Artificial Intelligence Uses in Cars and the Automotive Industry

AI in Automotive Supply Chain Management

Artificial intelligence plays a pivotal role in managing supply chains for the auto industry. It helps predict demand for car parts, determining how many should be made and where they need to go. This smart planning decreases production costs and reduces wait times, saving precious storage space.

With AI, automakers can almost look into the future: using collected data, they can predict demand for specific car models, and optimize inventory, ensuring there's never too many or too few parts in stock.

AI also maps out the fastest routes for delivering parts, considering factors like traffic and weather to save time and fuel. It even can help pick reliable suppliers and monitor their performance, as AI can analyze various data such as previous delivery times, the quality of parts, prices, and even the financial health of potential suppliers to determine the most reliable ones.

Here’s a short piece presenting AI use for sustainable chain supply in Audi.

How AI is Revving Up Car Manufacturing

Ever wondered how car companies churn out so many shiny new rides? It's not all human muscle anymore! Artificial intelligence (AI) is playing a major role on the assembly line, supercharging car manufacturing in a bunch of ways.

Think about those robotic arms you see in car factory videos. Those aren't just fancy decorations – they're AI-powered workhorses. They're faster, stronger, and way more consistent than humans. Imagine assembling a car with pinpoint accuracy at record speed – that's the magic of AI robots.

Take Tesla's factory for example. They've got a whole crew of AI robots that never get tired, working 24/7 to build electric vehicles. These robots follow specific instructions, constantly figuring out the most efficient way to get the job done without any bumps or bruises – all under the watchful eye of AI.

The bottom line? AI robots are tackling complex tasks that used to require human hands, which means faster production lines and cars that are built to last. Pretty cool, right?

AI in Autonomous Driving

While autonomous driving sounds like a new concept, it's been developed for years. It's divided into five levels, each indicating what a car should be capable of. By 2023, we had reached Level 4, where cars can drive without a driver's input, although it's still expected that a driver be present to respond to critical situations. At Level 5, there's no need for a driver, just passengers.

You can already see real-life applications of almost level 5 (autonomous but restricted to a certain area) rides in cities like San Francisco and Phoenix. For example, Waymo taxis provide people with self-driving transportation in white Jaguars. However, there have been instances where a software glitch in a Waymo taxi caused a city-wide traffic jam, so there’s still a long way to go.

AI-based Driver Assistance

Despite the grand implications of the term, an 'autonomous car' is composed of numerous smaller subsystems, all of which are driven by AI. Let's explore some examples.

Blind Spot Detection: This feature assists drivers by signaling a light or sound when other vehicles are in their blind spots. The more advanced versions of this system can even prevent you from changing lanes if it detects another car on the nearby road.

Lane Keeping Assist: This system uses cameras to detect the lines on the road and automatically adjusts the driving path to ensure that your car stays within the lanes.

Traffic Sign Recognition: This feature can recognize road signs, such as speed limits, and adjust the car's speed accordingly. The system has evolved significantly over time. Initially, there were situations where it would pick up the speed limit from a freeway exit, even though the driver wasn’t planning to exit.

Now, in addition to recognizing speed limits and adjusting accordingly, these systems can also identify who has the right of way at an intersection and know how to behave, for example, at a subordinate intersection.

Danger Detection: and let's be honest; not everyone behaves perfectly at intersections. :) That's why new cars have systems that react to danger when someone else doesn't follow the rules. They can brake the car when someone else runs a stop sign. Combined with AI algorithms, 360 cameras and sensors around the vehicle can detect potential risks like pedestrians darting into the road.

However, these systems have their glitches. An issue known as phantom braking is where AI-based driver-assistance systems may misinterpret a harmless object, like a shadow or an overhead sign, as a potential threat and abruptly apply the brakes. While these systems have improved significantly over time, it underscores the need for continuous refinement to balance the sensitivity of AI systems, ensuring they can accurately differentiate between real threats and harmless objects.

Driver Fatigue Detection: Modern cars have systems that closely monitor driver behavior, noting erratic steering wheel movements, pedal use, lane deviations (in tandem with Lane Assist), and even changes in blink frequency. This way, the car can estimate when you're starting to feel drowsy and suggest you take a break.

Automated Parking: Some models, like Tesla, allow for entirely autonomous parking, where you can get out of the car and ask it to find a spot and park. More traditional systems will detect if your car fits in a parallel parking spot, notify you, and then park the car. This AI algorithm relies on visual sensors and can judge distances to build a model of the world and decide whether to park.

Voice control: With the help of AI, you can control various functions in your car without taking your hands off the wheel. Voice control systems can understand and respond to multiple commands, from adjusting the air conditioning or radio volume to helping you navigate to your next destination.

Predictive Maintenance: Some car manufacturers have systems that can predict when service will be needed. They collect data from various car sensors to notify the driver when maintenance is required.

Adaptive Cruise Control: AI-Based Cruise Control allows you to set your speed and maintain a safe distance from the car in front of you. The system adjusts the speed based on the car's speed in front, making it an upgrade on traditional cruise control, which can only set a specific pace and stick to it regardless of road conditions.

AI Risk Scoring in the Insurance Industry

This might seem odd, but Yanosik, a Polish mobile app that combines radar detection, CB radio, and navigation, collaborated with an insurance company to offer an insurance policy whose price depends on how safely and lawfully the driver operates their vehicle. If you drive safely, you'll pay less for insurance than someone who breaks the rules.

This solution isn't popular in Poland yet. Still, with the development of AI systems in cars and the European Union's emphasis on safe driving, such insurance policies will likely become the norm.

Recently, however, EU's Parliament has passed the AI act pushing AI further, and laying the groundwork for advancing the field. See the pdf here.

Summary

We can only guess when we will reach the level of full vehicular autonomy. One thing is certain - the first mover advantage will be huge, and each company that wants to remain competitive must be preparing for the future of the industry. That's an opportunity for all companies wanting to enter the market, too. They may take advantage of lapses of any market leaders, and overtake them.
If you want to explore the future of AI, do not hesitate to contact us here.