Optimization-based control, estimation, and ldentification of urban road transport systems
Başlık çevirisi mevcut değil.
- Tez No: 720593
- Danışmanlar: PROF. C. N. JONES
- Tez Türü: Doktora
- Konular: Ulaşım, Şehircilik ve Bölge Planlama, Transportation, Urban and Regional Planning
- Anahtar Kelimeler: traÿc control, large-scale urban road networks, macroscopic fundamental diagram, perimeter control, route guidance, model predictive control, moving horizon estimation, model-based parameter estimation
- Yıl: 2020
- Dil: İngilizce
- Üniversite: Ecole Polytechnıque Federale de Lausanne (epfl)
- Enstitü: Yurtdışı Enstitü
- Ana Bilim Dalı: Belirtilmemiş.
- Bilim Dalı: Belirtilmemiş.
- Sayfa Sayısı: Belirtilmemiş.
Özet
Özet yok.
Özet (Çeviri)
Urbanization intensifies as a global trend, exposing transportation networks to ever increasing levels of congestion. As network usage increases with available infrastructure, building new roads is not a solution. Design of intelligent transportation systems, in-volving identification, estimation, and feedback control methods with dynamical traÿc models, is emerging as a feasible way to improve operation of existing infrastructure. Nevertheless, complexity of large-scale networks, spatiotemporal propagation of conges-tion, and uncertainty in traveler choices present considerable challenges for modeling, estimation, and control of road transport systems. This dissertation focuses on develop-ment of novel and practicable optimization-based traÿc control and estimation methods for improving mobility in large-scale urban road networks. Part I is dedicated to identification, estimation, and control methods based on macroscopic traÿc dynamics for perimeter controlled urban networks. Obtaining accurate estimates of model parameters and traÿc states is critical for feedback perimeter control systems. In chapter 2, a nonlinear moving horizon estimation (MHE) scheme is proposed for combined state and demand estimation for a two-region urban network with dynamical modeling via macroscopic fundamental diagram (MFD). A traÿc control framework consisting of identification, state estimation, and control methods is developed in chapter 3, enabling model-based feedback perimeter control of city-scale traÿc. Part II focuses on traÿc management methods considering regional route guidance. Equipping traÿc controllers with route guidance carries potential for high performance congestion management. Chapter 4 contains model predictive control (MPC) schemes integrating route guidance and perimeter control actuators, capable of superior perfor-mance compared to using only perimeter control. A hierarchical traÿc controller is designed in chapter 5, employing a path assignment mechanism to realize macroscopic route guidance commands of a network-level MPC.
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