AI and Auto: Applications & Implications
Artificial intelligence (AI) has come a long way in the last few years, bridging the gap between theoretical conversations and what are now practical possibilities. Nowhere are the possibilities more exciting than in the automotive industry. Between the design of the cars we currently drive (and the ones we’ll own in the future) and the process of manufacturing them, there is a lot of room for AI to expand, create efficiencies and make the process of auto-making and driving safer overall. The question is becoming when, not if, artificial intelligence will take over the automotive industry—and will manufacturers, suppliers and automakers be ready?
For the auto industry, there are four categories of AI that are the most relevant. The first is machine learning, or algorithms that learn from examples and experience, rather than predetermined processes. Machine learning forms one of the essential frameworks of AI and can be found in many of the technologies we already use in daily life. Deep learning, on the other hand, is a subset of machine learning formally patterned after human neural networks and serves as the second category. Deep learning allows computers to make accurate predictions about behavior; given the increasing amount of data made available via social networks and smartphones, deep learning is the fastest-growing part of AI.
The third category is natural language processing, or the ability for computers to recognize, interpret and respond to varied types of human speech. This includes accented speech, dialects, and slang—hence the title “natural”—and has come a long way in the last decade alone. Fourth is machine vision, which is the ability of computers to perceive and process visual cues like images, spatial distance, defects and speed—even when humans cannot.
When thinking about the power of artificial intelligence, top of mind for many are autonomous vehicles, which operate with minimal interference from human drivers. AI processes are now synthesizing data in order to learn how best to respond—and how humans respond—to driving conditions. For automobiles, this includes predicting how other cars will behave, how to gauge weather conditions, understanding road issues, and more. Eventually, this could change many automotive-driven industries, from taxis and rideshare vehicles to delivery companies and public transportation.
Vehicle manufacturers are also looking to AI to help people avoid human errors that lead to accidents. For example, safety features linked to automatic braking, collision avoidance systems, pedestrian and cyclist alerts, cross-traffic alerts and intelligent cruise controls are some of the other features being powered by AI. By working as an assistant to a human driver, these artificial intelligence advancements benefit everyone on the road.
Another significant contribution artificial intelligence is making is the use of biometrics to analyze driver security. This kind of technology would require a car to drive only when it recognizes a certain voice, which could be used to increase safety in ridesharing. Artificial intelligence could also track and synthesize biometric data about alertness and attention, preventing accidents when the vehicle senses the driver is unsafe to operate it.
The common thread through all of these applications is the increased safety of everyone on the road; this is a trend in AI development, and will be the focus for the foreseeable future. Concepts like vehicle-to-vehicle (V2V) technology, where connected cars have the ability to communicate with one another, are being developed; this technology could reduce accidents by connecting vehicles, alerting the network when something goes wrong, and allowing drivers (or even the vehicles) to take preventive measures.
Of course, given enough time, the manufacturing process could be reinvented with AI so much so that human laborers are no longer needed, at least not to perform the same jobs. Robotics and AI processes could eventually replace the need for low-skill workers, which, of course, has the potential to negatively impact the labor force in the short term. In the long term, the idea is to re-train those workers for higher level tasks.
Artificial intelligence will fundamentally change the automotive landscape; from manufacturing to the operation of vehicles. The increased efficiency, safety and productivity provided spell out a future that may completely defy our present understanding of how the industry works. The smartest choice for vehicle manufacturers and suppliers is to consider the benefits of leveraging artificial intelligence technologies to improve their day-to-day operations, future outlooks and overall success.
By James Gaffney, Product Engineer, Precision Grinding and Patrick D. Redington, Manager, Precision Grinding Business Unit, Norton Company (Worcester, MA)
Automotive manufacturers are meeting CAFE fuel-efficiency standards through lightweighting, which requires simulation software for design engineers.
The high-end automotive CAD/CAM systems do a whole lot more than their name implies. In addition to design and manufacturing, they have the ability to support analysis, product data management, and more.