Green-Pressure – a Weighted Queue-Length Approach towards Sustainable Intersection Management

The 64th IEEE Conference on Decision and Control (CDC 2025), Rio de Janeiro, Brazil, December 09-12, 2025

Urban transportation networks increasingly suffer from congestion. Negative externalities resulting from noise and pollution, affect public health, quality of life, and the economy. The major traffic bottlenecks in cities are conflicts at intersections, leading to this pressing issue. Intelligent transportation systems leverage sensors to optimize traffic flows, mainly by control of traffic lights. Green-Pressure is an extension of the Max-Pressure algorithm, that leverages vehicle category information from loop-detectors for a weighted queue-length approach, to reduce emissions at signalized intersections. A multi-modal, case study of a real-world artery network with seven intersections, and 96 traffic signals, demonstrates the feasibility of the proposed method using a calibrated microsimulation model. Interestingly, the differentiation of vehicle categories at traffic lights not only enables reductions in emissions up to $9%$ but also improves traffic efficiency significantly ($5%$ reduction of total travel time) when compared with the (unweighted) Max-Pressure controller. This is achieved by systematic prioritization of transporters, trucks, and buses, at the cost of slightly larger delays for passenger cars and motorcycles. Ultimately, the proposed method has the potential to achieve more sustainable road traffic leveraging existing sensor infrastructure.