AKILLI ŞEHİRLER KAPSAMINDA YAPAY ZEKÂ TEKNİKLERİ KULLANARAK ETKİN ULAŞIM PLANLARININ OLUŞTURULMASI ÜZERİNE BİR MODEL ÖNERİSİ
Abstract
Akıllı şehirler kapsamında her şehir
için farklı konularda çalışma yapılabilirken, ulaşım hizmetinin bütün akıllı
şehir örneklerinde oldukça önemli olduğu görülmüştür. Ulaşım hizmetinin akıllı
şehir kapsamında değerlendirilebilmesi için ulaşım planlanmasının etkin olarak
hazırlanması gerekmektedir. Ulaştırma sistemlerinin etkin bir şekilde
kullanımını sağlayabilmek amacıyla hazırlanan Toplu Ulaşım Ana Planları, uzman
kişiler tarafından belirli periyotlarda hazırlanmaktadır. Bu çalışmada, ulaşıma
etki eden faktörlerin ve parametrelerin dinamik bir yapıda toplanarak yapay
zekâ teknikleri analizleri neticesinde otomatik planların hazırlanması ve etkin
toplu ulaşım faaliyetlerinin yürütülmesi ile çevre kirliliğine, trafik
yoğunluğuna, yüksek maliyet problemlerine çözüm getirilmesi, bunun sonucunda,
belirli periyotlarda hazırlanan ulaşım planlaması iş yükü ve maliyetinin
azaltılması hedeflenmektedir. Gerçekleşen ulaşım hareketlerinin kayıt altında
tutulması ile ileride oluşacak olan ulaşım hareketlerinin analizi yapılabilecek
ve gelecekte gerçekleşmesi beklenen ulaşım hareketlerinin düşük bir yanılma
payı ile yaklaşık olarak tahmin edilerek ulaşım planlanmasının somut bir
bilgiye bağlı kalarak yapılması amaçlanmaktadır.
References
- Goodspeed, R. (2014). Smart cities: moving beyond urban cybernetics to tackle wicked problems. Cambridge Journal of Regions, Economy and Society, 8(1), 79-92.
- Glasmeier, A., & Nebiolo, M. (2016). Thinking about smart cities: The travels of a policy idea that promises a great deal, but so far has delivered modest results. Sustainability, 8(11), 1122.
- Hızlı Menü Otobüs Saatleri. (2019, 9 Ocak) Erişim Adresi: http://www.eskisehir.bel.tr/otobus_saatleri_dvm.php?otobus_hat_id=102&menu_id=57
- Ayataç, H. (2016). Kentsel Ulaşım Planlaması ve İstanbul. İTÜ Vakfı Dergisi, 71, 31-35.
- Ling, Y., Zong-fu, J., Shou-xu, J., Xiang-min, R., & Fu-sheng, Z. (2017, August). Urban night bus routes planning with taxi traces. In 2017 12th International Conference on Computer Science and Education (ICCSE) (pp. 375-379). IEEE.
- Neumann, T. (2017, April). Fuzzy Routing Algorithm in Telematics Transportation Systems. In International Conference on Transport Systems Telematics (pp. 494-505). Springer, Cham.
- Chen, Y., Ardila-Gomez, A., & Frame, G. (2017). Achieving energy savings by intelligent transportation systems investments in the context of smart cities. Transportation Research Part D: Transport and Environment, 54, 381-396.
- Franklina, R. S., van Leeuwenb, E. S., & Paezc, A. (2018). Transportation where people leave: An introduction. Population Loss: The Role of Transportation and Other Issues, 2, 1.
A MODEL PROPOSAL ON THE PREPARATION OF EFFECTIVE TRANSPORTATION PLANS USING ARTIFICIAL INTELLIGENCE TECHNIQUES WITHIN THE CONTEXT OF SMART CITIES
Abstract
While it is possible to work on different topics for
each city within the scope of smart cities, it is seen that transportation service
is very important in all smart city examples. In order to evaluate the
transportation service within the scope of smart city, transportation planning
must be prepared effectively. The Public Transportation Master Plans, which are
prepared in order to ensure the efficient use of transportation systems, are
prepared by experts in certain periods. In this study, by gathering the factors
and parameters affecting the transportation in a dynamic structure, preparing
automatic plans as a result of artificial intelligence techniques, and carrying
out effective public transportation activities, solving environmental
pollution, traffic density, high cost problems, and consequently,
transportation planning workload prepared in certain periods. and to reduce its
cost. It is aimed to carry out the transportation planning by adhering to a
concrete information by keeping a record of the realized transportation
movements and to analyze the transportation movements that will occur in the
future and to estimate the transportation movements that will be realized in
the future with a low margin of error.
Keywords
smart city artificial intelligent geographical information systems transportation planning effective transportation
References
- Goodspeed, R. (2014). Smart cities: moving beyond urban cybernetics to tackle wicked problems. Cambridge Journal of Regions, Economy and Society, 8(1), 79-92.
- Glasmeier, A., & Nebiolo, M. (2016). Thinking about smart cities: The travels of a policy idea that promises a great deal, but so far has delivered modest results. Sustainability, 8(11), 1122.
- Hızlı Menü Otobüs Saatleri. (2019, 9 Ocak) Erişim Adresi: http://www.eskisehir.bel.tr/otobus_saatleri_dvm.php?otobus_hat_id=102&menu_id=57
- Ayataç, H. (2016). Kentsel Ulaşım Planlaması ve İstanbul. İTÜ Vakfı Dergisi, 71, 31-35.
- Ling, Y., Zong-fu, J., Shou-xu, J., Xiang-min, R., & Fu-sheng, Z. (2017, August). Urban night bus routes planning with taxi traces. In 2017 12th International Conference on Computer Science and Education (ICCSE) (pp. 375-379). IEEE.
- Neumann, T. (2017, April). Fuzzy Routing Algorithm in Telematics Transportation Systems. In International Conference on Transport Systems Telematics (pp. 494-505). Springer, Cham.
- Chen, Y., Ardila-Gomez, A., & Frame, G. (2017). Achieving energy savings by intelligent transportation systems investments in the context of smart cities. Transportation Research Part D: Transport and Environment, 54, 381-396.
- Franklina, R. S., van Leeuwenb, E. S., & Paezc, A. (2018). Transportation where people leave: An introduction. Population Loss: The Role of Transportation and Other Issues, 2, 1.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Computer Software |
| Journal Section | Articles |
| Authors | |
| Publication Date | February 25, 2020 |
| Published in Issue | Year 2020 Volume: 3 Issue: 1 |
