A survey of deep learning applications to autonomous vehicle control

S Kuutti, R Bowden, Y Jin, P Barber… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Designing a controller for autonomous vehicles capable of providing adequate performance
in all driving scenarios is challenging due to the highly complex environment and inability to …

A review of motion planning for highway autonomous driving

L Claussmann, M Revilloud, D Gruyer… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Self-driving vehicles will soon be a reality, as main automotive companies have announced
that they will sell their driving automation modes in the 2020s. This technology raises …

A survey on trajectory-prediction methods for autonomous driving

Y Huang, J Du, Z Yang, Z Zhou… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In order to drive safely in a dynamic environment, autonomous vehicles should be able to
predict the future states of traffic participants nearby, especially surrounding vehicles, similar …

Waymax: An accelerated, data-driven simulator for large-scale autonomous driving research

C Gulino, J Fu, W Luo, G Tucker… - Advances in …, 2024 - proceedings.neurips.cc
Simulation is an essential tool to develop and benchmark autonomous vehicle planning
software in a safe and cost-effective manner. However, realistic simulation requires accurate …

Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness

G Li, Y Yang, S Li, X Qu, N Lyu, SE Li - Transportation research part C …, 2022 - Elsevier
Driving safety is the most important element that needs to be considered for autonomous
vehicles (AVs). To ensure driving safety, we proposed a lane change decision-making …

Deep reinforcement learning for autonomous driving: A survey

BR Kiran, I Sobh, V Talpaert, P Mannion… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
With the development of deep representation learning, the domain of reinforcement learning
(RL) has become a powerful learning framework now capable of learning complex policies …

Milestones in autonomous driving and intelligent vehicles—Part I: Control, computing system design, communication, HD map, testing, and human behaviors

L Chen, Y Li, C Huang, Y Xing, D Tian… - … on Systems, Man …, 2023 - ieeexplore.ieee.org
Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace
due to the convenience, safety, and economic benefits. Although a number of surveys have …

Survey of deep reinforcement learning for motion planning of autonomous vehicles

S Aradi - IEEE Transactions on Intelligent Transportation …, 2020 - ieeexplore.ieee.org
Academic research in the field of autonomous vehicles has reached high popularity in
recent years related to several topics as sensor technologies, V2X communications, safety …

A systematic survey of control techniques and applications in connected and automated vehicles

W Liu, M Hua, Z Deng, Z Meng, Y Huang… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …

[HTML][HTML] Automated vehicle-involved traffic flow studies: A survey of assumptions, models, speculations, and perspectives

H Yu, R Jiang, Z He, Z Zheng, L Li, R Liu… - … research part C: emerging …, 2021 - Elsevier
Automated vehicles (AVs) are widely considered to play a crucial role in future transportation
systems because of their speculated capabilities in improving road safety, saving energy …