Hierarchical MPC-based Motion Planning for Automated Vehicles in Parallel Autonomy
-
Published:2023-05-12
Issue:
Volume:
Page:1-12
-
ISSN:2301-3850
-
Container-title:Unmanned Systems
-
language:en
-
Short-container-title:Un. Sys.
Author:
Cheng Zijun1,
Zeng Xianlin1,
Fang Hao1,
Wang Gang12,
Dou Lihua1
Affiliation:
1. National Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of Technology, Beijing 100081, P. R. China
2. Beijing Institute of Technology Chongqing Innovation Center, Chongqing 401120, P. R. China
Abstract
Automated vehicles with parallel autonomy show advantages over fully automated vehicles and manual driving. This paper proposes a hierarchical motion planning method that mixes inputs of human drivers and the automated driving systems for automated vehicles in scenarios such as multi-lane roads and multi-intersections with dynamic obstacles. The proposed method comprises a reference path generator in the upper level and a nonlinear model predictive controller with mixed human-vehicle control in the lower level. The path planner considers dynamic obstacles, static obstacles, and human comfort to generate a reference path composed of splines with continuous curvatures in the upper level. In the lower level, the MPC generates a trajectory by tracking the reference path and optimizing the cost function containing inputs of drivers while avoiding both dynamic and static obstacles. The simulation verifies the efficacy and the computational tractability of the proposed method.
Funder
National Key R&D Program of China
National Natural Science Foundation of China
Chongqing Natural Science Foundation
Publisher
World Scientific Pub Co Pte Ltd
Subject
Control and Optimization,Aerospace Engineering,Automotive Engineering,Control and Systems Engineering
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献