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.
This data stems from a project in which researchers used a microscopic road traffic model with local travel activity data to simulate vehicle travel in San Francisco’s downtown central business district to explore traffic flow, VMT, and GHG effects of AV scenarios.
These data stem from a project that developed a powerful and user-friendly web-based version of the Integrated Transport and Health Impact Model tool for the Sacramento Area Council of Governments (SACOG) six county region
Researchers propose a hierarchical ramp control system that allows microscopic cooperative maneuvers for connected and automated electric vehicles (CAEVs) on the ramp to merge into mainline traffic flow under certain controlled ramp inflow rate.