congestion

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 real-time, distributed algorithm for offering personalized incentives to individual drivers to make socially optimal routing decisions.

Some field studies have observed reductions in travel time by coordinating freeway ramps with adjacent arterial signals. To advance the investigation, the researchers propose an integrated traffic management strategy that involves variable speed limit, lane change, ramp metering for freeway traffic flow control, and a traffic-responsive signal control scheme for adjacent traffic light intersections.

Researchers at the University of California, Davis conducted a review of practices in curbside management, and they conducted simulations to evaluate the impact of different management and design strategies on travel time, congestion, vehicle travel, and emissions in residential, commercial, and mixed-use neighborhoods in San Francisco.

This white paper examines the co-benefits of reducing vehicles miles of travel. Examples include reductions in air pollutant emissions, water pollution, wildlife mortality, and traffic congestion, as well as improvements in safety and health, and savings in public and private costs.

The data from this project is primarily randomly generated data sets and demand data for containers near the San Pedro Ports.

This data contains the GIS information of the three study areas from the project Fighting for Curb Space, as well as the SUMO scripts.