Research Article
BibTex RIS Cite

Acil durum araçlarının yönlendirilmesinde akıllı ulaşım çözümleri: Ambulans rota oluşturma optimizasyonu

Year 2025, Volume: 8 Issue: 1, 90 - 103, 25.03.2025
https://doi.org/10.51513/jitsa.1532308

Abstract

Doğal afetler, can ve mal kaybına yol açabilen yıkıcı olaylardır. Deprem, sel, yangın gibi afetlerin yarattığı tahribat, insan hayatının kurtarılması ve maddi zararların önlenmesi için acil durum planlaması ve koordinasyon gerektirir. Afet bölgesindeki insanların güvenli tahliyesi ve acil durum araçlarının etkin yönlendirilmesi hayati bir öneme sahiptir. Bu çalışmada, Türkiye’nin özgün trafik koşulları ve acil durum araçlarının gereksinimleri dikkate alınarak ambulanslar için bir rota optimizasyon modeli geliştirilmiştir. Bu model, mevcut yol ağlarının ambulansların kullanımına uygun hale getirilmesini ve acil durum müdahale sürelerinin iyileştirilmesini hedeflemektedir. Yenilikçi çözümler arasında trafik ışıklarında ambulanslara öncelik verilmesi, gerektiğinde ters yönde seyahat edebilme senaryoları ve zorlu trafik koşullarında etkili rotaların belirlenmesi yer almaktadır. Bu sayede ambulans hizmetlerinin iyileştirilmesi ve müdahale sürelerinin kısaltılmasıyla hasta ve yaralıların hayatta kalma oranlarının artırılması amaçlanmaktadır. Sonuçlar, ambulans hizmetlerinin verimliliğini artırdığını ve müdahale sürelerini azalttığını göstermektedir. Çalışma, Türkiye için ambulans rotası optimizasyonu ve acil durum yönetimi alanında önemli bir adım olarak değerlendirilmektedir

Ethical Statement

Çalışma kapsamında herhangi bir kurum veya kişi ile çıkar çatışması bulunmamaktadır

Supporting Institution

Bu çalışma Türkiye Bilimsel ve Teknolojik Araştırma Kurumu (TÜBİTAK) 2244 programı tarafından 119C200 numaralı proje kapsamında desteklenmiştir

