Research Team: Alexander Skabardonis (lead) and Nicholas Fournier
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 proposed research will investigate the feasibility and potential benefits of adopting a pre-pay option for dynamic tolling on California’s highway system. The system would function like a simple “futures” market mechanism by dividing travel demand for a specific facility (e.g., over a bridge, along a corridor, or in a zone) with a finite capacity (e.g., 2,000 vehicles per hour per lane) into time slots (e.g., between 8:00-8:15 or 8:00-9:00). Like other time-slotted systems (e.g., airlines, ferries, canal operators, etc.), travelers then have the option to pre-purchase a planned trip from the available capacity at a lower price in exchange for agreeing to travel during a specific travel window. The price for each unit of time increases as capacity in that timeframe is sold, and buying longer travel windows with more time slots also come at a higher cost. This mechanism not only encourages good travel planning by allowing travelers to avoid expensive peak charges by shifting their travel times, but also rewards punctuality since purchasing a narrower window is less expensive. Beyond greater congestion mitigation, an additional benefit of the proposed system is continual collection of future travel demand data. As users pre-purchase travel, a rolling sample of expected future travel demand is collected, providing a completely new source of data that could be used for a variety of purposes, such as operations, planning, maintenance scheduling, and travel behavior research.
Status: In Progress