5 reasons why autonomous cars still aren’t on our roads Posted on : Aug 19 - 2020

Elon Musk thinks his company Tesla will have fully autonomous cars ready by the end of 2020. “There are no fundamental challenges remaining,” he said recently. “There are many small problems. And then there’s the challenge of solving all those small problems and putting the whole system together.”

While the technology to enable a car to complete a journey without human input (what the industry calls “level 5 autonomy”) might be advancing rapidly, producing a vehicle that can do so safely and legally is another matter.

There are indeed still fundamental challenges to the safe introduction of fully autonomous cars, and we have to overcome them before we see these vehicles on our roads. Here are five of the biggest remaining obstacles.

1. Sensors

Autonomous cars use a broad set of sensors to “see” the environment around them, helping to detect objects such as pedestrians, other vehicles , and road signs. Cameras help the car to view objects. Lidar uses lasers to measure the distance between objects and the vehicle. Radar detects objects and tracks their speed and direction.

These sensors all feed data back to the car’s control system or computer to help it make decisions about where to steer or when to brake. A fully autonomous car needs a set of sensors that accurately detect objects, distance, speed , and so on under all conditions and environments, without a human needing to intervene.

Lousy weather, heavy traffic, road signs with graffiti on them can all negatively impact the accuracy of sensing capability. Radar, which Tesla uses, is less susceptible to adverse weather conditions, but challenges remain in ensuring that the chosen sensors used in a fully autonomous car can detect all objects with the required level of certainty for them to be safe.

To enable truly autonomous cars, these sensors have to work in all weather conditions anywhere on the planet, from Alaska to Zanzibar and in congested cities such as Cairo and Hanoi. Accidents with Tesla’s current (only level 2) “autopilot,” including one in July 2020 hitting parked vehicles, show the company has a big gap to overcome to produce such a global, all-weather capability.

2. Machine learning

Most autonomous vehicles will use artificial intelligence and machine learning to process the data that comes from its sensors and to help make the decisions about its next actions. These algorithms will help identify the objects detected by the sensors and classify them, according to the system’s training, as a pedestrian, a street light, and so on. The car will then use this information to help decide whether the car needs to take action, such as braking or swerving, to avoid a detected object.

In the future, machines will be able to do this detection and classification more efficiently than a human driver can. But at the moment there is no widely accepted and agreed basis for ensuring that the machine learning algorithms used in the cars are safe. We do not have agreement across the industry, or across standardization bodies, on how machine learning should be trained, tested, or validated. View More