Abstract
For autonomous driving, a control system that supports precise road maps is required to monitor the operation status of autonomous vehicles in the research stage. Such a system is also required for research related to automobile engineering, sensors, and artificial intelligence. The design of Google Maps and other map services is limited to the provision of map support at 20 levels of high-resolution precision. An ideal map should include information on roads, autonomous vehicles, and Internet of Things (IOT) facilities that support autonomous driving. The aim of this study was to design a map suitable for the control of autonomous vehicles in Gyeonggi Province in Korea. This work was part of the project “Building a Testbed for Pilot Operations of Autonomous Vehicles”. The map design scheme was redesigned for an autonomous vehicle control system based on the “Easy Map” developed by the National Geography Center, which provides free design schema. In addition, a vector-based precision map, including roads, sidewalks, and road markings, was produced to provide content suitable for 20 levels. A hybrid map that combines the vector layer of the road and an unmanned aerial vehicle (UAV) orthographic map was designed to facilitate vehicle identification. A control system that can display vehicle and sensor information based on the designed map was developed, and an environment to monitor the operation of autonomous vehicles was established. Finally, the high-precision map was verified through an accuracy test and driving data from autonomous vehicles.
Highlights
Autonomous vehicles have attracted significant research attention, with the research led by Google and global automotive companies such as Uber, Tesla, and Audi
Semi-autonomous Level 3 automobiles can be purchased. This level, which has been set by the American Society of Automotive Engineers (SAE), allows drivers to enjoy semi-autonomous driving on specific roads, while maintaining a frontal gaze
This paper reports the definition and design process of the schema and the construction and editing of a high-precision digital map and unmanned aerial vehicle (UAV) orthoimages that constitute the map
Summary
Autonomous vehicles have attracted significant research attention, with the research led by Google and global automotive companies such as Uber, Tesla, and Audi. A control system that supports a high-precision lane-level road map is required to monitor the operation status of autonomous vehicles in the research stage. The purpose of this study was to construct a high-precision 20th-level map for autonomous driving, to test the accuracy of the high-precision map through actual operation and monitoring, and to design a 20th-level map suitable for controlling autonomous vehicles.
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