Map Engine with Route and Slope Prediction for Autonomous Vehicles in Offroad Applications

Abstract: With an imminent future of fully autonomous heavy duty vehicles in offroad applications, the need for advanced control system will increase accordingly. By implementing a raster map with tiles and pixels, to which a vehicle can record slope and position data while driving, it is possible to map earth's surface. By adding a heat parameter to every pixel, i.e. the number of passings through it historically, it is possible in future visits of the same are to generate a route prediction made up by the "hottest" pixels. By fetching the slope values in the hottest pixels, it is possible to generate a slope horizon that can be utilized by control systems, e.g. when planning gear shifts in hilly offroad terrain. To mange the incrementally growing map, a memory management system was implemented. It buffers the relevant map data from the database, i.e. the vehicles closest surroundings, which is then used for route prediction and horizon generation. As the vehicle moves into other areas, new data is read from the database, and the recently passed area is written back to the database, however updated from the recent passing. The system is implemented so that it runs through another application in the telematics electrical controller unit (ECU) in a Scania vehicle. The ECU contains a GNSS module from which the vehicle fetches satellite positioning data. Slope data is fetched from a slope sensor mounted on the truck. Due to implications during testing and debugging of the resulting application developed and implemented during this thesis project, the application's performance couldn't be assessed properly. However, it is concluded that the background the application is built on is reliable, although tweaks to get the application fit for usage in offroad terrain had to be made. Mainly, the horizon length and map building techniques should not be the same as in similar applications for onroad driving.