Autonomous Vehicles Terms Glossary: Autonomous Vehicles Terms in 2024
A
Adas
ADAS stands for Advanced Driver Assistance Systems, which are systems designed to enhance vehicle safety and improve driving comfort by providing assistance and warnings to the driver.
Advanced Driver Assistance Systems
Advanced Driver Assistance Systems (ADAS) are safety features in autonomous vehicles that assist and enhance the driving experience, such as adaptive cruise control, lane keeping assist, and automatic emergency braking.
Artificial Intelligence
Artificial Intelligence (AI) refers to the simulation of human intelligence in machines.
Artificial Intelligence (Ai)
Artificial Intelligence (AI) refers to the simulation of human intelligence in machines, enabling them to perform tasks that typically require human intelligence.
Artificial Neural Network
An Artificial Neural Network (ANN) is a computational model inspired by the biological neural networks in the human brain, used for tasks such as pattern recognition and classification.
Augmented Reality (Ar)
Augmented Reality (AR) is a technology that overlays digital information, such as virtual objects or data, onto the real-world environment, enhancing perception and interaction.
Autonomous Valet Parking
Autonomous Valet Parking enables vehicles to autonomously park themselves in designated parking areas, enhancing convenience and efficient use of parking spaces.
Autonomous Vehicle
An autonomous vehicle is a vehicle capable of navigating and operating without human intervention.
Autonomous Vehicle Testing
Autonomous Vehicle Testing involves conducting tests and experiments to evaluate the performance and safety of autonomous vehicle systems in various scenarios and conditions.
C
Charging Infrastructure
Charging Infrastructure refers to the network of charging stations and associated infrastructure necessary to support the charging needs of electric vehicles (EVs).
Cloud Computing
Cloud Computing involves the delivery of computing services, including processing power, storage, and software, over the internet, providing scalable and on-demand resources.
Cloud Storage
Cloud Storage refers to the storage of data in a remote server or infrastructure accessible over the internet, offering scalability, accessibility, and data redundancy advantages.
Cognitive Computing
Cognitive Computing refers to the development of computer systems that mimic human cognitive functions, such as perception, learning, and problem-solving.
Collision Avoidance
Collision Avoidance refers to the systems and technologies designed to detect and prevent potential collisions with other vehicles, pedestrians, or objects.
Comfort Control
Comfort control in autonomous vehicles involves adjusting and optimizing various parameters, such as temperature, airflow, seat position, and lighting, to provide a comfortable and personalized experience for occupants.
Computer Vision
Computer Vision is a field of AI that focuses on enabling computers to gain high-level understanding from digital images or videos.
Context Awareness
Context awareness refers to the ability of an autonomous vehicle to understand and interpret the surrounding context, including factors such as traffic conditions, weather, road infrastructure, and the behavior of other road users.
Control Systems
Control Systems in autonomous vehicles refer to the algorithms and mechanisms that regulate and adjust the vehicle's behavior and motion.
Cost Optimization
Cost Optimization involves the analysis and minimization of costs associated with autonomous vehicle operations, including energy consumption, maintenance, infrastructure, and manufacturing.
Cruise Control
Cruise control is a feature in autonomous vehicles that automatically maintains a set speed without the need for constant driver input, improving comfort and reducing driver fatigue.
Cybersecurity
Cybersecurity refers to the practice of protecting computer systems, networks, and data from digital attacks and unauthorized access.
D
Data Annotation
Data Annotation is the process of labeling or annotating data, such as images or sensor readings, with specific attributes or information, enabling machine learning algorithms to learn from labeled examples.
Data Fusion
Data Fusion is the process of combining and integrating data from different sources and sensors to obtain a more comprehensive and accurate representation of the environment.
Data Logging
Data logging involves the capturing and storage of data from various sensors, systems, and components of autonomous vehicles for analysis, diagnostics, and research purposes.
Data Privacy
Data Privacy involves protecting the privacy and confidentiality of personal or sensitive data, ensuring appropriate consent, storage, and usage practices to comply with privacy regulations.
Data Visualization
Data Visualization involves the representation of data or information in visual formats, such as charts, graphs, or maps, facilitating the understanding, analysis, and communication of complex data.
Dead Reckoning
Dead Reckoning is a navigation technique that estimates a vehicle's position based on its previous known position, velocity, and orientation.
