Journals / Endüstri Mühendisliği / 2026 / Cilt: 37 Sayı: 1

FAULT TOLERANCE SOLUTIONS FOR VEHICLE FAILURES IN FLEET MANAGEMENT

FİLO YÖNETİMİNDE ARAÇ ARIZASI İÇİN HATA TOLERANS ÇÖZÜMLERİ

Mehmet Arıkan(ESKISEHIR OSMANGAZI UNIVERSITY, CENTER OF INTELLIGENT SYSTEMS APPLICATION RESEARCH)0009-0005-4364-8768
İnci Sarıçiçek(ESKISEHIR OSMANGAZI UNIVERSITY, FACULTY OF ENGINEERING-ARCHITECTURE, DEPARTMENT OF INDUSTRIAL ENGINEERING)0000-0002-3528-7342
Sinem Bozkurt Keser(ESKISEHIR OSMANGAZI UNIVERSITY, FACULTY OF ENGINEERING AND ARCHITECTURE, DEPARTMENT OF COMPUTER ENGINEERING)0000-0002-8013-6922
Yunus Sabri Kırca(ESKISEHIR OSMANGAZI UNIVERSITY, FACULTY OF ENGINEERING AND ARCHITECTURE, DEPARTMENT OF COMPUTER ENGINEERING)0000-0001-5938-2822
Ahmet Yazici(ESKISEHIR OSMANGAZI UNIVERSITY, FACULTY OF ENGINEERING AND ARCHITECTURE, DEPARTMENT OF COMPUTER ENGINEERING)0000-0001-5589-2032
Pages
25–47
Publication Date
2026-04-22
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This study creates potential for a fault-tolerant planning system by offering proactive solutions for vehicle failures within the scope of dynamic rerouting in fleet management software.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Designing fleet management systems with built-in fault tolerance across vehicles, operators, environment, communication, and software components is critical to ensuring the long-term sustainability of operations.
📊
Key Findings & Data:Ensuring operational continuity in the transport sector requires proactive strategies for anticipating and resolving such failures.
💡
Conclusion & Impact:This study creates potential for a fault-tolerant planning system by offering proactive solutions for vehicle failures within the scope of dynamic rerouting in fleet management software.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Hata toleransı · Dinamik rotalama · Proaktif yaklaşım

Abstract

Designing fleet management systems with built-in fault tolerance across vehicles, operators, environment, communication, and software components is critical to ensuring the long-term sustainability of operations. A key design priority is to minimise the negative impacts of vehicle failures on operational processes. Ensuring operational continuity in the transport sector requires proactive strategies for anticipating and resolving such failures. In this study, rerouting is carried out using recovery plans that are proactively generated based on existing vehicle routes to address potential electric vehicle failures. The proposed system performs rerouting while considering time window constraints through the Regret-2 and 2-opt approaches. If a charging need arises on the newly created routes, the vehicle is directed to a charging station suitable for the route. Simulation results conducted within the scope of test scenarios demonstrate that the proposed approach not only ensures service continuity but also addresses battery, load, and time constraints. This study creates potential for a fault-tolerant planning system by offering proactive solutions for vehicle failures within the scope of dynamic rerouting in fleet management software.

