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What are the Different Levels of Vehicle Automation?

If you want to know the different levels of vehicle automation, you have come to the right place as we will provide you with everything you need to know about the different levels of autonomous vehicles. Also, this post will provide you with various examples of the different levels of automation. 

What are the Different Levels of Vehicle Automation?

Image Source: SAE International

1. What is Level 0 Automation? (No Automation / No Autonomy) 

Most cars on the road fall under Level 0 Automation. That is, such cars may have features such as cruise control that helps drivers maintain a constant speed for long-distance driving, but nothing else. Most cars currently on the road offer this level of automation, which falls under the category of no automation.

2. What is Level 1 Automation? (Driver Assistance) 

At level 1 automation, a vehicle is completely controlled by the driver. However, vehicles that fall under this category are equipped with some advanced driving assistance features. For example, a vehicle that has adaptive cruise control is considered to have level 1 automation. Adaptive cruise control uses sensors and/or cameras to keep a vehicle at a safe distance from the vehicle in front of it. Additionally, lane-keep assist also falls under level 1 automation. Lane-keep assist also uses sensors and/or cameras to keep a vehicle in its lane. So, if you were to veer out of your lane unintendedly, lane keep assist would nudge your vehicle back into your lane. Thus, if you have a vehicle that can assist with steering or accelerating and braking, but not both at the same time, the vehicle is considered to have level 1 automation. Furthermore, features such as park assist are considered as level 1 automation because they only assist the driver and do not automate the process of driving. Level 1 automation is available on many car models currently offered today.

3. What is Level 2 Automation? (Partial Automation)

Level 2 automation, also known as partial automation, applies to vehicles that provide combined automated functions, such as acceleration and steering. At level 2 automation, you’re basically combining adaptive cruise control with some form of steering assist. At this level, the driver is still responsible for driving tasks and must monitor the environment surrounding the vehicle at all times. Simply stated, at this level of automation, the driver can take his feet off the pedals and his hands off of the steering wheel, but he must still pay attention to the environment surrounding the vehicle. This means that a driver cannot set the system to drive and proceed to perform a different task; he must keep his eyes on the road. This level of autonomous driving is great for helping drivers with stop-and-go traffic, making it great for commuters. You can find this level of automation on Tesla Autopilot, Volvo Pilot Assist, GM’s Super-Cruise, and Audi Traffic Jam Assist. There are others, but these are the most well-known examples.

4. What is Level 3 Automation?(Conditional Automation) 

Level 3 automation, also known as conditional automation, is where things get super interesting. At this level, the driver must be in the vehicle, but he is not required to monitor the vehicle at all times while it is driving. So, for example, the driver could command the vehicle to head to a destination and then proceed to browse his or her smartphone. However, at level 3 conditional automation, the driver must be ready to take control over the vehicle with advanced notice. Basically, level 3 autonomous vehicles are capable of transporting passengers from point A to point B with little to no intervention under ideal conditions. That said, some conditions may present themselves, requiring the driver to momentarily intervene in the operation of the vehicle.

5. What is Level 4 Automation? (High Automation) 

Level 4, also known as high automation, is a level of automation where the vehicle is capable of performing all driving functions under certain conditions; however, the driver has the control to take over and control the vehicle. At level 4 automation, a vehicle still requires a driver, but it can take them from point A to point B without any intervention. However, the driver does have the option of intervening. Simply stated, at level 4 automation, the vehicle is capable of performing all driving tasks in most environments and under most conditions, as well as monitor the environment in certain circumstances.

6. What is Level 5 Automation? (Full Automation) 

At level 5 automation, a driver is not required because the vehicle is capable of performing all driving tasks, going as far as eliminating the need for pedals and a steering wheel. This is the highest level of automation where the vehicle basically drives itself, not even requiring a driver in the driver’s seat of the car. 

Benefits of Vehicle Automation 

Now that we’ve discussed the different vehicle automation levels let’s look at the benefits of vehicle automation. 

  • Safety – Automated vehicles are significantly safer than having drivers drive vehicles; therefore, they have the potential to save lives and prevent passengers and pedestrians from being injured as a result of human error. This is so because self-driving cars are better able to identify hazards than people and can react extremely quickly to avoid crashing into other vehicles or pedestrians.


  • Economic Benefits – Since autonomous vehicles have the potential to reduce traffic collisions; society will save a significant amount of money in terms of lost lives, money spent on injuries, and money lost on workplace productivity. Reducing car accidents will save society a significant amount of money, with some estimates estimating the amount of money in the billions of dollars annually.


  • Efficiency – Autonomous vehicles have the ability to communicate with one another, easing the congestion and lowering the number of hours people spend stuck in traffic delays. This saves commuters time on their commutes, saves them money on gas, and reduces the amount of vehicle emissions since commuters will spend less time on the road.


  • Productivity – Autonomous vehicles will increase the productivity of commuters by allowing them to utilize their commute time performing tasks other than driving. On average, commuters spend 200 hours in their vehicles per year. Imagine what you can do with all of that time if you did not have to focus on operating a vehicle. 

