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AI in Autonomous Vehicles: Navigating the Road to Self-Driving Cars

Written by: Archie Williamson | Posted: 17-01-2024

AI in Autonomous Vehicles: Navigating the Road to Self-Driving Cars

This is an AI-generated image created with Midjourney by Molly-Anna MaQuirl 

As anyone who has sat through rush hour traffic will agree, driving just about anywhere is no simple task. There’s a reason everyone must take a rigorous test and prove they can handle a vehicle safely and correctly before being granted a driver’s license. We’ve all seen out-of-control motorists on the road and wondered if they have even the slightest idea about how to drive.

Autonomous vehicles, also called self-driving cars, are considered a viable solution to the problem of human errors on the road. In theory, an autonomous vehicle can safely complete all its journeys without any need for human intervention. However, if you follow AI news, you’ll know that the reality is slightly different.

There are no fully autonomous cars just yet, and even those partially powered by Artificial Intelligence (AI) run into complications once they hit the road. But despite this, the shift to autonomous vehicles has the potential to make transportation more environmentally friendly, sustainable, and accessible.

In this post, we will look at how AI is pushing forward the development of self-driving cars and driving much-needed change in the automobile industry.

Types of Autonomous Vehicles

The transition to self-driving vehicles isn’t going to happen overnight. The current generation of AI cars are the outcome of many iterations and advancements in technology over many years.

With the explosion in AI technology, progress has leaped forward. Today, the US Department of Transportation recognizes the Society of Automotive Engineers (SAE) classification of the six levels of driving automation:

Level 0: No Automation

The all-manual automobile, where a human driver controls every action and performs every vehicle task, such as braking, accelerating, indicating turns, and steering.

Level 1: Driver Assistance

Vehicles with a single automated system, such as cruise control or automatic braking, assist the human driver as they drive.

Level 2: Partial Automation

Vehicles with Advanced Driver Assistance Systems (ADAS) can perform tasks like steering or controlling speed, but only under the supervision of a human driver.

Level 3: Conditional Automation

Vehicles capable of performing most driving tasks along with embedded environmental detection capabilities. Human drivers will be required to take control occasionally.

Level 4: High Automation

The car can perform all driving tasks needed to complete a journey in certain conditions. Human intervention is only optional, not required.

Level 5: Full Automation

Vehicles that do not require human intervention at any point and can perform all driving tasks in any condition.

The first three levels of this tiered system (from 0 to 2) cannot be classified as autonomous vehicles because they require human drivers to monitor the road at all times. The remaining levels (from 3 to 5) meet the criteria for an autonomous vehicle because the AI is monitoring the driving environment. These can justifiably be called 'AI cars', since they have the ability to behave truly autonomously on the roads.

AI Technology in Autonomous Cars

Without AI technology, self-driving cars would be a far-fetched sci-fi concept. But thanks to the ability of AI to mimic human behavior, self-driving cars are far along in their development, and truly autonomous vehicles are on the horizon.

Many installed sensors and technology systems interact with the car’s AI, allowing the vehicle to drive itself.

1.    LIDAR

Light Detection and Ranging (LIDAR) systems in self-driving cars use light beams and their reflected pathways to create a 360° map of the immediate environment around the vehicle.

2.    RADAR

Radio Detection and Ranging (RADAR) systems use radio waves to determine the distance between objects and the sensor at the front of the vehicle.

3.    Cameras

A mounted camera system captures real-time obstacles and changes in the car’s environment. AI-powered computer vision then interprets the data collected from the camera’s visuals and uses it to dictate movement.

4.    Infrared Sensors

In conditions of low light, poor weather, or a generally unfavorable driving environment, infrared sensors can detect pedestrians, cyclists, lane markings, and other objects on the road.

5.    GPS and INS

To reach its destination safely, a self-driving car relies on Global Positioning Systems (GPS) and Inertial Navigation Systems (INS). The former triangulates positions using satellite signals, while the latter uses gyroscopes and accelerometers to measure the car’s speed, velocity, and orientation.

6.    Map Database

Most manufacturers augment GPS and INS by including prebuilt maps in the vehicle as a failsafe.

7.    Ultrasonic Sensors

These sensors are placed on the back and front of the vehicle, where they assist with parking.

8.    Dedicated Short-Range Communication (DSRC)

DSRC uses vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication systems to send and receive critical traffic and road data while driving.

AI Applications in Self-Driving Cars

AI’s defining quality is how it mimics human behavior, and driving is one of the most complex tasks we perform daily. Multiple cognitive processes are involved in driving safely, and they are all assigned to AI in autonomous vehicles.

AI can do the following:

  • Data processing
  • Path planning
  • Path execution
  • Vehicle maintenance
  • Data collection

Hazards of AI-Driven Autonomous Cars

Human drivers are prone to error. But while autonomous vehicles are designed to mitigate mistakes on the road, they come with their own set of hazards.

The dangers and obstacles to the widespread use of self-driving cars include:

  • Safety: Miscalculations in the programming and engineering of self-driving cars can lead to accidents.
  • Security: Location data and other private information tracked by sensors could lead to security concerns.
  • Ethics: Self-driving cars are convenient, but they could endanger the jobs of those in the transportation industry, such as cab drivers and long-haul truckers.

The Road Ahead for AI in Autonomous Vehicles

Automotive manufacturers have already realized autonomous vehicles' potential to change how people drive. The Tesla self-driving car is the current poster child of the segment, but the biggest companies in the world, including General Motors, Toyota, Nissan, Volkswagen, and Ford, are also in the mix. By 2024, 54 million cars worldwide are expected to have some automation built in. The self-driving,AI car movement is just starting to rev its engines!

