Challenges in current deployments 

Companies have started public testing with autonomous taxi services in the US, which are often driven at low speeds and nearly always with a security driver. 

A few of these autonomous taxi services are listed in the following table:

The fully autonomous vehicle announcements (including testing and beyond) are listed in the following table:

However, despite these advances, there is one question we must ask: SDC development has existed for decades, but why is it taking so long to become a reality? The reason is that there are lots of components to SDCs, and the dream can only become a reality with the proper integration of these components. So, what we have today is multiple prototypes of SDCs from multiple companies to showcase their promising technologies.

The key ingredients or differentiators of SDCs are the sensors, hardware, software, and algorithms that are used. Lots of system and software engineering is required to bring all these four differentiators together. Even the choice of these differentiators plays an important role in SDC development.

In this section, we will cover existing deployments and their associated challenges in SDCs. Tesla has recently revealed their advancements and the research they've conducted on SDCs. Currently, most Tesla vehicles are capable of supplementing the driver's abilities. It can take over the tedious task of maintaining lanes on highways; monitoring and matching the speeds of surrounding vehicles; and can even be summoned to you while you are not in the vehicle. These capabilities are impressive and, in some cases, even life-saving, but it is still far from a full SDC. Tesla's current output still requires regular input from the driver to ensure they are paying attention and capable of taking over when needed.

There are four primary challenges that automakers such as Tesla need to overcome in order to succeed in replacing the human driver. We'll go over these now.