Personalized Commuter Incentive System Could Reduce CO2 Emissions by up to 27 Percent.
A Study on the Effectiveness of a Personalized Travel Incentive Program in Los Angeles, California.
Date Posted

Congestion Reduction via Personalized Incentives

Summary Information

Roadway congestion continues to be a major problem in urban areas around the world. One potential strategy to help reduce congestion is to offer drivers incentives to change their travel behavior. These incentives could be offered through smartphones and centrally managed by public authorities. These incentives could encourage drivers to drive at different times, take different routes, use alternative travel modes, or even not drive at all. These incentives could be publicly funded, or they could be provided by businesses who offer discounts for drivers arriving at certain times of the day.

While driver incentive programs might be useful for congestion reduction, they are still mostly theoretical. A research team based at the University of Southern California modeled the effects of a driver incentive system to better understand the potential benefits of such a system.

To do this, the team conducted a detailed simulation of traffic in the greater Los Angeles area with and without a personalized incentive program. First, the team developed a series of mathematical models to simulate how people would respond to being offered cash incentives ranging from $0 to $1000. Second, the team gathered detailed traffic data from the Archived Data Management System which collects, archives, and integrates transportation datasets from the greater Los Angeles area. Finally, the team simulated traffic patterns with and without the incentives.

The incentive program was found to have the potential to reduce CO2 emissions by 27 percent during rush hour. The authors note, however, that this study only examined route choice incentives and that offering incentives to alter driver mode or trip time could have different effects.