A Central Navigation of the Autonomous Vehicles in Zone-based Tessellations with Target Velocities

Abstract

The autonomous are more adaptable to traffic congestion if they join with each other in propagating the situation of traffic around, and have a potential to avoid the traffic jam if they all drive along scheduled routes given from one centralized navigation system. This work presents a central navigation for autonomous travel through a number of tessellated zones. Routes are scheduled every area, and they could be partially altered by traffic situations. Each vehicles compliance with its scheduled route is checked for every route scheduling, and the vehicle positions should be accurate in the traversal through the zone. The vehicle position is estimated with its velocity calculated by imitating autonomous driving, especially for use in the situation of unavailable communication. The estimation technique does not adopt an inertial measuring unit and the accelerometer, differently from previous works in estimating the position of a moving entity. The velocity calculated by imitating autonomous driving has the lower deviation range of errors than that by linear interpolation at a feasible reporting interval through the simulation.