本文為瑞典查爾姆斯理工大學（作者：Robert Hult、Reza Sadeghi Tabar）的訊號系統碩士論文，共145頁。

在過去的二十年中，高度自動化車輛系統的願景吸引了學術界和工業界研究人員的興趣。本文的工作集中在該領域的路徑規劃子集上，該子集解決了車輛在充滿障礙物的環境中如何導航的問題。其目的在於研究和評估路徑規劃方法的現狀，並提出在當今客車存在的資源約束下可行的、滿足魯棒性和乘客舒適性要求的解決方案。

由於一般性路徑規劃問題的複雜性，本課題研究範圍僅限於在公路和鄉村道路上的行駛，包括通過轉彎處的入口和出口。提出了一種模組化的解決方案，將路徑規劃精簡為一組簡單軌跡集合的選擇；這種選擇基於過濾的複合代價函式，該函式考慮各種效能特點，例如與其它車輛之間的距離和舒適性等。對於高速公路和轉彎機動，通過求解約束最優的控制問題，簡化了車輛動力學的表示方法，從而求解得到簡單的軌跡形式。結果表明，當使用粒子模型與特定的代價函式一起逼近動力學特徵時，公路情況下的運動軌跡呈現為多項式形式。

然而，對於車輛轉彎的情況，相應的約束最優控制問題是數值化的，通過假定控制問題的引數化形式，詳細地推導了非線性規劃的表示式。論證了初始猜測對數值求解的重要性，提出了一種利用前饋神經網路（FFNN）函式擬合生成演算法起始點的新方法。證明了使用基於FFNN的高精度初始猜測的優越性，該演算法優於其它文獻中提出的方法。大量的模擬結果表明，本文提出的系統能夠解決複雜交通場景下的規劃問題。通過比較簡單模型和非線性自行車模型的動力學特性，驗證了簡單模型的合理性，後者被迫遵循前者的設計路徑。所推導的微分代數方程通過Dymola求解，並用於確定在什麼條件下進行簡化是有效的。最後，本文討論了使用模組化方法解決路徑規劃問題的優缺點。

The vision of highly automated vehicle systems has for the last twodecades enticed researchers in both academia and industry. The work in thisthesis focuses on the path planning subset of the field, which addresses theproblem of how a vehicle should navigate through an obstacle filledenvironment. The purpose is to study and evaluate the state of the art of pathplanning approaches and propose a solution that is feasible under the resourceconstraints present in today’s passenger vehicles and that satisfies demands onrobustness and passenger comfort. Due to the complexity of the general pathplanning problem, the scope is limited to operation on highways and countryroads, including entries and exits through turns.A modular solution ispresented where the planning is reduced to selection among a discrete set ofsimple trajectories. The selection is based on a filtered compound costfunction that capture various performance aspects, e.g. proximity to othervehicles and comfort. For both highway and turning manoeuvres, the simpletrajectories are found by solving a constrained optimal control problemsubjected to simplified representation of the vehicle dynamics. It is shownthat the trajectories for the highway case takes the form of a polynomial whena particle model is used to approximate dynamics together with a specific costfunctional. For the turning case however, it is shown that the correspondingconstrained optimal control problem is of numerical nature and thereformulation to a non linear program by assuming a parametrized form of thecontrol is detailed. The importance of the initial guess to the numericalsolver is demonstrated and a novel way of generating these algorithmic startingpoints using function fitting via Feed Forward Neural Networks (FFNN) ispresented. The benefit of using the highly accurate FFNN based initial guess isdemonstrated, and its superiority over other methods presented in theliterature is shown. Results from extensive simulations are presented whichdemonstrates that the proposed system is capable to solve planning throughcomplex traffic scenarios. The model simplifications made are justified by acomparison between the dynamics of the simple model and a non linear bicycle model,where the latter is forced to follow the path of the former. The resultingDifferential Algebraic Equations are solved through Dymola and used todetermine under what conditions the simplification is valid. The thesis isconcluded with a discussion on the results touching on both the benefits anddisadvantages of using a modular approach to the path planning problem.

1 引言
2 專案背景
3 本文提出的路徑規劃系統
4 模擬結果
5 討論
6 結論
附錄A 方法調研
附錄B 公路機動軌跡
附錄C 代價分量
附錄D 轉彎軌跡
附錄E 車輛建模

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