Evaluation of Urban Intelligent Transportation Systems from an Environmental Sustainability Perspective Using the TOPSIS Method

Öz

This study uses the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method to evaluate the performance of intelligent transportation systems from an environmental sustainability perspective. Four different transportation systems were analyzed: electric bus system (EBS), shared electric scooter system (SESS), autonomous vehicle sharing system (AVSS) and intelligent bicycle sharing system (IBSS). The analysis was carried out in line with the criteria of carbon emission reduction, energy efficiency, resource utilization, impact on air quality and use of renewable energy. According to the analysis results, the EBS performed the best with the highest relative proximity value. EBS shows superior performance in terms of carbon emission reduction and energy efficiency, and optimizes resource use by reducing fossil fuel use. IBSS ranked second and stands out as an environmentally friendly alternative. The AVSS ranks third and performs lower than the other systems in terms of energy efficiency and resource utilization. The SESS performed the lowest. The findings provide important information for urban planners and policy makers and contribute to the identification of the most appropriate options in line with the environmental sustainability goals of intelligent transportation systems.

Anahtar Kelimeler

• Intelligent bicycle sharing system
• electric bus system
• autonomous vehicle sharing system
• shared electric scooter system
• TOPSIS

Çevresel Sürdürülebilirlik Perspektifinden Şehir İçi Akıllı Ulaşım Sistemlerinin TOPSIS Analizi ile Değerlendirilmesi

Öz

Bu çalışma, çevresel sürdürülebilirlik perspektifinden akıllı ulaşım sistemlerinin performanslarını değerlendirmek amacıyla TOPSIS (İdeal Çözüme Benzerlik ile Tercih Sıralama Tekniği) yöntemini kullanmıştır. Elektrikli otobüs sistemi (EOS), paylaşımlı elektrikli skuter sistemi (PESS), otonom araç paylaşım sistemi (OAPS) ve akıllı bisiklet paylaşım sistemi (ABPS) olmak üzere dört farklı ulaşım sistemi analiz edilmiştir. Analiz; karbon emisyonlarının azaltılması, enerji verimliliği, kaynak kullanımı, hava kalitesine etki ve yenilenebilir enerji kullanımı kriterleri doğrultusunda gerçekleştirilmiştir. Analiz sonuçlarına göre, EOS en yüksek göreceli yakınlık değeriyle en iyi performansı sergilemiştir. EOS, karbon emisyonlarının azaltılması ve enerji verimliliği konularında üstün performans göstermekte ve fosil yakıt kullanımını azaltarak kaynak kullanımını optimize etmektedir. ABPS ikinci sırada yer alarak çevre dostu bir alternatif olarak öne çıkmaktadır. OAPS üçüncü sırada yer almakta olup, enerji verimliliği ve kaynak kullanımı açısından diğer sistemlere göre daha düşük performans sergilemektedir. PESS ise en düşük performansı göstermiştir. Bulgular, şehir plancıları ve politika yapıcılar için önemli bilgiler sunmakta olup, akıllı ulaşım sistemlerinin çevresel sürdürülebilirlik hedefleri doğrultusunda en uygun seçeneklerin belirlenmesine katkı sağlamaktadır.

Anahtar Kelimeler

• Akıllı bisiklet paylaşım sistemi
• elektrikli otobüs sistemi
• otonom araç paylaşım sistemi
• paylaşımlı e-skuter sistemi
• TOPSIS

Kaynakça

1. Akande, N. O., Arulogun, O. T., Ganiyu, R. A. ve Adeyemo, I. A. (2018). Improving the quality of service in public road transportation using real time travel information system. World Review of Intermodal Transportation Research, 7(1), 57-79. https://doi.org/10.1504/WRITR.2018.089529
2. Aslan, H. M., Yıldız, M. S. ve Uysal, H. T. (2015). Application of fuzzy TOPSIS method on location selection of disaster stations: A location analysis in Düzce. Journal of Politics, Economics and Management Research, 3(2), 111-128.
3. Auer, A., Feese, S., Lockwood, S. ve Hamilton, B. A. (2016). History of intelligent transportation systems. United States Department of Transportation. https://rosap.ntl.bts.gov/view/dot/30826
4. Barth, M. J., Wu, G. ve Boriboonsomsin, K. (2015). Intelligent transportation systems and greenhouse gas reductions. Current Sustainable/Renewable Energy Reports, 2(3), 90-97. https://doi.org/10.1007/s40518-015-0032-y
5. Behzadian, M., Otaghsara, S. K., Yazdani, M. ve Ignatius, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with Applications, 39(17), 13051-13069. https://doi.org/10.1016/j.eswa.2012.05.056
6. Bhaskar, A. S., Khan, A. ve Patre, S. R. (2021). Application potential of fuzzy embedded TOPSIS approach to solve MCDM based problems. Intelligent manufacturing içinde (ss. 99-121), Springer. https://doi.org/10.1007/978-3-030-50312-3_5
7. Brakewood, C. ve Watkins, K. (2019). A literature review of the passenger benefits of real-time transit information. Transport Reviews, 39(3), 327-356. https://doi.org/10.1080/01441647.2018.1472147
8. Brennand, C. A., Filho, G. P. R., Maia, G., Cunha, F., Guidoni, D. L. ve Villas, L. A. (2019). Towards a fog-enabled intelligent transportation system to reduce traffic jam. Sensors, 19(18), 3916, 1-29. https://doi.org/10.3390/s19183916