Decision-Making
Decision-making in autonomous vehicles involves selecting the most appropriate action or behavior based on the perception of the environment and the vehicle's objectives.
Deep Learning
Deep Learning is a subset of ML that focuses on using neural networks with multiple layers to model and understand complex patterns and relationships in data.
Deep Reinforcement Learning
Deep Reinforcement Learning is a subfield of ML that combines deep learning with reinforcement learning to enable agents to learn optimal policies through trial and error interactions with an environment.
Driving Policy
Driving Policy refers to the rules, guidelines, and algorithms that govern the behavior and actions of an autonomous vehicle, taking into account traffic regulations, safety rules, and user preferences.
Dynamic Environment
Dynamic Environment refers to an environment that is constantly changing and evolving, with moving objects, varying lighting conditions, and unpredictable events.
Dynamic Path Planning
Dynamic path planning in autonomous vehicles involves continuously adapting and optimizing the planned path or trajectory based on real-time sensor information, traffic conditions, and other dynamic factors.
E
Edge Computing
Edge Computing is a distributed computing paradigm that brings computation and data storage closer to the location where it is needed, reducing latency and network traffic.
Ego Vehicle
The Ego Vehicle refers to the autonomous vehicle itself, from which the perception, planning, and control systems operate.
Electrical Architecture
The electrical architecture of an autonomous vehicle refers to the arrangement and organization of electrical and electronic components, such as sensors, actuators, and control units, that enable the vehicle's autonomous functionality.
Emissions Monitoring
Emissions Monitoring involves measuring and monitoring the emissions produced by a vehicle, allowing for compliance with environmental regulations and the optimization of fuel efficiency.
Energy Optimization
Energy Optimization involves maximizing the energy efficiency and range of an autonomous vehicle by optimizing the use of power-consuming components and systems.
Environment Perception Sensors
Environment perception sensors in autonomous vehicles include cameras, radar, lidar, and other sensors that provide information about the surrounding environment, enabling perception and decision-making algorithms.
Environmental Perception
Environmental perception in autonomous vehicles refers to the ability to understand and interpret the surroundings, encompassing aspects such as road conditions, weather, and the behavior of other road users.
Ethical Considerations
Ethical considerations in autonomous vehicles involve addressing questions and dilemmas related to safety, liability, privacy, decision-making algorithms, and the impact of autonomous vehicles on society and the environment.
F
Fault Detection And Diagnosis
Fault Detection and Diagnosis involves the identification and diagnosis of faults or anomalies in an autonomous vehicle system, ensuring safe and reliable operation.
Fault Tolerance
Fault Tolerance refers to the ability of a system to continue operating properly in the presence of faults or errors.
Firmware
Firmware refers to the software or code that is embedded in hardware devices to control their operation and enable communication with other hardware components.
Fleet Management
Fleet Management involves managing and coordinating a fleet of vehicles, including autonomous vehicles, to optimize operations, maintenance, routing, and resource allocation.
Functional Safety
Functional Safety involves designing and implementing safety mechanisms and practices to ensure that an autonomous vehicle operates safely and reliably.
Fusion Control
Fusion control in autonomous vehicles refers to the process of integrating and coordinating the inputs from various control systems to achieve the desired vehicle behavior and performance.
G
Geofencing
Geofencing is a technology that uses GPS or RFID to create virtual geographic boundaries, allowing autonomous vehicles to be controlled or restricted within specific areas or zones.
Gesture Recognition
Gesture Recognition involves the identification and interpretation of human gestures, such as hand movements or facial expressions, enabling natural and intuitive human-computer interaction.
Gps
GPS stands for Global Positioning System, a global navigation satellite system that provides location and time information in all weather conditions.
H
Hd Mapping
High-Definition (HD) Mapping involves creating detailed and accurate maps of roads, traffic signs, and other relevant features, providing contextual information essential for autonomous vehicles.
Hd Maps
HD Maps, short for High-Definition Maps, are detailed maps that provide accurate and up-to-date information about an environment, including road geometry, lane markings, and traffic signs.
High-Definition Mapping
High-definition mapping involves creating detailed digital maps of the environment that include road geometry, lane markings, traffic signs, and other relevant information, which is crucial for autonomous vehicle navigation.
