Öz
Otonom Araç Sistemlerinin kullanımına yönelik çalışmalar gün geçtikçe artmaktadır. Otonom araçların arazi kullanımı denemelerinin yanında yaya ve insanlı araç trafiğinin de olduğu şehir içi trafiğinde kullanımına yönelik değişik yöntem ve uygulamar devam etmektedir. Otonom aracın karma trafik içerisinde, kendine ve diğer trafik unsurlarına zarar vermeden hareket edebilmesi çözüm bekleyen en önemli problemlerin başında gelmektedir. Yapılan çalışmalarda otonom aracın güvenli seyrüseferi için mantıksal karar vericiler ve pek çok kural tabanı oluşturulmakta ve sürücü davranışı modellenmeye çalışılmaktadır. Bu çalışma kapsamında potansiyel fonksiyonlar ile modellenmiş yol ve araçlardan oluşan kavşak yapısında hareket eden otonom araçların birlerine çarpmadan şerit takibi yaparak kavşak içerisinde geçiş öncelikleri oluşturması ve hedefledikleri noktaya güvenli şekilde ulaşmaları incelenmiştir. Çalışmanın amacı mantıksal karar verme karmaşık yapısını, oluşturulan yapay potansiye alan haritası ile sağlamaktır. Yapay potansiyel alan yaklaşımı otonom araç uygulamalarında yol planlaması, şerit takibi uygulamalarında başvurulan tekniklerden birisidir. Bu çalışma ile yapay potansiyel alan yaklaşımlı yol ve şerit ile kavşak içerisinde çarpışma ihtimali olan aracın hareketli(dinamik) engel olarak modellenmesi de birleştirilerek çözüm aranmıştır. Çalışma sonucunda görülmüştür ki mantıksal karar vericilerin kullanılmasının yerine, mantıksal kural tabanına uygun olarak hazırlanmış/optimize edilmiş yapay potansiyel alan kullanılması başarılı sonuçlar vermiştir. Çalışmada yapay potansiyel alan oluşturulması için harmonik ve gaussien fonksiyonların kullanımı ile istek dışı local minimaların oluşması engellenmiştir.
Anahtar Kelimeler
Seyrüsefer Yapay Potansiyel Alanlar Yol Planlaması Engelden Kaçınma.
Kaynakça
- Apostoloff, N., & Zelinsky, A., (2003). Robust vision based lane tracking using multiple cues and particle filtering. Intelligent Vehicles Symposium, Pages: 558 – 563,
- Arkin R.C., (1987). Towards cosmopolitan robots: Intelligent navigation in extended man-made environments. Technical reports COINS Department, University of Massachusetts.
- Brooks R.A., (1986). A robust layered control systems for a mobile robot. IEEE Journal of Robotics and Automation, Vol. 2, No.1, pp: 14-23.
- Connoly C.I., & Grupen R.A., (1992). Applications of Harmonic Functions to Robotics. University of Massachusetts at Amherst Thesis.
- Connoly C.I., (1997). Harmonic functions and collision probabilities. International Journal of Robotics Research, vol. 16-4, pp:497-507.
- Huang, X., & Houshangi, N., (2009). A vision-based autonomous lane following system for a mobile robot. Systems, Man and Cybernetics, SMC 2009. IEEE International Conference, Pages: 2344 – 2349. Khatib O., (1986). Real time obstacle avoidance for manipulators and mobile robots. International Journal of Robotics Research Vol. 5-1, pp: 90-99.
- Knoop, V.L., & Buisson, C., (2015). Calibration and validation of probabilistic discretionary lane-change models. IEEE Transactions on Intelligent Transportation Systems, , Volume: 16, Issue: 2 Pages: 834 – 843.
- Koditschek D.E., (1987). Exact robot navigation by means of potential functions: Some topological considerations. IEEE In International Conference on Robotics and Automation, pp: 1-6.
- Krough B.H., & Thorpe, C.E., (1986). Integrated path planning and dynamic steering control for aautonomous vehicles. IEEE International Conference on Robotics and Automation, pp: 1664-1669.
- Nair, R.R., Behera, L., Kumar, V., & Jamshidi, M., (2015). Multisatellite formation control for remote sensing applications using artificial potential field and adaptive fuzzy sliding mode control. IEEE Systems Journal. Volume: 9, No: 2, pp: 508 - 518.
- Oguz A.E., & Duymaz E., (2016). Artificial potantial field based autonomus UAV fligh in dynamic environment. 16th AIAA Aviation Technology, Integration, and Operations Conference, Doi: 10.2514/6.2016-3454
- Reyes, L.A.V.; & Tanner, H.G., (2015). flocking, formation control, and path following for a group of mobile robots. IEEE Transactions on Control System Technology Vol.23, Issue 4, 1268-1282.
- Shi C., Zhang M., & Peng J., (2007). Harmonic potential field method for autonomous ship navigation. Shanghai Maritime University Thesis China.
