+ "content": "- ### OntologyBlock\n id:: adas-ontology\n collapsed:: true\n\t- ontology:: true\n\t- term-id:: AI-0348\n\t- preferred-term:: ADAS\n\t- source-domain:: ai\n\t- status:: draft\n - public-access:: true\n\t- definition:: Advanced Driver Assistance Systems (ADAS) are electronic systems that assist vehicle operators with driving and parking functions through automated technologies including adaptive cruise control, lane keeping assist, automatic emergency braking, blind spot detection, and parking assistance. ADAS represents SAE Level 1-2 automation, providing driver support whilst requiring continuous driver supervision and intervention capability.\n\n\n\n## Academic Context\n\n- Advanced Driver Assistance Systems (ADAS) are electronic technologies designed to enhance vehicle safety and driving comfort by assisting drivers with various operational tasks.\n - These systems rely on sensors, cameras, radar, and increasingly sophisticated software algorithms to detect environmental conditions, obstacles, and driver behaviour.\n - ADAS research is grounded in control theory, computer vision, human-machine interaction, and automotive engineering.\n - The academic foundation includes studies on reducing human error in driving, improving situational awareness, and integrating automation with driver supervision.\n\n## Current Landscape (2025)\n\n- ADAS adoption is widespread in new vehicles globally, with many manufacturers including suites of driver assistance features as standard or optional equipment.\n - Common functions include adaptive cruise control, lane keeping assist, automatic emergency braking, blind spot detection, pedestrian and cyclist detection, and automated parking.\n - These systems typically correspond to SAE Levels 1 and 2 automation, meaning they provide driver support but require continuous driver attention and readiness to intervene.\n- Notable industry players include Mobileye, Valeo, and automotive OEMs such as Ford, Toyota, and BMW, each offering branded ADAS packages.\n- In the UK, including North England cities like Manchester, Leeds, Newcastle, and Sheffield, ADAS-equipped vehicles are increasingly common, supported by regional innovation hubs focusing on automotive technology and smart mobility.\n- Technical capabilities:\n - ADAS systems use sensor fusion combining radar, lidar, and cameras to improve detection accuracy.\n - Limitations include challenges in adverse weather, complex urban environments, and the need for driver vigilance.\n- Standards and frameworks:\n - SAE International’s automation levels provide a widely accepted classification.\n - UK and EU regulations increasingly mandate certain ADAS features for new vehicles to improve road safety.\n\n## Research & Literature\n\n- Key academic papers and sources:\n - Shladover, S.E. (2018). \"Connected and Automated Vehicle Systems: Introduction and Overview.\" *Journal of Intelligent Transportation Systems*, 22(3), 190-200. DOI:10.1080/15472450.2017.1336053\n - Koopman, P. & Wagner, M. (2017). \"Autonomous Vehicle Safety: An Interdisciplinary Challenge.\" *IEEE Intelligent Transportation Systems Magazine*, 9(1), 90-96. DOI:10.1109/MITS.2016.2571961\n - Favarò, F.M., et al. (2017). \"Automated Vehicles: The Road to Safety.\" *Accident Analysis & Prevention*, 99, 1-12. DOI:10.1016/j.aap.2016.11.011\n- Ongoing research focuses on improving sensor reliability, human-machine interface design, cybersecurity, and transitioning from driver assistance to higher levels of automation.\n\n## UK Context\n\n- The UK government supports ADAS development through funding and regulatory frameworks aimed at reducing road casualties.\n- North England hosts several innovation hubs and research centres contributing to ADAS technology, including:\n - The University of Leeds’ Institute for Transport Studies, focusing on intelligent transport systems.\n - Manchester’s Connected Autonomous Vehicle (CAV) testbed, a leading facility for real-world trials.\n - Newcastle University’s work on sensor fusion and driver behaviour modelling.\n- Regional case studies highlight the integration of ADAS in public transport fleets and commercial vehicles, improving safety in urban environments.\n- The UK’s commitment to mandating certain ADAS features in new vehicles aligns with EU and international safety standards.\n\n## Future Directions\n\n- Emerging trends include:\n - Integration of AI and machine learning for predictive and adaptive driving assistance.\n - Expansion of ADAS capabilities towards SAE Level 3 automation, enabling conditional automation with driver fallback.\n - Enhanced connectivity between vehicles and infrastructure (V2X) to improve situational awareness.\n- Anticipated challenges:\n - Ensuring cybersecurity resilience against hacking threats.\n - Balancing automation with driver engagement to prevent overreliance or complacency.\n - Addressing ethical and legal frameworks for automated interventions.\n- Research priorities focus on robust sensor fusion, fail-safe system design, and human factors engineering to optimise driver interaction.\n\n## References\n\n1. Shladover, S.E. (2018). Connected and Automated Vehicle Systems: Introduction and Overview. *Journal of Intelligent Transportation Systems*, 22(3), 190-200. DOI:10.1080/15472450.2017.1336053 \n2. Koopman, P. & Wagner, M. (2017). Autonomous Vehicle Safety: An Interdisciplinary Challenge. *IEEE Intelligent Transportation Systems Magazine*, 9(1), 90-96. DOI:10.1109/MITS.2016.2571961 \n3. Favarò, F.M., et al. (2017). Automated Vehicles: The Road to Safety. *Accident Analysis & Prevention*, 99, 1-12. DOI:10.1016/j.aap.2016.11.011 \n4. Wikipedia contributors. (2025). Advanced driver-assistance system. *Wikipedia*. Retrieved November 11, 2025, from https://en.wikipedia.org/wiki/Advanced_driver-assistance_system \n5. Valeo. (2025). Assistance Systems. Valeo Corporate Website. \n6. Mobileye. (2025). What is Advanced Driver-Assistance System (ADAS)? Mobileye Blog. \n7. QNX. (2025). What Is an Advanced Driver Assistance System (ADAS)? BlackBerry QNX. \n8. HERE Technologies. (2025). New levels of ADAS are on the rise—and fast. HERE Blog.\n\n\n## Metadata\n\n- **Last Updated**: 2025-11-11\n- **Review Status**: Comprehensive editorial review\n- **Verification**: Academic sources verified\n- **Regional Context**: UK/North England where applicable",
0 commit comments