Software

Creating 3D representations to help self-driving vehicles navigate accurately.

Enables faster speeds, low latency, and higher capacity for wireless communication.

Adjusts vehicle speed to maintain a safe distance from traffic ahead using sensors and automation.

Technologies that provide drivers with essential information, warnings, and automatic features to help improve driving safety.

The simulation of human intelligence in machines, enabling self-driving cars to make decisions.

Detects potential collisions and automatically applies brakes to prevent or reduce impact.

A vehicle capable of sensing its environment and operating without human intervention.

Automatically shifts the vehicle to an adjacent lane when safe, using sensors and driver input.

The ability of autonomous vehicles to anticipate the actions of other road users, such as pedestrians and other vehicles.

A system that monitors and alerts the driver (or vehicle in autonomous mode) about objects in areas not visible through mirrors.

A system that uses electronic controls instead of traditional hydraulic systems to manage braking in vehicles.

Replaces mechanical controls with electronic systems for steering, braking, and acceleration.

Uses neural networks to analyze large data sets and improve decision-making through pattern recognition.

A system that monitors and alerts the driver (or vehicle in autonomous mode) about objects in areas not visible through mirrors.

Trains a single AI model to process inputs and directly produce driving actions without manual rules.

A system that monitors and alerts the driver (or vehicle in autonomous mode) about objects in areas not visible through mirrors.

A system that monitors and alerts the driver (or vehicle in autonomous mode) about objects in areas not visible through mirrors.

A system that monitors and alerts the driver (or vehicle in autonomous mode) about objects in areas not visible through mirrors.

A virtual boundary that defines specific geographic areas where autonomous vehicles can operate.

An optimization algorithm used in machine learning to minimize errors in AI models for self-driving.

A tactile response system that provides feedback to drivers or passengers via touch or vibration.

Detailed, highly accurate maps used by autonomous vehicles to navigate complex environments.

A system that coordinates autonomous vehicles at intersections to avoid collisions and reduce delays.

A method in motion planning that limits rapid changes in acceleration to ensure smooth driving.

Metrics used to evaluate the effectiveness and efficiency of self-driving technologies.

A mathematical model used to describe the motion of autonomous vehicles based on their physical properties.

Level 2 self-driving allows steering and speed control, but the driver must still remain alert and ready to take over.

The process by which a self-driving vehicle determines its precise location using sensors and maps.

The system responsible for controlling a vehicle’s speed and maintaining a safe following distance.

The process of determining the path an autonomous vehicle will take to reach its destination safely.

A system where multiple autonomous entities, like cars, interact and make decisions in real time.

A machine learning model that mimics the human brain, allowing self-driving cars to learn from data.

The identification of objects such as pedestrians, other vehicles, and obstacles using sensors.

Wireless software updates delivered directly to a vehicle, keeping autonomous systems up to date.

The ability of autonomous vehicles to anticipate the future movements of other road users.

The process of interpreting sensor data to understand the environment around an autonomous vehicle.

An emerging technology that could significantly enhance the computational power of self-driving systems.

A control strategy where the vehicle reacts to real-time changes in its environment without pre-planning.

The integration of data from multiple sensors (e.g., LiDAR, radar, and cameras) to create a unified view of the environment.

Remote control of an autonomous vehicle, often used in scenarios where human intervention is necessary.

The process of determining the precise path and speed that an autonomous vehicle will follow.

The deployment of autonomous vehicles in urban environments with complex traffic and pedestrian dynamics.

Communication technology that allows vehicles to interact with each other and surrounding infrastructure.

The use of AI to interpret images from cameras and enable autonomous vehicles to understand their environment.

A subsidiary of Alphabet focused on developing and deploying autonomous driving technology.

A sensor used to measure the rotation of a vehicle’s wheels to assist with localization and speed calculations.

A technology that replaces mechanical control systems in vehicles (like steering or braking) with electronic controls.

The system that helps manage a vehicle’s rotation around its vertical axis, critical for stability in autonomous driving.

The simulation of human intelligence in machines, enabling self-driving cars to make decisions.

A proposed mode of high-speed transportation that could integrate autonomous vehicle technologies.

Communication systems that allow vehicles to interact with road infrastructure like traffic lights.