autonomous vehicle
In plain wordsA vehicle, usually a car, truck or shuttle, that can drive itself, sensing the road, deciding what to do and steering, braking and accelerating with no human driving.
A road vehicle whose automated driving system can carry out the whole driving task — sensing its surroundings, anticipating other road users, planning a route and trajectory, and working the steering, accelerator and brakes — with no human driving it, at least within a defined operational design domainoperational design domain, n.: The specific conditions an automated vehicle or robot is designed to work in, such as particular roads, speeds, weather and times of day, outside of which it must not operate on its own.. In the SAE levelslevels of driving automation, n.: A six-step scale, from Level 0 to Level 5, describing how much of the driving a car's automation does and how much the human must still watch the road and be ready to take over. this means Level 3 and above; Levels 1 and 2 are driver assistanceadvanced driver-assistance system, n.: Car features that help the driver but do not replace them, such as automatic emergency braking, lane-keeping help, adaptive cruise control and blind-spot warnings.. A typical system fuses cameras, radar and often lidarlidar, n.: A sensor that measures distances by firing laser pulses and timing their reflections, building a 3D picture of its surroundings out of millions of points; widely used on robots and self-driving cars. (sensor fusionsensor fusion, n.: Combining readings from several different sensors, such as cameras, radar, lidar, GPS and motion sensors, to get a more accurate and reliable picture than any one sensor gives alone.), localizes against detailed maps, detects and tracks objects, forecasts their motion, and plans with optimization-based or learned planners; since about 2022 developers have moved toward end-to-end neural networks trained on fleet driving data, supplemented by simulation and generative world modelsworld foundation model, n.: A large AI model trained on vast amounts of video that can imagine how a scene will unfold, used to create realistic practice worlds for robots and self-driving cars.. As of October 2026, fully driverless ride-hailing (robotaxisrobotaxi, n.: A taxi with no human driver: you summon it with a phone app, and a self-driving car picks you up and drives you to your destination.) was offered by Waymo in about ten US metropolitan areas, with roughly 500,000 paid rides per week reported in early 2026, and by Baidu's Apollo Go, Pony.ai and WeRide in Chinese cities; autonomous trucks and shuttles were in earlier deployment. Validating safety, handling rare 'long-tail' situations, liability and regulation remain the central issues.
The autonomous vehicle yielded to the cyclist, then waited for the double-parked van to move.
Origin
Radio-controlled 'phantom autos' were demonstrated in the 1920s; computer-driven vehicles appeared with Japan's Tsukuba Mechanical Engineering Laboratory (1977), Carnegie Mellon's Navlab (from 1984) and Ernst Dickmanns's camera-guided vehicles in Germany (1980s–1990s). The DARPA Grand Challenges (2004–2007) launched the modern industry; Google's project (2009), renamed Waymo in 2016, began fully driverless public service in Phoenix in 2020.
Usage note
Terminology is contested: SAE and many regulators prefer 'automated', since vehicles depend on maps, infrastructure and remote support, while 'autonomous' and 'self-driving' dominate everyday use and marketing. Cars sold with 'self-driving' features that require constant supervision are Level 2, not autonomous vehicles in this sense.
Related
- levels of driving automationlevels of driving automation, n.: A six-step scale, from Level 0 to Level 5, describing how much of the driving a car's automation does and how much the human must still watch the road and be ready to take over.
- robotaxirobotaxi, n.: A taxi with no human driver: you summon it with a phone app, and a self-driving car picks you up and drives you to your destination.
- operational design domainoperational design domain, n.: The specific conditions an automated vehicle or robot is designed to work in, such as particular roads, speeds, weather and times of day, outside of which it must not operate on its own.
- advanced driver-assistance systemadvanced driver-assistance system, n.: Car features that help the driver but do not replace them, such as automatic emergency braking, lane-keeping help, adaptive cruise control and blind-spot warnings.
- lidarlidar, n.: A sensor that measures distances by firing laser pulses and timing their reflections, building a 3D picture of its surroundings out of millions of points; widely used on robots and self-driving cars.
- sensor fusionsensor fusion, n.: Combining readings from several different sensors, such as cameras, radar, lidar, GPS and motion sensors, to get a more accurate and reliable picture than any one sensor gives alone.
- DARPA Grand ChallengeDARPA Grand Challenge, prop. n.: A series of US government-sponsored races for driverless vehicles held in 2004, 2005 and 2007. No robot finished the first race; within three years, cars were navigating mock city traffic.
