Autonomous Car Technology
What do you mean by autonomous vehicle🤔--
An autonomous vehicle, or a driverless vehicle, is one that is able to operate itself and perform necessary functions without any human intervention, through ability to sense its surroundings. An autonomous vehicle utilises a fully automated driving system in order to allow the vehicle to respond to external conditions that a human driver would manage.
Autonomous cars rely on sensors, actuators, complex algorithms, machine learning systems, and powerful processors to execute software.
Autonomous cars create and maintain a map of their surroundings based on a variety of sensors situated in different parts of the vehicle. Radar sensors monitor the position of nearby vehicles. Video cameras detect traffic lights, read road signs, track other vehicles, and look for pedestrians.
Sophisticated software then processes all this sensory input, plots a path, and sends instructions to the car’s actuators, which control acceleration, braking, and steering.
Levels of automation:
There are six levels of automation to distinguish between partially autonomous to full autonomous vehicles:
Level 0: A human does all the driving without assistance.
* Level 1: Braking and accelerating or steering assist the human driver using an advanced driver assistance system (ADAS).
* Level 2: Braking/accelerating and steering can be controlled autonomously at the same time, though the human must monitor conditions continuously and perform remaining tasks.
* Level 3: The automated driving system (ADS) can perform all driving tasks under certain conditions. The human driver must be ready and able to take back control when requested by the ADS and must perform all tasks when not under optimal conditions.
* Level 4: The ADS performs driving tasks and monitors the environment in certain conditions without the human driver needing to pay attention.
* Level 5: The ADS fully drives the vehicle in all conditions without the need for humans or passengers to pay attention or be involved in driving.
AI technologies power self-driving car systems. Developers of self-driving cars use vast amounts of data from image recognition systems, along with machine learning and neural networks, to build systems that can drive autonomously.
The neural networks identify patterns in the data, which are fed to the machine learning algorithms. That data includes images from cameras on self-driving cars from which the neural network learns to identify traffic lights, trees, curbs, pedestrians, street signs and other parts of any given driving environment.
AI software in the car is connected to all the sensors and collects input from google street view and video cameras inside the car.
The AI simulates human perceptual and decision-making processes using deep learning and controls actions in driver control systems, such as steering and brakes.
There are two main types of autonomous vehicle technologies: self-driving cars and automated trucks.
Self-driving cars rely on sensors, cameras, GPS, and other hardware to navigate roads without human intervention.
Automated trucks are similar, except they operate at high speeds on highways and freeways.
Features of Autonomous cars:
Lane Control - This is the ability to stay safely within the lane, which is achieved by monitoring distances to lane markers, road edges and adjacent vehicles. Some of these systems utilize the global positioning system (GPS) to pinpoint locations.
Adaptive Cruise Control (ACC) - This feature is an enhancement of the common cruise control that maintains a constant speed. ACC, by contrast, is a safety feature, dedicated to maintaining a safe distance from the vehicle ahead.
Automatic Emergency Braking System (AEBS) - This safety feature is essential for fully autonomous vehicles as it automatically stops the vehicle to avoid a collision.
Light Detection and Ranging (LIDAR) - This technology is used for distance determination and object identification. Standalone mountable units are used on drones as well as road vehicles.
Street Sign Recognition - This feature is a software program that is able to process sensor data and identify road signs. Although viable products do exist, this technology will be the subject of research and development for some time to come.
Vehicle-to-Vehicle (V2V) Communication - This feature is at the heart of a connected-vehicle technology where vehicles work together to improve the safety of the roadway system, including the vehicles on it.
Object or Collision Avoidance System (CAS) - An object avoidance system typically integrates multiple features, such as object detection or identification and AEBS to avoid a collision.
Top Autonomous Vehicles Companies to Watch in 2023
Advantages of autonomous vehicles
360° vision. Thanks to high-precision technology, autonomous vehicles possess the ability to view the environment in a 360° range, twice as much as humans, who have a viewing angle of only 180° horizontally.
Reduced accidents. Thanks to 360° vision and vehicles being interconnected with each other and in constant communication, accidents will be significantly reduced. Although (at least initially) accidents will not be reduced to zero, they will be much less than accidents caused by human driving.
Higher traffic efficiency. Although it is estimated that their speed in big cities will be lower, their traffic efficiency will be higher.
Access to the disabled and people with reduced mobility. Thanks to the fact that the automobile will be autonomous and will require practically no human interaction for its operation, even people with visual or hearing disabilities will be able to have one, i.e., they will become inclusive.
Sustainable vehicles. It is expected that these vehicles will operate based on clean energy, so carbon and greenhouse gas emissions will be practically zero.
Disadvantages of autonomous vehicles
Data protection issues. The first problem that arises, is in that, being connected all the time with the whole environment, it can become a cyber problem of data protection. Even the correct handling of road networks can be compromised.
High cost of implementation. Autonomous vehicle infrastructure revolves around 5G network coverage, which is still expensive, so it may take governments considerable time to invest in sufficient infrastructure for optimal performance of autonomous vehicles.
High cost of vehicles. Although significant progress has been made in reducing the cost of producing their implements, these cuts are not low enough to make them a financially viable alternative for the average family. It will be some years before they become an everyday reality within the reach of the middle class.
As technology expands throughout the world, self-driving cars will become the future mode of transportation universally.The increasing use of computer technology in transportation will provide us with much greater levels of safety and reliability