Autonomous vehicles localisation based on semantic map matching method

In autonomous driving systems, a positioning method that can be used in scenarios with no satellite signals or long signal interruptions is a must. In this paper, we address the problems in map construction methods and map matching methods in scenes without satellite signals or long signal interruptions, and construct a semantic map matching-based localization method to meet the localization requirements by means of monocular vision sensors on the basis of weighing the accuracy and cost of map construction and localization. In this paper, firstly, the method of map construction is studied and a static semantic map construction method based on monocular camera is constructed. Then the map matching localization method is studied, and a semantic map matching based localization method is constructed to align the local map built during localization with the pre-built global semantic map to obtain the current location information. Finally, this paper constructs a method to fuse the visual odometry and map matching localization results, so as to obtain more accurate localization results.