- advanced driver-assistance systemadvanced driver-assistance system, n.: Car features that help the driver but do not replace them, such as automatic emergency braking, lane-keeping help, adaptive cruise control and blind-spot warnings.
Sources
- Thrun, S. et al. (2006). Stanley: The robot that won the DARPA Grand Challenge. Journal of Field Robotics 23(9), 661–692.
- SAE International (2021). J3016: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles.
Mentioned in
dronedrone, n.: An aircraft that carries no one aboard to fly it: a person steers it from the ground, or its own software does. Small camera-carrying quadcopters are the most familiar kind., Elon MuskElon Musk, prop. n.: A South African-born American entrepreneur who runs Tesla and SpaceX, co-founded OpenAI, founded the AI company xAI, and has long warned that AI could endanger humanity., levels of driving automationlevels of driving automation, n.: A six-step scale, from Level 0 to Level 5, describing how much of the driving a car's automation does and how much the human must still watch the road and be ready to take over., physical AIphysical AI, n.: AI built to work in the physical world rather than on a screen: the intelligence inside robots, self-driving cars, drones and other machines that must sense real surroundings and move through them., robotrobot, n.: A machine that senses its surroundings, decides what to do and physically acts, moving itself or handling objects, with some independence from a human operator. Factory arms, robot vacuums and self-driving cars are all robots., advanced driver-assistance systemadvanced driver-assistance system, n.: Car features that help the driver but do not replace them, such as automatic emergency braking, lane-keeping help, adaptive cruise control and blind-spot warnings., BaiduBaidu, prop. n.: China's largest search-engine company and an early investor in deep learning, which makes the Ernie chatbot and models and runs driverless taxis., DARPA Grand ChallengeDARPA Grand Challenge, prop. n.: A series of US government-sponsored races for driverless vehicles held in 2004, 2005 and 2007. No robot finished the first race; within three years, cars were navigating mock city traffic., end-to-end learningend-to-end learning, n.: Training one AI system to go straight from raw input, such as camera images, to the final output, such as steering commands, instead of chaining hand-designed steps., lidarlidar, n.: A sensor that measures distances by firing laser pulses and timing their reflections, building a 3D picture of its surroundings out of millions of points; widely used on robots and self-driving cars., long taillong tail, n.: The huge number of rare things — uncommon words, unusual road situations, obscure facts — that each appear seldom but together make up a large share of what an AI system meets., model predictive controlmodel predictive control, n.: A control method that repeatedly plans the best moves a few seconds ahead using a model of the machine, carries out only the first move, then plans again with fresh measurements., perceptionperception, n.: How an AI system or robot turns raw sensor signals, such as camera pixels, microphone sound or laser scans, into an understanding of what is around it: objects, people, words and distances., point cloudpoint cloud, n.: A 3D picture made of many dots floating in space, each marking a spot on a surface, as captured by a laser scanner or worked out from photos., robotaxirobotaxi, n.: A taxi with no human driver: you summon it with a phone app, and a self-driving car picks you up and drives you to your destination., Scale AIScale AI, prop. n.: A company that pays large numbers of people to label examples, write model answers and grade chatbot replies, producing the data AI developers train and test on. Meta bought nearly half of it in 2025., sensor fusionsensor fusion, n.: Combining readings from several different sensors, such as cameras, radar, lidar, GPS and motion sensors, to get a more accurate and reliable picture than any one sensor gives alone., TeslaTesla, prop. n.: The American electric-car company led by Elon Musk, whose driver-assistance software, robotaxis and humanoid robot make it a major, and controversial, developer of AI., trolley problemtrolley problem, n.: A thought experiment asking whether you should divert a runaway tram so that it kills one person instead of five, often used to ask how self-driving cars should choose in an unavoidable crash., WaymoWaymo, prop. n.: A company owned by Google's parent, Alphabet, that runs fully driverless robotaxi services in several American cities., Alexandr WangAlexandr Wang, prop. n.: An American entrepreneur who founded Scale AI, a major supplier of human-labeled data for training AI, and became Meta's chief AI officer in 2025., ICRAICRA, prop. n.: The largest yearly robotics conference, run by the engineering society IEEE, covering everything from robot arms and drones to self-driving cars., operational design domainoperational design domain, n.: The specific conditions an automated vehicle or robot is designed to work in, such as particular roads, speeds, weather and times of day, outside of which it must not operate on its own., Sebastian ThrunSebastian Thrun, prop. n.: A German-American roboticist who led the Stanford team that won the 2005 desert race for self-driving cars, started Google's self-driving car project, and founded the online-learning company Udacity.