9. Browne, M., Allen, J. ve Leonardi, J. (2012). Evaluating the use of an urban consolidation centre and electric vehicles in central London. IATSS Research, 35(1), 1-6. https://doi.org/10.1016/j.iatssr.2011.06.002
10. Camodeca, R. ve Almici, A. (2021). Digital transformation and convergence toward the 2030 agenda’s sustainability development goals: Evidence from Italian listed firms. Sustainability, 13(21), 11831-11849. https://doi.org/10.3390/su132111831
11. Carter, C. R. ve Rogers, D. S. (2008). A framework of sustainable supply chain management: Moving toward new theory. International Journal of Physical Distribution & Logistics Management, 38(5), 360-387. https://doi.org/10.1108/09600030810882816
12. Chandrappa, S., Guruprasad, M. S., Kumar, H. N., Raju, K. ve Kumar, D. S. (2023). An IoT-based automotive and intelligent toll gate using RFID. SN Computer Science, 4(2), 154, 1-15. https://doi.org/10.1007/s42979-022-01569-0
13. Chen, S. J. ve Hwang, C. L. (1992). Fuzzy multiple attribute decision making: Methods and applications. Springer-Verlag.
14. Chen, F., Yang, B., Zhang, W., Ma, J., Lv, J. ve Yang, Y. (2017). Enhanced recycling network for spent e-bicycle batteries: A case study in Xuzhou, China. Waste Management, 60, 660-665. https://doi.org/10.1016/j.wasman.2016.09.027
15. Cheng, Z., Pang, M. S. ve Pavlou, P. A. (2020). Mitigating traffic congestion: The role of intelligent transportation systems. Information Systems Research, 31(3), 653-674. https://doi.org/10.1287/isre.2019.0894
16. Cho, S., Shrestha, B., Salah, B., Ullah, I. ve Salem, N. M. (2022). A proposed waiting time algorithm for a prediction and prevention system of traffic accidents using smart sensors. Electronics, 11(11), 1765, 1-19. https://doi.org/10.3390/electronics11111765
17. Crawford, D. (2021). Benefits of ITS. Road Network Operations Intelligent Transport Systems. https://rno-its.piarc.org/en/its-basics/benefits-its
18. De Oliveira, L. F. P., Manera, L. T. ve Da Luz, P. D. G. (2020). Development of a smart traffic light control system with real-time monitoring. IEEE Internet of Things Journal, 8(5), 3384-3393. https://doi.org/10.1109/JIOT.2020.3022392
19. Desertot, M., Lecomte, S., Gransart, C. ve Delot, T. (2012). Intelligent transportation systems. Computer Science and Ambient Intelligence, 285-306. https://doi.org/10.1002/9781118580974.ch13
20. Dreier, D., Silveira, S., Khatiwada, D., Fonseca, K. V., Nieweglowski, R. ve Schepanski, R. (2018). Well-to-Wheel analysis of fossil energy use and greenhouse gas emissions for conventional, hybrid-electric and plug-in hybrid-electric city buses in the BRT system in Curitiba, Brazil. Transportation Research Part D: Transport and Environment, 58, 122-138. https://doi.org/10.1016/j.trd.2017.10.015
21. Du, H. ve Kommalapati, R. R. (2021). Environmental sustainability of public transportation fleet replacement with electric buses in Houston, a megacity in the USA. International Journal of Sustainable Engineering, 14(6), 1858-1870. https://doi.org/10.1080/19397038.2021.1972491
22. Du, L. ve Dao, H. (2014). Information dissemination delay in vehicle-to-vehicle communication networks in a traffic stream. IEEE Transactions on Intelligent Transportation Systems, 16(1), 66-80. https://doi.org/10.1109/TITS.2014.2326331
23. Elassy, M., Al-Hattab, M., Takruri, M. ve Badawi, S. (2024). Intelligent transportation systems for sustainable smart cities. Transportation Engineering, 16, 100252-100270. https://doi.org/10.1016/j.treng.2024.100252
24. Fagnant, D. J. ve Kockelman, K. M. (2014). The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios. Transportation Research Part C: Emerging Technologies, 40, 1-13. https://doi.org/10.1016/j.trc.2013.12.001