How Does Vehicle Automation Take Place? 

For a company to produce an autonomous vehicle, it must develop an algorithm that is capable of analyzing the environment and conditions surrounding a vehicle in order to make decisions that ultimately guide the vehicle. A vehicle observes its surrounding environment by using a variety of cameras, sensors, and other sensory devices to collect information. The data gathered is then used to train deep learning or machine learning models. After the model is trained, its deployed in a vehicle onto a powerful computer that analyzes the sensory information and makes decisions that guide the vehicle.  

For example, autonomous self-driving vehicles use video cameras to detect road signs, traffic lights, other vehicles, and pedestrians. LiDAR bounces light pulses off the vehicle’s surroundings to detect how far away they are from the vehicle. Ultrasonic sensors in the wheels are used to detect curbs, road edges, and other vehicles. All of this data is gathered and used to train AI models to better drive road vehicles. 

Now, let’s focus on the systems that capture and process the data necessary to train machine learning and deep learning models. 

Vehicle Data Acquisition Systems For Autonomous Self-Driving Vehicles and ADAS (Advanced Driver Assistance Systems) 

This section will focus on the data acquisition systems that are used to collect and process the data being generated by the cameras and sensors. Data acquisition systems collect the data so that it can be used by the makers of ADAS (advanced driver assistance systems) and self-driving autonomous vehicles to train the deep learning or machine learning models that will be deployed in vehicles. The more real-world data that an organization has to train its vehicles, the better the vehicles will perform when facing new environments they have never seen before. 

That said, collecting and storing the data generated by self-driving vehicles or vehicles that employ advanced driver assistance systems poses some challenges because of the vast amount of data that has to be collected from multiple sources and stored. This requires powerful processing power and robust storage solutions that can handle large amounts of data. 

Premio has created a solution known as the AI edge inference computer. Ai edge inference computers are hardened computing solutions that provide the processing power and storage capabilities required to gather the information from vehicle cameras and sensors and store that information so that organizations can use it to teach their algorithms how to behave when faced with new environments they’ve never seen before. 

AI edge inference computers can be deployed at the edge in vehicles to collect and store data. They can be deployed in vehicles because they are rugged, meaning they are hardened to withstand exposure to dust, debris, shock, vibration, and extreme temperatures. 

Furthermore, they are specifically designed for use in vehicles thanks to the wide power range, making them compatible with a variety of power input scenarios, including being powered by a vehicle battery. So, suppose you’re searching for a solution that can be deployed in a vehicle for data acquisition purposes. In that case, Premio’s AI edge computing solutions are a great option because they can be configured with enough storage to house the data collected from cameras and sensors and has the processing power necessary to process all of the incoming sensor data. 

Lastly, if an organization requires a solution that can perform inference analysis in addition to collecting and storing data, AI edge inference computers can be outfitted with a GPU to accelerate AI workloads. GPUs are great for performing deep learning inference analysis because they can process multiple computations simultaneously, thanks to a larger number of cores than the CPUs used in computers have. 

Frequently Asked Questions (FAQs)

1. What is the highest level of automation?

The highest level of automation is level 5 automation. At level 5 automation, the vehicle is capable of performing all driving tasks, meaning there is no need for a driver to even be in the vehicle, and no need for break/gas pedals or even a steering wheel. At level 5, a vehicle can do everything without the need for a human being behind the wheel. So, you could simply command a vehicle to take you from point A to point B, and you would then be chauffeured by the vehicle without having to do anything else. For example, Google Waymo currently has a fleet of self-driving vehicles without a driver. So, you could get into the backset, enter a destination, and the vehicle would take you there without having to do anything else.

2. What sensors do autonomous vehicles use? 

Autonomous vehicles use the following types of sensors: Cameras, LiDAR, Sonar, Ultrasonic, GPS, lasers, and other sensors to assist the car with driving itself. Sensors are how the vehicle “sees” the surrounding environment, allowing a powerful computer to make decisions that guide the vehicle based on that sensory information.

3. What is the lowest level of automation?

The lowest level of automation is level 0 automation. Almost all vehicles on the road have level 0 automation. That is, the driver is entirely responsible for driving the car at all times. For example, vehicles equipped with cruise control, which most cars offer this feature, are considered to have level 0 automation.

4. What are the different levels of vehicle autonomy?

The different levels of vehicle autonomy are level 0 autonomy (no automation), level 1 autonomy (driver assistance), level 2 autonomy (partial automation), level 3 autonomy (conditional automation), level 4 autonomy (high automation), and level 5 autonomy (full automation). These are the six different levels of vehicle autonomy/automation. The first portion of this post explains the different levels of vehicle autonomy in much detail. 

5. Are Autonomous Self-Driving Cars Legal?

Autonomous self-driving automobiles are not expressly illegal, meaning no laws prohibit them from being on the roads. However, there are very few laws that expressly authorize their presence on the road. Most laws require a human being to operate a vehicle, while others merely assume that a human being is operating a vehicle. So, autonomous vehicles can technically operate over the roads so long as a human being is behind the wheel.