Automatic Semantic Waypoint Mapping Applied to Autonomous Vehicles

Abstract

Road network maps have been used for autonomous vehicle path planning. These maps are basically formed by GPS waypoints and can contain semantic information about the environment to help following traffic codes. This paper describes a novel method for automatic construction of a waypoint map containing semantic information about roads. The collected GPS points are stored into flexible waypoint data structures that can represent any relevant information for vehicle navigation. The mapping method also reduces the amount of waypoints by recognizing and converting them into traffic structures. The resulting waypoint map is stored in a text file which is both human and machine-readable. This work makes part of Carina II platform, an autonomous vehicle under development in the Mobile Robotics Laboratory (LRM) - ICMC/USP. Tests were conducted in urban environment and the resulting maps were consistent when compared to publicly available satellite maps.