Creating High-Definition Vector Maps for Autonomous Driving

Abstract

Autonomous driving holds many promises for transportation - increased safety, lower costs, and less burden to the environment. In light of some recent accidents, it is clear that the technology is not fully ready yet, and the robustness and research in the area need to be increased. Most of the autonomous driving solutions rely on high-definition maps (HD maps) - specialized lane-level maps with very high locational accuracy. Mobile mapping cars (specially equipped vehicles with sensors for map data collection) by big mapping companies are used to collect the data for creating HD maps. Along with required data processing the creating and keeping the HD maps up to date in a changing world is very costly. Availability of the HD maps would considerably lower the bar for adopting autonomous driving at large. To the best of the author’s knowledge, there are no freely available HD maps for self-driving available for Estonia. To be able to conduct research experiments with the University of Tartu's Autonomous Driving Lab (UT ADL) self-driving platform, such maps had to be created. Several available tools for creating the maps and existing data sources were reviewed. The custom workflow was created for mapping and a tool to convert the HD vector map to Autoware vector map format was created. Finally, quantitative measures about time estimates needed to create the HD vector maps and their usage in UT ADL were given.