Tesla Autonomous Vehicles/Mobility (diverse areas)

“Full autonomy is going to come a hell of a lot faster than anyone thinks it will and I think what we’ve got under development is going to blow people’s minds,” said Elon Musk, CEO of Tesla, in a press release press release in August 2016.

Fig. 9.1 Tesla, prime example of sensor based autonomous driving with AI

Did you know Tesla has never turned an annual profit and is not predicted to do so until 2020. So how does this firm have a market value on par with some of the world’s largest automobile manufacturers? Tesla is not just an automaker, but also a technology and design company with a focus on energy innovation. By using the latest computing technologies to bring new benefits to its customers, like autonomous driving and related services, it has disrupted the market.

Autonomous cars are vehicles capable of sensing the environment surrounding and navigating without human input. To achieve this, Tesla first used cameras and radars to detect and understand obstacles on the road to help steer its autonomous vehicles. The problem that emerged however is that sometimes these sensors could be tricked by complex and seemingly illogical situations. For example, a low bridge with a dip underneath it may appear to be a solid roadblock from far away (this also happens to the human perception, by the way). In response to this, Tesla began collecting data from other Tesla vehicles to observe how human drivers behaved at a particular location. If other vehicles did not brake consistently, then no braking would be required for autonomous driving. Similarly, when the observing AI noticed drivers slowing at certain locations, the AI implemented mild breaking for autonomous vehicles. These decisions are combined to data from sensors to formulate the best decision for any given situation. In doing so, Tesla built a map based on artificial intelligence, and is employing it as an input for all its cars in combination with the radar. It even works in very difficult visibility situations, providing additional safety for drivers and their cars.

For all of this Tesla is using artificial intelligence algorithms which also define the confidence levels. This means if there is a 99.99 percent confidence level that there is an obstruction, it will add a full break for that designated location on the map and combine that with the sensor input, at any given time.

Tesla estimates that, after 10 billion kilometers are recorded/combined from Tesla cars, their car will be 10 times safer than regular human driven cars. By driving this distance it helps the AI to learn and find the best decision for any given moment. The advantage of this self-learning method is that it can resolve some of the most complicated situations for the sensors of cameras and radars. The more drivers will use it, the smarter it will become. This combination of learning from observing behavior (of drivers) from a wide range of drivers and combining it with input from sensors of the local car illustrates the power of AI for autonomous vehicles. It can overcome complex hurdles in discovering and reacting to obstacles on the road based on sensory data streams in combination with behavioral pattern. There are many similar approaches taken in Internet of Things solutions worldwide.

Some key insights from this example:

CEO is driving it – Elon Musk is the driving force behind Tesla’s advancement in Artificial Intelligence. With his wiz kid science background, passion and engagements in leading AI initiatives like OPEN AI, Musk makes AI the center of his work. This makes it clear for the organization that AI is not just a nice to have technology but a key building block of the future of the company. Elon Musk makes it a top priority and makes sure all understand.

It’s a way to outcompete other players – By leveraging AI, Tesla is able to achieve new levels of safety compared to today’s human driven vehicles. While many competitors are playing catch-up by adding sensors to their vehicles to allow them to support drivers in certain situations, Tesla is fully committed to letting AI deliver self-learning autonomous driving.

It provides true value – Next to improved safety, Tesla’s AI-based autonomous driving offers a new level of comfort and frees-up personal time for its customers and, in doing so, creates a new value proposition. In addition, autonomous vehicles create even more value for customers by exercising the capacity to perform other services while not being in use.

Its value improves over time – Tesla vehicles are known to improve over time, just as smartphones improve with new app capabilities, Tesla vehicles are updated continuously. AI means their capabilities keep on improving, thus making them more valuable.

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