01128594

Component

https://doi.org/10.3141/2132-16

http://scholar.google.com...oyce&publication_year=2009

It is common knowledge that travelers often choose clusters or groups of nearby destinations that can be visited conveniently in a single tour. This propensity is becoming increasingly important in the context of rising fuel costs. However, gravity models, as well as most destination choice models, ignore these agglomeration effects and treat each trip or destination choice as independent. Some models have captured economies of agglomeration related to trip chaining through the use of accessibility variables. Accessibility variables, however, generally do not identify trip chaining effects uniquely, but measure differential spatial competition that arises because nearby destinations are generally better substitutes than distant ones. Because spatial competition effects generally dominate trip chaining agglomeration effects, models with a single accessibility variable have been called competing destinations models following Fotheringham. This paper presents an advance on Fotheringham’s approach by introducing two distinct accessibility variables to represent agglomeration and spatial competition among destinations separately rather than their net effect. These new agglomerating and competing destination choice models were applied in Knoxville, Tennessee. The new models, which outperformed both gravity and competing destinations models, began to present a new alternative to activity-based models by allowing the incorporation of some of the most important trip chaining effects in trip-based travel demand models. For example, a sensitivity test showed that a new factory employing 1,000 workers would attract 125 new nonwork trips to the surrounding area on an average day as a result of stops on the way to and from work.

01147879

09-1130

English

pp 143-151

2009

Transportation Research Record: Journal of the Transportation Research Board

9780309142632

Print

References (44) ; Tables (2)

Accessibility; Choice models; Gravity models; Spatial analysis; Traffic models; Travel demand; Trip chaining

Agglomeration; Destinations; Nonwork trips; Spatial competition

Knoxville (Tennessee)

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

TRIS, TRB, ATRI

Jan 30 2009 5:20PM

• Adding Mode Choice to Multiagent Transport Simulation
• Artificial Neural Network Delay Model for Traffic Assignment Incorporating Intersection Delay Costs
• Assessment of User Benefits in Presence of Random Taste Heterogeneity: Comparison of Parametric and Nonparametric Models
• Continuous Departure Time Models: A Bayesian Approach
• Estimating Random Coefficient Logit Models with Full Covariance Matrix: Comparing Performance of Mixed Logit and Laplace Approximation Methods
• Evacuation Planning Using the Integrated System of Activity-Based Modeling and Dynamic Traffic Assignment
• Heterogeneous Decision Rule Model of Mode Choice Incorporating Utility Maximization and Disutility Minimization
• How Travel Attributes Affect Planning Time Horizon of Activities
• Large Problems of Dynamic Network Assignment and Traffic Equilibrium: Computational Principles and Application to Paris Road Network
• Methods for Generating Connectors in Transport Planning Models
• Model for Person and Household Mobility Attributes
• Review of International Modeling Literature: Transit, Land Use, and Automobile Pricing Strategies to Reduce Vehicle Miles Traveled and Greenhouse Gas Emissions
• TRANSIMS Implementation in Chittenden County, Vermont: Development, Calibration, and Preliminary Sensitivity Analysis
• Understanding and Accommodating Risk and Uncertainty in Toll Road Projects: A Review of the Literature
• Work Departure Time Analysis Using Dogit Ordered Generalized Extreme Value Model