Existing research on human-automated vehicle (AV) interactions has largely focused on auditory explanations, with less attention to how voice characteristics shape user trust. This paper explores the influence of gender similarity between users and A...
BACKGROUND:  Given the high prevalence of hearing loss among truck drivers, using artificial neural networks (ANNs) to predict and detect contributing factors early can aid managers significantly.
Existing research on decision-making of autonomous vehicles (AVs) has mainly focused on normal road sections, with limited exploration of decision-making in complex traffic environments without lane markings. Taking toll plaza diverging area as an ex...
Left-turn slip lanes, also known as channelised right-turn lanes in right-hand driving countries, are widely implemented to facilitate left-turning at signalised intersections. However, pedestrian safety on slip lanes is not well known. At unsignalis...
Driver fatigue is a significant factor contributing to road accidents, highlighting the need for precise and reliable detection systems. This study introduces a comprehensive approach using multimodal neural networks, leveraging the DROZY dataset, wh...
Studies in health technology and informatics
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Identifying driver inattention is crucial for road safety, driver well-being and can be enhanced using multimodal physiological signals. However, effective fusion of multimodal data is highly challenging, particularly with intermediate fusion, where ...
Driver fatigue is one of the most common causes of road accidents, which means that there is a great need for robust and adaptive monitoring systems. Current models of fatigue detection suffer from domain-specific limitations in generalizing across d...
Driver fatigue is one of the major causes of traffic accidents, particularly for drivers of large vehicles, who are more susceptible to fatigue due to prolonged driving hours and monotonous conditions during their journeys. Existing vision-based driv...
Lane detection plays a crucial role in autonomous driving systems by enabling vehicles to comprehend road structure and ensure safe navigation. However, the current performance of lane line detection models, such as CCNet, exhibits limitations in han...
Target detection is an essential direction in artificial intelligence development, and it is a crucial step in realizing environmental awareness for intelligent vehicles and advanced driver assistance systems. However, the current target detection al...