مهران اسدي

The existing definitions of sustainable transportation in various sources indicate that a sustainable transportation system strives for a balance between different aspects of transportation sustainability. Each aspect encompasses specific goals that can be eva‎luated using various indicators. One such indicator used to assess the sustainability of urban transportation is the public transit share. Due to its numerous advantages, public transit has consistently remained a focal point for urban planners. However, research on various cities reveals that a city with a high public transit share does not necessarily indicate a good status in terms of transportation sustainability Other sustainability indicators also play a significant role in achieving sustainable transportation. The objective of this study is to estimate the public transit share based on the socio-economic characteristics of a city, along with other indicators of sustainable transportation, in order to establish a sustainable transportation system. To achieve this, we initially identified cities with commendable transportation sustainability and examined the relationship between socio-economic characteristics, sustainable transportation indicators, and their corresponding public transit share through correlation analysis. Subsequently, we developed several models using regression analysis and artificial neural networks. Finally, employing these models, we estimated the public transit share in Shiraz, Iran, taking into account factors such as population, business density, GDP, and more. Based on the results obtained, it is necessary to increase the public transit share in Shiraz from the current 14% to 45.55% by the target year, aligning with the principles of sustainability.

حمل‌ونقل پايدار , سهم حمل‌ونقل همگاني , مدل رگرسيون چندگانه , شبكه عصبي مصنوعي , شاخص‌هاي پايداري

Sustainable transportation , public transit share , Multiple regression model , Artificial neural network , Sustainability indicators

Mehran Asadi

Dr. Reza Golshan Khavas Dr. ‪Shahriar Afandizadeh