Mohammad Salim Ferwati, Arezou Shafaghat, Ali Keyvanfar


Transportation is the major contributor of ever-increasing CO2 and Greenhouse Gas emissions in cities all around the world; while the number of vehicles is rapidly growing. Growing concern on reducing transportation hazardous emissions and securing energy sources has led to New Urbanism and Smart Growth policies declarations. The urban and transportation professionals are attempting to develop innovative techniques to change people‘s travel mode selection to less energy-intensive modes, particularly, cycling. The current research has developed an urban index assessment model evaluates and analyzes cyclability of path segments in association with residents‘ decision making in cyclable route selection, called Path Cyclability Assessment Index (PACEX). The model was developed based on decision-tree-making (DTM) method to measure the qualitative data quantifiable. The model involves ninety (90) physical and environmental cyclability variables clustered into three layers of decision-tree-making (Layer 1: Features, Layer 2: Criteria, Layer 3: Sub-criteria). Although the model is applicable in any neighborhood, this research was implemented it in Doha, Qatar where specially needs for hosting FIFA 2022. The analysis result shows the sub-criterion F1.C1.S2 Existence of Crossing mostly affects to neighborhood cyclability (24.25%), in contrast, the sub-criterion F1.C3.S7 Street Surveillance affects least (4.82%); and overall neighborhood was ranked as grade B of cyclability ranking. The model supports both personal and society needs, preferences, and priorities of cyclable environment design and development. Using this model contributes to less energy consumption, less CO2 and GHG emissions, less street fatalities and accidents, simultaneously, promotes public health. Juxtaposing using the PACEX model aids decision makers and policy makers in sustainable urban development in prioritizing the allocation of resources for development and/or redevelopment of the area concerned.


Transportation, Low-emission urban development, decision tree making, path optimization, traffic congestion

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