If you’ve purchased a new car recently, you are probably amazed by all the different new technology that comes with your car, safety features like warnings that tell you if you haven’t fastened your belt, or led indicators in your mirror that tell you if a car is next to you but also various indicators like if your the air pressure in your tires is too low.
The sector has been completely transformed by technology, to the point where we now estimate that the electronics inside your car make up 8% more of your car’s value each year and that its mechanical counterpart represents 3% of the car’s price each year.
Recent cars don’t shine because of their roaring V8 but rather because of the brilliant technology and electronics that come with it.
Technology’s main point is to develop the features of an initial product. To make it either better in one area by implementing something new or simply to push an existing design further by making it more efficient or better in a certain way.
Technology has for example been used recently to allow for more fuel-efficient rides. The main direction that technology is taking however is in predictive measurements. Predicting the direction your car will go, predicting accidents and taking safety measures to prevent them, and predicting the distance you have left before running out of gas.
These predictions are here to provide the user with information about their vehicle, just like a wearable fitness watch would give you information about your heart rate, intensity, and duration. Giving you access to these features allows you to get the best use out of your vehicle but also makes sure it won’t have a problem in the middle of the highway.
As we’re quickly seeing, the automotive industry is starting to rely increasingly on technology for several reasons.
The greatest example of that is probably due to the rise of electric vehicles, the major problem with their implementation was their limited range. It is estimated that over the last 6 years, the median electric car range increased by 56%. That increase concerns electric vehicles but a lot of the technology put in place to achieve this result is also being implemented in other cars.
Another aspect of major importance is the predictive behaviors that your car is putting in place. This could be a turn signal that automatically activates when you turn or having the wipers automatically activate when it’s raining. This predictive trend is mainly used to simplify the life of the driver.
We’ve all seen the headlines, the future of automotive seems to be in self-driving cars. This topic follows the trend of predictive technology. It aims at understanding our human behaviors and the things we take for granted when driving to put them in place in an algorithm. The dream and ultimate goal is to have driverless taxis around to transport us. As the world would be full of these, the cars could communicate with one another to make the roads safer and more optimized.
In large cities we’ve seen the rise of CaaS, either through an app like Uber, you can access a car and driver for your commute. This removes the need for a driver’s license and removes any costs associated with owning a car, like insurance, the garage, and paying for gas, all the while enjoying the benefits of owning one.
A similar ongoing trend is the ability to rent out a car for the day or the hour. In large cities, you can often find cars on the street which you can unlock with an app for a given amount of time. The goal here is to offer a car that does require a driver’s license but removes the need for insurance and technical repairs.
Let’s try and understand the reasons why fundamentally, the automotive industry needs technology.
Taking the example of self-driving cars, you need to create artificial intelligence that combines various inputs in order to drive. These inputs, most of the time are cameras that map out the surroundings of the car. This live image is combined with other elements like proximity sensors that can guide the car and detect if something is coming close to it.
One implementation of these inputs can, for example, provide the driver with lane assistance, by detecting the white lines on the highway, the car already knows where to go, it just follows the line while keeping some distance with the cars in front and behind of it.
The self-driving car example actually leverages two technologies, big data and AI, a gigantic neural network takes in a large number of situations and trains itself to notice humans, trees, roads, stop signs, red lights, and others. This neural network is the artificial intelligence behind the self-driving car.
The challenge of creating a self-driving car is to first make the car understand what its surroundings are and then understand what it should do in various situations. As you cant teach your AI every single possible situation it will face, you also need to make sure it generalizes its training well enough to face the unknown.
We’ve already seen how technology is implemented in your car to allow for safer and more efficient vehicles. The automotive industry, however, heavily relies on technology to pursue its development in its greatest and most ambitious sector, autonomous vehicles.