توسعه راهكاري مكان مند براي مسيريابي بهينه خطوط BRT

Development of spatiol network for optimal routing of BRT lines

زﻣﯿﻨﻪ و ﻫﺪف: روش ﻫﺎي ﻣﺘﻔﺎوﺗﯽ ﺗﺎﮐﻨﻮن ﺑﺮاي ﺗﻌﯿﯿﻦ اﻣﺘﺪاد ﯾﺎ ﻣﺴﯿﺮﯾﺎﺑﯽ در ﺳﯿﺴﺘﻢ ﻫﺎي ﺣﻤﻞ وﻧﻘﻞ ﻋﻤﻮﻣﯽ ﻃﺮاﺣﯽ و اراﯾﻪ ﺷﺪه اﻧﺪ. ﻣﺴﺄﻟﻪ ﻣﺴﯿﺮﯾﺎﺑﯽ ﺑﺮاي ﺳﯿﺴﺘﻢ ﻫﺎي ﺣﻤﻞ وﻧﻘﻞ ﻋﻤﻮﻣﯽ ﺷﻬﺮي ﺑﻪ ﺻﻮرت ﺗﻌﯿﯿﻦ ﻣﺤﻞ ﯾﺎ ﻣﻮﻗﻌﯿﺖ ﺑﻬﯿﻨﻪ اﯾﺴﺘﮕﺎه ﻫﺎ و اﻣﺘﺪاد ﻣﺴﯿﺮ در ﯾﮏ ﺷﻬﺮ ﺗﻌﺮﯾﻒ ﻣﯽ ﺷﻮد. روش ﺑﺮرﺳﯽ: ﻃﺮاﺣﺎن در ﺣﻞ اﯾﻦ ﻣﺴﺎﯾﻞ ﺑﺎ ﮔﺴﺘﺮه ي ﺑﺰرﮔﯽ از اﻧﻮاع ﻣﻌﯿﺎرﻫﺎ ﻣﻮاﺟﻪ ﻫﺴﺘﻨﺪ ﮐﻪ در اﯾﻦ ﻣﯿﺎن ﻣﻌﯿﺎرﻫﺎي ﻫﺰﯾﻨﻪ، زﻣﺎن و ﭘﻮﺷﺶ از ﻣﻬﻢ ﺗﺮﯾﻦ آن ﻫﺎ ﻣﯽ ﺑﺎﺷﻨﺪ. در اﯾﻦ ﻣﻘﺎﻟﻪ ﺑﻬﯿﻨﻪ ﺳﺎزي ﻣﺴﯿﺮﯾﺎﺑﯽ در ﻣﻨﻄﻘﻪ اي از ﺷﻬﺮ ﺗﻬﺮان ﺻﻮرت ﮔﺮﻓﺖ ﮐﻪ ﺗﻌﺪاد 9 ﺧﻂ اﺗﻮﺑﻮس از درون آن ﺗﺮدد ﻣﯽ ﮐﻨﺪ. در اﯾﻦ ﺗﺤﻘﯿﻖ ﺟﻬﺖ ﺑﻬﯿﻨﻪ ﻧﻤﻮدن ﺧﻄﻮط، ﻣﺒﺪأ و ﻣﻘﺼﺪ ﻫﺮ ﺧﻂ ﺑﺪون ﺗﻐﯿﯿﺮ در ﻧﻈﺮ ﮔﺮﻓﺘﻪ ﺷﺪ و ﻣﺴﯿﺮﻫﺎي اﺗﺼﺎﻟﯽ ﺑﯿﻦ آن ﻫﺎ ﻣﻮرد ﺑﻬﯿﻨﻪ ﺳﺎزي ﻗﺮا ﮔﺮﻓﺖ. ﺑﺮاي اﻧﺠﺎم اﯾﻦ ﻋﻤﻞ از 8 ﻓﺎﮐﺘﻮر )ﻇﺮﻓﯿﺖ ﺟﺎده )ﺳﻄﺢ ﺳﺮوﯾﺲ راه 5LOS(، ﮐﺎرﺑﺮي اراﺿﯽ، وﺿﻌﯿﺖ روﺳﺎزي، ﻋﺮض ﺧﻂ ﻋﺒﻮر، اﺟﺰا ﺳﻄﺢ ﻣﻘﻄﻊ راه، ﺣﻮزه ﻫﺎي ﺗﺮاﮐﻢ ﺟﻤﻌﯿﺖ و ﻃﻮل ﻫﺮ ﻟﺒﻪ )ARC(( اﻧﺘﺨﺎب ﺷﺪ. ﺑﺮ اﺳﺎس اﻫﻤﯿﺖ ﻫﺮ ﻓﺎﮐﺘﻮر در ﻣﺴﯿﺮﯾﺎﺑﯽ وزﻧﯽ ﺑﻪ آن ﻫﺎ داده ﺷﺪ. ﭘﺲ از اﺟﺮاي اﻟﮕﻮرﯾﺘﻢ داﯾﺠﺴﺘﺮا ﻣﺴﯿﺮ 5 ﺧﻂ اﺗﻮﺑﻮس ﺗﻐﯿﯿﺮ ﯾﺎﻓﺖ. ﺗﻐﯿﯿﺮ ﻣﺴﯿﺮ ﺧﻄﻮط ﺧﻮد ﺑﺎﻋﺚ ﻧﯿﺎز ﺑﻪ ﻣﮑﺎن ﯾﺎﺑﯽ اﯾﺴﺘﮕﺎه ﻫﺎي ﺟﺪﯾﺪ ﮔﺸﺖ. ﯾﺎﻓﺘﻪ ﻫﺎ: ﭘﺲ از ﺗﻌﯿﯿﻦ ﻣﻌﯿﺎرﻫﺎي ﻣﮑﺎن ﯾﺎﺑﯽ و اﯾﺠﺎد ﻻﯾﻪ ﻫﺎي دﺧﯿﻞ، 16 اﯾﺴﺘﮕﺎه ﺟﺪﯾﺪ ﻣﮑﺎن ﯾﺎﺑﯽ ﮔﺮدﯾﺪ. ﺳﭙﺲ ﺑﻪ ﺗﻮﺳﻌﻪ ﻣﺴﯿﺮﻫﺎي ﭘﯿﺸﻨﻬﺎدي ﺑﯿﻦ اﯾﺴﺘﮕﺎه ﻫﺎي ﻣﮑﺎن ﯾﺎﺑﯽ ﺷﺪه ﭘﺮداﺧﺘﻪ ﺷﺪ. ﺑﺤﺚ و ﻧﺘﯿﺠﻪ ﮔﯿﺮي: ﯾﮑﯽ از ﻣﻬﻢ ﺗﺮﯾﻦ ﺟﻨﺒﻪ ﻫﺎي ﻧﻮآوري اﯾﻦ ﭘﮋوﻫﺶ اﯾﻦ اﺳﺖ ﮐﻪ ﺑﺎ اﺳﺘﻔﺎده از ﺗﻮاﻧﻤﻨﺪي ﻫﺎي GIS ﺑﺘﻮان راﻫﮑﺎرﻫﺎﯾﯽ ﻧﻮﯾﻦ ﺑﺮاي ﻣﮑﺎن ﻣﻨﺪي و ﻣﺴﯿﺮﯾﺎﺑﯽ ﺑﻬﯿﻨﻪ ﺧﻄﻮط BRT اراﯾﻪ ﮐﺮد.

Background and Objective: Numerous routing methods of public transportation systems have been designed. The main challenge of optimum routing of urban public transportation systems is defined as the determination of the optimal locations of the stations and the routh lengths in a city. Method: To address the challeng designers are confronted with a wide range of criteria, among which cost, time and coathing are the most important ones. In this paper, routing optimization for a configuration of 9 bus lines in one of the Tehran districts was implemented. In order to optimize the bus routes, the origin and destination of each line were considered fixed and the intermediate routes were optimized. Eight factors consisting of: road capacity (LOS), land use, pavement status, crossing line width, components of road cross sections, population density and length of each edge (Arc) were selected for optimization process. According to the importance of each factor for routing, a special weighting coefficient were assigned to each criteria. After implementating Dijkstra algorithm, the routes of 5 bus lines must be changed. The line direction changing subsequently caused to new stations allocation requirement. Findings: After determining the allocation criteria and creating corresponding layers, 16 new stations were allocated. Finally, the proposed routes between these stations were identified. Discussion and Conclusion: One of the most important aspects of innovation in this study is the use of GIS capabilities to provide novel solutions for optimal routing of BRT lines