2 1 Shi Ji Jing Ji Bao Dao·2025-12-13 10:35Core Insights - The 2025 Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Robotics Industry Conference highlighted the role of AI in transforming traffic systems and the challenges of commercialization [1][2]. Group 1: AI in Traffic Management - AI models are shifting traffic signal control from passive response to proactive prediction, enhancing traffic management efficiency [1]. - In Guangzhou, AI models are used to optimize traffic light configurations at major intersections, significantly improving traffic flow [2]. - The implementation of AI in traffic management has led to 24/7 AI oversight of hundreds of intersections, achieving substantial improvements in efficiency and control [2]. Group 2: Human-Robot Applications - Human-shaped robots are expected to be the first to achieve large-scale application in the traffic sector due to structured product design and stable environments [2]. - The automotive industry is exploring human-robot applications in traffic, with significant market potential identified [2]. Group 3: Challenges in AI Implementation - Two main challenges in deploying AI in urban traffic include the need for algorithm accuracy improvement from 90% to 99.9% and breaking down barriers between different traffic subsystems [2]. - The integration of AI in traffic systems requires a comprehensive approach to ensure effective coordination and response to emergencies [2]. Group 4: Talent Development and Collaboration - There is an urgent need to cultivate "AI + Traffic" interdisciplinary talent to support technological advancements [3]. - Educational institutions are restructuring curricula and establishing partnerships with enterprises to enhance practical skills among students [3]. - Collaboration between academia and industry is essential for sustainable innovation, focusing on shared data and real-world applications [3].