Victor James

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AI Software and the Future of Autonomous Vehicles

AI car

Do you remember the times when we were all wondering about and imagining self-driving cars that are able to react in split seconds? Well, this concept once belonged hand in hand with science fiction, but not today.

In today’s world, fully autonomous vehicles are a reality that keeps unfolding – keeping us more and more impressed with each new capability.

Autonomous vehicles are probably the most popular topic associated with artificial intelligence ever since people started talking about AI technology. But have in mind that autonomous cars are not the only use of AI in the automotive industry since it includes industrial robots that actually construct the cars.

Building autonomous cars has been a slow and expensive business. Even after billions of dollars of investments, it’s still in intensive development to a somewhat “perfection.”

This being said the future of self-driving car production is promising. So let’s go over the basics and the progress, where I’ll provide you with a solid understanding of human drivers simulation.

What is a self-driving car?

Car driving on its own

A self-driving car, also known as an autonomous car, is a vehicle capable of operating without driver interference. How can it operate on its own? Well, there’s a combined system of cameras, sensors, radar, and artificial intelligence (AI) behind it, creating self-driving software.

For vehicles to qualify as fully autonomous, they must be able to navigate without human intervention. I can see the skepticism for safety a driver felt when this kind of vehicle was first presented to the real world. But hear me out; it has come a long way!

The automotive industry has allowed us to get into a car and input a destination. Once you do that, AI software takes over by interpreting data from the surroundings of your car in order to correctly execute the decision-making processes like breaking, lane changes, and even more complex situations in traffic.

The whole idea of implementing artificial intelligence in driving is to reduce human error, enhance safety and develop a more convenient mode of transportation that will prevent accidents.

So let’s move on to talk about self-driving cars and how they actually work.

How self-driving cars work

Self-driving cars work thanks to the remarkable synergy between advanced hardware and complex artificial intelligence software. Developers are able to build systems that drive on their own in self-driving cars by using a large amount of data from machine learning and neural networks, as well as image recognition.

But let’s unravel the five parts of this fascinating mechanism of an autonomous vehicle so we can understand how it works.

Sensor Suite

Sensor suite is the most important part of a self-driving car operation. It includes several things that make a powerful computer vision and allow autonomous driving, and they are the following:

  • LiDAR (Light Detection and Ranging) – LiDAR sensors release laser beams that bounce off surrounding objects which allow the car to create a 3D map of its environment. Using this technology, the car is able to detect other vehicles, pedestrians, and obstacles of any kind.
  • Cameras – There are multiple cameras that capture real-time images of the car’s surroundings which are processed by AI algorithms to identify all the critical visual cues, including lane markings and traffic lights, and of course, traffic signs.
  • Radar – The radar sensors use radio waves that help self-driving vehicles detect the distance and speed of nearby objects in order to avoid collision and have adaptive cruise control.
  • Ultrasonic sensors – Ultrasonic sensors are important when it comes to short-range detection, which is practical for parking maneuvers and preventing collisions at low speeds.

Data Processing

This sensor data is sent to the central processing unit, also called the vehicle’s “brain.” The data is processed from numerous sensors in real time, which provides a comprehensive understanding of the vehicle’s surroundings at all times.

Mapping

For accurate navigation, self-driving vehicles rely on highly detailed maps often preloaded into their systems. The maps mainly include information about road layouts, speed limits, lane markings, and more. While at the same time, the vehicle uses GPS and other localization technology to track its exact position on the maps.

Artificial Intelligence Algorithms

The true magic happens within the artificial intelligence algorithms. The algorithms take into consideration the map information, data from the sensors, and localization, and based on that, they make decisions that control the vehicle.

Artificial intelligence determines when to break, accelerate, change lanes, and handle unexpected traffic scenarios. Also, it can help you with fuel efficiency on the road. Thanks to machine learning AI constantly learns from its experience and improves control over time.

Safety Protocols

Now despite the advanced self-driving capabilities of driverless cars – human life and safety remain a number one priority and a key element. This being said, most vehicles that have systems to drive autonomously come with redundancy.

For example, if AI technology faces a situation it can’t handle or senses a potential risk on public roads, it immediately prompts the human driver to regain control of the steering wheel.

In addition, many self-driving cars have backup systems that can take over if the main AI system faces a sudden failure.

Features of Autonomous cars

Modern Level 4 autonomous vehicle

The more I got familiar with the new world of the autonomous vehicle – the more amazed I got with how far it has come. Because it literally changes the way we interact with cars.

As I stated before, autonomous driving is available to us thanks to a powerful combination of deep learning and neural network. And this combination creates a powerful system that has remarkable features.

For context, one of the standout features of an autonomous car is hands-free steering. Think how refreshing that sounds to go down a highway and have your hands rest in your lap instead of gripping the steering wheel. Well, this is possible thanks to AI algorithms that operate based on real-time data. And yes, I’m talking about it in the real world, not games.

However, based on the technology and its progress in production to this day, a driver has to pay attention and be ready to take over if needed. This approach makes sure there is a balance between autonomous driving and the safety of human reaction, which creates a symbolic relationship between AI and drivers.

Another interesting feature is Adaptive Cruise Control or ACC, which is capable of automatically adjusting the car’s speed in order to maintain a safe following distance between two vehicles.

