When you think of AI applications in the automotive industry, you might first think of self-driving cars. But AI can do more than drive. It can keep us connected, on schedule, and safe even when we are driving ourselves.
That all adds up to big business. The value of artificial Intelligence in automotive manufacturing and cloud services will exceed $10.73 billion by 2024.
In this article, we will look at 5 applications of artificial intelligence that are impacting automakers, vehicle owners, and service providers.
1. AI Driving Features
When it comes to driving, cars with artificial intelligence offer two levels of functionality: driver assist and fully autonomous mode.
Here are the differences:
Driver Assist
Before the automotive industry is comfortable letting AI take the wheel, it first wants to put it in the co-pilot’s seat.
AI lends itself perfectly to powering advanced safety features for connected vehicles. And that helps customers, manufacturers, and regulators get comfortable with AI as the driver before it gets its own license to drive.
By monitoring dozens of sensors, AI can identify dangerous situations. It can then alert the driver, or take emergency control of the vehicle in order to avoid an accident. Emergency braking, cross traffic detectors, blind spot monitoring, and driver-assist steering can help avoid accidents, and save lives in the process.
Driverless Automobiles
The mechanical muscle needed to control vehicle steering, braking, and acceleration has been within reach for nearly a century. The reason autonomous cars are not jamming the streets now is because, till recently, they didn’t have a brain.
The amount of processing power needed to drive a vehicle is enormous. Despite the power of modern computers, conventional computer programs simply are not up to the task. The reason for that is driving involves more than following a set of rules, or an algorithm; it involves learning.
In other words, it requires AI. And while a number of automakers and automotive startups are working on AI applications for the automotive industry, two companies lead the pack in the development of truly driverless cars: Google and Tesla. Let’s see why.
Waymo is not only Google’s foray into the autonomous production vehicle market, it appears to be their long term plan to achieve market dominance. Waymo has been conducting test drives in Phoenix for the last year, and plans to launch a public ride-hailing service before the end of 2018.
Waymo’s AI software crunches data from the vehicles’ lidar, radar, high-resolution cameras, GPS, and cloud services to produce control signals that operate the vehicle.
AI does more than respond to what is happening in the vehicle’s vicinity. Powerful AI deep-learning algorithms can accurately predict what objects in the vehicle’s travel path are likely to do.
A pedestrian on the sidewalk? Waymo knows they might step into the street at any moment. A vehicle stalled in the turn lane? Waymo anticipates that it might start moving again.
The most valuable aspect of AI in automotive applications is that it is constantly learning, and adjusting the rules it uses to navigate the road. Each vehicle makes the information it learns available to the rest of the fleet. The result is a virtual neural network of self-driving vehicles that learn as they go.
Tesla
Tesla has succeeded in becoming a household name in the electric car market. Now it wants to so the same thing with self-driving vehicles.
Eight cameras, an array of ultrasonic sensors, sonar, forward-facing radar, and GPS cull pretty much the same kind of data from the environment as Waymo. And like Google, all that data is fed into an AI program that turns sensory data into vehicle control data.
Tesla’s Autopilot software goes beyond driving the car where you tell it to go. If you are not in the mood for talking, AutoPilot will check your calendar and drive you to your scheduled appointment.
Every new Tesla comes fully equipped for autonomous driving. All that is needed is regulatory approval so the company can enable the software, putting AI in the driver’s seat.
2. AI Cloud Services
Whether autonomous cars shuffle us around with an AI driver, or if driver assist merely lends a helping hand, connected vehicles need gobs of data to do their thing. The application of artificial intelligence cloud platforms ensure that data is available when needed.
Predictive Maintenance
Unlike conventional vehicles, connected vehicles can do more than alert us with check-engine lights, oil lights, and low-battery indicators. AI monitors hundreds of sensors and is able to detect problems before they affect vehicle operation.
By monitoring thousands of data points per second, AI can spot minute changes that may indicate a pending component failure — often long before the failure could leave you stranded.
In October of 2018, Volkswagen and Microsoft announced a partnership, designed to transform the auto company into a digital service-driven business. By tapping the power of Azure IoT, PowerBI, and Skype, Volkswagen plans to offer customer experience, telematics, and productivity solutions for the automotive market.
Volkswagen recognizes that customers need more than gimmicks to see the value in cloud-based AI solutions. That is why they intend to offer predictive maintenance and Over The AIr (OTA) software updates for their entire brand of vehicles.
Individualized Marketing
Between email ads that hide beneath trick subject lines, pay-per-click website ads, and social media monetization, advertising competition has become fierce.
To make matters worse, sorting through raw data to target qualified prospects has become impractical, to say the least.
AI-based cloud platforms offer the ideal solution to accurately target a captive audience of qualified prospects. In the advertising field, it doesn’t get any better than that.
With AI’s connection to big data, vehicle infotainment systems can be used to suggest products and services to drivers based on a wealth of raw data. Here are a few examples how this works.
