Developing sustainable road infrastructure performance indicators using a model-driven fuzzy spatial multi-criteria decision making method

Road infrastructure performance is closely associated with passengers and freight transportation systems socio-economic development. The of road commonly measured by sensor-monitored indicators, the ability monitored indicators in revealing actual generally determined decision makers users. However, it usually unreliable to directly apply evaluation, due limited aspects individual potential biases uncertainties human experience. To address issues, this study proposes a model-driven fuzzy spatial multi-criteria making (MFSD) approach derive comprehensive accurate indicator sustainable performance. In study, MFSD applied exploring network Wheatbelt region Western Australia, Australia. Spatial variables properties, traffic vehicles climate conditions are used as criteria making. Four sensor collected for estimating contributions criteria. Results show that MFSD-based can more comprehensively accurately characterize area, improve 30.46% correlation maintenance cost compared roughness, which optimal indicator. At local government areas, explain 45.8% practical cost. Sensitivity analysis from multiple indicates reliable method proposed have broad potentials network-level management.