@inproceedings{3d23e389034843af8352c8381342ec79,
title = "Trajectory Planning of Autonomous Driving Vehicles Based on Road-Vehicle Fusion",
abstract = "With the development of artificial intelligence and communication technology, road-vehicle fusion technology has become the trend of future traffic development. High-precision trajectory planning is required for the operation of autonomous driving vehicles. This paper focus on the trajectory planning problem for autonomous vehicles driving in the region where objects are occluded. At first, the space-time map and Frenet coordinate system of the road are established. Through cooperative perception between the autonomous driving vehicles and infrastructure system, the platform of road analyzes the potential risks. Hybrid A*path planning improved for the speed planning generates the optimal trajectory. The proposed framework is implemented through simulations in accident-prone scenarios in this paper. The simulation results show that the trajectory and speed smoothness of the autonomous driving vehicle is improved, and the driving safety of the autonomous driving vehicle is enhanced in the road-vehicle sensing cooperative system.",
author = "Han Li and Guizhen Yu and Bin Zhou and Da Li and Zhangyu Wang",
note = "Publisher Copyright: {\textcopyright} 2020 ASCE.; 20th COTA International Conference of Transportation Professionals: Transportation Evolution Impacting Future Mobility, CICTP 2020 ; Conference date: 14-08-2020 Through 16-08-2020",
year = "2020",
language = "英语",
series = "CICTP 2020: Transportation Evolution Impacting Future Mobility - Selected Papers from the 20th COTA International Conference of Transportation Professionals",
publisher = "American Society of Civil Engineers (ASCE)",
pages = "816--828",
editor = "Heng Wei and Haizhong Wang and Lei Zhang and Yisheng An and Xiangmo Zhao",
booktitle = "CICTP 2020",
address = "美国",
}