A survey of sensor suite designs for vehicle-based road surface condition sensing

Maintaining high-quality road surface conditions is essential for improving traffic safety, reducing vehicle operating costs, and supporting effective infrastructure management. Conventional inspection approaches, including manual surveys and specialised inspection vehicles, are expensive, infrequent, and difficult to scale, while non-vehicle-based methods such as roadside cameras and embedded sensors suffer from limited spatial coverage. Recent advances in sensing, computing, and connected vehicle technologies have enabled the paradigm of vehicles as mobile sensing platforms, allowing continuous, scalable, and cost-effective road surface monitoring. However, existing review studies largely focus on smartphone-based sensing, leaving critical gaps in the understanding of vehicle-mounted and onboard sensor suite designs and their system-level integration. This paper presents a systematic and critical review of vehicle-based road surface condition monitoring approaches that employ either external sensor suites or native vehicular sensors. Using a structured multi-database search protocol, 36 high-quality studies are analysed to develop a technical taxonomy of sensing modalities, data processing pipelines, and system architectures. Key implementation challenges related to sensor fusion, data quality, scalability, and deployment readiness are identified, and emerging research directions are discussed to support the development of next-generation, data-driven road monitoring systems.