What is an Autonomous Vehicle?

In it’s simplest terms, an autonomous vehicle is a self driving car. These vehicles use a combination of sensors, cameras, radar and artificial intelligence to travel between destinations without a human operator. To qualify as being fully autonomous, these vehicles must be able to function on roads that are not adapted for their use, without a human operator to a set destination.

Levels of Automation

HUMAN MONITORS DRIVING ENVIRONMENT / AUTOMATED SYSTEM MONITORS DRIVING ENVIRONMENT

1. Driver Assistance: The vehicle features a single automated system (e.g. monitors speed through cruise control)
2. Partial Automation: The vehicle can perform steering and acceleration. The human still monitors all tasks and can take control at any time.
3. Conditional Automation: Environmental detection capabilities. The vehicle can perform most driving tasks, but human override is still required.
4. High Automation: The vehicle performs all driving tasks under specific circumstances. Geofencing is required. Human override is still an option.
5. Full Automation: The vehicle performs all driving tasks under all conditions. Zero human attention or interaction is required.

How do they work?

Below is an explanation from synopsis.com:

Autonomous cars rely on sensors, actuators, complex algorithms, machine learning systems, and powerful processors to execute software. Autonomous cars create and maintain a map of their surroundings based on a variety of sensors situated in different parts of the vehicle. Radar sensors monitor the position of nearby vehicles. Video cameras detect traffic lights, read road signs, track other vehicles, and look for pedestrians. Lidar (light detection and ranging) sensors bounce pulses of light off the car’s surroundings to measure distances, detect road edges, and identify lane markings. Ultrasonic sensors in the wheels detect curbs and other vehicles when parking. Sophisticated software then processes all this sensory input, plots a path, and sends instructions to the car’s actuators, which control acceleration, braking, and steering. Hard-coded rules, obstacle avoidance algorithms, predictive modelling, and object recognition help the software follow traffic rules and navigate obstacles.

Challenges of Autonomous Vehicles

WEATHER CONDITIONS

• Sensors and cameras won’t be able to detect and track road markings if there is a layer of ice, snow or rain.

TRAFFIC CONDITIONS

• We are unsure how they truly perform in bad traffic. There is also conversation about what lanes they will be granted access to.

LIDAR AND RADAR

• If multiple autonomous cars drove on the same road in close proximity, would these frequencies interfere with each other?