Jointly dampening traffic oscillations and improving energy consumption with electric, connected and automated vehicles: A reinforcement learning based approach
It has been well recognized that human driver's limits, heterogeneity, and selfishness
substantially compromise the performance of our urban transport systems. In recent years, in …
substantially compromise the performance of our urban transport systems. In recent years, in …
基于改进遗传算法的移动机器人路径规划
魏彤， 龙琛 - 北京航空航天大学学报, 2020 - bhxb.buaa.edu.cn
路径规划是实现移动机器人自主导航的关键技术. 针对常规路径规划算法求解的路径长度非最短
以及在前后两次规划过程中规划路径不连贯的问题, 提出一种基于改进遗传算法的帧间关联平稳 …
以及在前后两次规划过程中规划路径不连贯的问题, 提出一种基于改进遗传算法的帧间关联平稳 …
Driving in dense traffic with model-free reinforcement learning
Traditional planning and control methods could fail to find a feasible trajectory for an
autonomous vehicle to execute amongst dense traffic on roads. This is because the obstacle …
autonomous vehicle to execute amongst dense traffic on roads. This is because the obstacle …
Learning from naturalistic driving data for human-like autonomous highway driving
Driving in a human-like manner is important for an autonomous vehicle to be a smart and
predictable traffic participant. To achieve this goal, parameters of the motion planning …
predictable traffic participant. To achieve this goal, parameters of the motion planning …
A hierarchical control system for autonomous driving towards urban challenges
ND Van, M Sualeh, D Kim, GW Kim - Applied Sciences, 2020 - mdpi.com
In recent years, the self-driving car technologies have been developed with many successful
stories in both academia and industry. The challenge for autonomous vehicles is the …
stories in both academia and industry. The challenge for autonomous vehicles is the …
Path planning of mobile robot based on improved genetic algorithm
Y Li, Z Huang, Y Xie - 2020 3rd International Conference on …, 2020 - ieeexplore.ieee.org
In order to solve the problems of slow convergence speed and avoid local optimum in the
path planning of mobile robot, the basic genetic algorithm was improved and a method for …
path planning of mobile robot, the basic genetic algorithm was improved and a method for …
Planning the trajectory of an autonomous wheel loader and tracking its trajectory via adaptive model predictive control
J Shi, D Sun, D Qin, M Hu, Y Kan, K Ma… - Robotics and Autonomous …, 2020 - Elsevier
In a typical operation mode, a wheel loader frequently accelerates and decelerates, and the
curvature of the driving path is inconsistent. In the past, autonomous vehicle trajectory …
curvature of the driving path is inconsistent. In the past, autonomous vehicle trajectory …
Interaction-aware kalman neural networks for trajectory prediction
Forecasting the motion of surrounding obstacles (vehicles, bicycles, pedestrians and etc.)
benefits the on-road motion planning for intelligent and autonomous vehicles. Complex …
benefits the on-road motion planning for intelligent and autonomous vehicles. Complex …
Multi-model-based local path planning methodology for autonomous driving: An integrated framework
Autonomous driving systems (ADSs) need to be able to respond quickly to changes in the
dynamic traffic scenario. However, regardless of the changes occurring in traffic scenes, the …
dynamic traffic scenario. However, regardless of the changes occurring in traffic scenes, the …
Dynamically constrained motion planning networks for non-holonomic robots
JJ Johnson, L Li, F Liu, AH Qureshi… - 2020 IEEE/RSJ …, 2020 - ieeexplore.ieee.org
Reliable real-time planning for robots is essential in today's rapidly expanding automated
ecosystem. In such environments, traditional methods that plan by relaxing constraints …
ecosystem. In such environments, traditional methods that plan by relaxing constraints …