基於多目標模型預測控制應用於自主駕駛小型巴士之路徑追踪控制設計

Path Tracking Control for an Autonomous Shuttle Based on Multi-Objective Model Predictive Control

張景翔(Zhang Jing-Xiang)

指導教授 ： 蔣欣翰 ； 王偉彥

國立臺灣師範大學/科技與工程學院/電機工程學系/碩士(2019年)

https://doi.org/10.6345/NTNU201900905

摘要

本論文主要提出一種多目標模型預測控制器(MOMPC)，應用於自主駕駛小型巴士的車輛最佳路徑規劃。多目標模型預測控制器是基於傳統的預測控制器改良而成，在規劃車輛路徑時並加入考慮自主駕駛小型巴士行徑過程中所產生的內側車輪行進軌跡與側向加速度進行規劃，此外並加入仿人類駕駛之Gipps縱向駕駛模型，可根據前方車輛進行加速度的調整，以確保自駕車安全的行駛速度與保持安全跟車距離。最後將所規劃好的車輛行駛最佳路徑，建置於車輛動態模擬軟體CarSim的虛擬環境中，並透過預視控制(Preview control)進行車輛最佳行徑路線追蹤控制，進而在虛擬環境中驗證與探討多目標模型預測控制器(MOMPC)應用於自主駕駛小型巴士路徑追踪控制的表現。

關鍵字

車輛動態 ； 路徑追蹤 ； 預視控制 ； 模型預測控制 ； 人類縱向駕駛模型 ； 自動駕駛

並列摘要

In this thesis, a design of multi-objective model predictive control (MOMPC) is proposed for optimal path-planning of an autonomous shuttle. As the improvement of traditional MPC method, the difference of radius between inner wheels and the lateral acceleration are more considered into the proposed MOMPC such that the optimal and safety oriented trajectory can be constructed for an autonomous shuttle traveling on curvature roads. Moreover, the speed-acceleration profile based on the Gipp’s car-following model is integrated into the MOMPC, and then a safe speed and distance can be maintained indefinitely during automated driving. The algorithm of MOMPC is implemented in the CarSim simulator software suite, and coordinated with the preview steering control algorithm to carry out the path tracking while confronting with the future road curvatures. The simulation results through the VR animation are presented to demonstrate the improved performance of MOMPC in path tracking of an autonomous shuttle compared to the MPC.

並列關鍵字

Vehicle Dynamics ； Path Tracking ； Preview Control ； Model Predictive Control ； Longitudinal Human Driving Model ； Automated Driving

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