Adaptive Traffic Signal Control using CV2X

Adaptive traffic signal (light) control technologiesoffer a significant improvement over pre-programmed fixedtiming signal control schema by reducing traffic delays. Adap-tive signal control predicts future traffic conditions based onreal-time traffic data and finds optimal timings of the red,yellow, and green phases of the light to accommodate changingtraffic patterns. But, current adaptive traffic signal systems arelimited by the availability of vehicle arrival data emitted bytraditional sensors like induction loops and camera systemswhich come with their own limitations such as; Induction loopscan only indicate if ONE vehicle is waiting at the head of alane and camera system perform poorly in bad weather andlighting. Alternatively, data from connected vehicles providemuch more data that can be used for adaptive traffic signalcontrol. Accordingly, we propose a 5G-MEC (Multi-AccessEdge Computing) based traffic signal control that utilizes BasicSafety Message (BSM) issued by connected vehicles to findtraffic arrival rates and optimizes traffic signal timings bysolving a mixed integer linear program (MILP) at the MECto adjust the signal phase timings dynamically. Our resultsindicate a noticeable improvement in reducing average delaysfor normal, high, and low arrival rates of the vehicles, and thedelay is reduced by as much as 19.6% in case of a lower arrivalrate of the vehicles in comparison to the fixed-time signal.