Gravel roads are essential for economic development as they facilitate the movement of people, transportation of goods and services, and promote cultural and social development. They typically connect sparsely populated rural areas to urban centres, providing essential access for residents and entrepreneurs. Maintaining these roads to an acceptable level of service is crucial for the efficient and safe transportation of goods and services. However, substantial maintenance investmentis required, yet resources are limited. Gravel roads are prone to dust, potholes, corrugations, rutting and loose gravel. They deteriorate faster than paved roads, and their failure development is affected by traffic action and physical, geometric and climatic factors. Thus, more condition monitoring and proper road condition assessment are necessary for dynamic maintenance planning to reach efficiency and effectiveness using objective, data-driven condition assessment methods to ensure all-year-round access.

However, objective data-driven methods (DDMs) are not frequently used for gravel road condition assessment, and where they have been applied, the practical implementation is limited. Instead, visual windshield assessment and manual methods are predominant. Visual assessments are unreliable and susceptible to human judgement errors, while manual methods are time-consuming and labour-intensive. Maintenance activities are predetermined despite dynamic maintenance needs, and the planning is based on historical failure data rather than the actual road condition. This thesis establishes a data-driven approach to gravel road maintenance describing the systematic assessment of the gravel road condition and collection of the condition data to ensure efficient and effective maintenance planning. This thesis uses a design research methodology based on a literature review, concept development, interview study and field experiments.

A holistic approach is proposed for data-driven maintenance of gravel roads encompassing objective condition data collection, processing, analysing, and interpreting the findings for obtaining reliable information concerning the condition to gravel road decision support by utilising the opportunities presented by technological advancements, particularly sensor technology. Then, decision-making is primarily influenced by the objectively collected gravel road condition data rather than the evaluator’s perception or experience. The successful implementation of a data-driven approach depends on the quality of the collected data; therefore, data relevance and quality are emphasised in this thesis. The lack of data quality and relevance hinders effective data utilisation, leading to less precisionin decision-making and ineffective decisions.

Furthermore, the thesis proposes a participatory data-driven approach for unpaved road condition monitoring, allowing road users to be part of the maintenance process and providing an efficient and effective alternative for collecting road condition data and accomplishing broad coverage at minimum cost. A top-down iiapproach for data-driven gravel road condition classification is proposed to achieve an objective assessment to address the lack of readily available quality and relevant condition data. The established data-driven approach to gravel road maintenance is evaluated and verified with field experiments on three gravel roads in Växjö municipality, Southern Sweden. The research findings indicate that properly implementing a data-driven approach to gravel road maintenance would ensure efficient and effective condition assessment and classification, which are a basis for a maintenance management system of gravel roads and enable road maintainers and authorities to achieve cost-effective decision-making. 

Unpaved roads, usually found in rural and sparsely populated areas, are prone to dust, potholes, corrugations, rutting and loose gravel and deteriorate faster than paved roads. Currently, subjective visual surveys and manual methods for monitoring and assessing the condition of unpaved roads dominate. In contrast, data-driven objective methods must be applied holistically for maintenance planning and decision-making. The paper proposes a participatory data-driven approach for unpaved road condition monitoring based on the literature and an exploratory case study of road maintenance practices in  Sweden and Zambia. Participatory data collection and sensing empower regular unpaved road users to collect road condition data with their smartphones using applications embedded with a global positioning system (GPS) while driving on an unpaved road and carrying out their typical day-to-day activities. The data is shared with the road governing bodies and processed to establish the current road condition (Nowcasting) and the expected future condition (Forecasting). The proposed approach allows road users to be part of the maintenance process, minimising the cost of collecting and evaluating road condition data, resulting in improved unpaved road maintenance planning and decision-making for unpaved roads. Based on the literature and the case study findings, participatory data collection and sensing for unpaved roads can provide an efficient and effective alternative for collecting road condition data, accomplishing broad coverage. The data collected can provide valuable information for unpaved road condition monitoring and maintenance planning and potentially improve unpaved road management. However, the participating road users must be trained in data acquisition to ensure quality data collection.

