智慧化是道路基础设施未来发展的主要方向，也是传统交通基础设施领域与人工智能、物联网、大数据等新技术和自动驾驶、车路协同等新业态深度融合的重要场景。通过构建数字化感知网络、智能化管控系统和网络化服务体系，实现道路基础设施表观与内部性态的全要素透明感知和全时空虚实映射，是智慧道路建设运维关键技术的核心，其中，数字化感知网络提供数据基础。本文聚焦透明道路服役性态的监测与检测技术，属于智慧道路数字化感知网络的重要组成环节。论文从道路服役性态的内嵌感知、道路结构性态的快速评估、道路表观病害的自动检测和道路隐蔽病害的智能识别四个方面，回顾了道路服役性态监–检感测技术的发展现状，归纳了目前监–检感测技术面临的瓶颈与挑战，梳理了人工智能技术在监–检感测方面的应用。最后，对AI赋能的透明道路服役性态感知研究做了展望，提出未来需从：“天-空-地”多源立体式感知体系、基于多源数据融合的解译方法、融合道路本体结构的数字孪生底座和端-边-云协同的智慧道路管控服务系统4各方面开展研究，进一步发展透明道路监-检感测方法，完善智慧道路建设运维关键技术和理论体系。

Intelligentization presently emerges as the primary direction for future developments of road infrastructure, providing specific scenarios that integrate conventional transport infrastructure research with cutting-edge technologies, such as artificial intelligence (AI), the Internet of Things (IoT), big data, and new forms of business, including automated driving and intelligent connected vehicles. The key technologies for the construction and operation of smart roads include digital sensor networks, intelligent management systems, and interconnected service frameworks, among which sensor networks provide a data foundation. This study focuses on monitoring and detection technologies for road service performance, which constitute an integral part of the digital sensor networks of smart roads. Reviews were conducted, and observations were made, from three perspectives: embedded sensing of road service performance, automated detection of road surface defects, and intelligent identification of hidden road defects. Advancements and existing challenges faced by monitoring and detection technologies for road service performance were examined, and applications of AI in monitoring road service performance and detecting road service problems were elucidated. Finally, a roadmap for future research on sensing and detection for AI-powered road service performance was proposed. Breakthroughs are expected in four areas: establishing a “space-air-ground” multi-source three-dimensional monitoring and detection system, developing monitoring and detection technologies based on multi-source data fusion algorithms, building a digital twin base integrating the physical structures of roads, and creating a road control and service system that integrates end-edge-cloud collaboration. This comprehensive approach aims to advance the key technologies and theoretical foundations that are essential for the construction and operation of smart roads.