Extending Obstacle Map of Autonomous Vehicles Based on Network Model of Local Positioning

Abstract

At present, an unmanned autonomous vehicle (AV) to provide accurate navigation during motion depends on GPS. The search and study for the alternative methods of AV localization is the demand to implement smart city concepts because in real-world conditions, the GPS signal may either be absent, or its accuracy may be insufficient to trajectory following and perform maneuvers. For collision avoidance to raise AV safety, the network model of local positioning is proposed. Control systems based on obtained local maps partially solve the problem of a safety motion. The presented simulation results confirm the effectiveness of the described approach to improving traffic safety in uncontrolled dynamic environments.