Impact of Sensing Range on Real-Time Adaptive Control of Signalized Intersections Using Vehicle Trajectory Information

Abstract

This study examines the impact of the detection sensing range on the quality of the signal control. The performance of advanced signal control methods, a Self-Organizing Algorithm (SOA) and Phase Allocation Algorithm (PAA), was tested in simulation with varying ranges within which the detection was able to measure vehicle positions and speeds. Three different traffic scenarios were developed: symmetric, asymmetric, and balanced. Both algorithms exhibited improvements in performance as the sensing range was increased. Under the symmetric volume scenario, SOA converged at 1000 ft and PAA converged at 1500 ft (with vehicles traveling at 45 mph). Under the asymmetrical and balanced volume scenarios, both algorithms outperformed conventional methods. Both algorithms performed better than coordinated-actuated control at sensing ranges of 660 ft or higher. For low sensing ranges, SOA experiences similar delay compared to conventional fully-actuated control with setback detection, and PAA experienced more delay than conventional coordinated-actuated control in the balanced and symmetric scenarios but performed better for the asymmetric scenario. The results suggest that for the SOA algorithm, the sensing range may constrain the maximum allowable secondary extension. Thus, as the sensing range increases, the vehicular delay decreases for arterial movements and increases for non-arterial movements. For PAA, arterial and non-arterial delay decreases as the sensing range increases until it converges.