Connected and Automated Vehicles
Expert-defined terms from the Professional Certificate in Intelligent Transportation Systems course at London School of Business and Administration. Free to read, free to share, paired with a globally recognised certification pathway.
Adaptive Cruise Control (ACC) #
A driving assistance system that uses sensors and cameras to keep a constant pace with nearby traffic and automatically maintain a safe following distance. It is an early form of autonomous driving technology that can be found in many modern vehicles.
Automated Driving Systems (ADS) #
A system that performs part or all of the dynamic driving task on a sustained basis, regardless of whether it is a driver assistance system or a fully automated vehicle. ADS include various levels of automation, from driver assistance to fully automated driving.
Automated Lane Keeping Systems (ALKS) #
A driving assistance system that uses sensors and cameras to automatically steer the vehicle within its lane and maintain a constant speed, while also responding to traffic around it. ALKS can operate at speeds up to 60 km/h and are considered a level 3 automated driving system.
Autonomous Vehicle (AV) #
A vehicle that is capable of operating without human input or intervention, using sensors, cameras, and artificial intelligence to navigate and make decisions.
Connected and Automated Vehicle (CAV) #
A vehicle that is connected to other vehicles, infrastructure, and networks, and is capable of automated driving. CAVs can communicate with each other and the surrounding environment to improve safety, efficiency, and convenience.
Connected Vehicle (CV) #
A vehicle that is connected to other vehicles, infrastructure, and networks, using wireless communication technologies such as DSRC or 5G. CVs can exchange information in real-time, such as speed, location, and traffic conditions, to improve safety and efficiency.
Cooperative Intelligent Transportation Systems (C #
ITS): A system that enables vehicles, infrastructure, and networks to communicate and cooperate with each other, using wireless communication technologies such as DSRC or 5G. C-ITS can improve safety, efficiency, and convenience by providing real-time information and coordination between vehicles and the surrounding environment.
Cybersecurity #
The practice of protecting vehicles, infrastructure, and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. Cybersecurity is essential for ensuring the safety, privacy, and reliability of CAVs.
Decision #
Making Algorithms: Software algorithms that use data from sensors, cameras, and networks to make decisions about the vehicle's behavior, such as acceleration, braking, and steering. Decision-making algorithms are a critical component of automated driving systems.
Dependent Automation #
A level of automation where the driver is still responsible for monitoring the driving environment and is expected to take over control of the vehicle when prompted by the automated driving system.
Deep Learning #
A subset of machine learning that uses artificial neural networks to learn and make decisions based on large amounts of data. Deep learning is used in many automated driving systems to recognize objects, such as other vehicles, pedestrians, and road signs.
Dedicated Short #
Range Communications (DSRC): A wireless communication technology that is specifically designed for use in transportation systems, such as CAVs and ITS. DSRC enables vehicles, infrastructure, and networks to communicate in real-time over short distances.
Driving Automation System #
A system that performs part or all of the dynamic driving task, using sensors, cameras, and artificial intelligence to navigate and make decisions. Driving automation systems include various levels of automation, from driver assistance to fully automated driving.
Dynamic Driving Task #
The operational and tactical aspects of driving, such as steering, acceleration, and braking, that are required to operate a vehicle in a safe and efficient manner.
Fully Automated Vehicle (FAV) #
A vehicle that is capable of operating without any human input or intervention, using sensors, cameras, and artificial intelligence to navigate and make decisions.
Highly Automated Vehicle (HAV) #
A vehicle that is capable of performing the dynamic driving task under certain conditions and circumstances, using sensors, cameras, and artificial intelligence to navigate and make decisions. The driver is still responsible for monitoring the driving environment and is expected to take over control of the vehicle when prompted by the automated driving system.
Human #
Machine Interface (HMI): The interface between the driver and the automated driving system, including the controls, displays, and feedback mechanisms. A well-designed HMI can improve the usability, safety, and efficiency of CAVs.
Intelligent Transportation Systems (ITS) #
A system that uses advanced technologies, such as sensors, cameras, and artificial intelligence, to improve the safety, efficiency, and convenience of transportation systems. ITS can include various applications, such as traffic management, road pricing, and public transportation.
Level 0 Automation #
A level of automation where the driver is responsible for performing all aspects of the dynamic driving task, without any assistance from the vehicle.
Level 1 Automation #
A level of automation where the vehicle can assist the driver with one or more aspects of the dynamic driving task, such as adaptive cruise control or lane departure warning. The driver is still responsible for monitoring the driving environment and is expected to take over control of the vehicle at any time.
Level 2 Automation #
A level of automation where the vehicle can perform two or more aspects of the dynamic driving task simultaneously, such as adaptive cruise control and lane centering. The driver is still responsible for monitoring the driving environment and is expected to take over control of the vehicle when prompted by the automated driving system.
Level 3 Automation #
A level of automation where the vehicle can perform all aspects of the dynamic driving task under certain conditions and circumstances, such as highway driving or in traffic jams. The driver is still responsible for monitoring the driving environment and is expected to take over control of the vehicle when prompted by the automated driving system.
Level 4 Automation #
A level of automation where the vehicle can perform all aspects of the dynamic driving task under a wide range of conditions and circumstances, without any human intervention. The driver is not expected to take over control of the vehicle in any situation.
Level 5 Automation #
A level of automation where the vehicle can perform all aspects of the dynamic driving task under all conditions and circumstances, without any human intervention or oversight. The vehicle is capable of operating in any environment, including urban and rural areas, and can handle any weather or traffic conditions.
Machine Learning #
A subset of artificial intelligence that enables computers to learn and make decisions based on data, without being explicitly programmed. Machine learning is used in many automated driving systems to recognize patterns, make predictions, and optimize performance.
Motion Planning Algorithms #
Software algorithms that use data from sensors, cameras, and networks to plan the vehicle's motion, such as trajectory, speed, and acceleration. Motion planning algorithms are a critical component of automated driving systems.
Object Recognition Algorithms #
Software algorithms that use data from sensors, cameras, and networks to recognize and classify objects, such as other vehicles, pedestrians, and road signs. Object recognition algorithms are a critical component of automated driving systems.
Platooning #
A driving formation where multiple vehicles travel in a convoy, with a short following distance between them, to improve fuel efficiency, reduce congestion, and enhance safety. Platooning requires CAVs to communicate and coordinate with each other in real-time.
Sensors #
Devices that detect and measure physical quantities, such as distance, speed, and orientation, and provide data to the automated driving system. Sensors can include cameras, radar, lidar, ultrasonic, and infrared sensors.
Traffic Management #
The use of advanced technologies, such as sensors, cameras, and artificial intelligence, to improve the safety, efficiency, and convenience of traffic flow. Traffic management can include various applications, such as traffic signal control, ramp metering, and incident detection.
Vehicle #
to-Everything (V2X): A wireless communication technology that enables vehicles, infrastructure, and networks to communicate with each other and the surrounding environment, using DSRC or 5G. V2X can improve safety, efficiency, and convenience by providing real-time information and coordination between vehicles and the environment.
Vehicle #
to-Infrastructure (V2I): A wireless communication technology that enables vehicles to communicate with infrastructure, such as traffic signals, road signs, and parking facilities, using DSRC or 5G. V2I can improve safety, efficiency, and convenience by providing real-time information and coordination between vehicles and the infrastructure.