Project Number

TUBITAK 2244/119C200

References

  • Abdeen, M. A. R., Ahmed, M. H., Seliem, H., Sheltami, T. R., Alghamdi, T. M., & El-Nainay, M. (2022). A Novel Smart Ambulance System—Algorithm Design, Modeling, and Performance Analysis. IEEE Access, 10, 42656-42672. IEEE Access. https://doi.org/10.1109/ACCESS.2022.3168736
  • Alamri, A. (2023). A Smart Spatial Routing and Accessibility Analysis System for EMS Using Catchment Areas of Voronoi Spatial Model and Time-Based Dijkstra’s Routing Algorithm. International Journal of Environmental Research and Public Health, 20(3), Article 3. https://doi.org/10.3390/ijerph20031808
  • Albano, R., Sole, A., Adamowski, J., & Mancusi, L. (2014). A GIS-based model to estimate flood consequences and the degree of accessibility and operability of strategic emergency response structures in urban areas. Natural Hazards and Earth System Sciences, 14(11), 2847-2865. https://doi.org/10.5194/nhess-14-2847-2014
  • Amr, M. F., Elgarej, M., Benmoussa, N., Mansouri, K., & Qbadou, M. (2021). Towards a Distributed SMA-based Solution for the Interoperability of Hospital Information Systems for Better Routing of Emergency Ambulances. International Journal of Online and Biomedical Engineering (iJOE), 17(12), Article 12. https://doi.org/10.3991/ijoe.v17i12.25455
  • Aringhieri, R., Bruni, M. E., Khodaparasti, S., & van Essen, J. T. (2017). Emergency medical services and beyond: Addressing new challenges through a wide literature review. Computers & Operations Research, 78, 349-368. https://doi.org/10.1016/j.cor.2016.09.016
  • Blodgett, J. M., Robertson, D. J., Pennington, E., Ratcliffe, D., & Rockwood, K. (2021). Alternatives to direct emergency department conveyance of ambulance patients: A scoping review of the evidence. Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, 29(1), 4. https://doi.org/10.1186/s13049-020-00821-x
  • Darwassh Hanawy Hussein, T., Frikha, M., Ahmed, S., & Rahebi, J. (2022). BA-CNN: Bat Algorithm-Based Convolutional Neural Network Algorithm for Ambulance Vehicle Routing in Smart Cities. Mobile Information Systems, 2022, e7339647. https://doi.org/10.1155/2022/7339647
  • Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269-271. https://doi.org/10.1007/BF01386390
  • Feroz, B., Mehmood, A., Maryam, H., Zeadally, S., Maple, C., & Shah, M. A. (2021). Vehicle-Life Interaction in Fog-Enabled Smart Connected and Autonomous Vehicles. IEEE Access, 9, 7402-7420. IEEE Access. https://doi.org/10.1109/ACCESS.2020.3049110
  • Hart, P. E., Nilsson, N. J., & Raphael, B. (1968). A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics, 4(2), 100–107. https://doi.org/10.1109/TSSC.1968.300136
  • Holland, J. H. (1975). Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence. University of Michigan Press.
  • Johnson, S., & Yu, D. (2020). From flooding to finance: NHS ambulance-assisted evacuations of care home residents in Norfolk and Suffolk, UK. Journal of Flood Risk Management, 13(1), e12592. https://doi.org/10.1111/jfr3.12592
  • Kula, U., Tozanli, O., & Tarakcio, S. (2012). Emergency Vehicle Routing in Disaster Response Operations. 23rd Annual Conference of the Production and Operations Management Society.
  • Mascarenhas, N., G, P., Agrawal, M., P, S., & A, A. (2013). A Proposed Model for Traffic Signal Preemption Using Global Positioning System (GPS). Computer Science & Information Technology ( CS & IT ), 219-226. https://doi.org/10.5121/csit.2013.3423
  • McDaniel, E. L., Akwafuo, S., Urbanovsky, J., & Mikler, A. R. (2023). Benchmarking a fast, satisficing vehicle routing algorithm for public health emergency planning and response: “Good Enough for Jazz”. PeerJ Computer Science, 9, e1541. https://doi.org/10.7717/peerj-cs.1541