Human Detection
Human Detection involves the identification and recognition of human presence or activities, often utilizing computer vision techniques for applications such as surveillance or safety systems.
Human-Like Decision Making
Human-like decision making in autonomous vehicles aims to emulate human decision-making processes, combining sensor data, perception algorithms, and models to make intelligent decisions in complex and uncertain situations.
Human-Machine Interface
The human-machine interface (HMI) provides the means for interaction and communication between humans and autonomous vehicles, often through visual, auditory, or haptic interfaces.
Human-Machine Interface (Hmi)
Human-Machine Interface (HMI) refers to the interface or interactions between humans and machines, such as touchscreens, voice commands, or gesture recognition, enabling effective communication and control.
I
Image Recognition
Image Recognition is the process of identifying and classifying objects or patterns in digital images.
Inertial Measurement Unit
An Inertial Measurement Unit (IMU) is an electronic device that measures and reports a vehicle's specific force, angular rate, and sometimes magnetic field.
Inertial Navigation System
An inertial navigation system (INS) is a navigation aid that uses a combination of accelerometers and gyroscopes to calculate an object's position, orientation, and velocity.
L
Lidar
LiDAR stands for Light Detection and Ranging, a remote sensing technology that uses laser light to measure distances and generate 3D maps.
Localization
Localization is the process of estimating a vehicle's position and orientation within a given environment or map.
Long Short-Term Memory (Lstm)
Long Short-Term Memory (LSTM) is a type of recurrent neural network (RNN) architecture that is particularly effective for processing and analyzing sequential data, often used in time-dependent tasks.
Long-Range Perception
Long-range Perception refers to the capability of an autonomous vehicle to detect and recognize objects and obstacles at a distance, enabling early detection and proactive decision-making.
M
Machine Learning
Machine Learning (ML) is a subset of AI that focuses on getting machines to learn from data.
Machine Learning (Ml)
Machine Learning (ML) is a subset of AI that focuses on enabling machines to learn from data and make decisions or predictions without explicit programming.
Machine Vision
Machine Vision involves the use of computer vision and image processing techniques to enable machines to interpret, analyze, and understand visual information, replicating human-like vision.
Machine-To-Machine Communication
Machine-to-machine (M2M) communication enables direct communication and interaction between autonomous vehicles or other machines without human intervention, facilitating coordination and cooperative behaviors.
Model Predictive Control
Model Predictive Control (MPC) is a control strategy used in autonomous vehicles that predicts the future evolution of the vehicle and optimizes control actions over a finite time horizon to achieve desired objectives.
N
Natural Language Processing
Natural Language Processing (NLP) is a field of AI that focuses on enabling computers to understand, interpret, and generate human language.
Natural Language Processing (Nlp)
Natural Language Processing (NLP) involves the interaction between computers and human language, enabling machines to understand, interpret, and generate human language.
Neural Network
A neural network is a computational model inspired by the structure and functioning of the human brain, composed of interconnected nodes or artificial neurons.
O
Object Detection
Object Detection is the process of identifying and localizing specific objects or instances of objects in an image or video.
Object Recognition
Object Recognition involves the detection and identification of specific objects or entities in images or video data, enabling autonomous vehicles to perceive and interact with the surrounding environment.
Object Tracking
Object Tracking is the process of monitoring and predicting the movement of objects in the environment over time.
Obstacle Detection
Obstacle Detection is the process of identifying and classifying objects in the environment that may pose a potential obstacle or hazard to the autonomous vehicle.
Occupancy Grid Mapping
Occupancy Grid Mapping is a technique used in simultaneous localization and mapping (SLAM) to represent the probability of occupancy or obstacles in the environment, creating grid-based maps.
Open Source
Open Source refers to software or hardware that is released with a license allowing anyone to study, modify, or distribute it, often resulting in collaborative development and community support.
Operating System
The operating system of an autonomous vehicle is the software that manages and controls the hardware resources, scheduling tasks, and facilitating communication and coordination between different subsystems.
P
Path Following
Path Following is the process of controlling a vehicle to follow a predefined path, adjusting its trajectory based on feedback from sensors and control algorithms.
Path Planning
Path Planning is the process of finding a feasible path from a starting point to a desired goal while avoiding obstacles and considering various constraints.