Özet

Filo yönetim sistemlerinin araçlar, operatörler, çevre, iletişim ve yazılım bileşenleri arasında yerleşik hata toleransı ile tasarlanması, operasyonların uzun vadeli sürdürülebilirliğini sağlamak için kritik öneme sahiptir. Araç arızalarının operasyonel süreçler üzerindeki olumsuz etkilerini en aza indirmek temel bir tasarım önceliğidir. Taşımacılık sektöründe operasyonel sürekliliğin sağlanması, bu tür arızaların öngörülmesi ve çözülmesi için proaktif stratejiler gerektirir. Bu çalışmada, potansiyel elektrikli araç arızalarını ele almak için mevcut araç rotalarına dayalı olarak proaktif bir şekilde oluşturulan kurtarma planları kullanılarak yeniden rotalama gerçekleştirilmektedir. Önerilen sistem, Regret-2 ve 2-opt yaklaşımları ile zaman penceresi kısıtlarını dikkate alan yeniden rotalama işlemini gerçekleştirmektedir. Yeniden oluşturulan rotalarda şarj ihtiyacı ortaya çıkıyor ise, rotaya uygun şarj istasyonuna yönlendirilme sağlanmaktadır. Test senaryoları kapsamında gerçekleştirilen simülasyon sonuçları, önerilen yaklaşımın yalnızca hizmet sürekliliğini sağlamakla kalmayıp, aynı zamanda batarya, yük ve zaman kısıtlamalarını da sağladığını göstermiştir. Çalışma, filo yönetim yazılımlarında dinamik rotalama kapsamında araç arızası için proaktif çözümler sunarak, hata toleranslı bir planlama sistemi için potansiyel oluşturmaktadır.

🔖

Cite This Article

Arıkan, M., Sarıçiçek, İ., Keser, S. B., Kırca, Y. S., Yazici, A. (2026). FAULT TOLERANCE SOLUTIONS FOR VEHICLE FAILURES IN FLEET MANAGEMENT. Endüstri Mühendisliği, Cilt: 37 Sayı: 1, 25–47. https://doi.org/10.46465/endustrimuhendisligi.1786581

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (41)

