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Ulaştırma Modlarının Geleceği: Yapay Zekânın Akıllı Ulaşım Sistemlerine Entegrasyonu

Year 2024, Volume: 1 Issue: 1, 60 - 76, 30.04.2024

Armağan Macit

Abstract

Temel ihtiyaç kapsamında değerlendirilmesi gereken ulaşıma bilgi teknolojileri, iletişim teknolojileri, algılama teknolojileri gibi sistemlerin entegre olması ile akıllı ulaşım teknolojileri gelişmiştir. Çok uzun yıllardır gelişen ulaştırma sistemleri günümüzde dijital, teknolojik, sürdürülebilir ve verimli bir hale gelmiştir. Ancak teknolojik gelişmelere paralel olarak tüm ulaştırma modlarında akıllı ulaşım sistemleri de gelişerek güncellenmektedir. Teknolojinin geldiği son noktada yapay zekâ iş süreçlerine, günlük yaşama dolayısı ile ulaşıma entegre olmaya başlamıştır. Tüm sektörlerde ve kullanım alanlarında köklü değişim yaratan yapay zekânın akıllı ulaşım sistemlerinde yaratacağı etki ile ulaşımın geleceğinin baştan kurgulanacağı kaçınılmaz bir gerçektir. Bu bağlamda, çalışmada geniş kapsamlı bir literatür taraması ile, yapay zekânın karayolu, denizyolu, demiryolu ve havayolu ulaştırma modlarına nasıl entegre olduğu ve olabileceği araştırılmıştır. Yapılan araştırma ile yapay zekâ ekseninde ulaştırma modlarının geleceği tartışılmıştır. Araştırma ile ulaştırma modlarında yapay zekâ ile ilgili yapılan akademik çalışmaların genel bir resmi çıkarılmıştır. Çalışmada yapay zekânın tüm ulaştırma modlarında akıllı ulaşım sistemlerinin merkezi konumuna geleceği, aynı zamanda akıllı şehirler içerisinde akıllı ulaşım sistemlerinin suç önleme, acil durum hizmetleri gibi diğer akıllı sistemlere de entegre olabileceği sonucuna ulaşılmıştır.

