A simulation study on the traffic delay and fuel consumption of connected and autonomous vehicles in superstreet with platooning, signal optimization, and trajectory planning

ABSTRACT

Connected and Autonomous Vehicles (CAVs) are a promising technology that is ready to be deployed in the near future to improve the traffic efficiency and safety as well as environment. Extensive studies have been done to investigate the potential performance of CAVs on freeways, at roundabouts, and conventional intersections. Nevertheless, innovative intersections, as an important component of today’s transportation infrastructure, have been seldom investigated in relation to the performance of CAVs. Hence, this research is designed to examine how CAV technologies can influence the performance of a superstreet, one of the popular innovative intersection designs. In this research, the car-following model, platooning, trajectory planning, and adaptive signal control are specified for CAVs and signal controllers in a superstreet. An equivalent conventional intersection with the same lane configurations is also constructed in the simulation environment to make a fair comparison and gain important insights. More importantly, the findings from this research may provide references for studies on other innovative intersections which share similar design characteristics.

KEYWORDS:

• Superstreet
• connected and autonomous vehicles
• trajectory planning
• platooning
• signal optimization

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The authors want to express their deepest gratitude to the financial support by the United States Department of Transportation, University Transportation Center through the Center for Advanced Multimodal Mobility Solutions and Education (CAMMSE) at The University of North Carolina at Charlotte [grant number: 69A3551747133].