Platooning-based trajectory planning of connected and autonomous vehicles at superstreets

ABSTRACT

Alternative intersection designs are popular existing strategies that can be used for handling heavy traffic in the U.S., and research on the performance of CAVs in the alternative intersection design can complement our knowledge of the impact of CAVs. Hence, this research attempts to mitigate this research gap through a simulation-based study on a superstreet, one of the popular alternative intersection designs. A real-world superstreet is selected for the simulation-based study with collected traffic volumes and average speeds. HDVs are modeled using Wiedemann 99 with calibrated parameters while CAVs are modeled using the intelligent driver model (IDM). Platooning and trajectory planning capabilities of CAVs are modeled in the designed simulation. The simulation results show that the proposed framework for CAVs can successfully reduce fuel consumption in different market penetration rates and traffic scales.

KEYWORDS:

• CAVs
• superstreet
• platooning
• trajectory planning
• market penetration rates
• fuel consumption
• operational performance

Acknowledgements

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).

Disclosure statement

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

Additional information

Funding

This work was supported by U.S. Department of Transportation: [Grant Number 69A3551747133].