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How Automotive AI Is Going to Disrupt (Almost) Every Industry

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How Automotive AI Is Going to Disrupt (Almost) Every Industry

We're about to reach a tipping point where automotive AI forever changes our relationship with displacement. You might be surprised how these advances will impact other sectors.

· AI Zone ·
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With almost every automaker on the planet launching predictions about the arrival date of driverless vehicles, we here at Arcbees are willing to bet that you’ve given at least a little thought to what that utopian future would be like napping, watching a movie, or getting work done in the backseat while your car deals with traffic. And how exciting would it be never to have to parallel park again?

Sound like yet another AI-related science fiction? Just consider the stated goals of these car companies:

  • Ford & Argo AI claim they’ll be “fully autonomous” by 2021

  • Honda, working with Waymo (a subsidiary of Google/Alphabet), wants to have cars with automated driving capabilities around 2020

  • Renault-Nissan, working with Microsoft, is aiming for 2025 for a fully driverless car

  • Volvo, working with Uber, has a goal of 2021

  • Hyundai, which is prioritizing affordability, has announced its goals for autonomous freeway driving by 2020 and the more complex navigation of urban driving by 2030.

Elon Musk of Tesla, on the other hand, is characteristically audacious and ambitious, already offering many driver-assist AI features and promising full automation, via a tweet, in “3 months maybe, 6 months definitely” — meaning by the end of 2017.

When it comes to AI-driven autonomous vehicles, however, it’s important to understand the terminology. SAE International has created the now-standard definitions for the six distinct levels of autonomy, from Level 1 representing only minor driver assistance (like today’s cruise control) to Level 6 being the utopian dream of full automation: naps and movie-watching permitted. However, any amount of driver assistance will bring numerous conveniences and better safety to drivers. It will also inevitably disrupt almost everything. In this post, we will focus on how automotive AI will impact closely related industries in particular.

Self Driving Levels.png

Photo credit: SAE

Transportation 2.0

The transport industry is clearly going to be heavily affected, even if drivers aren’t completely taken out of the picture. One of the ways is with the ability to maximize logistical efficiency by collecting data on routes, refueling schedules, and drivers’ needs for food and breaks. Real-time traffic and road condition information will also help with optimal route-planning, saving time and money to individuals and businesses alike. Nauto, a company that utilizes AI to increase transportation safety, uses a connected car network to operate vehicles more safely and more efficiently while reducing insurance costs by tracking driver behavior.

Many experts believe that AI-assisted driving will usher in a new era of safety on the roads. In fact, if human drivers (and thus, human error) become less and less of a factor in transportation, then it’s quite likely that the new infrastructure of the future will be built with features meant for AI, such as signs, signals, and lane patterns that are optimized for machine vision and sensor-controlled motion.

It’s true that AI stands to eliminate the traditional truck driver job as we know it at some point in the future. However, this only means that these jobs will change and adapt. Instead of the monotony of sitting behind the wheel mile after mile, transport operators of the future will have new jobs managing logistics through data or be working to maintain the systems and equipment. When it comes to AI, it’s all about optimizing and maximizing the symbiotic human-AI experiences in a way that improves and betters our relationship with the world as we know it.

Environmental Considerations

Both Tesla and Uber envision a future in which vehicles go about their own business throughout the day. Perhaps you subsidize your driving costs by renting your autonomous car out to others who need a ride, or maybe you’d rather be the renter. With high-efficiency use and no paid drivers, the cost of a ride decreases significantly. According to Fortune Magazine, cars today sit idle 95% of the time. What a waste! AI can help streamline how we travel in a number of creative ways that will result in a more efficient use of vehicles. One important way is to further reduce the need for independently owned vehicles altogether by harnessing the organizational power of AI to make ridesharing and carpooling more and more convenient and accessible.

Another promising use for AI is to make existing trips more efficient. UPS used this to great advantage over a decade ago. They made their routes smarter by eliminating left turns, thus shortening routes and idling time and minimizing the number of trucks needed. Amazingly, this strategy reduced the total distance covered by their trucks in 2005 by 747,000 kilometers and saved them 190,000 liters of fuel. All these developments mean less pollution and less bulky refuse when those cars eventually get junked, which is good news for Mother Nature. Fewer idle parked cars also means that parking lot sizes will likely decrease dramatically, leaving room for urban planners to replace those unsightly concrete parking lots with additional green spaces that reduce our carbon footprint.

