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Establishing an environment that allows for the quantitative evaluation of the ability of autonomous driving systems to respond to real-world adverse conditions is crucial to ensuring their safety and reliability. This study proposes a dynamic scenario-based simulation framework that simulates complex and sequential hazardous scenarios frequently encountered in actual road environments. The proposed scenarios are…

Mobility is a fundamental human desire. All societies aspire to safe and efficient mobility at low ecological and economic costs. ADAS systems (Advanced Driver Assistance Systems) are safety systems designed to eliminate human error in driving vehicles of all types. ADAS systems such as Radars use advanced technologies to assist the driver while driving and…

Compared to other types of autonomous vehicles, the single-seat is the simplest when designing, since its compact design makes it an option that can simplify different mechanical aspects and enhance those of greater importance such as the steering and the braking system. Likewise, the electronic and electrical design may be a great improvement on the…

Many recent studies on autonomous driving have focused on model-based control. A number of studies has addressed that simple models such as the Kinematic Bicycle Model are easier to design controls for autonomous driving systems. However, such a simple vehicle model has a weakness in that it is subject to modeling errors. This is because…

Haze removal is an extremely challenging task, and object detection in the hazy environment has recently gained much attention due to the popularity of autonomous driving and traffic surveillance. In this work, the authors propose a multiple linear regression haze removal model based on a widely adopted dehazing algorithm named Dark Channel Prior. Training this…

The paper treats a problem for detection and recognition objects in computer vision sector, where researchers recommended OpenCV software and development tool, it’s several and better-remembered library resource for isolating, detecting, and recognition of particular objects, what we would find an appropriate system for detecting and recognition traffic roads signs. The robustness with optimization is…

Computer Vision is a domain which deals with the challenge of enabling technology with vision capabilities. This goal is accomplished with the use of Convolutional Neural Networks. They are the backbone of implementing vision applications on embedded systems. They are complex but highly efficient in extracting features, thus, enabling embedded systems to perform computer vision…