Self Driving Cars

What’s the future of personal transportation? Well, you’ll likely be spending a lot less time behind the wheel, for one. The rise of self-driving cars means that some scenes out of movies are now a reality—and even more, will be available soon.

Cars today already include many semi-autonomous features, like assisted parking and self-braking systems. And completely autonomous vehicles are rapidly becoming more of a reality. You’re probably familiar with Google’s version, which has made headlines with its Google Chauffeur software, which the company hopes to bring to market by 2020.

The pros of autonomous cars are many; the sensors are always observing and they can scan in multiple directions simultaneously. This will make the roadways safer as approximately 94 percent of accidents are caused by human error. Cars with advanced safety features and eventually, self-driving cars, can significantly reduce the number of collisions. The impact of this innovation can be far-reaching, including reduced demand for emergency response systems and reduced auto insurance and health care costs.

What technology makes self-driving cars possible? It’s really three technologies: sensors, connectivity, and software/control algorithms.

Most of the sensors required for autonomous driving are available today and are used in advanced safety features such as blind-spot monitoring, lane-keep assistance, and forward-collision warning. Sensors for other features such as radar, ultrasonics, and cameras provide the input necessary to navigate the car safely.

Connectivity means cars have access to the latest traffic, weather, surface conditions, construction, maps, adjacent cars, and road infrastructure. This data is used to monitor a car’s surrounding operating environment to anticipate braking or avoid hazardous conditions.

Finally, software/control algorithms are needed to reliably capture the data from sensors and connectivity and make decisions on steering, braking, speed, and route guidance. This is by far the most complex part of self-driving cars, the decision-making of the algorithms must be able to handle a multitude of simple and complex driving situations flawlessly. The software used to implement these algorithms must be robust and fault-tolerant.

Two of the most known self-driving advancements come from Google and Tesla. They take different approaches: Google uses lidar (a radar-like technology that uses light instead of radio waves) sensor technology and goes straight to cars without steering wheels or foot pedals.