A cooperative framework for Urban SEMI actuated signa l control at signa lized t-intersections in mixed traffic flow

Alanazi, Fayez; Yi, Ping · 2022 · Crossref

DOI: 10.2495/tdi-v6-n2-122-142

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Summary

This paper addresses the challenge of traffic congestion and inefficiency at urban semi-actuated signalized T-intersections, particularly in mixed traffic environments containing both human-driven vehicles and Connected and Automated Vehicles (CAVs). The authors identify that semi-actuated control, which prioritizes major road flow but interrupts it to serve minor road vehicles, often causes significant delays and throughput losses when minor road demand is consistent. To mitigate this, the study proposes a cooperative framework that utilizes Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) communications to guide CAVs on the major road to create additional safe gaps for minor road vehicles, thereby reducing the need for signal interruptions. The methodology involves developing a modified signal control algorithm and validating it through microscopic traffic simulation using PTV VISSIM software integrated with Python. The framework operates by instructing CAVs to reduce speed and increase following distances when a minor road vehicle is detected and the existing gap is insufficient. The algorithm incorporates safety constraints, ensuring that the distance between the CAV and any following vehicle remains greater than the safe car-following distance before speed reduction occurs. The simulation tested various scenarios with different traffic volumes on major and minor roads and CAV penetration rates of 30%, 50%, and 70%. Performance was evaluated using measures of effectiveness including signal interruptions, control delay, intersection throughput, and fuel consumption. The results demonstrate that the proposed framework significantly improves intersection performance. As CAV penetration increases, the number of signal interruptions on the major road decreases substantially; for instance, at 70% CAV penetration, interruptions were reduced by 50% compared to a baseline with no CAVs. Consequently, control delay on the major road decreased, with delays dropping from 32 seconds to 13 seconds under specific high-volume conditions. Intersection throughput increased by up to 34% when CAV penetration reached 70%. Additionally, the framework yielded environmental benefits, with fuel consumption reductions of up to 48% attributed to smoother traffic flow and reduced idling. The study also found that increasing the maximum allowable waiting time for minor road vehicles further reduced mainline interruptions, allowing more opportunities for gap accommodation. The significance of this work lies in its demonstration that cooperative CAV technologies can enhance the efficiency of existing semi-actuated signal systems without requiring full infrastructure upgrades. By leveraging CAVs to manage gap creation, the framework reduces delays, increases capacity, and lowers emissions in mixed traffic conditions. The findings suggest that even partial penetration of CAVs can yield measurable improvements in intersection performance, offering a viable strategy for managing urban traffic congestion as automated vehicle adoption grows.

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