Improving Freight Traffic Efficiency at Urban Intersections Using Heavy Vehicle Platooning
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 algor...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/5/2682 |
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| author | Mohammad D. Alahmadi Ahmed S. Alzahrani |
| author_facet | Mohammad D. Alahmadi Ahmed S. Alzahrani |
| author_sort | Mohammad D. Alahmadi |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-6760ad70d3bf41e2b474822fbb1145f7 |
| institution | DOAJ |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-6760ad70d3bf41e2b474822fbb1145f72025-08-20T02:59:07ZengMDPI AGApplied Sciences2076-34172025-03-01155268210.3390/app15052682Improving Freight Traffic Efficiency at Urban Intersections Using Heavy Vehicle PlatooningMohammad D. Alahmadi0Ahmed S. Alzahrani1Software Engineering Department, College of Computer Science and Engineering, University of Jeddah, Jeddah 21493, Saudi ArabiaCivil Engineering Department, King Abdulaziz University, Jeddah 21589, Saudi ArabiaThe 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.https://www.mdpi.com/2076-3417/15/5/2682logistic delayconnected vehiclesplatooningVISSIMvehicle to vehiclevehicle to infrastructure |
| spellingShingle | Mohammad D. Alahmadi Ahmed S. Alzahrani Improving Freight Traffic Efficiency at Urban Intersections Using Heavy Vehicle Platooning Applied Sciences logistic delay connected vehicles platooning VISSIM vehicle to vehicle vehicle to infrastructure |
| title | Improving Freight Traffic Efficiency at Urban Intersections Using Heavy Vehicle Platooning |
| title_full | Improving Freight Traffic Efficiency at Urban Intersections Using Heavy Vehicle Platooning |
| title_fullStr | Improving Freight Traffic Efficiency at Urban Intersections Using Heavy Vehicle Platooning |
| title_full_unstemmed | Improving Freight Traffic Efficiency at Urban Intersections Using Heavy Vehicle Platooning |
| title_short | Improving Freight Traffic Efficiency at Urban Intersections Using Heavy Vehicle Platooning |
| title_sort | improving freight traffic efficiency at urban intersections using heavy vehicle platooning |
| topic | logistic delay connected vehicles platooning VISSIM vehicle to vehicle vehicle to infrastructure |
| url | https://www.mdpi.com/2076-3417/15/5/2682 |
| work_keys_str_mv | AT mohammaddalahmadi improvingfreighttrafficefficiencyaturbanintersectionsusingheavyvehicleplatooning AT ahmedsalzahrani improvingfreighttrafficefficiencyaturbanintersectionsusingheavyvehicleplatooning |