- Sisli U.Y., & Temeltas H., (2008). Decentralized formation control of multi vehicles systems with non-holonomic constraints using artificial potential field. 17th IFAC World Congress, Vol.17, 6815-6820,
- Wang, C.; & Coifman, B., (2008). The effect of lane-change maneuvers on a simplified car-following theory. IEEE Transactions on Intelligent Transportation Systems, Volume: 9, Issue: 3, Pages: 523 – 535,
Determination of Intersection Transition Priority of Autonomous Vehicles with Artificial Potential Field
Öz
Studies on the use of Autonomous Vehicle Systems are increasing day by day. In addition to the land use trials of autonomous vehicles, various methods and practices are continuing for the use of pedestrian and manned vehicle traffic in urban traffic. The ability of the autonomous vehicle to move in mixed traffic without harming itself and other traffic elements is one of the most important problems waiting for a solution. In the studies, logical decision makers and many rule bases are created for safe navigation of autonomous vehicles and driver behavior is tried to be modeled. Within the scope of this study, autonomous vehicles moving in the intersection structure, which consists of roads and vehicles modeled with potential functions, follow the lane without hitting each other and create transition priorities in the intersection and reach their target point safely. The aim of the study is to provide the logical decision making complex with the artificial potential area map created. Artificial potential field approach is one of the techniques used in road planning and lane tracking applications in autonomous vehicle applications. In this study, a solution was sought by combining the artificial potential field approach road and lane with the vehicle that is likely to collide in the intersection as a moving (dynamic) obstacle. As a result of the study, it was seen that instead of using logical decision makers, the use of artificial potential field prepared/optimized in accordance with the logical rule base gave successful results. In the study, the formation of undesired local minimas was prevented by the use of harmonic and Gaussian functions to create an artificial potential field.
Anahtar Kelimeler
Navigation Artificial Potential Field Path Planning Obstacle Avoiding.
Kaynakça
- Apostoloff, N., & Zelinsky, A., (2003). Robust vision based lane tracking using multiple cues and particle filtering. Intelligent Vehicles Symposium, Pages: 558 – 563,
- Arkin R.C., (1987). Towards cosmopolitan robots: Intelligent navigation in extended man-made environments. Technical reports COINS Department, University of Massachusetts.
- Brooks R.A., (1986). A robust layered control systems for a mobile robot. IEEE Journal of Robotics and Automation, Vol. 2, No.1, pp: 14-23.
- Connoly C.I., & Grupen R.A., (1992). Applications of Harmonic Functions to Robotics. University of Massachusetts at Amherst Thesis.
- Connoly C.I., (1997). Harmonic functions and collision probabilities. International Journal of Robotics Research, vol. 16-4, pp:497-507.
- Huang, X., & Houshangi, N., (2009). A vision-based autonomous lane following system for a mobile robot. Systems, Man and Cybernetics, SMC 2009. IEEE International Conference, Pages: 2344 – 2349. Khatib O., (1986). Real time obstacle avoidance for manipulators and mobile robots. International Journal of Robotics Research Vol. 5-1, pp: 90-99.
- Knoop, V.L., & Buisson, C., (2015). Calibration and validation of probabilistic discretionary lane-change models. IEEE Transactions on Intelligent Transportation Systems, , Volume: 16, Issue: 2 Pages: 834 – 843.
- Koditschek D.E., (1987). Exact robot navigation by means of potential functions: Some topological considerations. IEEE In International Conference on Robotics and Automation, pp: 1-6.
- Krough B.H., & Thorpe, C.E., (1986). Integrated path planning and dynamic steering control for aautonomous vehicles. IEEE International Conference on Robotics and Automation, pp: 1664-1669.
- Nair, R.R., Behera, L., Kumar, V., & Jamshidi, M., (2015). Multisatellite formation control for remote sensing applications using artificial potential field and adaptive fuzzy sliding mode control. IEEE Systems Journal. Volume: 9, No: 2, pp: 508 - 518.
- Oguz A.E., & Duymaz E., (2016). Artificial potantial field based autonomus UAV fligh in dynamic environment. 16th AIAA Aviation Technology, Integration, and Operations Conference, Doi: 10.2514/6.2016-3454
- Reyes, L.A.V.; & Tanner, H.G., (2015). flocking, formation control, and path following for a group of mobile robots. IEEE Transactions on Control System Technology Vol.23, Issue 4, 1268-1282.
- Shi C., Zhang M., & Peng J., (2007). Harmonic potential field method for autonomous ship navigation. Shanghai Maritime University Thesis China.
- Sisli U.Y., & Temeltas H., (2008). Decentralized formation control of multi vehicles systems with non-holonomic constraints using artificial potential field. 17th IFAC World Congress, Vol.17, 6815-6820,
- Wang, C.; & Coifman, B., (2008). The effect of lane-change maneuvers on a simplified car-following theory. IEEE Transactions on Intelligent Transportation Systems, Volume: 9, Issue: 3, Pages: 523 – 535,
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | Mühendislik |
| Bölüm | Makaleler |
| Yazarlar | |
| Yayımlanma Tarihi | 31 Aralık 2021 |
| Yayımlandığı Sayı | Yıl 2021 Sayı: 32 |
Cited By
- Makale Dosyaları