TY - GEN
T1 - Autonomous Vehicle Testing and Validation Platform
T2 - 2018 IEEE Intelligent Vehicles Symposium, IV 2018
AU - Chen, Yu
AU - Chen, Shitao
AU - Zhang, Tangyike
AU - Zhang, Songyi
AU - Zheng, Nanning
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/18
Y1 - 2018/10/18
N2 - With the development of autonomous driving, offline testing remains an important process allowing low-cost and efficient validation of vehicle performance and vehicle control algorithms in multiple virtual scenarios. This paper aims to propose a novel simulation platform with hardware in the loop (HIL). This platform comprises of four layers: the vehicle simulation layer, the virtual sensors layer, the virtual environment layer and the Electronic Control Unit (ECU) layer for hardware control. Our platform has attained multiple capabilities: (1) it enables the construction and simulation of kinematic car models, various sensors and virtual testing fields; (2) it performs a closed-loop evaluation of scene perception, path planning, decision-making and vehicle control algorithms, whilst also having multi-agent interaction system; (3) it further enables rapid migrations of control and decision-making algorithms from the virtual environment to real self-driving cars. In order to verify the effectiveness of our simulation platform, several experiments have been performed with self-defined car models in virtual scenarios of a public road and an open parking lot and the results are substantial.
AB - With the development of autonomous driving, offline testing remains an important process allowing low-cost and efficient validation of vehicle performance and vehicle control algorithms in multiple virtual scenarios. This paper aims to propose a novel simulation platform with hardware in the loop (HIL). This platform comprises of four layers: the vehicle simulation layer, the virtual sensors layer, the virtual environment layer and the Electronic Control Unit (ECU) layer for hardware control. Our platform has attained multiple capabilities: (1) it enables the construction and simulation of kinematic car models, various sensors and virtual testing fields; (2) it performs a closed-loop evaluation of scene perception, path planning, decision-making and vehicle control algorithms, whilst also having multi-agent interaction system; (3) it further enables rapid migrations of control and decision-making algorithms from the virtual environment to real self-driving cars. In order to verify the effectiveness of our simulation platform, several experiments have been performed with self-defined car models in virtual scenarios of a public road and an open parking lot and the results are substantial.
UR - https://www.scopus.com/pages/publications/85056795650
U2 - 10.1109/IVS.2018.8500461
DO - 10.1109/IVS.2018.8500461
M3 - 会议稿件
AN - SCOPUS:85056795650
T3 - IEEE Intelligent Vehicles Symposium, Proceedings
SP - 949
EP - 956
BT - 2018 IEEE Intelligent Vehicles Symposium, IV 2018
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 26 September 2018 through 30 September 2018
ER -