  • Mohd Nordin, N. A., Kadir, N., Zaharudin, Z. A., & Nordin, N. A. (2011). An application of the A* algorithm on the ambulance routing. 2011 IEEE Colloquium on Humanities, Science and Engineering, 855-859. https://doi.org/10.1109/CHUSER.2011.6163858
  • Ngo, T.-G., Dao, T.-K., Thandapani, J., Nguyen, T.-T., Pham, D.-T., & Vu, V.-D. (2021). Analysis Urban Traffic Vehicle Routing Based on Dijkstra Algorithm Optimization. Içinde H. Sharma, M. K. Gupta, G. S. Tomar, & W. Lipo (Ed.), Communication and Intelligent Systems (ss. 69-79). Springer. https://doi.org/10.1007/978-981-16-1089-9_7
  • Ong, M. E. H., Ng, F. S. P., Overton, J., Yap, S., Andresen, D., Yong, D. K. L., Lim, S. H., & Anantharaman, V. (2009). Geographic-time distribution of ambulance calls in Singapore: Utility of geographic information system in ambulance deployment (CARE 3). Annals of the Academy of Medicine, Singapore, 38(3), 184-191.
  • Ozcan-Tatar, C., Tukel, E., Yilmaz, E., Cabuk, S. N., & Ozturk, G. (2023). Routing and Navigation Solutions for Emergency Vehicles in Urban Emergency Management. Resourceedings, 3(1), 75-80. https://doi.org/10.21625/resourceedings.v3i1.946
  • Qing, G., Zheng, Z., & Yue, X. (2017). Path-planning of automated guided vehicle based on improved Dijkstra algorithm. 2017 29th Chinese Control And Decision Conference (CCDC), 7138-7143. https://doi.org/10.1109/CCDC.2017.7978471
  • Rout, R. R., Vemireddy, S., Raul, S. K., & Somayajulu, D. V. L. N. (2020). Fuzzy logic-based emergency vehicle routing: An IoT system development for smart city applications. Computers & Electrical Engineering, 88, 106839. https://doi.org/10.1016/j.compeleceng.2020.106839
  • Sarı, F. (2017). A GIS Based New Navigation Approach for Reducing Emergency Vehicle’s Response Time. Selçuk Üniversitesi Mühendislik, Bilim Ve Teknoloji Dergisi, 5(1), Article 1. https://doi.org/10.15317/Scitech.2017.69
  • Sayed, S., Ibrahim, R., & Hefny, H. (2018). An Efficient Ambulance Routing System for Emergency Cases based on Dijkstra’s Algorithm, AHP, and GIS.
  • Sutherland, M., & Chakrabortty, R. K. (2023). An optimal ambulance routing model using simulation based on patient medical severity. Healthcare Analytics, 4, 100256. https://doi.org/10.1016/j.health.2023.100256
  • Talarico, L., Meisel, F., & Sörensen, K. (2015). Ambulance routing for disaster response with patient groups. Computers & Operations Research, 56, 120-133. https://doi.org/10.1016/j.cor.2014.11.006
  • Tassone, J., & Choudhury, S. (2020). A Comprehensive Survey on the Ambulance Routing and Location Problems (arXiv:2001.05288). arXiv. https://doi.org/10.48550/arXiv.2001.05288
  • Tikani, H., & Setak, M. (2019). Ambulance routing in disaster response scenario considering different types of ambulances and semi soft time windows. Journal of Industrial and Systems Engineering, 12(1), 95-128.
  • Tsai, Y.-L., Rastogi, C., Kitanidis, P. K., & Field, C. B. (2021). Routing algorithms as tools for integrating social distancing with emergency evacuation. Scientific Reports, 11(1), Article 1. https://doi.org/10.1038/s41598-021-98643-z
  • Ueda, K., Shimizu, A., Nitta, H., & Inoue, K. (2012). Long-range transported Asian Dust and emergency ambulance dispatches. Inhalation Toxicology, 24(12), 858-867. https://doi.org/10.3109/08958378.2012.724729
  • Zeng, Z., Yi, W., Wang, S., & Qu, X. (2021). Emergency Vehicle Routing in Urban Road Networks with Multistakeholder Cooperation. Journal of Transportation Engineering, Part A: Systems, 147(10), 04021064. https://doi.org/10.1061/JTEPBS.0000577
  • Zong, F., Zeng, M., Cao, Y., & Liu, Y. (2021). Local Dynamic Path Planning for an Ambulance Based on Driving Risk and Attraction Field. Sustainability, 13(6), Article 6. https://doi.org/10.3390/su13063194
Year 2025, Volume: 8 Issue: 1, 90 - 103, 25.03.2025
https://doi.org/10.51513/jitsa.1532308

