Social interactions for autonomous driving: A review and perspectives
No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …
their goals in social traffic scenes. A rational human driver can interact with other road users …
Verification and validation methods for decision-making and planning of automated vehicles: A review
Verification and validation (V&V) hold a significant position in the research and development
of automated vehicles (AVs). Current literature indicates that different V&V techniques have …
of automated vehicles (AVs). Current literature indicates that different V&V techniques have …
A survey on autonomous vehicle control in the era of mixed-autonomy: From physics-based to AI-guided driving policy learning
This paper serves as an introduction and overview of the potentially useful models and
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
methodologies from artificial intelligence (AI) into the field of transportation engineering for …
Artificial intelligence for safety-critical systems in industrial and transportation domains: A survey
Artificial Intelligence (AI) can enable the development of next-generation autonomous safety-
critical systems in which Machine Learning (ML) algorithms learn optimized and safe …
critical systems in which Machine Learning (ML) algorithms learn optimized and safe …
Driver behavior modeling toward autonomous vehicles: Comprehensive review
Driver behavior models have been used as input to self-coaching, accident prevention
studies, and develo** driver-assisting systems. In recent years, driver behavior …
studies, and develo** driver-assisting systems. In recent years, driver behavior …
Joint task offloading and resource optimization in noma-based vehicular edge computing: A game-theoretic drl approach
Vehicular edge computing (VEC) becomes a promising paradigm for the development of
emerging intelligent transportation systems. Nevertheless, the limited resources and …
emerging intelligent transportation systems. Nevertheless, the limited resources and …
Simulation of vehicle interaction behavior in merging scenarios: A deep maximum entropy-inverse reinforcement learning method combined with game theory
W Li, F Qiu, L Li, Y Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Simulation testing based on virtual scenarios can improve the efficiency of safety testing for
high-level autonomous vehicles (AVs). In most traffic scenarios, such as merging scenarios …
high-level autonomous vehicles (AVs). In most traffic scenarios, such as merging scenarios …
A three-level game-theoretic decision-making framework for autonomous vehicles
In this paper, a three-level decision-making framework is developed to generate safe and
effective decisions for autonomous vehicles (AVs). A key component in this decision …
effective decisions for autonomous vehicles (AVs). A key component in this decision …
Comprehensive safety evaluation of highly automated vehicles at the roundabout scenario
A highly automated vehicle (HAV) is a safety-critical system. Therefore, a verification and
validation (V&V) process that rigorously evaluates the safety of HAVs is necessary before …
validation (V&V) process that rigorously evaluates the safety of HAVs is necessary before …
A hybrid deep reinforcement learning and optimal control architecture for autonomous highway driving
Autonomous vehicles in highway driving scenarios are expected to become a reality in the
next few years. Decision-making and motion planning algorithms, which allow autonomous …
next few years. Decision-making and motion planning algorithms, which allow autonomous …