Keywords

Akıllı Ulaştırma Sistemleri Yapay Zekâ Ulaştırma Modları

References

  • Abduljabbar, R., Dia, H., Liyanage, S., & Bagloee, S. A. (2019). Applications of artificial intelligence in transport: An overview. Sustainability, 11(1), 189.
  • Ajith, K. B. P., Harsha, P., Ompreeth, D, R., Prathvik, R. (2023). Implementing Smart Control of Traffic Light System using Artificial Intelligence. International Journal of Advanced Research in Science, Communication and Technology.(pp. 147-150)
  • Arkhiereev, N.V. (2023). Ulaştırma Alanında Yapay Zekâ Kullanımının Yasal Sorunları. Ulaştırma Faaliyetlerinin Özel Ve Kamu Hukuku Sorunları İçerisinde Düzenlenmesi (s. 35-39).
  • Ataner, E., Özdeş, B., Öztürk, G., Çelik, TYC, vd. (2020). İnsansız Sualtı Araçlarında Derin Öğrenme Yöntemleri. Avrupa Bilim Ve Teknoloji Dergisi 345-350.
  • Bešinović, N., De Donato, L., Flammini, F., Goverde, R. M., Lin, Z., Liu, R., ... & Vittorini, V. (2021). Artificial intelligence in railway transport: Taxonomy, regulations, and applications. IEEE Transactions on Intelligent Transportation Systems, 23(9), 14011-14024.
  • Bharadiya, J. (2023). Artificial intelligence in transportation systems a critical review. American Journal of Computing and Engineering, 6(1), 34-45.
  • Biolcheva, P., & Valchev, E. (2023). Safety through artıfıcıal ıntellıgence ın the marıtıme ındustry. Strategies for Policy in Science & Education/Strategii na Obrazovatelnata i Nauchnata Politika, 31(3).
  • Chu, D., & Cao, Y. (2022). Typical intelligent transportation applications. In Intelligent Road Transport Systems: An Introduction to Key Technologies (pp. 545-608). Singapore: Springer Nature Singapore.
  • Cocchioni, M., Bonelli, S., Westin, C., Borst, C., Bang, M., & Hilburn, B. (2023). Learning for Air Traffic Management: guidelines for future AI systems. In Journal of Physics: Conference Series (Vol. 2526, No. 1, p. 012105). IOP Publishing.
  • Çapalı, B. (2022). Intelligent transportation systems architecture: Recommendation for K-AUS. El-Cezeri, 9(4), 1249-1254.
  • Debnath, A. K., Chin, H. C., Haque, M. M., & Yuen, B. (2014). A methodological framework for benchmarking smart transport cities. Cities, 37, 47-56. Dempsey, P. (2022). AI helps fleet operators plan electric switch [Automotive Transport]. Engineering & Technology, 17(9), 40-41.
  • Durlik, I., Miller, T., Dorobczyński, L., Kozlovska, P., & Kostecki, T. (2023). Revolutionizing Marine Traffic Management: A Comprehensive Review of Machine Learning Applications in Complex Maritime Systems. Applied Sciences, 13(14), 8099.
  • Farahdel, A., Vedaei, S. S., & Wahid, K. (2022). An iot based traffic management system using drone and ai. In 2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 297-301). IEEE.
  • Ficzere, P. (2023). The role of artificial intelligence in the development of railway transportation. Design of Machines and Structures, 13(1), 67-73.
  • Guevarra, M., Das, S., Wayllace, C., Epp, C. D., Taylor, M., & Tay, A. (2023). Augmenting flight training with AI to efficiently train pilots. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 37, No. 13, pp. 16437-16439).
  • Guo, Y., Wu, S., Wang, Y., Wen, C., Luo, L., & Fu, Q. (2023, May). Application and Implementation of Artificial Intelligence Technology for Intelligent Vehicle. In Journal of Physics: Conference Series (Vol. 2508, No. 1, p. 012049). IOP Publishing.
  • Johnson, J. (2020). Artificial intelligence, drone swarming and escalation risks in future warfare. The RUSI Journal, 165(2), 26-36.
  • Kalinowski, M., & Weichbroth, P. (2023). The sensors-based artificial intelligence Train Control and Monitoring System (TCMS) for managing the railway transport fleet. Rail Vehicles/Pojazdy Szynowe.
