【摘要】：無人駕駛技術(shù)成為近年來國(guó)內(nèi)外研究的熱點(diǎn),無人車的彎道控制技術(shù)是無人駕駛技術(shù)的重要研究方向之一,它主要是將對(duì)外界路況的感知、智能與最優(yōu)控制、路徑規(guī)劃等技術(shù)集于一體的綜合技術(shù)。彎道控制的原理是先通過車載傳感器獲得無人車自身的狀態(tài)信息,然后通過物理學(xué)關(guān)系和預(yù)測(cè)算法估計(jì)得到下一時(shí)刻的彎道半徑值,根據(jù)當(dāng)前的車速與方向盤轉(zhuǎn)角值,最終使車輛在安全穩(wěn)定的條件下實(shí)現(xiàn)快速的過彎。本文根據(jù)無人駕駛智能車在不同彎道工況下實(shí)現(xiàn)平穩(wěn),快速過彎的功能要求,設(shè)計(jì)得到道路環(huán)境感知,車輛轉(zhuǎn)向行為控制的系統(tǒng)方案。全文圍繞無人駕駛智能車的快速平穩(wěn)的任務(wù)要求而展開,進(jìn)行的工作和研究?jī)?nèi)容重點(diǎn)包括：根據(jù)現(xiàn)實(shí)條件和系統(tǒng)基本的要求設(shè)計(jì)和搭建無人駕駛智能車控制系統(tǒng),主要包括車載傳感器和執(zhí)行行機(jī)構(gòu)硬件,以上都可用來進(jìn)行無人車的彎道控制的研究分析。影響車輛轉(zhuǎn)彎的兩個(gè)主要因素分別是懸架和輪胎。通過建立的線性二自由度車輛模型,研究分析懸架的側(cè)傾特性和輪胎的側(cè)偏特性對(duì)彎道控制的影響,之后建立起彎道半徑和橫擺角速度的運(yùn)算關(guān)系,彎道半徑和車廂側(cè)傾角的運(yùn)算關(guān)系。采用卡爾曼濾波算法對(duì)橫擺角速度預(yù)測(cè),自回歸分析算法對(duì)車身側(cè)傾角的預(yù)測(cè)實(shí)現(xiàn)對(duì)彎道半徑的預(yù)測(cè),最后對(duì)無人車的控制調(diào)節(jié)是根據(jù)預(yù)測(cè)得到的彎道半徑值來進(jìn)行。對(duì)于卡爾曼濾波算法進(jìn)行仿真實(shí)驗(yàn),自回歸分析算法采用實(shí)際道路環(huán)境下的過彎實(shí)驗(yàn),通過對(duì)所測(cè)數(shù)據(jù)的分析和討論,驗(yàn)證兩種算法的可行性,對(duì)比兩種算法在實(shí)際控制過程中的優(yōu)缺點(diǎn)。
[Abstract]:In recent years, driverless technology has become a hot research topic both at home and abroad. The bend control technology of unmanned vehicle is one of the important research directions of driverless technology. It is mainly concerned with the perception, intelligence and optimal control of road conditions. Integrated technology such as path planning. The principle of bend control is to obtain the state information of the unmanned vehicle through the vehicle sensor first, and then to estimate the radius of the bend at the next moment by the physical relation and the prediction algorithm, according to the current speed and steering wheel rotation angle. Finally, the vehicle can quickly overbend under the condition of safety and stability. According to the functional requirements of the driverless intelligent vehicle to achieve smooth and fast overbending under different bend conditions, the system scheme of road environment perception and vehicle steering behavior control is designed in this paper. The full text revolves around the fast and steady task requirement of the unmanned intelligent vehicle. The work and research focus include: design and build the control system of the unmanned intelligent vehicle according to the actual conditions and the basic requirements of the system. The above can be used to study and analyze the bend control of unmanned vehicle. The two main factors that affect the turning of the vehicle are suspension and tire. Based on the linear two-degree-of-freedom vehicle model, the effects of the roll characteristics of suspension and tire sideways on the bend control are studied and analyzed, and the calculation relationship between the curve radius and the yaw angular velocity is established. The relation between the radius of the bend and the roll angle of the car. The Kalman filtering algorithm is used to predict the yaw velocity, the auto-regression algorithm to predict the car body roll angle to predict the curve radius. Finally, the control adjustment of the unmanned vehicle is carried out according to the predicted curve radius value. For the Kalman filter algorithm simulation experiment, the self-regression analysis algorithm uses the actual road environment, through the analysis and discussion of the measured data, the feasibility of the two algorithms is verified. The advantages and disadvantages of the two algorithms in the actual control process are compared.
【學(xué)位授予單位】：西安工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：U463.6

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