Li, Shuoyuan (Tongji University), Wang, Haoran (Tongji University), Hu, Jia (Tongji University)

Balancing Mobility and Ecology: Eco-Approach at an Actuated Signalized Intersection

Scheduled for presentation during the Invited Session "S21a-Energy-Efficient Connected Mobility" (TH-LM-T21), Thursday, November 20, 2025, 10:30−10:50, Surfers Paradise 3

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Abstract

At the actuated signalized intersection, the duration of the signal phase varies and depends on real-time traffic volume, making it difficult for vehicles using traditional eco-approach controllers to identify the optimal driving trajectories. To address this issue, this study proposes a novel eco-approach controller tailored to the actuated signalized intersection. We first develop a green phase prediction method based on the Multivariate Markov chain theory. It enhances the prediction accuracy by incorporating real-time traffic states. Secondly, the spatial-temporal driving corridor planning method is proposed to guide the vehicle through the intersection without stopping at red lights. This method optimizes both fuel consumption and non-stop passage rate, with user-adjustable parameters to balance driving ecology and efficiency. Finally, a longitudinal and lateral coupled motion planning method is established based on Model Predictive Control, enabling precise tracking of the recommended driving corridor. Simulation results show that the proposed eco-approach controller could achieve a 16.2% reduction in energy consumption compared to a human driver, while causing a 6.1% increase in travel time due to gradual acceleration behavior.