25. Fan, Y. ve Zheng, S. (2020). Dockless bike sharing alleviates road congestion by complementing subway travel: Evidence from Beijing. Cities, 107, 102895, 1-16. https://doi.org/10.1016/j.cities.2020.102895
26. Fleming, G. (2009). Best practices for implementing quality control and quality assurance for tunnel inspection.. https://transportationops.org/research/best-practices-implementing-quality-control-and-quality-assurance-tunnel-inspection#downloads
27. Ganesh, K., Thrivikraman, M., Kuri, J., Dagale, H., Sudhakar, G. ve Sanyal, S. (2012). Implementation of a real time passenger information system. arXiv preprint arXiv:1206.0447, 1-14. https://doi.org/10.48550/arXiv.1206.0447
28. Geels, F. W., Kemp, R., Dudley, G. ve Lyons, G. (2012). Automobility in transition? A socio-technical analysis of sustainable transport. Routledge.
29. Guerrero-Ibanez, J. A., Zeadally, S. ve Contreras-Castillo, J. (2015). Integration challenges of intelligent transportation systems with connected vehicle, cloud computing, and internet of things technologies. IEEE Wireless Communications, 22(6), 122-128. https://doi.org/10.1109/MWC.2015.7368833
30. Hamilton, T. L. ve Wichman, C. J. (2018). Bicycle infrastructure and traffic congestion: Evidence from DC's capital bikeshare. Journal of Environmental Economics and Management, 87, 72-93. https://doi.org/10.1016/j.jeem.2017.03.007
31. Hollingsworth, J., Copeland, B. ve Johnson, J. X. (2019). Are e-scooters polluters? The environmental impacts of shared dockless electric scooters. Environmental Research Letters, 14(8), 084031, 1-10. https://doi.org/10.1088/1748-9326/ab2da8
32. Hwang, C. L., ve Yoon, K. (1981). Methods for multiple attribute decision making. Multiple attribute decision making içinde (Cilt 186, ss 58-191). Springer. https://doi.org/10.1007/978-3-642-48318-9_3
33. Ishizaka, A. ve Labib, A. (2011). Review of the main developments in the analytic hierarchy process. Expert Systems with Applications, 38(11), 14336-14345. https://doi.org/10.1016/j.eswa.2011.04.143
34. Kamalakannan, R., Ramesh, C., Shunmugasundaram, M., Sivakumar, P. ve Mohamed, A. (2020). Evaluvation and selection of suppliers using TOPSIS. Materials Today: Proceedings, 33, 2771-2773. https://doi.org/10.1016/j.matpr.2020.02.105
35. Karmakar, G., Chowdhury, A., Kamruzzaman, J. ve Gondal, I. (2020). A smart priority-based traffic control system for emergency vehicles. IEEE Sensors Journal, 21(14), 15849-15858. https://doi.org/10.1109/JSEN.2020.3023149
36. Kazmaier, M., Taefi, T. T. ve Hettesheimer, T. (2020). Techno-economical and ecological potential of electric scooters: Life cycle analysis. European Journal of Transport and Infrastructure Research, 20(4), 233-251. https://doi.org/10.18757/ejtir.2020.20.4.4912
37. Kopplin, C. S., Brand, B. M. ve Reichenberger, Y. (2021). Consumer acceptance of shared e-scooters for urban and short-distance mobility. Transportation Research Part D: Transport and Environment, 91, 102680, 1-14. https://doi.org/10.1016/j.trd.2020.102680
38. Lee, W. H., Tseng, S. S. ve Wang, C. H. (2008). Design and implementation of electronic toll collection system based on vehicle positioning system techniques. Computer Communications, 31(12), 2925-2933. https://doi.org/10.1016/j.comcom.2008.05.014
39. Lee, W. H. ve Chiu, C. Y. (2020). Design and implementation of a smart traffic signal control system for smart city applications. Sensors, 20(2), 508, 1-18. https://doi.org/10.3390/s20020508
40. Lin, Y., Wang, P. ve Ma, M. (2017, 26 Mayıs). Intelligent transportation system (ITS): Concept, challenge and opportunity [Konferans sunumu]. IEEE 3rd International Conference On Big Data Security On Cloud (Bigdatasecurity), Beijing, China.
