| Summary: | Roads represent a major long-term infrastructure investment. A well-managed and maintained road is therefore fundamental to the safety and availability of the road network as a whole. In carrying out pavement maintenance functions, Local Road Authorities face growing pressures arising from inadequate budgets and greater accountability, when many of the existing roads have reached the upper limits of their design life spans while being subjected to increasing traffic. There are many factors that influence the decision making process in pavement maintenance management, including road surface conditions, safety, traffic loading, cost, funding and prioritisation decisions, hence an efficient approach is vital to ensure optimisation and a satisfactory trade-off between conflicting factors. A Multi-criteria Decision Making (MCDM) approach is used to handle the trade-off between conflicting factors. It is processed in the Analytical Hierarchy Process (AHP) using Excel software, and the database developed in Excel is then imported into GIS in order to allow ease of query, analysis and visualisation of results. The main key output of this research will be the development of a GIS-based pavement maintenance management model to support decision making in pavement maintenance management. The most important factors influencing decision making in pavement maintenance management are established through a nationwide questionnaire survey, which is undertaken among the UK Local Authorities’ pavement maintenance experts. 14 factors were identified, which are: Remaining Service Life, Road Condition Indicator (RCI), Type of Deterioration, Observed Deterioration Rate, Traffic Diversion, Importance of Road/Classification, Annual Average Daily Traffic (AADT), Possible Conflict or Overlap with Other Road Works, Risk of failure, Safety Concern, Accident Rate (related to surface condition), Scheme Cost, Available Budget/Funding and Whole Life-Cycle Cost. Interviews were also conducted with experts in pavement maintenance within different Local Road Authorities to justify the rated factors affecting pavement maintenance prioritisation. The case study approach was adopted, based on Runnymede District roads within the Surrey County Council, for developing and testing the GIS-based decision support model. The output model was validated through interviews with four experts in pavement maintenance as target end-users, and the model was judged as a rational, simple and usable appropriate tool for network analysis as GIS. However, a risk of inadequate budgets might limit the practicability of the model.
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