Overview
ISO/TR 12786:2026 is a technical report from the International Organization for Standardization (ISO) that provides a comprehensive collection of use cases specific to intelligent transport systems (ITS). By focusing on the application of big data technologies and artificial intelligence (AI), this document outlines how advanced data analytics and AI-driven solutions are transforming the transport sector. This technical report is a key reference for stakeholders seeking to understand and leverage the potential of big data and AI in ITS to enhance safety, efficiency, sustainability, and service quality.
Key Topics
- Intelligent Transport Systems (ITS): Encompass a range of information, communication, and control systems in urban and rural transportation. ITS covers multiple service domains such as traveller information, traffic management, public transport, emergency services, freight transport, and performance management.
- Big Data Technologies: ITS increasingly relies on big data, characterized by large volumes, high velocity, variety, and variability. Big data enables more informed decision-making across traffic operations, safety, and mobility services.
- Artificial Intelligence in ITS: AI techniques, including machine learning and deep learning, support ITS applications such as real-time traffic prediction, incident detection, and safety monitoring.
- Use Case Compilation: The report presents numerous ITS-specific use cases that harness big data and AI, such as congestion estimation, dynamic traffic signal control, automated bus operations, asset monitoring, work zone safety, pedestrian detection, and predictive maintenance.
Applications
ISO/TR 12786:2026 serves as a vital resource for identifying how big data and AI can be applied in practical ITS scenarios:
- Safety Improvement: Use cases showcase AI-powered pattern recognition, incident detection from video streams, distracted driver behaviour detection, and work zone safety management to reduce road accidents and enhance road user safety.
- Traffic Optimization: Leveraging predictive analytics and real-time data, applications such as congestion prediction, traffic signal optimization, multimodal corridor management, and demand-responsive control support efficient traffic flow and reduced congestion.
- Public Transport and Mobility: Applications include AI-based transport information for automated buses, demand-responsive transit network optimization, and public-area mobile robot (PMR) planning.
- Infrastructure and Asset Management: Machine learning models are utilized for predictive maintenance, asset condition monitoring, and identification of infrastructure needs, leading to higher reliability and reduced downtime.
- Environmental and Societal Impact: The use of big data and AI also supports sustainable development goals by optimizing resources, improving emergency response, and monitoring environmental conditions.
By offering a range of use cases, the standard demonstrates how ITS stakeholders-including operators, authorities, service providers, manufacturers, and technology companies-can benefit from the integration of big data and artificial intelligence.
Related Standards
ISO/TR 12786:2026 references and aligns with several international standards, providing a robust foundation for its recommendations:
- ISO/IEC 22989: Artificial Intelligence – Concepts and Terminology
- ISO/IEC 23053: Framework for Artificial Intelligence (AI) Systems Using Machine Learning (ML)
- ISO/IEC 20546: Big Data – Overview and Vocabulary
- ISO/TS 14812: Intelligent Transport Systems – Reference Model Architecture(s) for ITS
- ISO 14813-1: Intelligent Transport Systems – Service Domains
- ISO 24315 Series: Management of Electronic Traffic Regulations
- ISO/IEC/IEEE 15288: Systems and Software Engineering – System Life Cycle Processes
- ISO/IEC/IEEE 42010: Systems and Software Engineering – Architecture Description
Practical Value
This technical report provides transport authorities, solution developers, and system integrators with essential insights on leveraging big data and AI within intelligent transport systems. The use cases illustrate strategies to improve safety, enhance operational efficiency, support predictive maintenance, and foster innovation within the ITS ecosystem. By applying the guidance and examples in ISO/TR 12786:2026, organizations can contribute to safer, smarter, and more sustainable transportation networks worldwide.