41. Liu, P. (2012). An approach to group decision making based on 2-dimension uncertain linguistic information. Technological and Economic Development of Economy, 18(3), 424-437. https://doi.org/10.3846/20294913.2012.702139
42. Lv, Z. ve Shang, W. (2023). Impacts of intelligent transportation systems on energy conservation and emission reduction of transport systems: A comprehensive review. Green Technologies and Sustainability, 1(1), 100002, 1-16. https://doi.org/10.1016/j.grets.2022.100002
43. Makarova, I., Shubenkova, K. ve Pashkevich, A. (2021). Efficiency assessment of measures to increase sustainability of the transport system. Transport, 36(2), 123-133. https://doi.org/10.3846/transport.2021.14996
44. Mao, F., Li, Z. ve Zhang, K. (2020). Carbon dioxide emissions estimation of conventional diesel buses electrification: A well-to-well analysis in Shenzhen, China. Journal of Cleaner Production, 277, 123048, 1-10. https://doi.org/10.1016/j.jclepro.2020.123048
45. Milanes, V., Villagra, J., Godoy, J., Simó, J., Pérez, J. ve Onieva, E. (2012). An intelligent V2I-based traffic management system. IEEE Transactions on Intelligent Transportation Systems, 13(1), 49-58. https://doi.org/10.1109/TITS.2011.2178839
46. Monjezi, M., Dehghani, H., Singh, T. N., Sayadi, A. R. ve Gholinejad, A. (2012). Application of TOPSIS method for selecting the most appropriate blast design. Arabian Journal of Geosciences, 5(1), 95. https://doi.org/10.1007/s12517-010-0133-2
47. Moreau, H., de Jamblinne de Meux, L., Zeller, V., D’Ans, P., Ruwet, C. ve Achten, W. M. (2020). Dockless e-scooter: A green solution for mobility? Comparative case study between dockless e-scooters, displaced transport, and personal e-scooters. Sustainability, 12(5), 1803, 1-17. https://doi.org/10.3390/su12051803
48. Ministère de la Transition écologique et solidaire- Ministère chargé des Transports (MTES/MCT). (2017). Les Systèmes de transport intelligents: L’expertise française. https://www.idrrim.com/ressources/documents/9/5218-14085_Transport-intelligent_Web_pla.pdf
49. National Operations Center of Excellence (NOCoE). (2010). Traffic incident management handbook. https://transportationops.org/publications/traffic-incident-management-handbook
50. Opricovic, S. ve Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445-455. https://doi.org/10.1016/S0377-2217(03)00020-1
51. Özkan, G. ve Deliktaş, E. (2020). Banka performanslarinin topsi̇s yöntemi̇yle anali̇zi̇. İzmir Katip Çelebi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 3(1), 31-40.
52. Öztaş Karlı, R. G. ve Çelikyay, H. (2022). Akıllı ulaşım sistemleri (AUS) üzerine Türkiye’deki politikaların araştırılması. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi, 5(2), 1-14. https://doi.org/10.51513/jitsa.1090659
53. Öztaş Karlı, R. G., Karlı, H. ve Çelikyay, H. S. (2022). Investigating the acceptance of shared e-scooters: Empirical evidence from Turkey. Case studies on Transport Policy, 10(2), 1058-1068. https://doi.org/10.1016/j.cstp.2022.03.018
54. Patella, S. M., Scrucca, F., Asdrubali, F. ve Carrese, S. (2019). Carbon Footprint of autonomous vehicles at the urban mobility system level: A traffic simulation-based approach. Transportation Research Part D: Transport and Environment, 74, 189-200. https://doi.org/10.1016/j.trd.2019.08.007
55. Pathak, D. K., Verma, A. ve Kumar, V. (2020). Performance variables of GSCM for sustainability in Indian automobile organizations using TOPSIS method. Business Strategy & Development, 3(4), 590-602. https://doi.org/10.1002/bsd2.124
56. Pojani, D. ve Stead, D. (2015). Sustainable urban transport in the developing world: Beyond megacities. Sustainability, 7(6), 7784-7805. https://doi.org/10.3390/su7067784
