Paylaşımlı E-Scooter Yerleştirmeye Yönelik Bir Karar Destek Sistemi: İstanbul İçin Vaka Çalışması

Abstract

Akıllı ve sürdürülebilir bir şehir, sakinlerinin yaşam kalitesini iyileştirmek için bilgi ve iletişim teknolojilerini kullanan, sağladığı hizmetlerde yenilikçi bir şehirdir. Bu şehirler, etkili hizmetler sunabilmek için çeşitli kaynaklardan toplanan açık verilerin kullanılmasıyla geliştirilmeli, yönetilmeli ve kontrol edilmelidir. Ulaşım, kente önemli veriler sağlayan temel hizmetlerinden biridir. Akıllı şehirlerdeki akıllı ulaşım sistemleri, ulaşım ağını oluşturan araç ve cihazların birbirleriyle etkileşime girmesini sağlayarak trafik sıkışıklığı, trafikte tüketilen yakıt miktarı gibi sorunların çözülmesine yardımcı olmaktadır. Ulaşım İstanbul’un önemli sorunlarından biridir ve bu nedenle örnek bir çalışma modeli olarak İstanbul şehri seçilmiştir. Kentlerde sürdürülebilir hareket kabiliyeti, ulaşım temelli problemler için uygun bir çözüm olarak görülmektedir. Elektrikli araçlar da düşük maliyetli ve sürdürülebilir ulaşım yöntemleridir. 2017'den bu yana e-scooter araçlarının da ulaşım sisteminin bir parçası olduğu görülmekte ve birçok şehir ulaşım alternatifi olarak paylaşımlı e-scooter sistemlerini kullanmaktadır. Ancak, e-scooter araçları şehirde rastgele yerlere yerleştirilmekte, yerleşim kararlarında herhangi bir algoritma kullanılmamaktadır. Buna bağlı olarak bazı bölgelerdeki kullanıcılar, bulundukları çevrede e-scooter olmaması nedeniyle paylaşım sisteminden tam olarak yararlanamamaktadır. Sosyal medya, çeşitli karar destek sistemlerinde yararlanılmak üzere değerli bilgiler toplayan yeni araçlardan biridir. Bu çalışmada sosyal medya ağlarından konum etiketlerini gerçek zamanlı toplayarak, Google Haritalar’dan sağlanan araç ve yaya trafiği bilgilerini Analitik Hiyerarşi Yöntemi (AHP) ile belirlenen İstanbul’daki bölge alternatifleriyle birleştiren prototip bir sistem geliştirilmiştir. Böylelikle e-scooter araçlarının konumlandırılma seçenekleri trafik uygulamalarından ve sosyal medyadan gelen verilere göre değişmekte ve oluşturan prototip e-scooter araçlarının şehir içinde ihtiyaç olduğu yerlere zamanında yerleştirilmesine yardımcı olmaktadır.

Keywords

• Akıllı ve sürdürülebilir şehirler
• Analitik hiyerarşi yöntemi
• Karar destek sistemleri
• Paylaşımlı e-scooter sistemleri
• Sosyal medya.

A Decision Support System for Placing Shared E-Scooters: A Case Study for Istanbul

Abstract

A smart and sustainable city should be an innovative city that uses information and communication technologies to improve the quality of life via its operations. They need to be planned, managed, and regulated by open data collected through different data sources to provide efficient services. Transportation services can be accepted as one of the essential services of a city. In smart cities, intelligent transportation systems help to solve problems such as traffic congestion or the amount of fuel spent in traffic by providing communication between vehicles and devices that build the whole transportation network. In order to achieve the success of intelligent transportation systems, transportation methods should be planned dynamically according to the collected data and the requirements of the city's transportation network. E-scooters are also a part of the transportation system, and since 2017, shared e-scooter systems have been used as a transportation alternative in some cities. However, e-scooters are placed in random locations in cities without relying on a precise algorithm. Thus, users in some locations cannot benefit from the e-scooter sharing system efficiently due to the lack of e-scooter in neighborhoods. In this study, a decision support system for e-scooter sharing systems is suggested, which helps to place e-scooters dynamically in areas that are needed in the city. This system is intended to offer select options by combining the traffic density information of the regions and alternative region data provided by the multi-criteria analysis made using the Analytical Hierarchy Method (AHP) with real-time social media data.

Keywords

• Analytic hierarchy process
• Decision support systems
• Shared e-scooter systems
• Smart and sustainable cities
• Social media

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