Self Driving Cars Tutorials
An Introduction to Self-Driving Car
A self-driving car is a vehicle that travels between locations without the assistance of a human operator, using a mix of sensors, cameras, radar, and artificial intelligence (AI).
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Machine Learning Algorithms and Techniques in Self-Driving Cars
Self-driving automobiles are made feasible by computer vision and deep learning algorithms. They enable an automobile to acquire data from cameras and other sensors about its surroundings, analyze it, and decide what actions to take.
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Localization for Self-Driving Cars
Localization is one of the most important capabilities for self-driving cars, making it possible to detect their exact location within centimeters inside a map.
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Perception for Self-Driving Cars
The capacity of an autonomous system to gather information and extract useful knowledge from its surroundings is referred to as perception.
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Hardware and Software Architecture of Self-Driving Cars
Engineers are considering using more sophisticated sensors and technology for software and hardware technology in self-driving cars to make it better day by day.
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Sensor Fusion for Self-Driving Car
Self-driving cars need sensors such as cameras and radar in order to ‘see’ the world around them. But sensor data alone isn’t enough. Autonomous vehicles also need computing power and advanced machine intelligence.
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Self-Driving Car Path Prediction and Routing
Self-driving vehicles often take different routes than human drivers would, even when driving to the same destination to reach faster and safer.
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Self-Driving Car Decision-Making and Control System
Decision-making is an important part of self-driving technology. The decision-making module plans suitable driving behaviors based on the information supplied by the environment perception module and sends them to the motion control module.
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Cloud Platform for Self-Driving Cars
Cars may interact with one another through the cloud to avoid accidents and update traffic information and maps.
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Dynamic Modeling of Self-Driving Car
Self-driving car dynamic modeling is how the vehicle performs and reacts dynamically through the input of the autonomous system.
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Safety of Self-Driving Cars
Self-driving cars and driver assistance systems have the potential to decrease collisions, prevent injuries, and save lives.
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Testing Methods for Self-Driving System
Self-driving systems are becoming increasingly complex and must be tested effectively before deployment.
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Operating Systems of Self-Driving Cars
An operating system is the brain of a system. An operating system of a self-driving car makes it intelligent to operate itself without any help from a driver.
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Training a YOLOv8 Model for Traffic Light Detection
Learn to train a YOLOv8 model for traffic light detection in self-driving cars. This tutorial covers setup, training, validation & testing on images and videos.
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Deployment of Self-Driving Cars
The transportation system is about to be revolutionized by self-driving cars. Hundreds of companies all around the world have been working on autonomous driving.
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