Using fuzzy inference systems to evaluate sidewalk quality in Ahvaz, Iran

Sidewalks and pedestrians are vital components of urban life, playing a crucial role in sustaining the sustainability and livability of cities. High-quality sidewalks contribute to creating safer and more vibrant urban spaces. Given the significant social, economic, and cultural benefits of walking, efforts to improve sidewalk conditions have attracted considerable attention in recent years. This study seeks to evaluate the condition and quality of urban sidewalks in Ahvaz, a city in southwestern Iran. The assessment is based on data collected through questionnaires completed by geography and urban planning experts. A fuzzy inference system implemented in MATLAB software was employed to identify the rules underlying the evaluation of sidewalk quality. Subsequently, the questionnaire data were analyzed using Entropy, WASPAS, and IDW interpolation methods. The analysis resulted in the identification of 18 distinct rules for assessing sidewalk quality. The findings indicate that sidewalks in Region Three exhibit the highest quality, while those in Region Seven rank the lowest. Overall, the study reveals that most sidewalks in Ahvaz are of very poor quality, with issues such as unsuitable slopes being significant contributing factors.