Question

What are the trends of Automation and Artificial Intelligence in the Automotive Industry? Write down in at least 1000 words with references.

Answer 1

Artificial Intelligence ( AI) and self-driving cars are also complementary subjects in technology. Simply put, you can't even think about one without the other. While AI is being applied at rapid pace in a variety of industries, the way it is being used in the automotive industry is a hot-button issue right now. With every car maker and their mother racing to develop artificial intelligence and self-driving technologies, there is also a host of technology companies and start-ups with the same intent. Although many believe that personal, autonomous vehicles are the future, there are several ways in which AI and machine learning are implemented in the construction of vehicles.
Many big auto manufacturers are focusing on developing their own self-propelled cars and driving apps, but we're going to concentrate on fairly young tech companies and start-ups that have arisen from the concept of self-driving vehicles.
Whether their technology is for use in public transport, ride sharing or personal needs, the following companies are at the forefront of autonomous vehicle technology.
NuTonomoy 's technology, nuCore enables robust and human-like handling of vehicles (without error). The program helps vehicles to handle even the most complicated traffic conditions. The goal of the organization is to have fleets of autonomous cars wherever they are required to ensure safer highways, less traffic and less emissions. Industry impact: Recently, NuTonomy partnered with Lyft to test vehicles in the Boston Seaport District, provide Lyft riders with rides and gain more momentum to change the way people get around.
Until the automotive industry is comfortable having AI take the wheel, it first needs to position it in the co-driver 's seat. AI lends itself perfectly to the potential of innovative safety technology for connected vehicles. And this allows consumers, suppliers, and regulators to get acquainted with AI as a driver before they get their own license to drive. Through tracking hundreds of sensors, AI will identify hazardous situations. It may warn the driver or take emergency control of the vehicle to prevent an accident. Emergency braking, cross-traffic warnings, blind spot tracking, and driver-assisted steering can help avoid accidents and save lives in the process.
The mechanical muscle required to control steering, braking, and acceleration of the vehicle has been within reach for almost a century. The reason Autonomous Cars don't block the streets now is that they haven't had a brain until recently.
The amount of computing power needed to drive a vehicle is enormous. Given the strength of modern computers, traditional computer programs are simply not up to the challenge. The explanation for this is driving involves more than following a set of rules or an algorithm; it involves learning. In other words , it includes AI. And although a variety of automakers and auto companies are working on AI applications for the automotive industry,
Waymo is not just Google's entry into the Autonomous Vehicle Production Industry, it seems to be its long-term attempt to gain market domination. Waymo has been conducting test drives in Phoenix for the last year with plans to launch a public hailing service by the end of 2018. Waymo's AI software crashes vehicle lidar data, radar, high-resolution cameras, GPS, and cloud services to generate the vehicle's control signals.
AI is doing more than listening to what is happening in the vicinity of the car. Powerful deep-learning AI algorithms can reliably predict what artifacts are likely to do in the vehicle's travel direction.Waymo knows that at any moment they could walk into the street. Waymo predicts that it could start moving again. The most useful feature of AI in automotive applications is that it is continually learning and changing the rules that it uses to navigate the lane. Every vehicle makes the information it learns available to the rest of the fleet. The effect is a virtual neural network of self-driving vehicles that learn the way they go.
Tesla has succeeded in becoming a household name on the electric car market. Already she tries to do the same thing for self-driving cars.

Eight cameras, an array of ultrasonic sensors, a sonar, a forward-facing radar, and a GPS collect virtually the same kind of data from the world as Waymo. And like Google, all the data is fed into an AI system that transforms sensory data into vehicle control data.
The Tesla Autopilot app goes beyond driving a car where you tell it to go. If you're not in the mood to chat, AutoPilot will check your calendar and drive you to your scheduled appointment.
If autonomous cars shuttle us around with an AI driver, or if the driver assist only lends a helping hand, the connected vehicles require a gob of data to do their thing. The use of artificial cloud intelligence systems means that data is accessible when needed.
Unlike traditional cars, connected vehicles can do more than warn us to check-engine lights, oil lights and low-battery indicators. AI tracks hundreds of sensors and is capable of identifying issues until they impact the operation of the vehicle.
Through tracking thousands of data points per second, AI can detect minute adjustments that may signify an outstanding component failure often long before the failure could leave you stranded. In October 2018, Volkswagen and Microsoft announced a collaboration to turn the car maker into a digital service-driven business. Through taping the power of Azure IoT, PowerBI, and Skype, Volkswagen aims to bring customer service, telematics, and collaboration solutions to the automotive industry.
Between email ads hidden behind trick subject lines, pay-per - click website ads, and social media monetization, advertising competition has become intense. To make matters worse, sorting through raw data to target qualified prospects has become, to say the least, unworkable. AI-based cloud services provide the perfect solution for targeting a captive audience of eligible prospects. It doesn't get any better than that in the advertising industry.
With AI 's link to big data, vehicle infotainment systems can be used to provide drivers with goods and services based on a wealth of raw data. Here are a few examples of how this works. A driver whose social media posts have revealed wedding plans may be alerted to a sale in a wedding store just up the street. A low-fuel situation will immediately recommend the nearest gas station (which, of course, paid for the fortunate one). Or the eating habits of the driver can lead the device to recommend an appropriate restaurant just around the corner. AI has the ability to know the needs and desires of the driver, and to know when they are in close proximity to the companies that can serve them.

Reference- Book on Automation in Automotive Industries