Abstract Abstract Robots present an innovative solution to the construction industry’s challenges, including safety concerns, skilled worker shortages, and productivity issues. Successfully collaborating with robots requires new competencies to ensure safety, smooth interaction, and accelerated adoption of robotic technologies. However, limited research exists on the specific competencies needed for human—robot collaboration in construction. Moreover, the perspectives of construction industry professionals on these competencies remain underexplored. This study examines the perceptions of construction industry professionals regarding the knowledge, skills, and abilities necessary for the effective implementation of human—robot collaboration in construction. A two-round Delphi survey was conducted with expert panel members from the construction industry to assess their views on the competencies for human—robot collaboration. The results reveal that the most critical competencies include knowledge areas such as human—robot interface, construction robot applications, human—robot collaboration safety and standards, task planning and robot control system; skills such as task planning, safety management, technical expertise, human—robot interface, and communication; and abilities such as safety awareness, continuous learning, problemsolving, critical thinking, and spatial awareness. This study contributes to knowledge by identifying the most significant competencies for human—robot collaboration in construction and highlighting their relative importance. These competencies could inform the design of educational and training programs and facilitate the integration of robotic technologies in construction. The findings also provide a foundation for future research to further explore and enhance these competencies, ultimately supporting safer, more efficient, and more productive construction practices.

Abstract Rapid urbanization is reshaping mobility demands, calling for advanced intelligence and management capabilities in urban transport systems. Generative Artificial Intelligence (AI) presents new opportunities to enhance the efficiency and responsiveness of Intelligent Transportation Systems (ITS). This paper reviews the existing literature in transportation and AI to investigate the core technologies of Artificial Intelligence Generated Content (AIGC)–including dialog and reasoning, prediction and decision making, and multimodal generation. Applications are summarized across the four primary ITS subsystems (road subsystem, vehicle subsystem, traveler subsystem and management subsystem). This paper finds that AIGC has become an important way to promote the progress and development of ITS by exploring the research progress of cutting-edge technologies such as data generation, assisted driving decision-making, and intelligent traffic prediction. Meanwhile, this paper explores the potential challenges that AIGC brings to human society from the perspectives of safety risks of fake content, human-machine relationships, social cognition and emotional trust, and related ethical issues, providing insights for the development of safer and more sustainable ITS in the future.