Collision Avoidance System at Urban Intersections Using V2X Communication

<div class="section abstract"><div class="htmlview paragraph">Driving safely through urban intersections is quite challenging for self-driving vehicles due to complicated road geometries and the highly dynamic maneuvers of oncoming traffic, which can cause a high risk of collisions. Traditional onboard sensors like cameras, radar, and lidar give limited visibility in this environment. To overcome these limitations, this paper explores implementing a collision avoidance system at urban intersections utilizing vehicle-to-everything (V2X) communication. The system leverages V2X map data to identify warning zones and uses vehicle-to-vehicle (V2V) communication to estimate the maneuver types and paths of approaching vehicles. The system assesses collision risk by calculating the intersection points of predicted paths for the ego vehicle and oncoming traffic. Depending on the level of collision risk, the system generates a collision warning signal to the driver or activates emergency braking when necessary to prevent accidents. We implement the system using Simulink and the RoadRunner scenario simulation tool. To evaluate system performance in a virtual simulation environment, we create a complex urban scene with intersections and traffic signals using RoadRunner. The high-definition (HD) map from RoadRunner is converted into V2X map messages compliant with the T/CSAE 53-2020 standard. RoadRunner’s Signal Tool configures junction signalization and traffic phases. RoadRunner Scenario uses this traffic signal phase information to simulate traffic signals, which are then converted into V2X SPaT (Signal Phase and Timing) messages.</div></div>