Abstract

Project Number

TUBITAK 2244/119C200

References

  • Abdeen, M. A. R., Ahmed, M. H., Seliem, H., Sheltami, T. R., Alghamdi, T. M., & El-Nainay, M. (2022). A Novel Smart Ambulance System—Algorithm Design, Modeling, and Performance Analysis. IEEE Access, 10, 42656-42672. IEEE Access. https://doi.org/10.1109/ACCESS.2022.3168736
  • Alamri, A. (2023). A Smart Spatial Routing and Accessibility Analysis System for EMS Using Catchment Areas of Voronoi Spatial Model and Time-Based Dijkstra’s Routing Algorithm. International Journal of Environmental Research and Public Health, 20(3), Article 3. https://doi.org/10.3390/ijerph20031808
  • Albano, R., Sole, A., Adamowski, J., & Mancusi, L. (2014). A GIS-based model to estimate flood consequences and the degree of accessibility and operability of strategic emergency response structures in urban areas. Natural Hazards and Earth System Sciences, 14(11), 2847-2865. https://doi.org/10.5194/nhess-14-2847-2014
  • Amr, M. F., Elgarej, M., Benmoussa, N., Mansouri, K., & Qbadou, M. (2021). Towards a Distributed SMA-based Solution for the Interoperability of Hospital Information Systems for Better Routing of Emergency Ambulances. International Journal of Online and Biomedical Engineering (iJOE), 17(12), Article 12. https://doi.org/10.3991/ijoe.v17i12.25455
  • Aringhieri, R., Bruni, M. E., Khodaparasti, S., & van Essen, J. T. (2017). Emergency medical services and beyond: Addressing new challenges through a wide literature review. Computers & Operations Research, 78, 349-368. https://doi.org/10.1016/j.cor.2016.09.016
  • Blodgett, J. M., Robertson, D. J., Pennington, E., Ratcliffe, D., & Rockwood, K. (2021). Alternatives to direct emergency department conveyance of ambulance patients: A scoping review of the evidence. Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, 29(1), 4. https://doi.org/10.1186/s13049-020-00821-x
  • Darwassh Hanawy Hussein, T., Frikha, M., Ahmed, S., & Rahebi, J. (2022). BA-CNN: Bat Algorithm-Based Convolutional Neural Network Algorithm for Ambulance Vehicle Routing in Smart Cities. Mobile Information Systems, 2022, e7339647. https://doi.org/10.1155/2022/7339647
  • Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1(1), 269-271. https://doi.org/10.1007/BF01386390
  • Feroz, B., Mehmood, A., Maryam, H., Zeadally, S., Maple, C., & Shah, M. A. (2021). Vehicle-Life Interaction in Fog-Enabled Smart Connected and Autonomous Vehicles. IEEE Access, 9, 7402-7420. IEEE Access. https://doi.org/10.1109/ACCESS.2020.3049110
  • Hart, P. E., Nilsson, N. J., & Raphael, B. (1968). A formal basis for the heuristic determination of minimum cost paths. IEEE Transactions on Systems Science and Cybernetics, 4(2), 100–107. https://doi.org/10.1109/TSSC.1968.300136
  • Holland, J. H. (1975). Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence. University of Michigan Press.
  • Johnson, S., & Yu, D. (2020). From flooding to finance: NHS ambulance-assisted evacuations of care home residents in Norfolk and Suffolk, UK. Journal of Flood Risk Management, 13(1), e12592. https://doi.org/10.1111/jfr3.12592
  • Kula, U., Tozanli, O., & Tarakcio, S. (2012). Emergency Vehicle Routing in Disaster Response Operations. 23rd Annual Conference of the Production and Operations Management Society.
  • Mascarenhas, N., G, P., Agrawal, M., P, S., & A, A. (2013). A Proposed Model for Traffic Signal Preemption Using Global Positioning System (GPS). Computer Science & Information Technology ( CS & IT ), 219-226. https://doi.org/10.5121/csit.2013.3423
  • McDaniel, E. L., Akwafuo, S., Urbanovsky, J., & Mikler, A. R. (2023). Benchmarking a fast, satisficing vehicle routing algorithm for public health emergency planning and response: “Good Enough for Jazz”. PeerJ Computer Science, 9, e1541. https://doi.org/10.7717/peerj-cs.1541
  • Mohd Nordin, N. A., Kadir, N., Zaharudin, Z. A., & Nordin, N. A. (2011). An application of the A* algorithm on the ambulance routing. 2011 IEEE Colloquium on Humanities, Science and Engineering, 855-859. https://doi.org/10.1109/CHUSER.2011.6163858
  • Ngo, T.-G., Dao, T.-K., Thandapani, J., Nguyen, T.-T., Pham, D.-T., & Vu, V.-D. (2021). Analysis Urban Traffic Vehicle Routing Based on Dijkstra Algorithm Optimization. Içinde H. Sharma, M. K. Gupta, G. S. Tomar, & W. Lipo (Ed.), Communication and Intelligent Systems (ss. 69-79). Springer. https://doi.org/10.1007/978-981-16-1089-9_7