A driver whose social media posts announced wedding plans can be alerted of a sale at a bridal store just up the street. A low-fuel situation can automatically suggest the nearest gas station (which, of course, paid for the privileged). Or the driver’s eating habits can lead the system to suggest a relevant restaurant just around the corner.
AI has the power to know the driver’s needs and wants, and to know when they are in close proximity to businesses that can serve them.
3. AI Automotive Insurance
The insurance industry and AI have one thing in common, and it’s a biggie. Both spend a great deal of time predicting the future. It is no surprise, then, that insurance has embraced the use of AI in cars to help make risk assessments in real time.
AI does something else that even insurance customers like. It speeds up the process of filing claims when accidents do occur.
The applications of AI in insurance has spawned a brand new buzzword: Insurtech. And here are just a couple of examples of how AI is setting the insurance industry abuzz with deep learning technology.
AI-Powered Driver Risk Assessment
AI levels the playing field for drivers by creating risk profiles based on drivers’ individual risk factors found in big data. Rather than relying on driving history to set premiums, AI looks a myriad of less-obvious factors that can predict how safe a driver is likely to be.
From health issues to a recent divorce, AI can find details about a driver that may affect his or her ability to drive safely. Since such issues may be recent, they might not have affected the driver in the past, but potentially could in the future.
DIY Auto Claims
Art Financial solidified its position in the Chinese auto market in May of 2018 with the version 2.0 release of its AI-powered video app, Dingsunbao 2.0. The app enables drivers to perform their own auto damage assessment for their insurance companies.
On-screen instructions guide the user on how to video their vehicle damage for their insurance claim. While a human insurance adjuster still must sign off on each claim, AI quickly informs the driver how to have their vehicle repaired, and what will be covered by insurance.
Dingsunbao is typical of the AI apps that every automotive insurance company will eventually provide to their customers. The 1 billion renminbi that the app has already saved the Chinese auto insurance industry leaves no room for doubt.
4. AI in Car Manufacturing
AI is not only changing what a vehicle can do, it is also changing how vehicles are built.
Assembly line robots are nothing new. They have helped assemble vehicles since the 60s. What is new are smart robots that work with their human counterparts, rather than just along side of them.
In early 2018, Kia Motors began working with Hyundai Vest Exoskeleton (H-VEX) to develop wearable industrial robots for their assembly lines. Having identified AI as one of its top 5 future growth areas, Kia assembled a robotics team to lead the way.
The Vest Exoskeleton (H-VEX) and Hyundai Chairless Exoskeleton (H-CEX) wearable robots help protect workers knees, back, and neck while giving them the mobility and strength to perform tenuous jobs.
AI is helping build cars in other ways, as well.
Collaborative robots use AI to sense what human workers are doing, and they adjust their motions to avoid injuring their non-metallic co-workers.
Automated Guided Vehicles (AVGs) are being used to move materials around automotive plants without human intervention. AI enables these autonomous delivery vehicles to identify objects in their paths, and to adjust their route accordingly.
Painting and welding robots, when powered by AI, can do more than follow a pre-programmed routine. AI empowers them to identify defects or irregularities in materials and to adjust accordingly, or to alert quality control personnel.
5. Driver Monitoring
AI enables cars to do more than watch the road, it can help them keep an eye on the driver, as well.
Israeli automotive computer vision startup eyeSight uses AI and deep learning to offer an absolute plethora of in-car automotive solutions. Using advanced Time-of-Flight (TOF) cameras and IR sensors, eyeSight’s AI software detects driver behavior in four key areas.
Driver Identification
AI software detects whether or not the driver is in the vehicle.
Driver Recognition
Using advanced AI facial recognition algorithms, eyeSight can detect which driver is operating the vehicle. Since the husband, wife, and young adult child each have their own preferences, the system can automatically adjust the seat, mirrors, and temperature to suit the individual.
eyeSight offers both stand-alone proprietary software, and hardware and software bundles.
Driver Monitoring
By “observing” eye gaze, eye openness, and head position, eyeSight can detect distracted driving and alert the driver to keep their eyes on the road.
Through the use of AI in cars, drowsiness is detected by eye openness and head position, allowing the system to wake the driver up if necessary.
Contextual control allows eyeSight to tailor the content of the Heads-Up Display (HUD) according to where the driver’s eyes are focused.
Upper body detection detects the driver’s posture. In case of a crash, air bags can be deployed in a manner that will reduce injury based on how the driver is sitting.
Infotainment Control
Just because someone is driving does not mean they do not need to interact with the vehicle infotainment system. eyeSight recognizes simple hand gestures to allow the driver to control the infotainment system without taking their eyes off the road.
How Ignite Can Help?
Car AI promises to revolutionize the automotive industry and, more importantly, the automobile. Tremendous advances in technology mean opportunities not only for Google, Tesla, and major automotive companies, but for startups as well.
Ignite is an expert in automotive and AI technologies, and we would like to be your technology partner. We operate six R&D labs across Europe, giving us the capability to handle any size project at competitive outsource pricing.
Why not contact us today for a free consultation?
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