposed framework and model formulation are demonstrated with an empirical case study using data from the 2008–2009 National Household Travel Survey. Replication and forecasting results are presented to demonstrate the feasibility and applicability of the proposed framework and model formulation. The results provide evidence in support of the bi-level structure and its ability to capture the various constraints and interrelationships across tour- and stop-level participation and time allocation decisions.