A self-driving car or autonomous vehicle is a car that moves on its own on the road using a combination of software, hardware, and machine learning. Self-driving cars are developed to maneuver obstacles and various road conditions, even weather conditions, by the analysis of real-time data. They say that self-driving cars are the cars of the future. Let’s get to know what this technology is and how safe it is, especially when you meet one soon on the open road.
There Are 5 Levels Of Automation
In 2014, SAE International outlined 5 levels of autonomous vehicles. Their goal was to create a common point of reference in the independent vehicle industry. Each of the levels is dependent on the vehicle's level of automation, and the degree of human development is needed.
Level 0 means there’s no automation; level 1 means the vehicle is capable of self-driving, but the operation still requires some assistance of a driver. In level 2, there is partial automation, while level 3 vehicles have conditional automation, which means the driver can take the wheel if necessary. In level 4, the car is highly-automated, while level 5 means the driver is no longer needed, and there's full automation.
Some Technologies Behind Self-Driving Vehicles
Self-driving technologies are based on how the car interfaces with its surroundings. This is a combination of software, hardware, and machine learning to create a car that is at least level 3 or higher. Self-driving cars employ different systems, such as radar, lidar, and computer vision. Cars use radar to identify the presence, speed, and direction of other objects while lidar finds the accurate depth and perception information with the aid of lasers. Meanwhile, camera computer vision systems train the car to recognize the surroundings.
Self-driving cars also use microphones to get audio information, including emergency sirens. Finally, these cars also use online information like maps, traffic, weather conditions, and nearby vehicles.
Software Behind Self-Driving Cars
Self-driving cars use algorithms according to complicated matrices that are made to recognize patterns while driving. These algorithms are trained using data to become more effective in analyzing situations and based on their decisions. Just some of the algorithms used are regression algorithm, decision-making algorithm, pattern recognition algorithm, and clustering algorithm.
Possible Issues Of Self-Driving Cars
Experts say that the potential point of failure of self-driving cars is in the vehicle's software. Potential problems pertaining to software are poor prediction of other agents on the road, inadequate understanding of the perception of complexity, and threats to cybersecurity.
Self-driving cars are the future, but driver and vehicle safety and public safety have to be addressed first.
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