Open AccessDevelopment of a self-driving car prototype for educational and research purposes
Author(s) -
Xinxin Fan,
Z Zhang,
Y Wang
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1905/1/012013
Subject(s) - self driving , computer science , kalman filter , software , open source , embedded system , systems engineering , human–computer interaction , artificial intelligence , transport engineering , engineering , operating system
Self-driving car (SDC) is one of the most challenging topics in artificial intelligence. However, current off-the-shelf SDC platforms are expensive and difficult to modify, which prevents more researchers from working towards the improvement of self-driving technologies. This paper presents the development of a SDC prototype with low-cost sensors and an open-source software platform for educational and academic research purposes. The goal of such a SDC prototype is to serve as a testbench, which allows students and researchers to easily test new algorithms of SDC. Localization is one of the most basic and important problems in SDC. To achieve high performance using low-cost sensors, a localization method based on Lidar-INS fusion was investigated under the framework of Kalman filtering. Autonomous driving experiments were conducted on roads of a university campus environment and the results are used to show the performance.