Maps are constantly developing, also, the newly defined High Definition (HD) maps increase the map content remarkably. They are based on three-dimensional survey, like laser scanning, and then stored in a fully new structured way to be able to support modern-day vehicles. Beyond the traditional lane based map content, they contain information about the roads’ neighbourhood. The goal of these maps is twofold. Primarily, they store the connections where the vehicles can travel with the description of the road-environment. Secondly, they efficiently support the exact vehicle positioning. The paper demonstrates the first results of a pilot study in the creation of HD map of an urban and a rural environment. The applied data collection technology was the terrestrial laser scanning, where the obtained point cloud was evaluated. The data storage has been solved by an in-house developed information storage model with the ability to help in vehicle control processes.
Driving a road vehicle is a very complex task in terms of controlling it, substituting a human driver with a computer is a real challenge also from the technical side. An important step in vehicle controlling is when the vehicle plans its own trajectory. The input of the trajectory planning are the purpose of the passengers and the environment of the vehicle. The trajectory planning process has several parts, for instance, the geometry of the path-curve or the speed during the way. Furthermore, a traffic situation can also determine many other parameters in the planning process.
This paper presents a basic approach for trajectory design. To reach the aim a map will be given as a binary 2204 x 1294 size matrix where the roads will be defined by ones, the obstacles will be defined by zeros. The aim is to make an algorithm which can find the shortest and a suitable way for vehicles between the start and the target point. The vehicle speed will be slow enough to ignore the dynamical properties of the vehicle. The research is one of the first steps to realize automated parking features in a self-drive car.