57. Saaty, T. L. (1980). The analytic hierarchy process. McGraw-Hill.
58. Shih, H. S., Shyur, H. J. ve Lee, E. S. (2007). An extension of TOPSIS for group decision making. Mathematical and Computer Modelling, 45(7-8), 801-813. https://doi.org/10.1016/j.mcm.2006.03.023
59. Shyjith, K., Ilangkumaran, M. ve Kumanan, S. (2008). Multi‐criteria decision‐making approach to evaluate optimum maintenance strategy in textile industry. Journal of Quality in Maintenance Engineering, 14(4), 375-386. https://doi.org/10.1108/13552510810909975
60. Qi, L. (2008, 2-3 Ağustos). Research on intelligent transportation system technologies and applications [Konferans sunumu]. 2008 Workshop on Power Electronics and Intelligent Transportation System IEEE, Guangzhou, China.
61. Qiu, L. Y. ve He, L. Y. (2018). Bike sharing and the economy, the environment, and health-related externalities. Sustainability, 10(4), 1145, 1-10. https://doi.org/10.3390/su10041145
62. Reis, A. F., Baptista, P. ve Moura, F. (2023). How to promote the environmental sustainability of shared e-scooters: A life-cycle analysis based on a case study from Lisbon, Portugal. Journal of Urban Mobility, 3, 100044, 1-12. https://doi.org/10.1016/j.urbmob.2022.100044
63. Society of Automotive Engineers. (2018). Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles. https://www.sae.org/standards/content/j3016_201806/
64. Severengiz, S., Finke, S., Schelte, N. ve Forrister, H. (2020). Assessing the environmental impact of novel mobility services using shared electric scooters as an example. Procedia Manufacturing, 43, 80-87. https://doi.org/10.1016/j.promfg.2020.02.114
65. Tektaş, M. ve Tektaş, N. (2019). Akıllı ulaşım sistemleri (AUS) uygulamalarının sektörlere göre dağılımı. Akıllı Ulaşım Sistemleri ve Uygulamaları Dergisi, 2(1), 32-41.
66. Tyrinopoulos, Y. ve Antoniou, C. (2020). Review of factors affecting transportation systems adoption and satisfaction. C. Antoniou, D. Efthymiou ve E. Chaniotakis (Ed.) Demand for emerging transportation systems içinde (ss. 11-36). Elsevier.
67. Uluçay, U. ve Tanyaş, M. (2023). Trafik akışı iyileştirmesinin trafik sıkışıklığını azaltmaya etkisi: Simülasyonlu alternatif bakış. Trafik ve Ulaşım Araştırmaları Dergisi, 6(2), 96-110. https://doi.org/10.38002/tuad.1274489
68. Urfalıoğlu, F. ve Genç, T. (2013). Çok kriterli karar verme teknikleri ile Türkiye’nin ekonomik performansının Avrupa Birliği üye ülkeleri ile karşılaştırılması. Marmara Üniversitesi İktisadi ve İdari Bilimler Dergisi, 35(2), 329-360. https://doi.org/10.14780/iibdergi.201324469
69. Wadud, Z., MacKenzie, D. ve Leiby, P. (2016). Help or hindrance? The travel, energy and carbon impacts of highly automated vehicles. Transportation Research Part A: Policy and Practice, 86, 1-18. https://doi.org/10.1016/j.tra.2015.12.001
70. Welch, T. F. ve Widita, A. (2019). Big data in public transportation: A review of sources and methods. Transport Reviews, 39(6), 795-818. https://doi.org/10.1080/01441647.2019.1616849
71. Yurdakul, M. ve İç, Y. (2003). Türk otomotiv firmalarının performans ölçümü ve analizine yönelik TOPSIS yöntemini kullanan bir örnek çalışma. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 18(1), 1-18.
72. Zaghal, R., Thabatah, K. ve Salah, S. (2017, 18-20 Temmuz). Towards a smart intersection using traffic load balancing algorithm [Konferans sunumu]. 2017 Computing Conference IEEE, London, UK.
73. Zhou, B., Wu, Y., Zhou, B., Wang, R., Ke, W., Zhang, S. ve Hao, J. (2016). Real-world performance of battery electric buses and their life-cycle benefits with respect to energy consumption and carbon dioxide emissions. Energy, 96, 603-613. https://doi.org/10.1016/j.energy.2015.12.041