  • Khan, S., Adnan, A., & Iqbal, N. (2022). Applications of artificial intelligence in transportation. In 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) (pp. 1-6).
  • Kolotusha, V. (2022). Application of artificial intelligence technology in the process of individualized training of air traffic controllers. In 2022 12th International Conference on Dependable Systems, Services and Technologies (DESSERT) (pp. 1-4).
  • Kontzinos, C., Kanellou, I., Michalakopoulos, V., Mouzakitis, S., Tsapelas, G., Kapsalis, P., ... & Askounis, D. (2022). State-Of-The-Art Analysıs Of Artıfıcıal Intellıgence Approaches In The Marıtıme Industry. In Proceedings of the International Conferences on Applied Computing.
  • Kour, S. P., Sharma, P., & Jalal, M. (2022). Artificial Intelligence in Transport-A Survey. In 2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) (pp. 1-6).
  • Kumar, H., Singh, M. K., & Gupta, M. P. (2018). Smart mobility: Crowdsourcing solutions for smart transport system in smart cities context. In Proceedings of the 11th International Conference on Theory and Practice of Electronic Governance (pp. 482-488).
  • Lee, E., Khan, J., Son, W. J., & Kim, K. (2023). An efficient feature augmentation and LSTM-based method to predict maritime traffic conditions. Applied Sciences, 13(4), 2556.
  • Li, J., Cheng, H., Guo, H., & Qiu, S. (2018). Survey on artificial intelligence for vehicles. Automotive Innovation, 1, 2-14.
  • Lyons, G., & Davidson, C. (2016). Guidance for transport planning and policymaking in the face of an uncertain future. Transportation Research Part A: Policy and Practice, 88, 104-116.
  • Machin, M., Sanguesa, J. A., Garrido, P., & Martinez, F. J. (2018, April). On the use of artificial intelligence techniques in intelligent transportation systems. In 2018 IEEE wireless communications and networking conference workshops (WCNCW) (pp. 332-337).
  • Mahardhika, S. P., & Putriani, O. (2023, January). A Review of Artificial Intelligence-Enabled Electric Vehicles in Traffic Congestion Management. In ICSEDTI 2022: Proceedings of the 1st International Conference on Sustainable Engineering Development and Technological Innovation, ICSEDTI 2022, 11-13 October 2022, Tanjungpinang, Indonesia (p. 255). European Alliance for Innovation.
  • Manoharan, S. (2019). An improved safety algorithm for artificial intelligence enabled processors in self driving cars. Journal of artificial intelligence, 1(02), 95-104.
  • Mathew, E. (2019). Intelligent transport systems and its challenges. In International Conference on Advanced Intelligent Systems and Informatics (pp. 663-672). Cham: Springer International Publishing.
  • Mobin, G., & Roy, A. (2021). A literature review on cloud based smart transport system. In 2021 5th International conference on trends in electronics and informatics (ICOEI) (pp. 1245-1250).
  • Mouzakitis, S., Kontzinos, C., Kapsalis, P., Kanellou, I., Kormpakis, G., Tsapelas, G., & Askounis, D. (2022, July). Optimising maritime processes via artificial intelligence: The vesselai concept and use cases. In 2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA) (pp. 1-5).
  • Plötner, K. (2018). Key drivers and technical developments in aviation. Biokerosene: Status and Prospects, 33-41.
  • Poulus, R. W., Van Kempen, E. A., & Van Meijeren, J. C. (2018). Automatic train operation. Driving the future of rail transport.
  • Prakash, K., Ravva, S. K., Rathnamma, M. V., & Suryanarayana, G. (2023). AI Applications of Drones. Drone Technology: Future Trends and Practical Applications, 153-182.
  • Ran, B., Cheng, Y., Leight, S., & Parker, S. (2019). Development of an integrated transportation system of connected automated vehicles and highways. ITE Journal, 89(11).
  • Rudra, T. (2023). How Can AI Help in Reducing Traffic in India?. Indian Scientific Journal Of Research In Engineering And Management. Vol:7 Issue: 1.
