Disaggregate Multimodal Travel Demand Modeling Based on Road Pricing and Access to Transit

Abstract

In this paper, the conventional disaggregate travel demand model, a probability model for the modeling of multiple modes, generally called random utility maximization (RUM), is expanded to a model of count of mode choice. The extended travel demand model is derived from general economic theory—maximizing instantaneous utility on the time horizon, subject to a budget constraint—and can capture the dynamic behavior of countable travel demand. Because the model is for countable dependent variables, it has a more realistic set of assumptions to explain travel demand than the RUM model. An empirical test of the theoretical model using a toll facility user survey in the New York City area was performed. The results showed that the theoretical model explained more than 50% of the trip frequency behavior observed in New York City toll facility users. Travel demand for toll facility users increased with respect to household employment, household vehicle count, and employer payment of tolls and decreased in terms of travel time, road pricing, travel distance, and mass transit access.

Understanding the effects of transit benefits on employees’ travel behavior: Evidence from the New York-New Jersey region

“…For instance, benefits such as toll payments, mileage reimbursements or free parking decrease the likelihood to commute by public transport over private car by 82%. This result is similar to the finding in Peters et al (2011) with respect to toll payment by employers and the frequency of use of toll facilities. Moreover, we have found that private vehicle benefits are associated with a significant decrease in the probability of choosing alternative modes such as walking (À57%) or cycling (À60%) over driving, which reveals the importance of commuter benefits for promoting more sustainable options for short distances.…”

Traveler Response to Coexisting Multiple Pricing Schemes

“…Preferences also differed between work-related journeys and nonwork journeys and all income groups illustrated a positive attitude towards the new toll motorway. The study reported by Peters et al tested the extended model to capture dynamic behavior of countable travel demand using a toll facility user survey in the New York City area (7). Results implied that the theoretical model is consistent with the observed behavior of toll facility users in New York City.…”

“…For decades, tolls have been charged on certain bridges, tunnels, and roads, not only to stimulate particular behavior but also to finance the facility, reinvest in capacity expansion, pay for operations and maintenance of the facility, or simply to generate general tax funds (1,2). In addition, various congestion pricing and value pricing strategies have been discussed at length and implemented in cities worldwide (3)(4)(5)(6)(7). More recently, parking charges trip and transportation supply characteristics.…”

Location choice, life cycle and amenities

“…Our theoretical modeling is motivated mainly by Peters, Shim, and Kress (), Turnbull (, ), Turnbull, Glascock, and Sirmans (), and Ng (). Our theoretical predictions are consistent with the literature on location choice and commuting behavior, by Albouy and Lue () and Timothy and Wheaton ().…”