  1. Abbaspour, A., Mokhtari, S., Sargolzaei, A., & Yen, K. K. (2020). A survey on active fault-tolerant control systems. Electronics, 9(9), 1513. Doi: https://doi.org/10.3390/electronics9091513
  2. Abid, A., Khan, M. T., & Iqbal, J. (2021). A review on fault detection and diagnosis techniques: basics and beyond. Artificial Intelligence Review, 54(5), 3639–3664. Doi: https://doi.org/10.1007/s10462-020-09934-2
  3. Amin, A. A., & Hasan, K. M. (2019). A review of fault tolerant control systems: advancements and applications. Measurement, 143, 58–68. Doi: https://doi.org/10.1007/s10462-020-09934-2
  4. Aslan, Ö., Sarıçiçek, İ., & Yazıcı, A. (2025). ESOGU-CEVRPTW [Data set]. Mendeley Data. Doi: https://doi.org/10.17632/7vjzvxh72d.1
  5. Bennett, J. W., Atkinson, G. J., Mecrow, B. C., & Atkinson, D. J. (2011). Fault-tolerant design considerations and control strategies for aerospace drives. IEEE Transactions on Industrial Electronics, 59(5), 2049–2058. Doi: https://doi.org/10.1109/TIE.2011.2159356
  6. Buffa, E. S. (1964). Allocating facilities with CRAFT. Harvard Business Review, 3, 136–158.
  7. dos Santos, V. A., Manacero, A., Lobato, R. S., Spolon, R., & Cavenaghi, M. A. (2020). A systematic review of fault tolerance solutions for communication errors in open source cloud computing. 2020 15th Iberian Conference on Information Systems and Technologies (CISTI), 1–6. Doi: https://doi.org/10.23919/CISTI49556.2020.9140933
  8. Dulai, T., Werner-Stark, A., & Hangos, K. M. (2018). Algorithm for directing cooperative vehicles of a vehicle routing problem for improving fault-tolerance. Optimization and Engineering, 19, 239–270. Doi: https://doi.org/10.1007/s11081-017-9353-6
  9. Eglese, R., & Zambirinis, S. (2018). Disruption management in vehicle routing and scheduling for road freight transport: a review. Top, 26, 1–17. Doi: https://doi.org/10.1007/s11750-018-0469-4
  10. ESOGU CISAR. (2025, September 17). Fault Tolerance Solutions for Electric Vehicle Failures in Fleet Management [Video file]. YouTube. Retrieved from https://youtu.be/gIVbGlS2C_0
  11. Faramarzzadeh, M., & Akpınar, Ş. (2023). A grey wolf optimizer algorithm for the vehicle routing problem with time windows and simultaneous pick-ups and deliveries. Endüstri Mühendisliği, 34(2), 141-160. Doi: https://doi.org/10.46465/endustrimuhendisligi.1232511
  12. FIWARE Foundation. (2016). Cygnus Architecture. Retrieved from https://fiware-cygnus.readthedocs.io/en/1.5.0/architecture/index.html
  13. FIWARE Foundation. (2025, May 6). Orion Context Broker Documentation. Retrieved from https://fiware-orion.readthedocs.io/
  14. Hasebe, K., Sasaki, S., & Kato, K. (2018). Fault tolerance in the traffic management system of a last-mile transportation service. VEHITS, 552–557. Doi: https://doi.org/10.5220/0006794505520557
  15. Hu, X., Sun, L., & Liu, L. (2013). A PAM approach to handling disruptions in real-time vehicle routing problems. Decision Support Systems, 54(3), 1380–1393. Doi: https://doi.org/10.1016/j.dss.2012.12.014
  16. Keser, S. B., Sarıçiçek, İ., & Yazıcı, A. (2025). Electric vehicle routing with recharging stations: trade-offs in last-mile delivery. IET Intelligent Transport Systems, 19(1). Doi: https://doi.org/10.1049/itr2.70052
  17. Koren, I., & Krishna, C. M. (2020). Fault-tolerant systems. Morgan Kaufmann. Doi: https://doi.org/10.1016/B978-0-12-818105-8.00018-8
  18. Kumar, P., Nair, K., & others. (2024). Fault tolerance and reliability in advanced computing systems: Techniques and trends. Journal of Advanced Computing Systems, 4(7). Doi: https://doi.org/10.69987/
  19. Lala, J. H., & Harper, R. E. (1994). Architectural principles for safety-critical real-time applications. Proceedings of the IEEE, 82(1), 25–40. Doi: https://doi.org/10.1109/5.259424
  20. Lee, P. A., & Anderson, T. (1990). Fault tolerance. Springer. Doi: https://doi.org/10.1007/978-3-7091-8990-0
  21. Li, J. Q., Mirchandani, P. B., & Borenstein, D. (2009). Real-time vehicle rerouting problems with time windows. European Journal of Operational Research, 194(3), 711–727. Doi: https://doi.org/10.1016/j.ejor.2007.12.037
  22. Li, X., & Zhang, W. (2010). An adaptive fault-tolerant multisensor navigation strategy for automated vehicles. IEEE Transactions on Vehicular Technology, 59(6), 2815–2829. Doi: https://doi.org/10.1109/TVT.2010.2050014
