發(fā)布時(shí)間：2019-05-28 12:32

【摘要】：智能車輛作為智能交通控制領(lǐng)域中一項(xiàng)主要的研究?jī)?nèi)容,其將多種現(xiàn)代電子信息技術(shù)集成于一體。隨著當(dāng)前社會(huì)對(duì)于現(xiàn)代車輛的智能化、安全化的需求越來(lái)越高,智能車輛成為世界上各個(gè)國(guó)家在交通領(lǐng)域競(jìng)相研究的熱點(diǎn)問題和技術(shù)前沿。在國(guó)家自然科學(xué)基金項(xiàng)目(編號(hào)61104165)的資助下,本文主要針對(duì)智能交通公路系統(tǒng)中,智能車輛的路徑跟蹤聯(lián)合仿真控制問題進(jìn)行了研究分析。 為了使建立的車輛動(dòng)力學(xué)結(jié)構(gòu)模型盡可能接近實(shí)車的機(jī)械系統(tǒng)動(dòng)力學(xué),本文首先對(duì)車輛的復(fù)雜結(jié)構(gòu)進(jìn)行了簡(jiǎn)化分析,然后以ADAMS/Car為仿真分析平臺(tái)建立了智能車輛的各子系統(tǒng)模型,最后將各子系統(tǒng)組裝成整車虛擬樣機(jī)模型并定義了系統(tǒng)仿真時(shí)的輸入變量和輸出變量。 為了降低路徑跟蹤過程中的橫向偏差與方向偏差,本文設(shè)計(jì)了一種基于車輛橫擺角速度反饋方法的路徑跟蹤控制策略�；谲囕v的運(yùn)動(dòng)學(xué)模型和位姿誤差模型,通過對(duì)車輛實(shí)際位置與預(yù)瞄點(diǎn)之間虛擬路徑的跟蹤來(lái)生成期望橫擺角速度,并采用滑模算法和RBF神經(jīng)網(wǎng)絡(luò)算法相結(jié)合的控制方法設(shè)計(jì)了車輛的路徑跟蹤控制器,從而使智能車輛能夠較好地跟蹤期望的運(yùn)動(dòng)軌跡。 經(jīng)過大量的實(shí)驗(yàn)表明,在車輛行駛過程中遭遇突發(fā)狀況時(shí),駕駛員的最優(yōu)操作是采用轉(zhuǎn)向而不是剎車來(lái)避開障礙物,本文針對(duì)城市道路交通中車輛主動(dòng)防碰撞進(jìn)行了研究分析,基于車輛和障礙物之間的臨界安全距離設(shè)計(jì)了避障決策曲面,并通過對(duì)幾種避障軌跡進(jìn)行了比較分析設(shè)計(jì)了等速偏移軌跡和正弦函數(shù)加權(quán)疊加的避障軌跡。 針對(duì)不同道路曲率的期望路徑,本文在ADAMS/Car和Matlab/Simulink軟件平臺(tái)下對(duì)車輛路徑跟蹤控制系統(tǒng)進(jìn)行了聯(lián)合仿真分析研究,解決了控制參數(shù)在線調(diào)整的問題。仿真分析結(jié)果表明,本文所設(shè)計(jì)的智能車輛路徑跟蹤控制系統(tǒng)能夠控制車輛準(zhǔn)確地跟蹤不同曲率的期望運(yùn)動(dòng)軌跡,整個(gè)控制過程運(yùn)行平穩(wěn),具有較好的動(dòng)態(tài)特性和魯棒性,并且本文的控制算法提高了系統(tǒng)的控制精度,改善了系統(tǒng)的跟蹤性能。
[Abstract]:As a main research content in the field of intelligent traffic control, intelligent vehicle integrates a variety of modern electronic information technology. With the intelligence of modern vehicles and the increasing demand for safety in the current society, intelligent vehicles have become a hot issue and technical frontier in the field of transportation in the world. With the support of the National Natural Science Foundation of China (No. 61104165), this paper mainly studies and analyzes the joint simulation control problem of intelligent vehicle path tracking in intelligent transportation highway system. In order to make the established vehicle dynamic structure model as close as possible to the mechanical system dynamics of the real vehicle, the complex structure of the vehicle is simplified and analyzed in this paper. Then each subsystem model of intelligent vehicle is established with ADAMS/Car as the simulation analysis platform. Finally, each subsystem is assembled into the virtual prototype model of the whole vehicle and the input variables and output variables of the system simulation are defined. In order to reduce the lateral deviation and direction deviation in the process of path tracking, a path tracking control strategy based on vehicle yaw angular velocity feedback method is designed in this paper. Based on the kinematic model and pose error model of the vehicle, the desired yaw angular velocity is generated by tracking the virtual path between the actual position of the vehicle and the preset point. The path tracking controller of the vehicle is designed by using the control method of sliding mode algorithm and RBF neural network algorithm, so that the intelligent vehicle can track the desired trajectory well. A large number of experiments show that when the driver encounters a sudden situation in the process of driving, the optimal operation of the driver is to use steering instead of braking to avoid obstacles. In this paper, the active collision prevention of vehicles in urban road traffic is studied and analyzed. Based on the critical safe distance between the vehicle and the obstacle, the obstacle avoidance decision surface is designed, and several obstacle avoidance trajectories are compared and analyzed, and the equal velocity migration trajectory and the weighted superposition of sinusoidal function are designed. In this paper, the vehicle path tracking control system is simulated and studied under ADAMS/Car and Matlab/Simulink software platform for the expected path of different road curvature, and the problem of on-line adjustment of control parameters is solved. The simulation results show that the intelligent vehicle path tracking control system designed in this paper can control the vehicle to track the desired trajectory with different curvature accurately, and the whole control process runs smoothly and has good dynamic characteristics and robustness. The control algorithm in this paper improves the control accuracy and tracking performance of the system.
【學(xué)位授予單位】：大連理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U495

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本文編號(hào)：2487063