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AI in Autonomous Vehicles: Navigating the Road to Self-Driving Cars

Written by: Archie Williamson | Posted: 17-01-2024

AI in Autonomous Vehicles: Navigating the Road to Self-Driving Cars

This is an AI-generated image created with Midjourney by Molly-Anna MaQuirl 

As anyone who has sat through rush hour traffic will agree, driving just about anywhere is no simple task. There’s a reason everyone must take a rigorous test and prove they can handle a vehicle safely and correctly before being granted a driver’s license. We’ve all seen out-of-control motorists on the road and wondered if they have even the slightest idea about how to drive.

Autonomous vehicles, also called self-driving cars, are considered a viable solution to the problem of human errors on the road. In theory, an autonomous vehicle can safely complete all its journeys without any need for human intervention. However, if you follow AI news, you’ll know that the reality is slightly different.

There are no fully autonomous cars just yet, and even those partially powered by Artificial Intelligence (AI) run into complications once they hit the road. But despite this, the shift to autonomous vehicles has the potential to make transportation more environmentally friendly, sustainable, and accessible.

In this post, we will look at how AI is pushing forward the development of self-driving cars and driving much-needed change in the automobile industry.

Types of Autonomous Vehicles

The transition to self-driving vehicles isn’t going to happen overnight. The current generation of AI cars are the outcome of many iterations and advancements in technology over many years.

With the explosion in AI technology, progress has leaped forward. Today, the US Department of Transportation recognizes the Society of Automotive Engineers (SAE) classification of the six levels of driving automation:

Level 0: No Automation

The all-manual automobile, where a human driver controls every action and performs every vehicle task, such as braking, accelerating, indicating turns, and steering.

Level 1: Driver Assistance

Vehicles with a single automated system, such as cruise control or automatic braking, assist the human driver as they drive.

Level 2: Partial Automation

Vehicles with Advanced Driver Assistance Systems (ADAS) can perform tasks like steering or controlling speed, but only under the supervision of a human driver.

Level 3: Conditional Automation

Vehicles capable of performing most driving tasks along with embedded environmental detection capabilities. Human drivers will be required to take control occasionally.

Level 4: High Automation

The car can perform all driving tasks needed to complete a journey in certain conditions. Human intervention is only optional, not required.

Level 5: Full Automation

Vehicles that do not require human intervention at any point and can perform all driving tasks in any condition.

The first three levels of this tiered system (from 0 to 2) cannot be classified as autonomous vehicles because they require human drivers to monitor the road at all times. The remaining levels (from 3 to 5) meet the criteria for an autonomous vehicle because the AI is monitoring the driving environment. These can justifiably be called 'AI cars', since they have the ability to behave truly autonomously on the roads.

AI Technology in Autonomous Cars

Without AI technology, self-driving cars would be a far-fetched sci-fi concept. But thanks to the ability of AI to mimic human behavior, self-driving cars are far along in their development, and truly autonomous vehicles are on the horizon.

Many installed sensors and technology systems interact with the car’s AI, allowing the vehicle to drive itself.

1.    LIDAR

Light Detection and Ranging (LIDAR) systems in self-driving cars use light beams and their reflected pathways to create a 360° map of the immediate environment around the vehicle.

2.    RADAR

Radio Detection and Ranging (RADAR) systems use radio waves to determine the distance between objects and the sensor at the front of the vehicle.

3.    Cameras

A mounted camera system captures real-time obstacles and changes in the car’s environment. AI-powered computer vision then interprets the data collected from the camera’s visuals and uses it to dictate movement.

4.    Infrared Sensors

In conditions of low light, poor weather, or a generally unfavorable driving environment, infrared sensors can detect pedestrians, cyclists, lane markings, and other objects on the road.

5.    GPS and INS

To reach its destination safely, a self-driving car relies on Global Positioning Systems (GPS) and Inertial Navigation Systems (INS). The former triangulates positions using satellite signals, while the latter uses gyroscopes and accelerometers to measure the car’s speed, velocity, and orientation.

6.    Map Database

Most manufacturers augment GPS and INS by including prebuilt maps in the vehicle as a failsafe.

7.    Ultrasonic Sensors

These sensors are placed on the back and front of the vehicle, where they assist with parking.

8.    Dedicated Short-Range Communication (DSRC)

DSRC uses vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication systems to send and receive critical traffic and road data while driving.

AI Applications in Self-Driving Cars

AI’s defining quality is how it mimics human behavior, and driving is one of the most complex tasks we perform daily. Multiple cognitive processes are involved in driving safely, and they are all assigned to AI in autonomous vehicles.

AI can do the following:

  • Data processing
  • Path planning
  • Path execution
  • Vehicle maintenance
  • Data collection

Hazards of AI-Driven Autonomous Cars

Human drivers are prone to error. But while autonomous vehicles are designed to mitigate mistakes on the road, they come with their own set of hazards.

The dangers and obstacles to the widespread use of self-driving cars include:

  • Safety: Miscalculations in the programming and engineering of self-driving cars can lead to accidents.
  • Security: Location data and other private information tracked by sensors could lead to security concerns.
  • Ethics: Self-driving cars are convenient, but they could endanger the jobs of those in the transportation industry, such as cab drivers and long-haul truckers.

The Road Ahead for AI in Autonomous Vehicles

Automotive manufacturers have already realized autonomous vehicles' potential to change how people drive. The Tesla self-driving car is the current poster child of the segment, but the biggest companies in the world, including General Motors, Toyota, Nissan, Volkswagen, and Ford, are also in the mix. By 2024, 54 million cars worldwide are expected to have some automation built in. The self-driving,AI car movement is just starting to rev its engines!