Public acceptance of driver state monitoring for automated vehicles: Applying the UTAUT framework
Driver state monitoring (DSM) systems aim to measure driver/occupant state, considering
factors such as fatigue, workload, attentiveness, and wellbeing. They are influential for some …
factors such as fatigue, workload, attentiveness, and wellbeing. They are influential for some …
A survey on datasets for the decision making of autonomous vehicles
Autonomous vehicles (AVs) are expected to reshape future transportation systems, and
decision making is one of the critical modules toward high-level automated driving. To …
decision making is one of the critical modules toward high-level automated driving. To …
Knowledge engineering using large language models
Knowledge engineering is a discipline that focuses on the creation and maintenance of
processes that generate and apply knowledge. Traditionally, knowledge engineering …
processes that generate and apply knowledge. Traditionally, knowledge engineering …
Combining reinforcement learning with rule-based controllers for transparent and general decision-making in autonomous driving
The design of high-level decision-making systems is a topical problem in the field of
autonomous driving. In this paper, we combine traditional rule-based strategies and …
autonomous driving. In this paper, we combine traditional rule-based strategies and …
A survey on image enhancement for Low-light images
In real scenes, due to the problems of low light and unsuitable views, the images often
exhibit a variety of degradations, such as low contrast, color distortion, and noise. These …
exhibit a variety of degradations, such as low contrast, color distortion, and noise. These …
[HTML][HTML] Path planning algorithms in the autonomous driving system: A comprehensive review
This comprehensive review focuses on the Autonomous Driving System (ADS), which aims
to reduce human errors that are the reason for about 95% of car accidents. The ADS …
to reduce human errors that are the reason for about 95% of car accidents. The ADS …
Vehicle trajectory prediction considering aleatoric uncertainty
Trajectory prediction is imperative in the operation of autonomous vehicles because it aids
in understanding the surrounding environment through perception fusion of multiple sensors …
in understanding the surrounding environment through perception fusion of multiple sensors …
Toward autonomous vehicles and machinery in mill yards of the forest industry: Technologies and proposals for autonomous vehicle operations
The use of autonomous systems at wood processing sites of forest industries can
significantly increase safety, productivity and efficiency by reducing the number of …
significantly increase safety, productivity and efficiency by reducing the number of …
Anomaly detection against GPS spoofing attacks on connected and autonomous vehicles using learning from demonstration
GPS spoofing attacks pose great challenges to connected vehicle (CVs) safety applications
and localization of autonomous vehicles (AVs). In this paper, we propose to utilize …
and localization of autonomous vehicles (AVs). In this paper, we propose to utilize …
Not all neuro-symbolic concepts are created equal: Analysis and mitigation of reasoning shortcuts
Abstract Neuro-Symbolic (NeSy) predictive models hold the promise of improved
compliance with given constraints, systematic generalization, and interpretability, as they …
compliance with given constraints, systematic generalization, and interpretability, as they …