efficiency

This policy brief reviews various eco-driving studies to determine eco-driving's impacts on fuel economy and to evaluate most effective strategies.

n this work, the authors developed a scheduling assignment for loaded and empty containers that builds on earlier models but incorporates stochastic (random) future demand. This report shows that the truck miles needed to satisfy the demand at all locations is reduced by about 4-7% when considering future stochastic demand as opposed to only considering today’s demand.

With rapid population growth and urban development, traffic congestion has become an inescapable issue, especially in large cities. Many congestion reduction strategies have been proposed in the past, ranging from roadway extension to transportation demand management programs. In particular, congestion pricing schemes have been used as negative reinforcements for traffic control. This project studies a different approach of offering positive incentives to drivers to take alternative routes.

Researchers at the University of Southern California developed a centrally coordinated freight routing system and ran several simulations to minimize the social costs of freight transportation, also accounting for adoption of electric trucks. This policy brief summarizes the findings from that research and provides policy implications.