  • Saeed, A., Aftab, A. B., Junejo, F., & Amin, I. (2023). Current and Future Trends in an Intelligent Transportation System with Applications of AI. Artificial Intelligence in Cyber-Physical Systems, 75-93.
  • Sarol, S. D., Mohammad, M. F., & Rahman, N. A. A. (2022). Mobile Technology Application in Aviation: Chatbot for Airline Customer Experience. In Technology Application in Aviation, Tourism and Hospitality: Recent Developments and Emerging Issues (pp. 59-72). Singapore: Springer Nature Singapore.
  • Satpute, M. B. V., Done, M. D. B., Salave, M. R. A., Zameer, M. A., Shaikh, P., & Gunjal, A. K. (2022). Intelligent Transportation System. International Journal for Research in Applied Science & Engineering Technology (IJRASET). Volume 10 Issue V May 2022.
  • Saxena, A. K., Tripathi, R. C., & Khan, G. (2023, February). Design of a smart public transport system based on IoT. In AIP Conference Proceedings (Vol. 2427, No. 1). AIP Publishing.
  • Scarlat, C., Ioanid, A., & Andrei, N. (2023). Use of the geospatial technologies and its implications in the maritime transport and logistics. The International Maritime Transport and Logistic Journal, 12, 19-30.
  • Schneider, M., Kutila, M., & Höß, A. (2022). Applications of AI in Transportation Industry. In Artificial Intelligence for Digitising Industry–Applications (pp. 355-362). River Publishers.
  • Singh, P., Dulebenets, M. A., Pasha, J., Gonzalez, E. D. S., Lau, Y. Y., & Kampmann, R. (2021). Deployment of autonomous trains in rail transportation: Current trends and existing challenges. IEEE Access, 9, 91427-91461.
  • Soy, H. (2023). Edge AI-Based Crowd Counting Application for Public Transport Stops. In Convergence of Deep Learning and Internet of Things: Computing and Technology (pp. 182-205). IGI Global.
  • Stappen, L., Dillmann, J., Striegel, S., Vögel, H. J., Flores-Herr, N., & Schuller, B. W. (2023). Integrating Generative Artificial Intelligence in Intelligent Vehicle Systems. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC) (pp. 5790-5797).
  • Sukhadia, A., Upadhyay, K., Gundeti, M., Shah, S., & Shah, M. (2020). Optimization of smart traffic governance system using artificial intelligence. Augmented Human Research, 5(1), 13.
  • Taner, T., Ünal, H. T., Mendi, A. F., Özkan, Ö., & Nacar, M. A. (2023). Artificial Intelligence Based Transportation System. In 2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA) (pp. 1-8).
  • Telang, S., Chel, A., Nemade, A., & Kaushik, G. (2021). Intelligent transport system for a smart city. Security and privacy applications for smart city development, 171-187.
  • Türkkan, A. Z. (2019). Yapay zekâ ve kentsel sistemler: Akıllı ulaştırma sistemlerinin kentsel güç içindeki rolü. Bahçesehir Üniversitesi, Fen Bilimleri Enstitüsü, Yayımlanmış Yükseklisans Tezi.
  • Vatakov, V., Pencheva, E., & Dimitrova, E. (2022). Recent advances in artificial intelligence for improving railway operations. In 2022 30th National Conference with International Participation (TELECOM) (pp. 1-4).
  • Veitch, E., & Alsos, O. A. (2021). Human-centered explainable artificial intelligence for marine autonomous surface vehicles. Journal of Marine Science and Engineering, 9(11), 1227.
  • Zhang, M., Yu, T., & Zhai, G. F. (2011). Smart transport system based on “The Internet of Things”. Applied mechanics and materials, 48, 1073-1076.
  • Zhu, Y., Ni, K., Li, X., Zaman, A., Liu, X., & Bai, Y. (2024). Artificial intelligence aided crowd analytics in rail transit station. Transportation research record.
  • Ziakkas, D., Pechlivanis, K., & Flores, A. (2023). Artificial intelligence (AI) implementation in the design of single pilot operations commercial airplanes. In 14th International Conference on Applied Human Factors and Ergonomics (pp. 20-24).

