Self-Driving Car

There are two main benefits of a Self-Driving Car. One is safety; the other is driver convenience. Initial levels of self-driving are closely associated with Advanced Driver-Assistance Systems (ADAS), which provide safety functions such as lane centering, adaptive cruise control, automatic emergency braking, and collision avoidance. These reduce the chances of accidents by providing interventions to aid the driver.

As greater autonomy is added, a Self-Driving Car can take over more duties from the operator, enabling a more relaxed journey. At the highest levels of autonomy, the car takes complete control, enabling all occupants to enjoy entertainment or other activities while they travel rather than driving.

A fully Self-Driving Car could also act as a driverless taxi service, reducing journey costs and increasing availability. This could make those unable to drive or use public transport more mobile. Alongside electrification, self-driving taxis could also negate the need for personal vehicles in urban areas, reducing the number of parked cars on residential and commercial streets. This will have positive effects on emissions and air quality in cities.

The key enablers of Self-Driving Cars are high-resolution sensors, powerful local computer processing within the vehicle, and sophisticated driving scenario models. The sensors employed include cameras, radar, LiDAR, and ultrasonics. These provide live environmental data and may be combined using sensor fusion to improve accuracy.

The vehicle’s onboard computer will be loaded with a driving model, which requires extensive development and testing with the help of automotive engineering experts such as the BlackBerry QNX Autonomous Vehicle Innovation Center. This model will combine detailed mapping information with behavioral scenarios based on environmental inputs. These inputs could be the motion of other vehicles, cyclists, pedestrians, or animals and objects detected, such as traffic cones or road debris.

The vehicle sensors can read road markings, signage, traffic signals, and other features. Powerful onboard vehicle computing will employ AI inference based on the sensor inputs and self-driving models to generate driving action outputs. For example, the vehicle could steer around a bend, stop at a red traffic signal, or leave a road junction when traffic flow conditions are safe. Based on a navigational destination, the Self-Driving Car can plot a route and transport passengers safely with little or no operational input from a human driver.