  Autonomous driving has been among the most popular and challenging topics in
the past few years. On the road to achieving full autonomy, researchers have
utilized various sensors, such as LiDAR, camera, Inertial Measurement Unit
(IMU), and GPS, and developed intelligent algorithms for autonomous driving
applications such as object detection, object segmentation, obstacle avoidance,
and path planning. High-definition (HD) maps have drawn lots of attention in
recent years. Because of the high precision and informative level of HD maps in
localization, it has immediately become one of the critical components of
autonomous driving. From big organizations like Baidu Apollo, NVIDIA, and
TomTom to individual researchers, researchers have created HD maps for
different scenes and purposes for autonomous driving. It is necessary to review
the state-of-the-art methods for HD map generation. This paper reviews recent
HD map generation technologies 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 generation
techniques. We will also discuss the limitations of the current HD map
generation technologies to motivate future research.
