Abstract

The use of managed lanes to control and maximize freeway throughput is increasing. One way of encouraging more managed lane use is through the implementation of incentives. In the Dallas-Fort Worth area, a managed lane is being added to the I-30 (Tom Landry freeway) and incentives to maximize the use of this lane were planned. Since the managed lanes were not yet open and the incentives were hypothetical, a stated preference survey was used to gauge the potential impact of the incentives on traveler behavior. The stated preference questions were designed using Db-efficient and random adaptive designs. The incentives were chosen by looking at other programs around the country and through discussion with transportation experts. Once ready, the survey was administered online to travelers in the area and a total of 898 usable responses were gathered. From the responses, a mixed-logit model was developed to describe and predict traveler behavior. From the model, elasticities were calculated to predict the impact of the incentives on mode choice. The model found that incentives with discounts and free trips (a transit fare discount, express bus service to downtown, a free trip for every X number of paid trips, and a discount offered to select businesses) were more effective at encouraging managed lane use. The other incentives (gift card worth $5 for every X number of trips and $5 in credit for every X number of trips taken by transit) had less of an impact.

Highlights

  • One of the biggest challenges in transportation is traffic congestion on urban freeways

  • Travelers were generally set in their specific mode choice

  • The incentives made an impact in the models and any bit of change can help maximize managed lane use

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Summary

Introduction

One of the biggest challenges in transportation is traffic congestion on urban freeways. One of the main reasons is the lack of funds to build new infrastructure This has led to the increased use of managed lanes (MLs) to control and optimize freeway traffic. MLs offer planners and officials a way to manage traffic on freeways through various methods including pricing, access control, and vehicle eligibility [1]. They offer travelers an alternate path that will be less congested, but for a price. Other facilities may allow single occupancy vehicles (SOV) on the managed lane but charge a toll These facilities are known as high-occupancy/toll (HOT) lanes. The research will help agencies examine how to optimize the use of their MLs

Research Problem
Incentives Used in Practice
Pilot Programs
Long-Term Programs
Survey Development and Execution
Stated Preference Questions
Incentive Design
Stated Preference Question Design
TDF where
Analysis of Survey Results
Preliminary Analysis
Model Development
Elasticities
Findings
Conclusions
Full Text
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