The Future of Transportation Modes: Integration of Artificial Intelligence into Intelligent Transportation Systems

Year 2024, Volume: 1 Issue: 1, 60 - 76, 30.04.2024

Armağan Macit

Abstract

Smart transportation technologies have developed with the integration of systems such as information technologies, communication technologies and perception technologies into transportation, which should be considered within the scope of basic needs. Transportation systems, which have been developing for many years, have now become digital, technological, sustainable and efficient. However, in parallel with technological developments, smart transportation systems are developed and updated in all transportation modes. At the latest point in technology, artificial intelligence has begun to be integrated into business processes, daily life and therefore transportation. It is an inevitable fact that the future of transportation will be reimagined with the impact that artificial intelligence, which creates radical changes in all sectors and areas of use, will create in smart transportation systems. In this context, the study investigated how artificial intelligence can be integrated into road, sea, railway and air transportation modes through a comprehensive literature review. With the research, the future of transportation modes was discussed on the axis of artificial intelligence. With the research, a general picture of the academic studies on artificial intelligence in transportation modes was obtained. The study concluded that artificial intelligence will become the center of smart transportation systems in all transportation modes, and that smart transportation systems in smart cities can also be integrated with other smart systems such as crime prevention and emergency services.

Keywords

Intelligent Transportation Systems Artificial Intelligence Transportation Modes

References

  • Abduljabbar, R., Dia, H., Liyanage, S., & Bagloee, S. A. (2019). Applications of artificial intelligence in transport: An overview. Sustainability, 11(1), 189.
  • Ajith, K. B. P., Harsha, P., Ompreeth, D, R., Prathvik, R. (2023). Implementing Smart Control of Traffic Light System using Artificial Intelligence. International Journal of Advanced Research in Science, Communication and Technology.(pp. 147-150)
  • Arkhiereev, N.V. (2023). Ulaştırma Alanında Yapay Zekâ Kullanımının Yasal Sorunları. Ulaştırma Faaliyetlerinin Özel Ve Kamu Hukuku Sorunları İçerisinde Düzenlenmesi (s. 35-39).
  • Ataner, E., Özdeş, B., Öztürk, G., Çelik, TYC, vd. (2020). İnsansız Sualtı Araçlarında Derin Öğrenme Yöntemleri. Avrupa Bilim Ve Teknoloji Dergisi 345-350.
  • Bešinović, N., De Donato, L., Flammini, F., Goverde, R. M., Lin, Z., Liu, R., ... & Vittorini, V. (2021). Artificial intelligence in railway transport: Taxonomy, regulations, and applications. IEEE Transactions on Intelligent Transportation Systems, 23(9), 14011-14024.
  • Bharadiya, J. (2023). Artificial intelligence in transportation systems a critical review. American Journal of Computing and Engineering, 6(1), 34-45.
  • Biolcheva, P., & Valchev, E. (2023). Safety through artıfıcıal ıntellıgence ın the marıtıme ındustry. Strategies for Policy in Science & Education/Strategii na Obrazovatelnata i Nauchnata Politika, 31(3).
  • Chu, D., & Cao, Y. (2022). Typical intelligent transportation applications. In Intelligent Road Transport Systems: An Introduction to Key Technologies (pp. 545-608). Singapore: Springer Nature Singapore.
  • Cocchioni, M., Bonelli, S., Westin, C., Borst, C., Bang, M., & Hilburn, B. (2023). Learning for Air Traffic Management: guidelines for future AI systems. In Journal of Physics: Conference Series (Vol. 2526, No. 1, p. 012105). IOP Publishing.
  • Çapalı, B. (2022). Intelligent transportation systems architecture: Recommendation for K-AUS. El-Cezeri, 9(4), 1249-1254.
  • Debnath, A. K., Chin, H. C., Haque, M. M., & Yuen, B. (2014). A methodological framework for benchmarking smart transport cities. Cities, 37, 47-56. Dempsey, P. (2022). AI helps fleet operators plan electric switch [Automotive Transport]. Engineering & Technology, 17(9), 40-41.
  • Durlik, I., Miller, T., Dorobczyński, L., Kozlovska, P., & Kostecki, T. (2023). Revolutionizing Marine Traffic Management: A Comprehensive Review of Machine Learning Applications in Complex Maritime Systems. Applied Sciences, 13(14), 8099.
  • Farahdel, A., Vedaei, S. S., & Wahid, K. (2022). An iot based traffic management system using drone and ai. In 2022 14th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 297-301). IEEE.
