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Collaborative optimization method for traffic efficiency and fuel consumption at intersections in connected traffic environment
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AI
DOI：10.1080/21680566.2025.2560989.png)
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Abstract
En 中文
The existing multi-objective joint optimization of traffic efficiency and fuel consumption ignores the impact of vehicle idling, restarting, and other processes on fuel consumption. To address this issue, this study proposes a Collaborative Optimization Method for Traffic Efficiency and Fuel Consumption (COM-TEFC) at signalized intersections. The method jointly optimizes signal timing and vehicle trajectories to minimize a combined cost function that integrates fuel consumption and travel time. Fuel consumption under varying driving conditions is evaluated using the VT-Micro model, which estimates instantaneous fuel use based on vehicle speed and acceleration. The optimization problem is solved using a dynamic programming approach. The simulation results demonstrate that COM-TEFC can simultaneously enhance traffic efficiency and reduce fuel consumption. The observed fuel savings are primarily attributed to trajectory optimization, while the efficiency gains stem from adaptive signal timing. Even with some uncontrolled connected human-driven vehicles, the performance of COM-TEFC still showed significant improvements.
Keywords:
Collaborative optimization
signal timing
fuel consumption
trajectory planning
connected traffic
Journal
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3.4
Papers:
559
Citations:
1.2K