Exploring the Operational and Equity Benefits of a Pre-Pay Dynamic Tolling System

Research Team: Alexander Skabardonis (lead), Nicholas Fournier, and Anthony Patire

UC Campus(es): UC Berkeley

Problem Statement: Dynamic toll pricing is a highly effective policy lever for both reducing road congestion and collecting revenue. Under this approach the toll increases in real time when demand is highest, typically during rush hours, and decreases when road use is light. Unfortunately, price uncertainty for many travelers is a major barrier to public acceptance. Also, the demand response to price changes for short-term travel (e.g., commuting) is much weaker than for long-term travel planning (e.g., air travel), meaning that whether the price goes up or down, drivers are less likely to change their short-term travel behavior, for example by traveling at an earlier or later time. While this is due to a plethora of factors (e.g., time flexibility, housing choice, automobile investment, etc.), a critical factor is that travelers simply lack sufficient information for future travel planning. It is possible that a pre-pay system may make dynamic tolling more effective and minimize public concerns.

Project Description: This research explores a simple “futures market” pricing mechanism in which travelers can lock in a toll price for expected trips by prepaying for future tolls, with the future price increasing as more travelers book an overlapping time slot. This approach encourages travelers to avoid driving during the peak periods when pricing increases toward capacity or to purchase trips in advance when the price remains low or discounted, thus using infrastructure capacity more efficiently. Travelers that do not prepurchase their trip are subject to the real-time market price, which is determined by dynamic congestion pricing. This futures-market mechanism can augment existing toll collection technologies and provide travelers with sufficient pricing information and purchasing options to preplan their travel and avoid excessive prices. To evaluate the effectiveness of such a system, this research conducts a thorough sensitivity analysis of elasticity and pricing constraints to explore possible system outcomes for reducing delay and collecting revenue.

Status: Completed

Budget: $80,000