The Rural Access Index (RAI) is a measure of access, developed by the World Bank in 2006. It was adopted as Sustainable Development Goal (SDG) indicator 9.1.1 in 2015, to measure the accessibility of rural populations. It is currently the only indicator for the SDGs that directly measures rural access.The indicator relies on three major items of geospatial data: population, road network location and the "all-season" status of those roads. The RAI measures the proportion of the rural population that lives within 2 km of an all-season road, as defined below from the original World Bank study that initiated the RAI:

Rural roads play a crucial role in fostering economic and social development in Africa. Local Road Authorities (LRAs) struggle to collect road condition data using conventional means due to logistical and resource issues. Poor road conditions and restricted mobility have severe economic consequences for the transport of goods and services. Lack of maintenance can increase costs three-fold. In this work, a novel framework is proposed in which earth observations using high-resolution optical satellite imagery are applied to measure the condition of unpaved roads, providing a vital input to maintenance planning and prioritisation. A trial was conducted using this method on 83 roads in Tanzania totalling 131.7 km. The experimental results demonstrate that, by analysing variations in pixel intensity of the road surface, the condition can be estimated with an accuracy of 71.9% when compared to ground truth information. Machine Learning techniques are applied to the same network to test the performance of the system in predicting road conditions. A blended classifier approach achieves an accuracy of 88%. The proposed framework enables LRAs to define the information they receive based on their specific priorities, offering a rapid, objective, consistent and potentially cost-effective system that overcomes the current challenges faced by LRAs.

Survey vehicles, operating at traffic-speed, are deployed across the road network to assess the condition of road pavements. These apply high-quality (and high cost) equipment to measure condition. However, significant progress has been made in the development of low-cost sensors and data collection units that may have potential for application in highways. This project has aimed to understand the capabilities of this emerging technology. The project explores the technologies and combines a Raspberry-Pi based Data Acquisition System, compact camera, GPS, inertial measurement system, Wifi and 4G GSM comms and a low-cost Solid State LiDAR into a prototype device. The total cost is a few hundred pounds. Trials characterise the prototype system. Although the solid-state LiDAR sensors are not found to be robust in this application, the remaining sensors show strong potential for use in road condition assessment. A wider trial of the prototype system in a potential application – the measurement of roughness (IRI) on developing world road networks – was carried out in El Salvador. The prototype shows comparable performance with alternatives, combined with higher levels of practicality and capability, and the potential for higher levels of consistency through a common low-cost measurement platform. In the light of this research, it is felt that, following refinements to the prototype, the initial application for the device would be for condition surveys in developing world nations.

The application of consistent, reliable information is a key component of highway asset management. However, the tools to understand asset performance have developed rapidly over the last decade. These include asset surveys, intelligent infrastructure monitoring, crowd sourcing, remote sensing, data analytics and visualisation. However, their potential is not yet being fully exploited within the highway environment. By bringing these components of sensing and measurement together we could better understand highway assets and improve reactive and proactive decisions. This paper discusses the tools now available to understand the performance of highway assets. It explores their current and future capabilities, the benefits they bring, and the possibilities that could be achieved through their application within an integrated toolkit. Whilst these tools are not in themselves “new”, a key objective of the paper has been to highlight their emerging capabilities, bring awareness to highway asset managers, and encourage their take up. Increased application will inevitably lead to further development in capability and, importantly, accessibility. There are a number of challenges to overcome to draw full value from these technologies. These include the technical, commercial, and social barriers that influence development and accessibility. The paper discusses actions that could help overcome these, which are presented within the context of a roadmap to the implementation of an integrated toolkit. The roadmap is not definitive - it aims to stimulate further thinking, debate and discussion. The effective management of infrastructure assets is essential to deliver a clean, efficient, safe, reliable and accessible network. A joined up and collaborative approach will help the community achieve the benefits of the integrated toolkit that will help asset managers achieve this.