  • Ong, M. E. H., Ng, F. S. P., Overton, J., Yap, S., Andresen, D., Yong, D. K. L., Lim, S. H., & Anantharaman, V. (2009). Geographic-time distribution of ambulance calls in Singapore: Utility of geographic information system in ambulance deployment (CARE 3). Annals of the Academy of Medicine, Singapore, 38(3), 184-191.
  • Ozcan-Tatar, C., Tukel, E., Yilmaz, E., Cabuk, S. N., & Ozturk, G. (2023). Routing and Navigation Solutions for Emergency Vehicles in Urban Emergency Management. Resourceedings, 3(1), 75-80. https://doi.org/10.21625/resourceedings.v3i1.946
  • Qing, G., Zheng, Z., & Yue, X. (2017). Path-planning of automated guided vehicle based on improved Dijkstra algorithm. 2017 29th Chinese Control And Decision Conference (CCDC), 7138-7143. https://doi.org/10.1109/CCDC.2017.7978471
  • Rout, R. R., Vemireddy, S., Raul, S. K., & Somayajulu, D. V. L. N. (2020). Fuzzy logic-based emergency vehicle routing: An IoT system development for smart city applications. Computers & Electrical Engineering, 88, 106839. https://doi.org/10.1016/j.compeleceng.2020.106839
  • Sarı, F. (2017). A GIS Based New Navigation Approach for Reducing Emergency Vehicle’s Response Time. Selçuk Üniversitesi Mühendislik, Bilim Ve Teknoloji Dergisi, 5(1), Article 1. https://doi.org/10.15317/Scitech.2017.69
  • Sayed, S., Ibrahim, R., & Hefny, H. (2018). An Efficient Ambulance Routing System for Emergency Cases based on Dijkstra’s Algorithm, AHP, and GIS.
  • Sutherland, M., & Chakrabortty, R. K. (2023). An optimal ambulance routing model using simulation based on patient medical severity. Healthcare Analytics, 4, 100256. https://doi.org/10.1016/j.health.2023.100256
  • Talarico, L., Meisel, F., & Sörensen, K. (2015). Ambulance routing for disaster response with patient groups. Computers & Operations Research, 56, 120-133. https://doi.org/10.1016/j.cor.2014.11.006
  • Tassone, J., & Choudhury, S. (2020). A Comprehensive Survey on the Ambulance Routing and Location Problems (arXiv:2001.05288). arXiv. https://doi.org/10.48550/arXiv.2001.05288
  • Tikani, H., & Setak, M. (2019). Ambulance routing in disaster response scenario considering different types of ambulances and semi soft time windows. Journal of Industrial and Systems Engineering, 12(1), 95-128.
  • Tsai, Y.-L., Rastogi, C., Kitanidis, P. K., & Field, C. B. (2021). Routing algorithms as tools for integrating social distancing with emergency evacuation. Scientific Reports, 11(1), Article 1. https://doi.org/10.1038/s41598-021-98643-z
  • Ueda, K., Shimizu, A., Nitta, H., & Inoue, K. (2012). Long-range transported Asian Dust and emergency ambulance dispatches. Inhalation Toxicology, 24(12), 858-867. https://doi.org/10.3109/08958378.2012.724729
  • Zeng, Z., Yi, W., Wang, S., & Qu, X. (2021). Emergency Vehicle Routing in Urban Road Networks with Multistakeholder Cooperation. Journal of Transportation Engineering, Part A: Systems, 147(10), 04021064. https://doi.org/10.1061/JTEPBS.0000577
  • Zong, F., Zeng, M., Cao, Y., & Liu, Y. (2021). Local Dynamic Path Planning for an Ambulance Based on Driving Risk and Attraction Field. Sustainability, 13(6), Article 6. https://doi.org/10.3390/su13063194
There are 31 citations in total.

Details

Primary Language Turkish
Subjects Artificial Intelligence (Other), Navigation and Position Fixing
Journal Section Articles
Authors

Ceren Özcan Tatar 0000-0003-4075-8329

Zahra Khoda Karimi 0000-0002-9735-4635

Murat Akın 0000-0003-0001-1036

Ozan Kıvanç 0009-0004-2869-0688

Emrah Yılmaz This is me 0000-0001-8850-8199

Mehmet Küçükpehlivan 0000-0002-9686-481X

Project Number TUBITAK 2244/119C200
Early Pub Date March 19, 2025
Publication Date March 25, 2025
Submission Date August 12, 2024
Acceptance Date February 12, 2025
Published in Issue Year 2025 Volume: 8 Issue: 1

Cite

APA Özcan Tatar, C., Khoda Karimi, Z., Akın, M., Kıvanç, O., et al. (2025). Acil durum araçlarının yönlendirilmesinde akıllı ulaşım çözümleri: Ambulans rota oluşturma optimizasyonu. Akıllı Ulaşım Sistemleri Ve Uygulamaları Dergisi, 8(1), 90-103. https://doi.org/10.51513/jitsa.1532308