Exploring the effects of connected and automated vehicles at fixed and actuated signalized intersections with different market penetration rates

ABSTRACT

To investigate the effects of different market penetration rates (MPRs) of intelligent vehicles – Intelligent Driving Model (IDM) for autonomous vehicles (AVs), Adaptive Cruise Control (ACC) for AVs, and Cooperative Adaptive Cruise Control (CACC) for connected and automated vehicles (CAVs) – in mixed traffic flows with human driving vehicles (HDVs) at intersections, three signalized intersections (fixed signal, gap-based actuated signal, and delay-based actuated signal-controlled intersections) with low, medium, and high traffic demands are investigated. The simulation results indicate that CAVs with the CACC system outperform AVs with ACC or IDM systems and could reduce the average delay under low and high demand scenarios by 49% to 96%. CAVs with the CACC system could also significantly reduce average delay with a 20% MPR, while significant drops could only be observed after 60% and 80% MPRs for AVs with the ACC/IDM system. Gap-based and delay-based actuated signal control schemes are preferred under medium traffic flow demand, and CACC/ACC systems could significantly improve the performance of actuated signal-controlled intersections under high traffic flow demand.

KEYWORDS:

• Connected and automated vehicle
• market penetration rates
• traffic flow
• simulation
• fixed signal
• actuated signal
• intersections

Acknowledgements

The authors want to express their deepest gratitude to the financial support by the US 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

The authors want to express their deepest gratitude to the financial support by the US 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).