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Fleets of autonomous vehicles can mitigate traffic congestion through simple actions, thus improving many socioeconomic factors such as commute times and gas costs. However, these approaches are limited in practice as they assume precise control over ...

Lane detection, which relies on front-view RGB cameras, is a crucial aspect of Advanced Driver Assistance Systems (ADAS), but its effectiveness is notably reduced in low-light conditions. This issue is exacerbated by the lack of specialized ...

• A new nighttime lane detection dataset is introduced.
• A novel low-light enhancement method with attention fusion is developed.
• A real-time and robust lane detection framework is designed.
• An embedded lane detection ...

As Advanced Driver-Assistance Systems (ADAS) pave the way for autonomous vehicles, they also improve safety by decreasing the risk of hazardous events. Essential for ADAS, lane detection ensures that vehicles stay on their intended path and ...

White matter hyperintensity (WMH) is a common feature of brain aging, often linked with cognitive decline and dementia. This study aimed to employ deep learning and radiomics to develop models for detecting cognitive impairment in WMH ...

• The LR model based on white matter features of MRI could be used to detect cognitive impairment in WMH patients with high accuracy.
• The WMH was recognized and segmented automatically by our artificial intelligence system.
• The ...

Big data, AI, and machine learning have ushered in a transformative era in computer processing and application. AI's capacity to emulate human cognition spans a spectrum of industries, from rudimentary tasks to intricate decision-making ...

As many as 4,601 people were injured or killed on the roads in Norway in 2022. This number is too high and highlights the necessity of putting road safety on the agenda. The car industry today is represented by a vast increase in advanced ...

Research on autonomous vehicles has been at a peak recently. One of the most researched aspects is the performance degradation of sensors in harsh weather conditions such as rain, snow, fog, and hail. This work addresses this performance ...

The role played by emotions and attention is crucial for the development of advanced driver assistance systems that improve safety by flexibly adapting to the current state of the driver. In the present study, we used immersive virtual reality as ...

This research project, conducted within a PhD program in Engineering Sciences at the Autonomous University of Zacatecas, Mexico, aims to develop and validate a multimodal model for emotion recognition in drivers using convolutional neural networks. The ...

Connectivity is a key element enabling intelligent vehicles to communicate with each other and the Smart Road. In general, the connectivity is allowed by an On‐Board Unit enabling the Vehicle to Everything communication. This paper proposes an ...

Connected and automated vehicles will characterize the future of the mobility, featured by Smart Roads and Internet of Things technologies. Vehicles will behave as mobile nodes of a network enabling communication between them and with respect to ...

Advanced driving assistance systems are a useful technology that helps improve driving safety. These systems provide the driver with multi-modal information about the driving performance, however, the interaction between the driver and these interfaces ...

The ability of Advanced Driving Assistance Systems (ADAS) is to identify and understand all objects around the vehicle under varying driving conditions and environmental factors is critical. Today’s vehicles are equipped with advanced driving ...

Log-based anomaly detection is important for improving the reliability and availability of software systems, especially those evolving using DevOps, owing to the huge number of logs generated during continuous practices. However, ...

Drivable area detection is an important component of various levels of autonomous driving starting from advanced driver assistance systems (ADAS) to fully automated vehicles. A drivable area detection system detects the road segment in front of ...

Deep neural networks have been established by researchers to perform significantly better than prior algorithms in multiple domains, notably in computer vision. Naturally, this resulted in its deployment as a perception module in modern Autonomous ...

Recent advances in state-of-the-art camera-based AI mechanisms in the automated driving field have leveraged great progress in the installation and widespread use of this technology along the recent years. However, vehicles with automated driving ...

Availability of realistic driver models, also able to represent various driving styles, is key to add traffic in serious games on automotive driving. We propose a new architecture for behavioural planning of vehicles, that decide their motion ...

We introduce 2D blind spot estimation as a critical visual task for road scene understanding. By automatically detecting road regions that are occluded from the vehicle’s vantage point, we can proactively alert a manual driver or a self-driving ...

We present a new on-road driving dataset, called “Look Both Ways”, which contains synchronized video of both driver faces and the forward road scene, along with ground truth gaze data registered from eye tracking glasses worn by the drivers. Our ...