The first public demonstration of a self-driving car took place in 1984 at Carnegie Mellon University's campus in Pittsburgh, Pennsylvania.

Sensors, such as cameras, radar, and lidar, are used to collect data about the surrounding environment, including other vehicles, pedestrians, and road conditions.

Self-driving cars have the potential to improve safety by reducing human error, reduce traffic congestion by optimizing traffic flow, and improve fuel efficiency by optimizing driving patterns.

Self-driving cars face several challenges, including the high cost of development, technical complexity, legal and regulatory issues related to liability and safety, and public acceptance of this new technology.

The United States is considered a leader in the development and testing of self-driving cars, with companies like Google, Tesla, and Uber actively involved in this field.

Self-driving cars are expected to have a significant impact on the transportation industry, potentially leading to increased job opportunities in the development and maintenance of these vehicles, reduced need for personal car ownership, and improved public transportation systems.

Experts predict that self-driving cars will become widely available to consumers sometime between 2030 and 2035.

Computer Vision, involving the use of cameras and deep learning algorithms, is widely used in self-driving cars for object detection and classification.

Autonomous Driving refers to the ability of self-driving cars to operate without human intervention, making decisions and controlling the vehicle's movement.

Radar technology is commonly used in self-driving cars to measure the distance and velocity of objects in the surrounding environment.

Actuators in self-driving cars are responsible for controlling the vehicle's movement, such as steering, acceleration, and braking.

Dedicated Short-Range Communications (DSRC) is a wireless communication technology specifically designed for V2V and V2I communication in self-driving cars.

Localization and mapping (SLAM) algorithms in self-driving cars are used to estimate the vehicle's position and orientation in its environment.

The trolley problem is a classic ethical dilemma that is often discussed in relation to self-driving cars, as it raises questions about the ethical decision-making capabilities of these vehicles in complex situations.