Applications of explainable AI for 6G: Technical aspects, use cases, and research challenges
When 5G began its commercialisation journey around 2020, the discussion on the vision of
6G also surfaced. Researchers expect 6G to have higher bandwidth, coverage, reliability …
6G also surfaced. Researchers expect 6G to have higher bandwidth, coverage, reliability …
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 …
Robust lane change decision making for autonomous vehicles: An observation adversarial reinforcement learning approach
Reinforcementlearning holds the promise of allowing autonomous vehicles to learn complex
decision making behaviors through interacting with other traffic participants. However, many …
decision making behaviors through interacting with other traffic participants. However, many …
A progressive review: Emerging technologies for ADAS driven solutions
J Nidamanuri, C Nibhanupudi, R Assfalg… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Over the last decade, the Advanced Driver Assistance System (ADAS) concept has evolved
significantly. ADAS involves several technologies such as automotive electronics, vehicle-to …
significantly. ADAS involves several technologies such as automotive electronics, vehicle-to …
Towards robust decision-making for autonomous driving on highway
Reinforcement learning (RL) methods are commonly regarded as effective solutions for
designing intelligent driving policies. Nonetheless, even if the RL policy is converged after …
designing intelligent driving policies. Nonetheless, even if the RL policy is converged after …
Robust decision making for autonomous vehicles at highway on-ramps: A constrained adversarial reinforcement learning approach
Reinforcement learning has demonstrated its potential in a series of challenging domains.
However, many real-world decision making tasks involve unpredictable environmental …
However, many real-world decision making tasks involve unpredictable environmental …
Highway decision-making and motion planning for autonomous driving via soft actor-critic
In this study, a decision-making and motion planning controller with continuous action space
is constructed in the highway driving scenario based on deep reinforcement learning. In the …
is constructed in the highway driving scenario based on deep reinforcement learning. In the …
A survey of driving safety with sensing, vehicular communications, and artificial intelligence-based collision avoidance
Accurately discovering hazards and issuing appropriate warnings to drivers in advance or
performing autonomous control is the core of the Collision Avoidance (CA) system used to …
performing autonomous control is the core of the Collision Avoidance (CA) system used to …
Multiple vehicle cooperation and collision avoidance in automated vehicles: Survey and an AI-enabled conceptual framework
Prospective customers are becoming more concerned about safety and comfort as the
automobile industry swings toward automated vehicles (AVs). A comprehensive evaluation …
automobile industry swings toward automated vehicles (AVs). A comprehensive evaluation …
A selective federated reinforcement learning strategy for autonomous driving
Currently, the complex traffic environment challenges the fast and accurate response of a
connected autonomous vehicle (CAV). More importantly, it is difficult for different CAVs to …
connected autonomous vehicle (CAV). More importantly, it is difficult for different CAVs to …