Pedestrian Detection
Pedestrian Detection refers to the capability of autonomous vehicles to identify and detect pedestrian presence or potential collisions with pedestrians, ensuring safety and pedestrians' right-of-way.
Perception
Perception refers to the process of understanding and interpreting the environment through sensors, such as cameras, LiDAR, and RADAR.
Predictive Analytics
Predictive Analytics involves using historical data, statistical algorithms, and machine learning techniques to make predictions or determinations about future events or outcomes.
Predictive Maintenance
Predictive maintenance involves continuously monitoring and analyzing vehicle data to predict and prevent potential failures or breakdowns, improving reliability and reducing maintenance costs.
Predictive Modeling
Predictive Modeling involves using historical data and statistical algorithms to make predictions and forecasts about future events or behaviors.
R
Radar
RADAR stands for Radio Detection and Ranging, a remote sensing technology that uses radio waves to detect and locate objects.
Range Anxiety
Range Anxiety refers to the fear or concern of an electric vehicle (EV) driver about running out of battery charge before reaching their destination or a charging station.
Real-Time Localization
Real-time localization is the ability of an autonomous vehicle to accurately determine its own position and orientation in real-time, often using techniques such as GPS, inertial sensors, and odometry.
Real-Time Processing
Real-time Processing refers to the ability of a system or application to process and respond to data immediately as it is received, often crucial for time-sensitive tasks in autonomous vehicles.
Reinforcement Learning
Reinforcement Learning is a type of machine learning that involves an agent learning from interactions with an environment by receiving feedback or rewards, aiming to maximize long-term cumulative reward.
Remote Control
Remote Control enables the control and operation of a vehicle or system from a remote location, often utilizing wireless communication and human-machine interfaces.
Remote Monitoring
Remote Monitoring enables the real-time monitoring and remote viewing of vehicle operations and performance, facilitating proactive maintenance, troubleshooting, and support.
Remote Vehicle Diagnostics
Remote Vehicle Diagnostics enables monitoring and analyzing a vehicle's performance, health, and usage remotely, allowing for predictive maintenance and optimization of operational efficiency.
Road Condition Monitoring
Road condition monitoring involves assessing the quality and safety of road surfaces, identifying hazards, and detecting changes or abnormalities that may affect the performance or safety of autonomous vehicles.
Road Database
Road Database refers to a digital database that contains detailed information about roads, including alignment, geometry, and road attributes, used for navigation and path planning.
Road Infrastructure Analysis
Road infrastructure analysis involves assessing the condition, capacity, and suitability of road infrastructure, such as roads, traffic signals, and intersections, to ensure compatibility and safety for autonomous vehicles.
Road Infrastructure Perception
Road Infrastructure Perception involves the detection and recognition of road signs, traffic lights, and other infrastructure elements that provide critical information for autonomous vehicles.
Road Lane Detection
Road lane detection is a computer vision technique that involves identifying and delineating road lanes using image processing algorithms, which is crucial for tasks such as lane keeping and autonomous navigation.
Road Network Analysis
Road network analysis involves studying and analyzing the characteristics, topology, traffic flow, and capacity of road networks to optimize autonomous vehicle routes and navigation.
Road User Communication
Road user communication involves the exchange of information and signals between autonomous vehicles and human drivers, pedestrians, or other road users to ensure safe and efficient interactions.
Road User Interaction
Road User Interaction involves the interaction between autonomous vehicles and other road users, such as pedestrians, bicyclists, and human-driven vehicles.
Robotic Process Automation (Rpa)
Robotic Process Automation (RPA) involves automating routine and repetitive tasks in business processes using software robots, improving efficiency and reducing human intervention.
Route Planning
Route Planning is the process of determining the optimal route from a starting location to a desired destination, taking into account various factors such as traffic, weather, and road conditions.
S
Scenario-Based Testing
Scenario-based Testing involves designing and executing tests that simulate specific real-world scenarios or critical situations that an autonomous vehicle may encounter.
Semantic Segmentation
Semantic Segmentation is the task of partitioning an image into multiple segments, where each segment represents a meaningful object or region.
Sensor Array
Sensor Array refers to a group or arrangement of multiple sensors, such as cameras, LiDAR, and radar, working together to provide a more comprehensive perception of the environment.