The technology behind this feature is that when a slower-moving vehicle is detected in your lane, the ACC system automatically reduces your car’s speed to maintain a safe distance. Once the road clears, your car goes back to the chosen driving speed. This way, your driving is more relaxed, and your safety is enhanced.

Levels of Autonomy in self-driving cars

There is a concept that categorizes vehicles based on their capabilities since automation didn’t happen overnight. The categories, also referred to as levels of autonomy, show how much human intervention is needed during different stages of driving.

So let’s get into each of the six levels, where eventually I’ll explain the progression towards fully autonomous vehicles. The levels are the following:

  1. Level 0 (No Automation) – Level 0 has no automation involved. This means human drivers are fully responsible for the control of the vehicle with no assistance from an AI system involved. Level 0 represents traditional driving – an experience well-known to us for centuries.
  2. Level 1 (Driver Assistance) – At Level 1, the car can assist with either steering or acceleration, but not both at the same time. These features came out in the late 1990s when the car was able to automatically adjust its moving speed to maintain a safe distance in traffic. Even if the features are helpful, the driver must be engaged and monitor the road at all times.
  3. Level 2 (Partial Automation) – Level 2 was a significant step forward in the automotive industry, where the features of Level 1 could be operated simultaneously. This allows a more hands-off experience but is still dependent on the driver to take control of the vehicle at any time. For context, Tesla’s Autopilot in their electric cars is an excellent example of partial automation.
  4. Level 3 (Conditional Automation) – At this level, cars with AI software can manage most aspects of driving, but only in specific conditions and environments like highway driving. But still, even if the car can navigate on its own and make decisions, it’s not quite ready to handle all scenarios like adverse weather conditions. So, in addition to this, if the AI requests from the drivers, they must be ready to take over.
  5. Level 4 (High Automation) – Level 4 allows vehicles to handle most of the driving scenarios within predefined conditions and environments. These cars, for most situations, don’t require a driver’s intervention at all. Because cars with automation heavily depend on geofenced areas and mapped zones, they can be good for city driving but as good for off-road situations. So if you as a driver enjoy the off-road experience, don’t rely on the simulation so much.
  6. Level 5 (Full Automation) – This level is yet to be achieved since it means full automation in cars. With full automation, vehicles are expected to handle all driving situations regardless of any environment and condition. This means a driver is not needed to intervene, and frankly, there are no pedals nor a wheel. If full AI automation is ever available to the general public, it would mean that a car driver is not needed at all. Hence, drivers become only passengers.

Is It Safe to Use Artificial Intelligence in Cars?

The safety of using AI in vehicles is a concern all over the world, and I guess it’s normal because we, as humans, find it hard to depend on technology for our daily tasks fully. But I can say that all manufacturers in the world approach AI software integration ultra-careful with diligent testing.

So let me elaborate more on the artificial intelligence use and give you clearance on your concerns.

How Is AI Used in Cars?

Even thou self-driving cars is not fully automated yet, there are AI systems present in certain parts of the vehicles. At the moment, more advanced AI is mostly seen in electric cars, but not necessarily since AI is progressing its way to motorcycles and vans.

However, some manufacturers in the industry have clearer goals and focus on AI integration to ultimately reach full autonomous driving. So let’s see the role that AI plays in car production and how it advances modern cars.

Accident Prevention

Accident due to slow reaction

According to statistics, more than a million people lose their lives in car accidents worldwide. Now that’s a large number affecting the lives of approximately 4000 people daily. So given that road traffic is the most used way of transportation, it’s somewhat expected to have accidents to this scale based on the current world population.

The use of AI is expected to actually reduce this outcome because accident prevention is a key element in almost every modern car design of today. Let’s take the Tesla’s Collision Avoidance Assist feature, for example, that gives collision warnings and emergency braking, which immediately sets the car in place if it senses a dangerous situation.

The goal is to monitor and analyze the driver’s behavior and gather the mistakes drivers make while driving. AI can recognize distracted driving, and it can prevent the driver from situations that can endanger the driver’s life.

Steering and Braking Assistance

Steering assistance AI feature

In poor weather conditions, the roads are challenging to navigate. But using AI driving can be easier when the environment does not appear safe for drivers. For context, AI is proven to be helpful when there’s fog or pouring rain and even uneven terrain.

And not just that, AI is capable of sensing obstacles and making real-time adjustments that can help with brake assistance. If you find yourself in a hard-to-react situation, AI helps you break more gradually, which will give you a more safe and comfortable drive.

In the last three years, Tesla has been testing full AI self-driving cars, which are currently in the public beta stage. However, even with the varying performance, it’s still impressive that they rely on neural networks, which allow the AI system to learn.

Automated Parking

Parking for cars

Parking has always been a challenge for some people, especially in tight spaces. This is where AI features come in handy and are highly beneficial because they can park the vehicle on their own – making parking safer for everyone.

FAQ

What is AI in a car?

AI in a car refers to the human simulation of artificial intelligence in vehicles allowing them to execute driving tasks and make decisions that were traditionally done only by humans.

Is Tesla an AI car?

Tesla cars are equipped with advanced AI systems, but there are no fully AI self-driving cars yet available to the public. However, they have been testing Level 5 autonomous vehicles on public roads.

What exactly AI means?

AI refers to the ability of computer systems with advanced algorithms to simulate human intelligence.

Is AI driving safe?

AI driving is still a concern, but the automotive industry is dedicated to intensive testing and validation to make sure AI systems are reliable.

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