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Computer Vision In Self-Driving Vehicles


Computer vision is one of the most compelling AI tools which has revolutionised various industry sectors worldwide. Decades ago, computer vision was just a fictional notion. But over the past few years, the development of new algorithms, deep learning, Artificial Intelligence (AI), and powerful hardware has given a boost to computers and computing power like never before. 


Computer vision is a powerful tool in computer science that has also led to major breakthroughs in the automobile sector. With the use of an artificial neural network, computer vision mimics the human vision system and performs pattern recognition. With this, computers can easily differentiate and interpret data which is in the form of images or videos. 


The Various Aspects of Technology in Computer Vision

For its applications in self-driving vehicles, the working of computer vision and its data interpretation needs to be accurate and reliable. In order to ensure the precise perception of reality by computer vision technology in self-driving vehicles, the following technologies in combination with other AI systems are used.


·        LIDAR

The Lighting Detection And Radar technology uses lasers instead of radio waves. It gives quick and reliable real-time information regarding the distance and position of any item or obstacle on the path of the self-driving vehicle.

·        Cameras

The use of cameras is well established in the automotive industry. It enhances image recognition and provides better judgement as the data obtained is from a wide range. 

·        Radars

Radars are commonly used in automobiles and give accurate information regarding distance and position.

·        Ultrasonic radars

These function similar to radars. They involve the use of ultrasounds and are specially used as sensors, such as parking sensors in cars and other vehicles. 



The Use of Computer Vision in Self-driving Vehicles

Self-driving vehicles incorporate various radars, cameras, sensors, computer vision, and other AI systems for operating without human intervention. Computer vision can in fact help in analysing various situations and obstacles such as barriers, road blockers, and signboards, thereby increasing passenger safety. Its features such as driving in low light mode, detection of lanes, creation of 3D maps, deployment of airbags, and most importantly, recognising objects while driving are important for the creation of next-gen vehicles. 


Recent Updates Regarding Self-driving Vehicles

On the 29th of August 2022, WEY, owned by GWM revealed its Mocca DHT-PHEV Edition. Its technology functions using computer vision rather than using high precision mapping. It is expected to offer better functionality at a lower cost and has enabled the self-driving car to perceive like a human being. Computer vision, along with other systems in the car, is equipped to perform functions such as automatic lane changes, overtaking, lane recognition, and traffic light recognition.



Incorporation of computer vision in next-gen vehicles will definitely enhance the user’s driving experience whilst ensuring utmost safety. There are a few challenges to be addressed before ensuring the smooth sailing of this technology. However, with the rigour and pace at which the AI and machine learning sectors are progressing, we will soon be seeing self-driving cars on the roads in numbers.