Unpaved roads, usually found in rural and sparsely populated areas, are prone to dust, potholes, corrugations, rutting and loose gravel and deteriorate faster than paved roads. Thus, they require regular condition monitoring to keep them at the required level of service. However, the cost of condition assessment could be huge, considering how vast and far away they are from the cities. Currently, subjective visual surveys and manual methods for monitoring and assessing the condition of unpaved roads dominate, while data-driven objective methods are not commonly applied for maintenance planning and decision-making. The paper proposes a participatory data-driven approach for unpaved road condition monitoring based on the literature and an exploratory case study of road maintenance practices in Sweden and Zambia. Participatory data collection empowers regular unpaved road users to collect road condition data, for instance, by equipping their vehicles with the relevant data acquisition devices embedded with a global positioning system (GPS) as they drive on unpaved roads on a typical day. By integrating open data collection aligned with sustainable practices, regular unpaved road users (garbage collectors, postal service providers, and road owners) share the collected condition data with the road governing bodies and process it for Nowcasting and Forecasting the unpaved road condition, thus providing valuable information for condition monitoring of unpaved roads. Thus, road users can support long-term maintenance planning and decision-making, potentially improving unpaved road management and minimising the cost of collecting and evaluating unpaved road condition data. However, the participating road users require training in data acquisition, and the vehicles must be calibrated according to the sensor properties, vehicle vibration response and speed to ensure quality data collection. Based on the literature and the case study findings, participatory data collection for unpaved roads can provide an efficient and effective alternative for collecting road condition data, accomplishing broad coverage.

Gravel roads are important assets forgeographically sparse countries, but the maintenance of theseroads is costly and inefficient. In addition, as failure developmentis highly affected by environmental factors, the planning shouldbe dynamic for reaching efficiency and effectiveness, which isachieved by data-driven maintenance approaches. This paperproposes applying a data-driven approach in gravel roadmaintenance following the steps of the OSA-CBM specifications.The conceptual approach is developed and illustrated based on thefindings of an extensive literature review. The approach thuscontextualises OSA-CBM in gravel road maintenance and pointsout further development and research areas. It was found that theresearch has mainly focused on data acquisition techniques, roadcondition classification, diagnostics, and deterioration models,while data manipulation methods and prognostic models forgravel roads are rather unresearched areas. In addition, a holisticapproach towards data-driven maintenance of gravel roads iscurrently lacking. In this perspective, the approach presented inthis paper could serve as a base for the further development ofdata-driven methods to reach efficient and effective gravel roadmaintenance practices.

Gravel roads form a significant share of the global road network, usually in sparsely populated rural areas. They are important, especially in agriculture, tourism, and forestry, connecting rural to urban areas. This systematic literature study comprises 105 reviewed publications on gravel road maintenance. Review articles on maintenance management practices, especially concerning objective condition assessment and data-driven methods (DDMs), are lacking. Therefore, this review provides a concise overview of current gravel road maintenance practices and ongoing research on objective condition assessment and DDMs for gravel road maintenance. It offers researchers in gravel road maintenance and other related fields a clear indication of where to focus their research efforts, as it suggests the direction for future research. Visual assessment methods are predominant for monitoring the condition of gravel roads, while objective methods and DDMs are not common. Research on gravel roads and their maintenance has increased in the last two decades, especially in North America and Northern Europe. Condition assessment is shifting from subjective to objective methods, utilizing knowledge from technological advancements in image processing, vibration and acoustics analysis, and so forth. There are some excellent research initiatives for objectively assessing the condition of gravel roads and DDMs, but the practical implementation is limited. Implementing objective assessment methods and DDMs generally improves the management of gravel roads with regard to decision-making, maintenance costs, safety, and the stability and comfort of the ride. Objective condition assessment and DMs have the potential to enhance maintenance practices in the maintenance of gravel roads.