  • Ficzere, P. (2023). The role of artificial intelligence in the development of railway transportation. Design of Machines and Structures, 13(1), 67-73.
  • Guevarra, M., Das, S., Wayllace, C., Epp, C. D., Taylor, M., & Tay, A. (2023). Augmenting flight training with AI to efficiently train pilots. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 37, No. 13, pp. 16437-16439).
  • Guo, Y., Wu, S., Wang, Y., Wen, C., Luo, L., & Fu, Q. (2023, May). Application and Implementation of Artificial Intelligence Technology for Intelligent Vehicle. In Journal of Physics: Conference Series (Vol. 2508, No. 1, p. 012049). IOP Publishing.
  • Johnson, J. (2020). Artificial intelligence, drone swarming and escalation risks in future warfare. The RUSI Journal, 165(2), 26-36.
  • Kalinowski, M., & Weichbroth, P. (2023). The sensors-based artificial intelligence Train Control and Monitoring System (TCMS) for managing the railway transport fleet. Rail Vehicles/Pojazdy Szynowe.
  • Khan, S., Adnan, A., & Iqbal, N. (2022). Applications of artificial intelligence in transportation. In 2022 International Conference on Electrical, Computer and Energy Technologies (ICECET) (pp. 1-6).
  • Kolotusha, V. (2022). Application of artificial intelligence technology in the process of individualized training of air traffic controllers. In 2022 12th International Conference on Dependable Systems, Services and Technologies (DESSERT) (pp. 1-4).
  • Kontzinos, C., Kanellou, I., Michalakopoulos, V., Mouzakitis, S., Tsapelas, G., Kapsalis, P., ... & Askounis, D. (2022). State-Of-The-Art Analysıs Of Artıfıcıal Intellıgence Approaches In The Marıtıme Industry. In Proceedings of the International Conferences on Applied Computing.
  • Kour, S. P., Sharma, P., & Jalal, M. (2022). Artificial Intelligence in Transport-A Survey. In 2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) (pp. 1-6).
  • Kumar, H., Singh, M. K., & Gupta, M. P. (2018). Smart mobility: Crowdsourcing solutions for smart transport system in smart cities context. In Proceedings of the 11th International Conference on Theory and Practice of Electronic Governance (pp. 482-488).
  • Lee, E., Khan, J., Son, W. J., & Kim, K. (2023). An efficient feature augmentation and LSTM-based method to predict maritime traffic conditions. Applied Sciences, 13(4), 2556.
  • Li, J., Cheng, H., Guo, H., & Qiu, S. (2018). Survey on artificial intelligence for vehicles. Automotive Innovation, 1, 2-14.
  • Lyons, G., & Davidson, C. (2016). Guidance for transport planning and policymaking in the face of an uncertain future. Transportation Research Part A: Policy and Practice, 88, 104-116.
  • Machin, M., Sanguesa, J. A., Garrido, P., & Martinez, F. J. (2018, April). On the use of artificial intelligence techniques in intelligent transportation systems. In 2018 IEEE wireless communications and networking conference workshops (WCNCW) (pp. 332-337).
  • Mahardhika, S. P., & Putriani, O. (2023, January). A Review of Artificial Intelligence-Enabled Electric Vehicles in Traffic Congestion Management. In ICSEDTI 2022: Proceedings of the 1st International Conference on Sustainable Engineering Development and Technological Innovation, ICSEDTI 2022, 11-13 October 2022, Tanjungpinang, Indonesia (p. 255). European Alliance for Innovation.
  • Manoharan, S. (2019). An improved safety algorithm for artificial intelligence enabled processors in self driving cars. Journal of artificial intelligence, 1(02), 95-104.
  • Mathew, E. (2019). Intelligent transport systems and its challenges. In International Conference on Advanced Intelligent Systems and Informatics (pp. 663-672). Cham: Springer International Publishing.
  • Mobin, G., & Roy, A. (2021). A literature review on cloud based smart transport system. In 2021 5th International conference on trends in electronics and informatics (ICOEI) (pp. 1245-1250).
  • Mouzakitis, S., Kontzinos, C., Kapsalis, P., Kanellou, I., Kormpakis, G., Tsapelas, G., & Askounis, D. (2022, July). Optimising maritime processes via artificial intelligence: The vesselai concept and use cases. In 2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA) (pp. 1-5).
  • Plötner, K. (2018). Key drivers and technical developments in aviation. Biokerosene: Status and Prospects, 33-41.
  • Poulus, R. W., Van Kempen, E. A., & Van Meijeren, J. C. (2018). Automatic train operation. Driving the future of rail transport.
  • Prakash, K., Ravva, S. K., Rathnamma, M. V., & Suryanarayana, G. (2023). AI Applications of Drones. Drone Technology: Future Trends and Practical Applications, 153-182.
