Improving Freight Traffic Efficiency at Urban Intersections Using Heavy Vehicle Platooning - Mohammad D. Alahmadi; Ahmed S. Alzahrani (Applied Sciences)
The increasing presence of heavy connected vehicles (HCVs) in urban traffic necessitates optimized signal-control strategies to improve efficiency. This study develops a platoon-based signal-optimization algorithm to reduce delays, minimize stops, and enhance traffic flow at intersections. The algorithm collects real-time CV data (speed, position, and inter-vehicle distances) to identify platoons, then dynamically adjusts signal timings using platoon-prioritized signal control and advisory speed coordination to synchronize HCV arrivals with green intervals. The algorithm was tested using a VISSIM microscopic traffic-simulation model, calibrated with real-world traffic data from Tallahassee, Florida, under varying traffic-demand scenarios and connected vehicle penetration levels. Performance was evaluated based on average HCV delay and the total number of stops, comparing the platoon-based approach to actuated and vehicle-based signal-control methods. Results show a significant reduction in both delay and stops, with the greatest improvements observed under higher CV penetration and over-saturated conditions. These findings confirm the effectiveness of platoon-based optimization in improving intersection performance and overall traffic progression. Future research will focus on multi-intersection applications and V2I integration to further optimize signal-control strategies.