01015553

Component

https://doi.org/10.3141/1921-04

http://scholar.google.com...Bovy&publication_year=2005

Travelers in multimodal networks make many choices (e.g., main mode, access modes, egress modes, boarding nodes, transfer nodes, and egress nodes). One way to address this complexity of choices is to analyze choice sets of multimodal routes. However, choice sets for multimodal networks are large, and overlap of routes within choice sets is substantial. This paper focuses on overlap in multimodal transport networks. An overview of the topic of overlap and route choice modeling is given and is followed by an analysis of how overlap might be defined in the context of multimodal networks. Three definitions of “overlap” are proposed, based on number of legs, time, or distance. The different definitions are analyzed using path size logit estimations, which show that path size must be accounted for. Furthermore, the definition of “path size” for multimodal transport networks should be different from that used for road networks: for multimodal transport networks, a definition using number of legs yields substantially better results. Estimation results suggest that the weighting parameter corresponding with the path size variable should be equal to 1, implying that the path size variable based on number of legs accounts for the correlation of error terms of overlapping parts.

01015546

English

pp 27-34

2005

Transportation Research Record: Journal of the Transportation Research Board

0309093953

Print

References (13) ; Tables (4)

Choice models; Logits; Multimodal transportation; Route choice

Multimodal networks; Overlapping; Path size

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

TRIS, TRB, ATRI

Jan 18 2006 2:09PM

• Analysis of Joint Household Decisions About Car and Motorbike Ownership and Use in Taiwan
• Development of a Scheduling Model for Car Tourists’ 1-Day Tours
• Discrete Choice with Social and Spatial Network Interdependencies: An Empirical Example Using Mixed Generalized Extreme Value Models with Field and Panel Effects
• Efficiently Estimating Nested Logit Models with Choice-Based Samples: Example Applications
• Escorting Children to School: Statistical Analysis and Applied Modeling Approach
• Evaluation of Optimization Methods for Estimating Mixed Logit Models
• Florida Activity Mobility Simulator: Overview and Preliminary Validation Results
• Incorporating Trip-Chaining Behavior into Network Equilibrium Analysis
• Market-Based Framework for Forecasting Parking Cost in Traditional and Microsimulation Modeling Applications
• Simulation Estimation of Mixed Discrete Choice Models with the Use of Randomized Quasi-Monte Carlo Sequences: A Comparative Study
• Testing Mixed Logit and Probit Models by Simulation
• Tests of a Family of Trip Table Refinements for Long-Range, Quick-Response Travel Forecasting
• Travel Demand Modeling for Regional Visioning and Scenario Analysis
• Urban Commercial Vehicle Movement Model for Calgary, Alberta, Canada