Studying the Effect of Gravel Roads Geometric Features on Corrugation Behavior

Daoud, Osama Abu; Ksaibati, Khaled

doi:10.1007/s42947-021-00110-5

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…Generally, the surface layer properties of gravel roads can undergo significant changes from one day to another due to intense rainfall and high local traffic levels. Abu Daoud & Ksaibati (2021) found more severe corrugation at curves and steep slopes on gravel roads, indicating that geometric features affect the deterioration. The study by Albatayneh et al (2021) compared various factors, including annual daily truck traffic, dust levels, ride quality, access road width, terrain, speed, and average annual daily traffic, on their impact on the overall LOS rating for gravel roads.…”

Section: Gravel Roads Deterioration and Maintenancementioning

confidence: 99%

“…Smartphones are becoming famous for gravel road condition assessment and have been used to capture images (Abu Daoud & Ksaibati, 2021;Albatayneh et al, 2021) and vibration data (Aleadelat et al, 2018) of gravel roads. The vehicle type, suspension condition, and driving speed influence the vibration response from a smartphone (Edvardsson et al, 2015).…”

Section: Objective Assessment Of Gravel Roadsmentioning

confidence: 99%

“…Thermal cameras and smartphones can cost-effectively estimate surface roughness and ride quality of gravel roads (Aleadelat et al, 2018;Marinello et al, 2017). While most objective assessment research has focused on road surface roughness, dust (Abu Daoud & Ksaibati, 2021) and loose gravel (Saeed et al, 2021) are receiving attention. Furthermore, ongoing research exploits digital image processing techniques for pattern recognition, feature extraction and gravel road classification (Albatayneh et al, 2019).…”

Section: Objective Assessment Of Gravel Roadsmentioning

confidence: 99%

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On the establishment of a data-driven approach to gravel road maintenance

Mbiyana¹

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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.

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Section: Gravel Roads Deterioration and Maintenancementioning

confidence: 99%