A review of high-definition map creation methods for autonomous driving

Autonomous driving has been among the most popular and challenging topics in the past few years. Among all modules in autonomous driving, High-definition (HD) map has drawn lots of attention in recent years due to its high precision and informative level in localization. Since localization is a significant module for automated vehicles to navigate an unknown environment, it has immediately become one of the most critical components of autonomous driving. Big organizations like HERE, NVIDIA, and TomTom have created HD maps for different scenes and purposes for autonomous driving. However, such HD maps are not open-source and are only available for internal research or automotive companies. Even though researchers have proposed various methods to create HD maps using different types of sensor data, there are few papers that review and summarize those methods. New researchers do not have a clear insight into the current state of HD map creation methods to work on their HD map research. Due to the reason above, reviewing, classifying, comparing, and summarizing the state-of-the-art techniques for HD map creation is necessary. This paper reviews recent HD map creation methods that leverage both 2D and 3D map generation. This review introduces the concept of HD maps and their usefulness in autonomous driving and gives a detailed overview of HD map creation methods. We will also discuss the limitations of the current HD map creation methods to motivate future research. Additionally, a chronological overview is created with the most recent HD map creation methods in this paper.