本研究藉由非線性模型預估控制法NMPC (Nonlinear Model Predictive Control)建立一整合縱向橫向控制的駕駛人模型，並在模擬中以方向盤、油門、煞車量來操控商用模擬軟體CarSim®所提供之車輛動力學模型。在預估模型上，車輛動力學模型為包含縱向橫向變數之非線性模型，且車輛內部的各機構模型，如引擎模型、輪胎模型等亦屬於非線性之模型，而本駕駛人模型可以包含這些因素之考量。為描述駕駛人在操控車輛時所考量的各種因素，NMPC內部也包含多重目標函數與限制式。在駕駛風格描述上，本駕駛人可以藉由調整不同的權重與限制式設定，描述不同駕駛風格的過彎行為。此外為充分發揮NMPC架構可包含非線性預估模型與目標函數之特性，本研究以一特殊的目標函數描述駕駛人忽略細微橫向誤差的行為，並在高速急迫過彎模擬中探討包含不同精確度的輪胎模型對駕駛人模型操控能力之影響。

In this research, by using Nonlinear Model Predictive Control (NMPC), a driver model is proposed, which is capable of controlling CarSim® vehicle model by applying steering wheel angle, engine throttle, and brake in simulation. In order to maintain success in different simulations, the models of both vehicle and the parts inside, such as engine, tire, and bake system … etc., should be included in prediction model. For describing different considerations in driver’s thought, multiple objectives and constraints are included in NMPC. In result, by different arrangements in weightings and constraints, the NMPC driver model behaves differently in driving style. In further research, by using the ability of NMPC which can solve nonlinear optimization problems, we discussed driver’s tendency of ignoring small lateral error from center of lane and the nonlinear behavior in tire. In order to describe the tendency of ignoring small lateral error, we used a nonlinear objective function. Furthermore, during the simulation of high speed cornering, we also verified that the prediction model with different accuracy will affect the control capability of the driver model.

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