  23. Li, Y., & Phillips, W. (2018). Learning from route plan deviation in last-mile delivery. Retrieved from http://hdl.handle.net/1721.1/118135
  24. Lipiec, B., Mrugalski, M., Witczak, M., & Stetter, R. (2022). Towards a health-aware fault tolerant control of complex systems: A vehicle fleet case. International Journal of Applied Mathematics and Computer Science, 32(4), 619–634. Doi: https://doi.org/10.34768/amcs-2022-0043
  25. Mamasis, K., Minis, I., & Dikas, G. (2013). Managing vehicle breakdown incidents during urban distribution of a common product. Journal of the Operational Research Society, 64(6), 925–937. Doi: https://doi.org/10.1057/ jors.2012.93
  26. Mu, Q., Fu, Z., Lysgaard, J., & Eglese, R. (2011). Disruption management of the vehicle routing problem with vehicle breakdown. Journal of the Operational Research Society, 62(4), 742–749. Doi: https://doi.org/10.1057/ jors.2010.19
  27. Nelson, V. P. (1990). Fault-tolerant computing: Fundamental concepts. Computer, 23(7), 19–25. Doi: https://doi.org/10.1109/2.56849
  28. Österberg, D., & Lilius, J. (2003). Rethinking software updating: Concepts for improved updatability. Turku Centre for Computer Science.
  29. Polat, A. A., Bozkurt Keser, S., Sarıçiçek, İ., Erdoğmuş, A. K., Kafalı, A., & Yazıcı, A. (2025). A dataset for state of charge and range estimation of an L5 type electric vehicle that is used for Urban Logistic. Data in Brief, 62. Doi: https://doi.org/10.1016/j.dib.2025.111933
  30. Polat, A. A., Bozkurt Keser, S., Sarıçiçek, İ., & Yazıcı, A. (2025). Analysis of factors affecting electric vehicle range estimation: A case study of the Eskisehir Osmangazi University Campus. Sustainability (Switzerland), 17(8). Doi: https://doi.org/10.3390/su17083488
  31. Pasham, S. D. (2020). Fault-tolerant distributed computing for real-time applications in critical systems. The Computertech, 1–29. Doi: https://doi.org/10.18535/ijsrm/v8i01.ec04
  32. Ropke, S., & Pisinger, D. (2006). An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows. Transportation Science, 40(4), 455–472. Doi: https://doi.org/10.1287/trsc.1050.0135
  33. Rullo, A., Serra, E., & Lobo, J. (2019). Redundancy as a measure of fault-tolerance for the Internet of Things: A review. Policy-Based Autonomic Data Governance, 202–226. Doi: https://doi.org/10.1007/978-3-030-17277-0_11
  34. Seo, S. H., Moon, T. Y., Kim, J. H., Kwon, K. H., Jeon, J. W., & Hwang, S. H. (2008). A fault-tolerant gateway for in-vehicle networks. 2008 6th IEEE International Conference on Industrial Informatics, 1144–1148. Doi: https://doi.org/10.1109/INDIN.2008.4618275
  35. Su, P. H., Shih, C. S., Hsu, J. Y. J., Lin, K. J., & Wang, Y. C. (2014). Decentralized fault tolerance mechanism for intelligent IoT/M2M middleware. 2014 IEEE World Forum on Internet of Things (WF-IoT), 45–50. Doi: https://doi.org/10.1109/WF-IoT.2014.6803115
  36. Thomas, M. O., & Rad, B. B. (2017). Reliability evaluation metrics for internet of things, car tracking system: a review. Int. J. Inf. Technol. Comput. Sci.(IJITCS), 9(2), 1–10. Doi: https://doi.org/10.5815/ijitcs.2017.02.01
  37. Torres-Huitzil, C., & Girau, B. (2017). Fault and error tolerance in neural networks: A review. IEEE Access, 5, 17322–17341. Doi: https://doi.org/10.1109/ACCESS.2017.2742698
  38. Umer, A., Ali, M., & Jehangiri, A. I. (2025). Fault tolerant and mobility-aware task offloading and scheduling model for IoT logistics. Journal of Supercomputing, 81(11). Doi: https://doi.org/10.1007/s11227-025-07627-7
  39. Ünal, Y., Sarçiçek, İ., Bozkurt Keser, S., & Yazcı, A. (2025). Electric vehicle routing with time windows and charging stations from the perspective of customer satisfaction. Applied Sciences, 15(9), 4703. Doi: https://doi.org/10.3390/app15094703
  40. Xiang, J., Weng, C., Zhao, D., Tian, J., Xiong, S., Li, L., & Andrzejakb, A. (2018). A new software rejuvenation model for Android. 2018 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW), 293–299. Doi: https://doi.org/10.1109/ISSREW.2018.00021
  41. Zeimpekis, V., Giaglis, G. M., & Minis, I. (2005). A dynamic real-timefleet management system for incident handling in city logistics. 2005 IEEE 61st Vehicular Technology Conference, 5, 2900–2904. Doi: https://doi.org/10.1109/VETECS.2005.1543877