  • Ran, B., Cheng, Y., Leight, S., & Parker, S. (2019). Development of an integrated transportation system of connected automated vehicles and highways. ITE Journal, 89(11).
  • Rudra, T. (2023). How Can AI Help in Reducing Traffic in India?. Indian Scientific Journal Of Research In Engineering And Management. Vol:7 Issue: 1.
  • Saeed, A., Aftab, A. B., Junejo, F., & Amin, I. (2023). Current and Future Trends in an Intelligent Transportation System with Applications of AI. Artificial Intelligence in Cyber-Physical Systems, 75-93.
  • Sarol, S. D., Mohammad, M. F., & Rahman, N. A. A. (2022). Mobile Technology Application in Aviation: Chatbot for Airline Customer Experience. In Technology Application in Aviation, Tourism and Hospitality: Recent Developments and Emerging Issues (pp. 59-72). Singapore: Springer Nature Singapore.
  • Satpute, M. B. V., Done, M. D. B., Salave, M. R. A., Zameer, M. A., Shaikh, P., & Gunjal, A. K. (2022). Intelligent Transportation System. International Journal for Research in Applied Science & Engineering Technology (IJRASET). Volume 10 Issue V May 2022.
  • Saxena, A. K., Tripathi, R. C., & Khan, G. (2023, February). Design of a smart public transport system based on IoT. In AIP Conference Proceedings (Vol. 2427, No. 1). AIP Publishing.
  • Scarlat, C., Ioanid, A., & Andrei, N. (2023). Use of the geospatial technologies and its implications in the maritime transport and logistics. The International Maritime Transport and Logistic Journal, 12, 19-30.
  • Schneider, M., Kutila, M., & Höß, A. (2022). Applications of AI in Transportation Industry. In Artificial Intelligence for Digitising Industry–Applications (pp. 355-362). River Publishers.
  • Singh, P., Dulebenets, M. A., Pasha, J., Gonzalez, E. D. S., Lau, Y. Y., & Kampmann, R. (2021). Deployment of autonomous trains in rail transportation: Current trends and existing challenges. IEEE Access, 9, 91427-91461.
  • Soy, H. (2023). Edge AI-Based Crowd Counting Application for Public Transport Stops. In Convergence of Deep Learning and Internet of Things: Computing and Technology (pp. 182-205). IGI Global.
  • Stappen, L., Dillmann, J., Striegel, S., Vögel, H. J., Flores-Herr, N., & Schuller, B. W. (2023). Integrating Generative Artificial Intelligence in Intelligent Vehicle Systems. In 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC) (pp. 5790-5797).
  • Sukhadia, A., Upadhyay, K., Gundeti, M., Shah, S., & Shah, M. (2020). Optimization of smart traffic governance system using artificial intelligence. Augmented Human Research, 5(1), 13.
  • Taner, T., Ünal, H. T., Mendi, A. F., Özkan, Ö., & Nacar, M. A. (2023). Artificial Intelligence Based Transportation System. In 2023 5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA) (pp. 1-8).
  • Telang, S., Chel, A., Nemade, A., & Kaushik, G. (2021). Intelligent transport system for a smart city. Security and privacy applications for smart city development, 171-187.
  • Türkkan, A. Z. (2019). Yapay zekâ ve kentsel sistemler: Akıllı ulaştırma sistemlerinin kentsel güç içindeki rolü. Bahçesehir Üniversitesi, Fen Bilimleri Enstitüsü, Yayımlanmış Yükseklisans Tezi.
  • Vatakov, V., Pencheva, E., & Dimitrova, E. (2022). Recent advances in artificial intelligence for improving railway operations. In 2022 30th National Conference with International Participation (TELECOM) (pp. 1-4).
  • Veitch, E., & Alsos, O. A. (2021). Human-centered explainable artificial intelligence for marine autonomous surface vehicles. Journal of Marine Science and Engineering, 9(11), 1227.
  • Zhang, M., Yu, T., & Zhai, G. F. (2011). Smart transport system based on “The Internet of Things”. Applied mechanics and materials, 48, 1073-1076.
  • Zhu, Y., Ni, K., Li, X., Zaman, A., Liu, X., & Bai, Y. (2024). Artificial intelligence aided crowd analytics in rail transit station. Transportation research record.
  • Ziakkas, D., Pechlivanis, K., & Flores, A. (2023). Artificial intelligence (AI) implementation in the design of single pilot operations commercial airplanes. In 14th International Conference on Applied Human Factors and Ergonomics (pp. 20-24).
There are 55 citations in total.

Details

Primary Language Turkish
Subjects Intelligent Mobility, Air Transportation and Freight Services
Journal Section 1
Authors

Armağan Macit 0000-0002-5694-8285

Publication Date April 30, 2024
Published in Issue Year 2024 Volume: 1 Issue: 1

Cite

APA Macit, A. (2024). Ulaştırma Modlarının Geleceği: Yapay Zekânın Akıllı Ulaşım Sistemlerine Entegrasyonu. Ege Üniversitesi Ulaştırma Yönetimi Araştırmaları Dergisi, 1(1), 60-76.
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