AI-powered cars — Is AI upgrading Self-driving cars?

6 min readJan 19, 2024

Self-driving cars are the new go — here’s a guide for Car enthusiasts!

Are you fond of vehicles? Do you dream of having a garage filled with cars? Thinking of electric cars? Autonomous vehicles? If you nodded your head to these questions, then you’re one of the people who’re curious about the future of the automotive industry. There must be a lot of questions running through your mind about whether cars in the future will upgrade or stay the same.

In this revolutionary era of Artificial Intelligence, no industry has escaped the influence of AI. Even if it is only 1% integration, every sector, corporation, and even small-scale household is utilizing artificial intelligence to improve efficiency and simplify complex operations.

In healthcare, AI and machine learning are being utilized to improve medical imaging and precision pharmaceutical operations, ultimately improving patient care.
In education, people are increasingly turning to online education to save time and money.
In the industrial industry, AI and machine learning are used to ensure that machinery is maintained or replaced on schedule.
In the banking sector, AI is employed for critical processes such as fraud detection, transaction tracking, customer data analysis, and so on.

Digitization is everywhere. The four businesses mentioned above represent only 1% of what Artificial Intelligence can do to other industries, completely changing the global economy. Machines are becoming AI-powered, and practically every task is now faster and more efficient thanks to the integration of AI and machine learning into business workflows. To contribute, Kodexo Lab’s AI and Machine Learning specialists have assured that AI is used efficiently in their business models, and they encourage other tech enthusiasts to employ AI to its full potential.

How is Artificial Intelligence (AI) impacting the Automotive Industry:

Artificial intelligence will change transportation in the future. AI and machine learning in transportation have greatly improved traffic flow, road safety, and efficiency. Nonetheless, autonomous vehicles and traffic control are two of the most contentious applications of AI in transportation. Let’s continue our exploration!

Self-Driving Cars:

Autonomous vehicles (AVs), often known as self-driving automobiles, use AI to make judgments and take actions. Self-driving automobile technology combines machine learning, computer vision, and sensing. This has the potential to change the transportation industry! However, how? How do self-driving cars improve with AI?

How is AI used in Self-Driving Cars?

Sensors:

Self-driving automobiles must perceive their surroundings and measure the distance between themselves and all other objects in their vicinity. Multiple sensory components, like as cameras, radar, and LiDARs, are integrated into the car to meet the necessity of censoring objects and movements around it.

These devices give a 3D model of the environment to assist the vehicle in navigating and avoiding obstructions. These components are supposed to be equipped with cutting-edge artificial intelligence (AI) technology, allowing them to correctly monitor their immediate surroundings and environment.

Computer Vision:

Computer imaging is a necessary component for self-driving automobiles to function properly. It enables the car to perceive and comprehend visual data from its instruments, such as lane markers, traffic lights, and other driving cars.

Machine Learning:

Self-driving automobiles use machine learning to improve their decision-making abilities. These algorithms examine sensor data and forecast based on historical performance and trends.

But, if there are multiple automobile models, including electric vehicles, is there a need for self-driving cars? Are there any perks or advantages? Yes, self-driving automobiles provide numerous benefits. These benefits will have an impact on both the automotive industry and the daily lives of those who travel on roads.

Benefits of Self-driving cars:

Enhanced Safety:

Self-driving cars have the potential to significantly reduce the number of car accidents. According to the National Highway Traffic Safety Administration (NHTSA), human error and inattention while driving account for 94% of all traffic accidents each year. This highlights the importance of self-driving cars for road safety and security. Because these automobiles are capable of precise measurement with exact distance, they can drive in-lane.

Lighter Traffic:

Everyone has experienced excessive traffic, which results in arriving at your location on time. Some factors that influence traffic flow include congested roadways, blocked traffic, and accidents. AI and machine learning are integrated into self-driving cars, along with other mentioned components such as radars, cameras, and LiDARs, to instantly figure out the empty roads and unblocked shortest paths to the destination, potentially resulting in less traffic congestion.

How do Self-driving Cars Work?

Autonomous Vehicles (AV) use AI techniques and technologies to provide autonomous travel with guaranteed safety and precision. AI and machine learning specialists use complicated neural network techniques to create effective picture recognition systems.

Neural networks examine data patterns, which are then input into machine learning algorithms. Self-driving cars collect this information for future use in detecting diverse images such as trees, curbs, roadsides, and other automobiles on the road.

Renowned Companies’ Autonomous Projects:

Google’s Self-Driving Car — Waymo:

For example, Google’s Waymo self-driving car project uses a number of sensors, cameras, and lidar (light detection and ranging), a technology similar to RADAR, to recognize everything in the vehicle’s area and anticipate its probable behaviors. This happens in just a fraction of a second. These systems should be mature. The more driving the system conducts, the more knowledge it has to feed into its deep learning algorithms and make increasingly smarter driving judgments.

Tesla’s Autonomous Vehicle:

Tesla is well-known for its cutting-edge technology advances, including ADAS and self-driving automobiles. The Tesla vehicle represents a significant advancement in the development of smart automobiles since it employs powerful AI algorithms that give precise control and exceptional decision-making capabilities.

NVIDIA:

NVIDIA has developed a comprehensive portfolio of AI computing platforms and technologies for the automotive sector, assisting in the integration of AI into car management and design. The company’s Drive platform, which improves autonomous vehicles’ reasoning and navigational capabilities, exemplifies how AI features such as sensing, mapping, and strategic route planning have been effectively incorporated.

Uber Vehicles:

Uber has become a self-driving car industry leader after investing heavily in autonomous vehicle research and development. Their major objective is to provide a trustworthy and safe ride-sharing service using AI-powered self-driving cars. Their emphasis on technological developments reflects their commitment to offer the most modern transportation experience possible.

BMW:

BMW has made a considerable commitment to incorporating AI into a variety of automotive technology applications, including infotainment and driver assistance systems. BMW uses cutting-edge natural language processing in its Intelligent Personal Assistant to demonstrate its commitment to offering a more customized and convenient experience. What is natural language processing? NLP is a technique that enables robots to understand, comprehend, and generate human-like text.

Features of a Self-driving Car:

Hands-free steering keeps the car balanced even when the driver’s hands are not on the wheel. It still needs the driver to stay vigilant.
The driver’s car and the vehicle in front of it are automatically kept at a specified distance via adaptive cruise control or ACC.
When a driver crosses a lane line, lane-centering steering automatically directs the vehicle in the direction of the other lane marker.

Conclusion:

Artificial intelligence (AI) is revolutionizing transportation by increasing environmental sustainability, productivity, and safety. Self-driving cars and improved traffic control systems are only the start. Technology must advance while addressing social, legal, and cybersecurity concerns to guarantee that future travel is efficient, secure, and accessible to all!