Introduction to Autonomous Vehicle
Autonomous vehicles, also known as self-driving cars, have the potential to revolutionize transportation by improving safety, reducing traffic congestion, and increasing accessibility for individuals with disabilities who cannot drive. To fully grasp the potential of this technology, it is essential to understand the engineering aspects that enable these vehicles to navigate complex environments without human intervention.
Society of Automotive Engineers (SAE) has classified driving automation into various levels of automation, ranging from Level 0 (no automation) to Level 5 (full automation), representing the extent to which the vehicle can operate without human control of the vehicle.
This article will delve into the below key components of autonomous vehicles that are critical for achieving this automation:
- Sensors and perception systems,
- Localization and mapping,
- Control systems,
- Communication and networking, and
- Cybersecurity and privacy.
By exploring these topics, you will gain a deeper understanding of the engineering principles that underpin the development and operation of autonomous vehicles.
Autonomous Driving Sensors: Revolutionizing Perception Systems
Sensors play a crucial role in vehicle automation, as they collect data from the surrounding environment to enable safe and efficient navigation. There are several types of sensors used in autonomous vehicles, including LiDAR, cameras, and radar. These sensors work together to provide a comprehensive understanding of the vehicle's surroundings, detect obstacles, identify traffic lights, and tracking other vehicles' movements. On the other hand, perception systems enables autonomous vehicle technology to recognize and differentiate between pedestrians, vehicles, cyclists, road signs, lane markings, and ot
