車道維持輔助系統 (LKA, Lane Keeping Assist System) 是先進駕駛輔助系統 (ADAS, Advanced Driver Assistance Systems) 中非常重要的系統之一，它通過主動轉向輔助之介入過程，防止車輛偏離車道，與被動式輔助系統相比，此類型的主動式輔助系統之功能會直接干預駕駛人的操控，駕駛人因主動式輔助系統的存在導致的行為變化，成為非常重要的車輛安全議題。本研究將駕駛人與LKA系統之互動關係作為探討的主軸，針對駕駛人受到 LKA 系統干預時的行為變化作為研究目的，利用適應性模型預測控制法 (APC, Adaptive Predictive Control) 將駕駛人行為進行建模，結合駕駛人的預視時間，將模型中對誤差的權重提出新的假設與方法，並以此量化有無受到系統干預之駕駛人行為的差異。
本研究建立駕駛在環即時模擬器作為研究與實驗平台，由 MATLAB/Simulink 搭建車輛動態模型，結合RoadRunner 建構模擬場景與 Unreal Engine 遊戲引擎渲染模擬環境，模擬真實開車之情境與環境；同時設計並實現LKA系統於模擬器中，除了對系統介入策略的車道偏離時間進行演算法驗證，並依據ISO11270測試規範對LKA系統進行功能性驗證。
最後透過駕駛模擬器實驗，將受試者實驗數據進行建模，並將實驗結果進行個體與群體統計分析，觀察到部分駕駛人有無受到LKA系統干預的實驗結果，預視時間內的權重參數呈現顯著差異，群體統計顯示駕駛人更重視車輛偏航角誤差且同樣呈現顯著差異。實驗結論證明本研究提出之駕駛人模型中，預視時間內的權重變化可量化駕駛人受到系統干預的行為差異，同時可針對不同駕駛人行為進行建模並作量化與統計分析。

Lane Keeping Assist System (LKA) is one of the most important systems in Advanced Driver Assistance Systems (ADAS). Compared with the passive assistance system, the function of this type of active assistance system will directly interfere with the driver's control, and the driver's behavior change caused by the existence of the active assistance system has become a very important vehicle safety issue. This study takes the interaction between the driver and the LKA system as the main axis of the discussion, and aims at the behavior change of the driver when the LKA system is intervened. Modeling driver behavior using Adaptive Model Predictive Control (APC), combined with the driver's preview time, puts forward new assumptions and methods for the weight of errors in the model, and quantifies the difference in driver behavior with or without system intervention.
In this study, a real-time driving-in-the-loop simulator is established as a research and experimental platform. The vehicle dynamic model is built by MATLAB/Simulink, and the simulation scene is constructed by combining the RoadRunner and the Unreal Engine game engine to render the simulation environment to simulate the real driving situation and environment. The LKA system is used in the simulator, in addition to the algorithm verification of the time to lane crossing (TLC) of the system intervention strategy, and the functional verification of the LKA system according to the ISO11270 test specification.
Finally, through the driving simulator experiment, the experimental data of the subjects is modeled, and the experimental results are analyzed by individual and group statistics. It is observed whether some drivers are intervened by the LKA system. The weight parameters in the preview time are presented. Significant differences, group statistics show that drivers pay more attention to vehicle yaw angle error and also show significant differences. The experimental conclusion proves that in the driver model proposed in this study, the weight change in the preview time can quantify the difference in the driver's behavior under the system intervention, and at the same time, it can model and quantify and statistically analyze the behavior of different drivers.

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