Autonomous and unmanned vehicles are transport systems that can move autonomously, without the need for direct human control. They use advanced technologies, such as Artificial intelligence, sensors, and navigation systems, to autonomously analyse the environment, make decisions, and move through the environment. Such vehicles are widely used in transport, logistics, agriculture, military, and exploration.
Autonomous/Unmanned Vehicles
Type of technology
Description of the technology
Basic elements
- Navigation systems: Complex GPS and LIDAR systems enable autonomous vehicles to determine their location and analyse their surroundings.
- Artificial intelligence (AI): Machine learning algorithms that enable vehicles to analyse data and make decisions in real time.
- Sensors: Cameras, radars, LIDAR, and ultrasound used to monitor vehicle surroundings, detect obstacles, and navigate.
- Communication systems: Technologies that enable a vehicle to communicate with other vehicles (V2V) or infrastructure (V2X) to enhance safety and optimise traffic flow.
- Control software: Software to manage all aspects of an autonomous vehicle, from route planning to interaction with the surroundings.
Industry usage
- Public transport: Autonomous vehicles in public transport can automate the movement of buses and cabs.
- Logistics: Unmanned delivery vehicles can deliver goods more efficiently and reliably.
- Agriculture: Autonomous tractors and harvesters can work autonomously, increasing farmers’ productivity.
- Exploration: Unmanned vehicles can be used to explore hard-to-reach areas, such as underwater or space.
- Military: Unmanned land and air vehicles can be used for reconnaissance and rescue missions.
Importance for the economy
Autonomous vehicles have the potential to revolutionise the transport and logistics sector, offering more efficient and safer ways to travel. In the transport industry, they can reduce operating costs by eliminating the need for drivers to be present at all times. In logistics, they will ensure faster and more precise deliveries. In the military and exploration sectors, autonomous vehicles can enhance the safety and efficiency of missions while reducing risks to humans.
Related technologies
Artificial Intelligence
AI enables autonomous vehicles to make decisions on their own and adapt to changing road conditions.
Big Data
Collecting and analysing vast amounts of data from sensors and AI systems support the development and optimisation of autonomous vehicles.
Internet of Things
Autonomous vehicles can be part of a larger IoT ecosystem in which they communicate with city infrastructure and other vehicles.
Automation
Autonomous vehicles are a key part of the automation of transport and logistics, reducing the need for human intervention.
Mechanism of action
- Autonomous vehicles use a combination of technologies such as Artificial intelligence, navigation systems, and sensors to navigate their surroundings. Sensors collect environmental data to be analysed by AI systems, enabling the vehicle to make decisions, such as avoiding obstacles, responding to changing road conditions, and choosing the best route. Communication systems enable vehicles to exchange information with other units, further improving efficiency and safety.
Advantages
- Increasing safety: Autonomous vehicles can reduce accidents due to human error.
- Reduction of operating costs: Eliminating the need for drivers can reduce transport costs.
- Traffic optimisation: By communicating with other vehicles and infrastructure, autonomous systems can optimise traffic on roads, reducing congestion and emissions.
- Increasing logistical efficiency: Autonomous vehicles can operate 24/7, making freight transport more efficient.
- Improving military missions: Unmanned vehicles can carry out missions in difficult and dangerous conditions, minimising risks to humans.
Disadvantages
- Cyber threats: Autonomous vehicles can become targets of cyber attacks, posing security risks.
- Regulatory problems: The lack of uniform regulations for autonomous vehicles may hinder their mass deployment.
- Replacing jobs: The introduction of autonomous vehicles could lead to job cuts in the transport sector.
- High implementation costs: Investments in autonomous vehicles and their infrastructure and software are expensive.
- Limited adaptation: Technological complexity and public concerns may hinder mass deployment of autonomous vehicles.
Implementation of the technology
Required resources
- Navigation systems: Advanced GPS and LIDAR systems for precision navigation.
- Artificial intelligence: Machine learning algorithms for sensor data analysis and decision making.
- Sensors: Cameras, LIDAR, radars, and other sensors to monitor the vehicle’s surroundings.
- Control software: Software for managing vehicle movement and interaction with the surroundings.
- IT infrastructure: Integrated systems for monitoring and communication between vehicles and infrastructure.
Required competences
- AI programming: Ability to develop and implement Artificial intelligence algorithms in autonomous vehicles.
- Management of navigation systems: Knowledge of how to manage and optimise navigation systems, such as GPS and LIDAR.
- Robotics engineering: Competence in the design and implementation of autonomous systems.
- Cybersecurity: Ability to protect autonomous vehicles from cyber attacks.
- IT infrastructure management: Competence in the management of communication and information systems supporting autonomous vehicles.
Environmental aspects
- Energy consumption: Autonomous vehicles can increase energy consumption, especially those powered by electricity.
- IT equipment recycling: Autonomous vehicles use advanced electronic systems that generate electronic waste.
- Resource optimisation: Autonomous vehicles can optimise fuel or electricity consumption.
- Emission reduction: Autonomous vehicles can reduce emissions through more efficient driving and route optimisation.
Legal conditions
- Data protection: Autonomous vehicle systems must comply with data protection regulations, such as GDPR (example: processing data from GPS).
- Traffic regulations: Autonomous vehicles must operate in accordance with national and international traffic regulations (example: standards for autonomous cars in the EU).
- Patents and licences: Technologies used in autonomous vehicles must be protected by intellectual property laws (example: licences for vehicle control software).
- Safety standards: Autonomous vehicles must comply with motor vehicle safety standards, such as ISO 26262 (example: compliance with ISO 26262 for vehicle safety functions).
- Export regulations: Autonomous technologies, including navigation systems and AI, may be subject to export regulations (example: export restrictions on autonomous technologies in the US).