Sensor Calibration
Sensor Calibration is the process of aligning and adjusting the sensor measurements to account for any systematic errors or biases.
Sensor Fusion
Sensor Fusion is the process of combining data from multiple sensors to obtain a more accurate and robust perception of the environment.
Sensor Selection
Sensor Selection is the process of choosing the most appropriate sensors for a specific autonomous vehicle application, taking into account factors such as cost, performance, and reliability.
Simulation
Simulation involves creating a virtual environment or model that imitates real-world scenarios, allowing for testing and evaluation of autonomous vehicle systems and algorithms.
Simulator
A simulator is a software or hardware system that emulates the behavior of a real-world environment, allowing for testing and validation of autonomous vehicle systems.
Simultaneous Localization And Mapping (Slam)
Simultaneous Localization and Mapping (SLAM) is a technique used by autonomous vehicles to build a map of an unknown environment while simultaneously localizing themselves within the map.
Situational Awareness
Situational Awareness refers to the perception and understanding of the current state of the environment, including the location and movement of objects, to support decision-making and planning.
Slam
SLAM stands for Simultaneous Localization and Mapping, a technique used in robotics and autonomous systems for mapping an unknown environment while simultaneously keeping track of the system's location within the map.
System Integration
System Integration involves combining different subsystems and components of an autonomous vehicle into a cohesive and functional whole.
T
Telematics
Telematics involves the integrated use of telecommunications and informatics to monitor and transmit data related to remote objects, such as vehicles, enabling tracking, diagnostics, and analysis.
Teleoperation
Teleoperation is the control of a vehicle from a remote location through a communication link, often used as a backup solution for autonomous vehicles.
Traffic Prediction
Traffic Prediction involves using historical and real-time data to forecast future traffic conditions, helping autonomous vehicles make informed decisions and plan efficient routes.
Traffic Sign Recognition
Traffic Sign Recognition involves the detection and recognition of traffic signs or road markings, enabling autonomous vehicles to interpret and comply with traffic rules and regulations.
Traffic Simulation
Traffic simulation involves creating virtual models of traffic systems and analyzing their behavior under various scenarios, providing insights for optimizing traffic flow and testing autonomous vehicle algorithms.
U
Unsupervised Learning
Unsupervised Learning is a type of machine learning where the algorithm learns patterns or structures within input data without being directly guided or labeled by a supervisor or external source.
V
V2X
Vehicle-to-Everything (V2X) communication enables vehicles to communicate with other vehicles (V2V), infrastructure (V2I), pedestrians (V2P), and networks (V2N), enhancing road safety and efficiency.
V2X Communication
V2X Communication, short for Vehicle-to-Everything Communication, is a wireless communication technology that enables vehicles to exchange information with other vehicles, infrastructure, pedestrians, and the cloud.
Validation And Verification
Validation and Verification (V&V) involves the testing, inspection, and analysis of an autonomous vehicle system to ensure that it meets the required specifications and performance standards.
Vehicle Dynamics
Vehicle Dynamics is the study of how vehicles move and behave in response to various forces and inputs, such as acceleration, braking, and steering.
Vehicle Platooning
Vehicle Platooning refers to a group of vehicles traveling closely together in a convoy, connected and coordinated through wireless communication, with the potential to improve traffic flow and fuel efficiency.
Vehicle Routing
Vehicle Routing involves determining the optimal routes and sequences for a fleet of vehicles to complete a set of delivery or transportation tasks, considering various constraints and objectives.
Vehicle-To-Infrastructure Communication
Vehicle-to-Infrastructure (V2I) Communication enables vehicles to communicate with roadside infrastructure, such as traffic signals and road signs, to improve traffic flow and safety.
Vehicle-To-Vehicle (V2V)
Vehicle-to-Vehicle (V2V) communication enables wireless exchange of information between vehicles, fostering cooperative driving, collision avoidance, and traffic efficiency.
Vehicle-To-Vehicle Communication
Vehicle-to-Vehicle (V2V) Communication enables vehicles to exchange information with other nearby vehicles, enabling safer and more efficient driving.
Velocity Estimation
Velocity Estimation involves determining the speed and direction of an object, often utilizing sensor measurements and/or visual information to estimate its motion in real-time.