Towards the Trilateration of Non-Connectable Vehicles for Digital Twin: Estimating Distance Between Vehicles Based on Camera-Lidar Data Fusion

With emerging technologies in connected cooperative automated mobility, on-road situation awareness of vehicles has been broadly discussed recently. To achieve greater situation awareness cloud-based digital twin could be utilized. The data from this model could subsequently be used in collision avoidance systems. Unfortunately, transitioning from vehicles with low-level automation and no connectivity to highly automated and connected vehicles will take time. During the period, vehicles with connectivity, together with non-connectable vehicles, will share the same roads. To enhance mobility safety, methods for announcing the dynamics and positions of non-connectable vehicles must be implemented. In this paper, the authors proposed a simplistic method to determine the position of the non-connectable vehicle based on trilateration in two-dimensional space. Also, the paper provides proof-of-concept of estimating the distance between a connected and a non-connectable vehicle, which is the first step toward a proposed solution.