Attention-based highway safety planner for autonomous driving via deep reinforcement learning
G Chen, Y Zhang, X Li - IEEE Transactions on Vehicular …, 2023 - ieeexplore.ieee.org
In this article, a motion planning for autonomous driving on highway is studied. A high-level
motion planning controller with discrete action space is designed based on deep Q network …
motion planning controller with discrete action space is designed based on deep Q network …
Frenet-cartesian model representations for automotive obstacle avoidance within nonlinear mpc
In recent years, nonlinear model predictive control has been extensively used for solving
automotive motion control and planning tasks. In order to formulate the nonlinear model …
automotive motion control and planning tasks. In order to formulate the nonlinear model …
An efficient planning method based on deep reinforcement learning with hybrid actions for autonomous driving on highway
M Zhang, K Chen, J Zhu - International Journal of Machine Learning and …, 2023 - Springer
Due to the complexity and uncertainty of the traffic, planning for autonomous driving (AD) on
highway is challenging. Traditional planning algorithms have the problems of low and …
highway is challenging. Traditional planning algorithms have the problems of low and …
[HTML][HTML] In search of the best fitness function for optimum generation of trajectories for Automated Guided Vehicles
This paper presents an offline optimization method designed for use with industrial robots in
environments with static obstacles. It is particularly useful in industry where stability and …
environments with static obstacles. It is particularly useful in industry where stability and …
Nonlinear Model Predictive Control for Time-Optimal Turning Around of an Autonomous Vehicle Under Steering Lag
H Li, B Li, H Yang, C Mu - IEEE/ASME Transactions on …, 2024 - ieeexplore.ieee.org
In this article, a time-optimal turning around method is designed based on model predictive
control (MPC) for an autonomous vehicle under steering lag. To address the steering lag …
control (MPC) for an autonomous vehicle under steering lag. To address the steering lag …
Intelligent Vehicle Path Based on Discretized Sampling Points and Improved Cost Function-A Quadratic Programming approach
C Zhang, W Xu - IEEE Access, 2024 - ieeexplore.ieee.org
The paper introduces a quadratic programming algorithm for real-time local path planning of
autonomous vehicles. The algorithm relies on discretized sampling points and an enhanced …
autonomous vehicles. The algorithm relies on discretized sampling points and an enhanced …
Progressive Smoothing for Motion Planning in Real-Time NMPC
Nonlinear model predictive control (NMPC) is a popular strategy for solving motion planning
problems, including obstacle avoidance constraints, in autonomous driving applications …
problems, including obstacle avoidance constraints, in autonomous driving applications …
Variable Velocity Planning Algorithm for Autonomous Robot or Car
RA Prunean, R Solea… - 2023 IEEE 28th …, 2023 - ieeexplore.ieee.org
The aim of this paper is to propose a planning techniques for the longitudinal and angular
velocity profile for autonomous robot or car. This paper addresses this problem proposing a …
velocity profile for autonomous robot or car. This paper addresses this problem proposing a …
Enhancing Autonomous Vehicles: An Experimental Analysis of Path Planning and Decision-Making Processes through Simulink-Based Architecture
 Morgado, C Gonçalves… - 2023 IEEE 17th …, 2023 - ieeexplore.ieee.org
The development of autonomous vehicles has been a rapidly growing field, with increasing
interest in the technology and its potential applications. However, there are currently no …
interest in the technology and its potential applications. However, there are currently no …