BRIDGING THE GAP: AI-HUMAN COLLABORATION IN AUTONOMOUS VEHICLE INCIDENT RESOLUTION
Keywords:
Autonomous Vehicles, Human-AI Collaboration, System Architecture, Machine Learning Integration, Transportation SafetyAbstract
This comprehensive article explores the integration of AI-human collaborative systems in autonomous vehicles, addressing the limitations of purely AI-driven approaches. The article presents a novel framework that combines artificial intelligence capabilities with human expertise to enhance vehicle safety and operational efficiency. The article examines system architecture, machine learning integration, implementation challenges, regulatory compliance, and market implications. By analyzing real-world deployments and field trials, the article demonstrates significant improvements in safety metrics, operational performance, and public acceptance through this hybrid approach. The article suggests that human-AI collaboration provides a scalable solution for autonomous vehicle deployment while establishing new industry standards for safety and reliability.
References
Nastaran Moradloo, "Safety in higher level automated vehicles: Investigating edge cases in crashes of vehicles equipped with automated driving systems," Accident Analysis & Prevention, 2024. Available: https://www.sciencedirect.com/science/article/abs/pii/S0001457524001520
Nacer Eddine Bezai, et al., "Future cities and autonomous vehicles: analysis of the barriers to full adoption," Internet of Things, 2021. Available: https://www.sciencedirect.com/science/article/pii/S2666123320300398
Hamed Nabizadeh Rafsanjani, et al., "Towards human-centered artificial intelligence (AI) in architecture, engineering, and construction (AEC) industry," Vehicular Communications, 2023. Available: https://www.sciencedirect.com/science/article/pii/S2451958823000520
Hanan Alolaiyan, et al., "Optimization of autonomous vehicle control system reliability on a commercial scale through LIF dombi methodologies," Scientific Reports, 2024. Available: https://www.nature.com/articles/s41598-024-77586-1
Aymane Ezzaim, et al., "AI-Based Adaptive Learning: A Systematic Mapping of the Literature," ResearchGate Technical Reports, 2023. Available: https://www.researchgate.net/publication/375058045_AI-Based_Adaptive_Learning_A_Systematic_Mapping_of_the_Literature
Arzoo Miglani, et al., "Deep learning models for traffic flow prediction in autonomous vehicles: A review, solutions, and challenges," Vehicular Communications, 2019. Available: https://www.sciencedirect.com/science/article/abs/pii/S2214209619302311
Brett Heyns, "Effective Human-AI Collaboration Strategies for Enhanced Productivity and Innovation," Smythos Technical Review, 2024. Available: https://www.crossml.com/human-ai-collaboration-enhancing-creativity-and-productivity/
LeadVent, "System Reliability and Redundancy in Autonomous Vehicles," LeadVent Technical Reports, 2024. Available: https://www.leadventgrp.com/blog/system-reliability-and-redundancy-in-autonomous-vehicles
Tamjeed Ahmad,, "The Future of Regulatory Compliance in AI and Tech," Corpzo Technology Review, 2024. Available: https://www.corpzo.com/the-future-of-regulatory-compliance-in-ai-and-tech
Stuart Ballingall, et al., "Standards relevant to automated driving system safety: A systematic assessment," Transportation Engineering, Volume 13, September 2023, 100202. Available: https://www.sciencedirect.com/science/article/pii/S2666691X23000428
Kaushal Reddy, et al., "Impact of Artificial Intelligence in Autonomous Vehicles: Revolutionizing Transportation," ResearchGate Transportation Studies, 2024. Available: https://www.researchgate.net/publication/387227765_Impact_of_Artificial_Intelligence_in_Autonomous_Vehicles_Revolutionizing_Transportation
Larissa Marioni, "What might be the economic implications of autonomous vehicles?," Economics Observatory Reports, 2024. Available: https://www.economicsobservatory.com/what-might-be-the-economic-implications-of-autonomous-vehicles
