Automated Vehicle’s Overtaking Maneuver with Yielding to Oncoming Vehicles in Urban Area Based on Model Predictive Control
نویسندگان
چکیده
The rapid development of automated driving technology has brought many emerging technologies. collision avoidance (CA) function by braking and/or steering maneuver advanced driver assistance systems (ADAS), which contributes to the improvement safety vehicles, been playing an important role in recent modern passenger cars and commercial vehicles. When vehicle needs avoid multiple obstacles at same time, consuming travel time assurance CA need be carefully considered especially case related unpredictable motion obstacles. This paper proposes a feasible solution this situation controlling speed wheel angle. proposed re-planning based on post-encroachment (PET) provides judgment calculates possibility unavoidable road accidents. Then path layer novel two-layer model predictive control (TL-MPC) will re-plan local trajectory give reference acceleration. Finally, tracking outputs angle follow under premise ensuring constraints. system is evaluated co-simulations MATLAB/Simulink CarSim software. results show that for various conditions ego adopting strategy conduct reasonable behavior consequently successfully
منابع مشابه
Modeling and Intelligent Control System Design for Overtaking Maneuver in Autonomous Vehicles
The purpose of this study is to design an intelligent control system to guide the overtaking maneuver with a higher performance than the existing systems. Unlike the existing models which consider constant values for some of the effective variables of this behavior, in this paper, a neural network model is designed based on the real overtaking data using instantaneous values for variables. A fu...
متن کاملObstacle avoidance of autonomous vehicles based on model predictive control
This paper presents an obstacle avoidance scheme for autonomous vehicles as an active safety procedure in unknown environments. Safe trajectories are generated using the non-linear model predictive framework, in which the simplified dynamics of the vehicle are used to predict the state of the vehicle over the look-ahead horizon. To compensate for the slight dissimilarity between the simplified ...
متن کاملManeuver Control based on Reinforcement Learning for Automated Vehicles in An Interactive Environment
Operating a robot safely and efficiently can be considerably challenging in an interactive and complex environment. Other surrounding agents may be cooperative or adversarial in their interactions with the robot. It will be desirable to develop control strategies that can enable the robot agent to handle diverse situations and respond with appropriate behaviors in an interactive environment. In...
متن کاملVisualizing Model Predictive Control of Vehicles
Model predictive control is a useful technique for controlling autonomous vehicles, enabling additional performance and safety over simpler controllers. However, its additional complexity means it produces more data and can be harder to debug and tune. This project aims to provide an interactive tool that aids engineers working with MPC by providing an easy way to view planned trajectories over...
متن کاملState Estimation Based Model Predictive Control for LHD Vehicles
LHD (load-haul-dump) vehicles are used extensively in underground mining operations for ore transporting, primarily in tunnels where access is difficult or dangerous. To ensure underground efficient and safe LHD’s performance, a robust feedback control strategy is needed. A state estimation based MPC scheme was designed for control purposes, and evaluated by simulation. The state estimator was ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied sciences
سال: 2021
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app11199003