Plus, before we reach Level 6 automation, enterprise companies are discovering other methods of employing AI and machine learning insights to reduce emissions and become more energy efficient. Last year, Google’s DeepMind AI used machine learning to reduce the energy they use for cooling their data centers by 40%. This is a big win, considering that cooling is one of a data center’s primary energy draws and, in conjunction, this will help other companies running on the Google Cloud reduce their energy usage as well. Google explains that their algorithm is a general-purpose framework for understanding complex dynamics--in other words, it’s a method for adapting and optimizing responses to unpredictable situations that can be put to good use in a wide range of scenarios. These kinds of developments in energy efficiency are transferable to other industries. Specifically, Google expects it to improve efficiency across a range of manufacturing processes. Where there’s a will to use it, AI could do wonders to boost green energy and the green economy.

Adaptive Insurance

Naturally, automotive AI will also have a significant impact on the insurance industry. More data means the ability to determine probabilities with more accuracy, which is at the heart of the insurance industry. Many of the features of AI-assisted driving center around increased safety, like automatic braking, collision avoidance systems, pedestrian and cyclists alerts, cross-traffic alerts, and intelligent cruise control. There’s also what is called vehicle-to-vehicle (V2V) technology when cars are connected so they can communicate with one another. Cars’ ability to share information in real time — such as their location, velocity, sudden braking, etc. — will allow them to override or assist drivers, bringing down the rate of accidents and reducing insurance prices.

A connected vehicle could also share performance data directly with the manufacturer (called “cognitive predictive maintenance”), allowing for diagnosis and even correction of performance issues without a stop at the dealer. This, too, could work to bring down the cost of car insurance as this kind of real-time maintenance would keep the cars on the road in better shape, preventing breakdowns and reducing accidents.

On the other hand, sharing so much information opens the door to privacy concerns or other abuses. Desjardins Insurance launched their app Ajusto in 2015, which tracks data about driving habits as well as your every move. According to their sales pitch, all it means is that good driving can reduce your rates up to 25%, however, one must be aware that this also means that they can raise your rates at their discretion, depending on how they choose to interpret your data. Do you roll through stop signs or push the speed limit a little? You could see all new fees on that bill in the future. Furthermore, do you feel comfortable with a company accumulating information about every time and place that you travel? This is a controversial matter that many people rightly feel uneasy about.

Rethinking Healthcare

Although it may not at first appear directly tied to automotive AI, the health and medical industry stands to experience some significant disruptions as well. There are a number of possibilities for new safety features that have never before been possible. For example, smart sensors could monitor a passenger or driver’s vital signs, protecting the safety of those in the car and on the road. They could detect a drowsy, impaired, or distracted driver, and implement the relevant safety protocol. In the event of medical emergencies, like a person with a sudden health crisis or in the case of a vehicular accident, emergency personnel could be called to the scene located via GPS. And, perhaps one day, automotive AI just might be able to detect these medical issues before they even occur.

Automotive AI could also make driving accessible to those with impairments or physical disabilities. Consider people who currently are unable to drive themselves due to impaired vision, physical disabilities, or age (either the elderly or the pre-16s). Not to mention, some people are banned from driving after having had a heart attack, or due to the unpredictable nature of their seizures. Independence through mobility can significantly improve one’s quality of life and well-being, and automotive AI could be what finally delivers it. How empowering would all of this new found accessibility and autonomy be?

If that wasn’t enough, AI is already helping paramedics in their day-to-day by allowing them to focus more on pre-medic patient care and less on the logistical details of their work. Consider Prehos, a tech company that specializes in advanced solutions for Emergency Medical Services (EMS) providers. They optimize ambulance routes, triage, and search tools; they implement accurate real-time data collection to capture a more accurate picture of patients’ vital stats, and EMS team performance; and they use the data to improve mechanical inspection follow-ups, streamline paperwork, simplify inventory, manage workload scheduling, and the list goes on. Prehos’s tools offer an amazing advantage to both EMS providers and hospitals, but most importantly, they deliver life-saving benefits to patients, who ultimately receive better and faster care.

The range of potential disruptions from automotive AI is truly staggering. While there are certainly negatives to be wary of, as there are any time industries amass data about our behavior and habits, the positive payoffs in safety and efficiency look as though they’ll outweigh the dangers. On top of that, it’s a hopeful future indeed that eliminates such daily grinds as navigating traffic, finding and paying for parking, or enduring fender-benders, to say nothing of serious car accidents.

Automotive AI is an industry that anyone with interest in artificial intelligence will do well to pay close attention to — stay tuned on this fascinating and fast-developing sector of AI, and be sure to get in touch with me if you have any questions about AI.

On that note, how do you think automotive AI will affect your industry sector? Tell me about it in the comments below.

automotive ,ai ,artificial intelligence

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