@inproceedings{2c51e0cce4704686a746ecefc2cabe5e,
title = "Autonomous Driving System Design for Formula Student Driverless Racecar",
abstract = "This paper summarizes the work of building the autonomous system including detection system and path tracking controller for a formula student autonomous racecar. A LIDAR-vision cooperating method of detecting traffic cone which is used as track mark is proposed. Detection algorithm of the racecar also implements a precise and high rate localization method which combines the GPS-INS data and LIDAR odometry. Besides, a track map including the location and color information of the cones is built simultaneously. Finally, the system and vehicle performance on a closed loop track is tested. This paper also briefly introduces the Formula Student Autonomous Competition (FSAC) in 2017.",
keywords = "Autonomous Racecar, Autonomous Vehicle, Environment Detection, Formula Student Autonomous, Localization and Mapping, Trajectory Tracking",
author = "Hanqing Tian and Jun Ni and Jibin Hu",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Intelligent Vehicles Symposium, IV 2018 ; Conference date: 26-09-2018 Through 30-09-2018",
year = "2018",
month = oct,
day = "18",
doi = "10.1109/IVS.2018.8500471",
language = "English",
series = "IEEE Intelligent Vehicles Symposium, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "874--879",
booktitle = "2018 IEEE Intelligent Vehicles Symposium, IV 2018",
address = "United States",
}