What is autonomous vehicle technology?

Autonomous vehicle technology refers to vehicles equipped with sensors, cameras, radar, and artificial intelligence (AI) that enable them to navigate and drive without human intervention. This technology is designed to operate vehicles in a way similar to experienced human drivers, making decisions based on their environment, which includes detecting traffic, pedestrians, and physical hazards.

The Society of Automotive Engineers (SAE) defines six levels of driving automation, ranging from Level 0 (fully manual) to Level 5 (fully autonomous)^[3]. For a vehicle to qualify as fully autonomous, it must navigate without human involvement over roads that are not specially adapted for its use^[5]. Levels 3 and 4 allow for certain levels of self-driving under specific conditions, where a human may need to take control^[2].

Autonomous vehicles rely on a combination of technologies to function effectively. They use multiple sensors, including radar, cameras, and LiDAR (light detection and ranging), to create a comprehensive 3D map of their surroundings, while advanced algorithms process this sensory information to steer, accelerate, and brake appropriately^[1][2][5]. Machine learning plays a crucial role, as it allows these vehicles to learn from vast amounts of data, improving their decision-making capabilities over time^[4][5].

In addition to safety advancements, which aim to reduce human errors leading to accidents, self-driving technology has implications for traffic flow, environmental benefits, and accessibility for individuals unable to drive^[1][2][5]. However, challenges remain in terms of technological reliability, regulatory frameworks, and ethical considerations related to decision-making during unexpected traffic situations^[3][4][5].