Vision-based autonomous vehicle systems based on deep learning: A systematic literature review
In the past decade, autonomous vehicle systems (AVS) have advanced at an exponential
rate, particularly due to improvements in artificial intelligence, which have had a significant …
rate, particularly due to improvements in artificial intelligence, which have had a significant …
Decision making of autonomous vehicles in lane change scenarios: Deep reinforcement learning approaches with risk awareness
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 …
vehicles (AVs). To ensure driving safety, we proposed a lane change decision-making …
Remote sensing data fusion techniques, autonomous vehicle driving perception algorithms, and mobility simulation tools in smart transportation systems
T Kliestik, H Musa, V Machova, L Rice - Contemporary Readings in Law …, 2022 - ceeol.com
The objective of this paper is to systematically review remote sensing data fusion
techniques, autonomous vehicle driving perception algorithms, and mobility simulation tools …
techniques, autonomous vehicle driving perception algorithms, and mobility simulation tools …
Lane change strategies for autonomous vehicles: a deep reinforcement learning approach based on transformer
End-to-end approaches are one of the most promising solutions for autonomous vehicles
(AVs) decision-making. However, the deployment of these technologies is usually …
(AVs) decision-making. However, the deployment of these technologies is usually …
Driving conflict resolution of autonomous vehicles at unsignalized intersections: A differential game approach
Considering personalized driving preferences, a new decision-making framework is
developed using a differential game approach to resolve the driving conflicts of autonomous …
developed using a differential game approach to resolve the driving conflicts of autonomous …
Intention prediction and mixed strategy nash equilibrium-based decision-making framework for autonomous driving in uncontrolled intersection
J Nan, W Deng, B Zheng - IEEE Transactions on Vehicular …, 2022 - ieeexplore.ieee.org
Decision-making in uncontrolled intersection is one of the main challenges in urban
autonomous driving. This paper proposed a new decision-making framework in uncontrolled …
autonomous driving. This paper proposed a new decision-making framework in uncontrolled …
Learning automated driving in complex intersection scenarios based on camera sensors: A deep reinforcement learning approach
Making proper decisions at intersections that are one of the most dangerous and
sophisticated driving scenarios is full of challenges, especially for autonomous vehicles …
sophisticated driving scenarios is full of challenges, especially for autonomous vehicles …
Joint optimization for autonomous intersection management and trajectory smoothing design with connected automated vehicles
Trajectory smoothing design (TSD) may significantly reduce fuel consumption and improve
driving comfort at intersections. In this paper, a mixed integer linear programming (MILP) …
driving comfort at intersections. In this paper, a mixed integer linear programming (MILP) …
Recent advances in reinforcement learning-based autonomous driving behavior planning: A survey
Autonomous driving (AD) holds the potential to revolutionize transportation efficiency, but its
success hinges on robust behavior planning (BP) mechanisms. Reinforcement learning (RL) …
success hinges on robust behavior planning (BP) mechanisms. Reinforcement learning (RL) …
Motion planning and object recognition algorithms, vehicle navigation and collision avoidance technologies, and geospatial data visualization in network connectivity …
V Konecny, M Jaśkiewicz, S Downs - Contemporary Readings in Law …, 2022 - ceeol.com
This article reviews and advances existing literature concerning motion planning and object
recognition algorithms, vehicle navigation and collision avoidance technologies, and …
recognition algorithms, vehicle navigation and collision avoidance technologies, and …