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Uncertainty-Aware Model-Based Offline Reinforcement Learning for Automated Driving
IEEE Robotics and Automation Letters, 2023Offline reinforcement learning (RL) provides a framework for learning decision-making from offline data and therefore constitutes a promising approach for real-world applications such as automated driving (AD). Especially in safety-critical applications,
Christopher Diehl +4 more
semanticscholar +1 more source
Operational Design Domain for Automated Driving Systems: Taxonomy Definition and Application
2023 IEEE Intelligent Vehicles Symposium (IV), 2023To allow the large-scale deployment of automated and connected vehicles, their safety must be ensured. The Operational Design Domain (ODD) aims to define under which conditions an Automated Driving System (ADS) can operate safely: speed, type of road ...
Léo Mendiboure +5 more
semanticscholar +1 more source
International journal of human computer interactions, 2023
Human-machine co-driving presents a significant hurdle in automated driving system. The takeover process in automated driving system involves complex human factors, failure to takeover the vehicle and control driving behavior during the takeover process ...
Zhen-Dong Wu +5 more
semanticscholar +1 more source
Human-machine co-driving presents a significant hurdle in automated driving system. The takeover process in automated driving system involves complex human factors, failure to takeover the vehicle and control driving behavior during the takeover process ...
Zhen-Dong Wu +5 more
semanticscholar +1 more source
IEEE Sensors Journal, 2023
The recent proliferation of sensing and computing technologies has promoted the rapid development of automated driving. A series of automated driving systems are consecutively released by manufactures in recent years. These systems at different automated
Tian-Chuang Meng +4 more
semanticscholar +1 more source
The recent proliferation of sensing and computing technologies has promoted the rapid development of automated driving. A series of automated driving systems are consecutively released by manufactures in recent years. These systems at different automated
Tian-Chuang Meng +4 more
semanticscholar +1 more source
Roadside Infrastructure Support for Urban Automated Driving
IEEE transactions on intelligent transportation systems (Print), 2023Automated driving offers excellent opportunities for ecology, economy as well as society. Especially in urban intersections, there is a considerable margin for benefits in these sectors. This work takes a structured simulation approach to find answers on
Mathias Pechinger +3 more
semanticscholar +1 more source
IEEE Transactions on Intelligent Vehicles, 2023
Automated vehicles offer various benefits for private transport. Besides an increase in road safety and driving comfort, higher levels of automated driving provide the opportunity to perform non-driving related tasks and to save time.
Johannes Ossig +3 more
semanticscholar +1 more source
Automated vehicles offer various benefits for private transport. Besides an increase in road safety and driving comfort, higher levels of automated driving provide the opportunity to perform non-driving related tasks and to save time.
Johannes Ossig +3 more
semanticscholar +1 more source
Accident Analysis and Prevention, 2023
Existing studies identified targeted audiences showing increases in Automated Vehicles (AV) acceptance after experiencing automated driving. However, there is still uncertainty regarding the reasons.
Song Wang +4 more
semanticscholar +1 more source
Existing studies identified targeted audiences showing increases in Automated Vehicles (AV) acceptance after experiencing automated driving. However, there is still uncertainty regarding the reasons.
Song Wang +4 more
semanticscholar +1 more source
Transportation Research Part C: Emerging Technologies, 2021
The last decade witnessed a great development of automated driving vehicles (ADVs) and vehicle intelligence. The significant increment of machine intelligence poses a new challenge to the community, which is the collaboration between human drivers and ...
Xing Yang +3 more
semanticscholar +1 more source
The last decade witnessed a great development of automated driving vehicles (ADVs) and vehicle intelligence. The significant increment of machine intelligence poses a new challenge to the community, which is the collaboration between human drivers and ...
Xing Yang +3 more
semanticscholar +1 more source
Accident Analysis and Prevention, 2021
Automated driving systems are becoming increasingly prevalent throughout society. In conditionally automated vehicles, drivers may engage in non-driving-related tasks (NDRTs), which can negatively affect their situation awareness (SA) and preparedness to
Nade Liang +7 more
semanticscholar +1 more source
Automated driving systems are becoming increasingly prevalent throughout society. In conditionally automated vehicles, drivers may engage in non-driving-related tasks (NDRTs), which can negatively affect their situation awareness (SA) and preparedness to
Nade Liang +7 more
semanticscholar +1 more source
Automated Evaluation of Large Vision-Language Models on Self-Driving Corner Cases
IEEE Workshop/Winter Conference on Applications of Computer VisionLarge Vision-Language Models (LVLMs) have received widespread attentions for advancing the interpretable self-driving. Existing evaluations of LVLMs primarily focus on multi-faceted capabilities in natural circumstances, lacking automated and ...
Kai Chen +12 more
semanticscholar +1 more source