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Artificial Intelligence Touches Almost Everything Automotive

Artificial Intelligence Touches Almost Everything Automotive

Artificial intelligence is a huge buzzword these days, especially in the automotive industry. AI has many applications and can mean different things, even within the automotive world.

But the general concept can be imagined as a future where human beings have been completely removed from the entire driving equation. This could lead to a vehicular utopia with no more highway accidents, injuries, or deaths— all the result of driverless cars. However, we are a long way from reaching this point.

Many people don’t realize that in the automotive industry, artificial intelligence was in use long before the term “artificial intelligence” was even created. It started in the form of industrial robots. Prototypes of these robots go back to the early ‘60s, during the post-World War II rise of industrial automation and computers. In the beginning, the robots were used by General Motors and only did spot welding.

The robots were gradually trained to do additional tasks, such as “pick and place,” and soon an “arms race” broke out as different types of increasingly-advanced robotic arms were developed. The Stanford Arm was developed in 1969, followed by the Silver Arm from MIT in 1974 . This represented the beginning of adding sensors and microprocessors to mechanical arms. Doing so enabled robots to accomplish many new tasks, especially in assembly, during the 1980s and 1990s. Today, after billions of dollars invested, the robotics in manufacturing plants are semi-autonomous, utilizing machine vision to interact with the environment and humans.

Artificial intelligence requires computing power. Lots of it. Computers started appearing in cars around the late 1960s. Before then, cars had been completely mechanical. The original impetus to include computers in cars was saving fuel, which came in handy during the fuel shortages of the early ‘ 70s. Volkswagen introduced the first computer-controlled electronic fuel injection in 1968. Soon afterward, stricter emission standards led to all cars needing a processor-intensive engine control unit (ECU) which managed fuel emissions and fuel economy (among other things) through closed-loop controls (output monitoring controlling system inputs). The ECUs performed millions of calculations by looking up values in tables and calculating the results of long equations, which is similar to the basic algorithms which form the foundations of AI today.

Nowadays, artificial intelligence continues to be deeply involved in trying to reduce traffic accidents and fatalities caused by human error.

As mentioned, a lot of investment by auto manufacturers and work by engineers and technical experts is being expended to reach what’s known as full autonomy. This is where on-board computers will use artificial intelligence to fuse sensor data from cameras, radar, lidar, and other sensors in order to fully automate the entire driving process.

Eventually, drivers will not need to supervise the cars they ride in and the vehicle will be able to be “driven” anywhere, no matter the road or weather conditions. This is known as Level 5 autonomy. The Society of Automotive Engineers (SAE) is an international organization that has defined the levels of autonomy for the autonomous vehicle industry.

Currently, the ongoing advancement of automated driver assistance systems (ADAS) in vehicles has the automotive manufacturers nearing Level 3 autonomy — where some sections of the drive will be completely automated while others are still manual — but we are not quite there yet. Currently, AI contributes to features such as electronic stability control, anti-lock brakes, lane departure warning, adaptive cruise control, and traction control. But all of these features still have to be “supervised” by the driver with his or her hands on the wheel.

The most publicized advances towards full autonomy are being made in the long-haul trucking industry. The United States Postal Service, Amazon , and UPS are all testing self-driving trucks. Some trucks still have individuals behind the wheel while others are being monitored and driven remotely (Level 4 autonomy). We are beginning to see these trucks appear more frequently on the road and the distances traveled are getting longer. The trucking industry is particularly suited to benefit from driverless trucks. The industry notoriously suffers from a lack of drivers, not to mention the obvious potential savings in fuel costs and more efficient fleet utilization.

Incidentally, artificial intelligence is already contributing to the management of trucks and other large fleets . Companies are springing up that rely on artificial intelligence to maximize the efficiency of their inventory and to put vehicles in the right spots at the right time. The volumes of data captured and analyzed through machine learning by these systems will provide new standards for safety and operating efficiency. AI-driven management systems should accelerate the advancement of robo-taxis, which is expected to be the initial consumer application of autonomous vehicles.

Another automotive industry offshoot for artificial intelligence is within the insurance industry . AI and the connections provided by the Internet of Things (IoT) sensors will go a long way towards identifying the personal behavior of drivers, resulting in more fact-based pricing for premiums. People will pay based on the actual risk they demonstrate, instead of actuarial tables. The industry is also prime for the use of virtual reality (VR) online or through smart glasses to efficiently settle and pay claims and will put a dent in the likelihood of fraud. Some of these changes are already happening.

These advancements in artificial intelligence could be considered good news for all industries, but that’s not necessarily the case⁠. There are predictions that the personal auto insurance sector will contract by 60 percent within 25 years due to safer vehicles and the corresponding decline in accidents. Other aspects of the automobile industry may go away if we ever reach the ideal of full and complete autonomy of transportation. Why would we even need airbags, for example? Moreover, artificial intelligence points to a world where we no longer need to own an automobile. It’s hard to imagine such a disruption to our world order. But the environmental and societal benefits that will result remain a strong enough impetus for innovation. While some industries will decline, new economic opportunities will reveal themselves. Humans will adapt to the new realities brought about by artificial intelligence, as we always have.

Shmulik Shapiro is Executive Vice President-Global Business Development & Strategy at RSIP Vision. Shmulik leads RSIP’s efforts in delivering customized solutions that meet the most complex technology challenges in the hi-tech and healthcare industries. Before joining RSIP Vision, Shmulik was VP of Business Development for DiA Imaging Analysis, where he promoted use of advanced pattern recognition and machine learning technology to create automated, fast and accurate tools to analyze ultrasounds. RSIP Vision is headquartered in Jerusalem, with U.S. offices in San Jose, California, and Boston.

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