Evaluating Effects of Toll Strategies on Route Diversion and Travel Times for Origin–Destination Pairs in a Regional Transportation Network

Abstract

Congestion on freeway facilities is a growing menace. Interstate 4 (I-4) in the Central Florida region has been experiencing delays during peak hour; this has warranted research on traffic management strategies. The public, through the media, had proposed removing tolls on state toll roads to divert traffic from I-4. A microsimulation model, Paramics, was used to examine the potential impact of this proposal. SR-417 is a relatively uncongested toll road alternative to I-4. SR-528 is the east–west toll road connecting SR-417 and I-4. Commuters on SR-417 have to travel 15 mi longer and pay $5 compared with no monetary cost on I-4 for the same trip. The public and politicians are reluctant to toll I-4 to relieve congestion. The results from the simulation indicated that under recurring congestion conditions on I-4, removing tolls on SR-417 and SR-528 would not divert enough traffic from I-4 because of the 15-mi advantage. Under incident and lane closure scenarios on I-4 with toll reduction on SR-417 and SR-528, the travel time would increase on I-4. This result would prompt some diversion, with volumes and travel times increasing on SR-417. It was concluded that the amount of traffic that would be diverted from I-4 to the toll roads would not significantly relieve congestion on I-4. When specific origin–destination pairs were analyzed, average travel time savings on I-4 were only around 5 min. It was concluded that contrary to the media and public perception, toll reduction would only have a minimum impact on reducing I-4 congestion.

Application of Traffic Weighted Multi-Maps Based on Disjoint Routing Areas for Static Traffic Assignment

“…Ref. [41] considers the origin and destination tuples for the tolling service. In all cases, a microscopic simulation is used.…”

Design and evaluation of road pricing: state-of-the-art and methodological advances

“…• Linear, log-linear and translog econometric models employing micro-data and, possibly, inequality (Gini, Theil's index) measures [129] and nonparametric methods [130] to evaluate distributional effects, • Discrete choice models, like those based on count data (e.g., Poisson and negative binomial) regression techniques [383], binomial and multinomial logit [4,51,162,400], nested logit [122,183]), conditional logit [389], rankordered logit [56], ordered-response probit [143], mixed logit [49,270,326,337] and Generalized Extreme Value (GEV) with correlated randomutility error terms [429], • Heuristic acceptability models [320], • Strategic niche management (SNM) approaches [173], • Microscopic (and, possibly, mesoscopic) network models for simulating traffic and users' responses to road pricing and other management and control measures [2,96,212,262], which may be integrated with discrete choice models, and • Agent-based computational models of travelers' behavior and interactions [29,167,240,427].…”

A Methodology to Estimate Time Varying User Responses to Travel Time and Travel Time Reliability in a Road Pricing Environment

“…• Microscopic or mesoscopic network models for simulating traffic and user responses to road pricing and other management and control measures (Al-Deek et al, 2007;De Palma et al, 2005;Lee et al, 2007;Murray et al, 2001), which may be integrated with discrete choice models; and…”