本文選題：智能車輛 + 道路幾何特征��； 參考：《武漢理工大學(xué)》2014年博士論文

【摘要】：近年來，隨著我國汽車數(shù)量的急劇增多，道路交通安全問題日趨嚴(yán)重。由于車輛具有高速移動(dòng)性，且道路存在陡坡、急彎、不規(guī)則路面等復(fù)雜的幾何特征，行駛在相關(guān)道路上的車輛經(jīng)常會(huì)出現(xiàn)追尾、側(cè)翻等交通事故。智能車輛作為智能交通系統(tǒng)的關(guān)鍵載體，廣泛涵蓋了以主動(dòng)安全為導(dǎo)向的先進(jìn)車輛輔助駕駛與自動(dòng)駕駛功能，可以提高道路通行能力，提升交通安全性和快捷性，并在此基礎(chǔ)上節(jié)約能源、減少污染等。在不同道路幾何特征條件下的車速自適應(yīng)控制一直是智能車輛關(guān)鍵技術(shù)的研究重點(diǎn)和難點(diǎn)。半實(shí)物仿真技術(shù)在系統(tǒng)設(shè)計(jì)與測試的便捷性、復(fù)驗(yàn)性、適應(yīng)性以及安全性方面具有實(shí)車道路實(shí)驗(yàn)無可比擬的優(yōu)勢。本文依托武漢理工大學(xué)智能交通系統(tǒng)研究中心構(gòu)建的道路交通仿真系統(tǒng)，采用半實(shí)物仿真技術(shù)，針對不同道路幾何特征的車速自適應(yīng)控制問題，提出了一些新的評價(jià)函數(shù)，以提高控制律的適應(yīng)性。 首先，引入相似理論，對理論模型與仿真縮微車之間的幾何相似、運(yùn)動(dòng)相似以及動(dòng)力相似三個(gè)方面進(jìn)行分析，構(gòu)建了縮微車模型與智能調(diào)控模擬實(shí)驗(yàn)平臺參數(shù)標(biāo)定方法。在道路幾何建模方面，采用回旋線函數(shù)建立彎道和坡道幾何模型。在車輛運(yùn)動(dòng)學(xué)建模方面，采用拉格朗日法建立基于3自由度的車輛縱橫向耦合模型，包括縱向運(yùn)動(dòng)、橫向運(yùn)動(dòng)與橫擺運(yùn)動(dòng)的耦合�；诘缆方煌ǚ抡嫫脚_和車輛硬件在環(huán)系統(tǒng)，建立了車速自適應(yīng)控制方法實(shí)驗(yàn)環(huán)境。 接著，分別引入坡道和彎道幾何線形特征，提出考慮道路幾何特征的評價(jià)函數(shù)，設(shè)計(jì)了車速自適應(yīng)控制方法。在坡道條件下，，推導(dǎo)了坡度角及其變化率的計(jì)算公式。根據(jù)系統(tǒng)耗散性所反映的能量損耗特性，將車速自適應(yīng)控制轉(zhuǎn)化成以能量存儲函數(shù)為優(yōu)化目標(biāo)的H∞控制問題。建立關(guān)于車速調(diào)控的γ耗散性能準(zhǔn)則，采用HJI方法(Hamilton-Jacobi-Issacs)，將控制律的設(shè)計(jì)轉(zhuǎn)化為構(gòu)造包含坡道幾何特征激勵(lì)費(fèi)用和車速、縱向加速度變化補(bǔ)償費(fèi)用的能量存儲函數(shù)。采用Backstepping方法，沿著車速控制系統(tǒng)的積分器鏈信號傳遞的正向，通過逐步逼近γ耗散不等式的方式，設(shè)計(jì)車速自適應(yīng)控制律。在MATLAB環(huán)境下開展坡道自主駕駛的智能車速調(diào)控仿真實(shí)驗(yàn)，對整個(gè)上、下坡道的牽引力變化分析，結(jié)果表明考慮坡道幾何特征的車速自適應(yīng)控制律不僅可以根據(jù)上下坡的坡度角變化自動(dòng)調(diào)節(jié)車速，且具有車輛行駛安全性高，能量消耗低的優(yōu)勢。 在彎道條件下，對彎道曲率及其變化率的計(jì)算公式進(jìn)行推導(dǎo)，建立車速調(diào)控γ耗散性能準(zhǔn)則，將橫向偏差自調(diào)節(jié)轉(zhuǎn)化成以偏差平方和最小的最優(yōu)控制問題。構(gòu)造包含彎道幾何特征激勵(lì)費(fèi)用和車速、橫向加速度變化補(bǔ)償費(fèi)用的評價(jià)函數(shù)，采用LMI方法將控制律設(shè)計(jì)轉(zhuǎn)換為滿足橫向偏差控制系統(tǒng)Hurwitz穩(wěn)定的正定矩陣的求解。實(shí)現(xiàn)彎道自主駕駛的縱橫向最優(yōu)調(diào)控MATLAB仿真，考慮彎道幾何特征的縱橫向最優(yōu)控制律不僅可以根據(jù)彎道曲率變化自動(dòng)調(diào)節(jié)車速和橫向偏差，并且整個(gè)彎道過程中的前輪轉(zhuǎn)角的范圍較小，能量消耗較低，更能增強(qiáng)車輛彎道行駛的安全性。 最后，開展不同道路條件下的縮微車智能調(diào)控模擬實(shí)驗(yàn)，包括坡道的智能車速調(diào)控和彎道縱橫向最優(yōu)調(diào)控。驗(yàn)證了車速自適應(yīng)控制與橫向偏差自調(diào)節(jié)方法在道路交通仿真平臺上的的可行性和有效性。
[Abstract]:In recent years, with the rapid increase of the number of cars in our country, the problem of road traffic safety is becoming more and more serious. Because the vehicle has high-speed mobility, and the road has the complicated geometric features such as steep slope, sharp bend, irregular pavement and so on, vehicles running on the related roads often appear tailing, rollover and other traffic accidents. Intelligent vehicles are used as intelligent traffic. The key carrier of the system covers an active safety oriented advanced vehicle driving and autopilot function, which can improve road traffic capacity, improve traffic safety and shortcut, and save energy and reduce pollution on this basis. Adaptive speed control of vehicle speed under different road geometric characteristics has always been intelligent. The hardware in the loop simulation technology has an unparalleled advantage in the convenience of the system design and testing, the retesting, the adaptability and the safety of the vehicle road experiment. This paper relies on the simulation system built by the research center of the intelligent transportation system of Wuhan University of Technology, which adopts the semi physical imitation. In order to improve the adaptability of the control law, some new evaluation functions are proposed for vehicle speed adaptive control of different road geometry characteristics.
First, the similarity theory is introduced, and the geometric similarity between the theoretical model and the simulated micro vehicle, motion similarity and dynamic similarity are analyzed in three aspects. The calibration method of the parameters of the model and the intelligent control simulation experiment platform is constructed. In the aspect of road geometric modeling, the curve and the geometric model of the ramp are used to establish the curve and the geometric model of the ramp. In the vehicle kinematics modeling, the vehicle longitudinal and transverse coupling model based on 3 degrees of freedom is established by Lagrange method, which includes the longitudinal motion, the coupling of transverse motion and the yaw motion. Based on the road traffic simulation platform and the vehicle hardware in the ring system, the experimental environment of the speed adaptive control method is established.
Then, the geometric linear features of the ramp and bend are introduced, and the evaluation function of the geometric characteristics of the road is put forward, and the adaptive control method of the speed is designed. The calculation formula of the slope angle and the rate of change is derived under the slope condition. The adaptive control of vehicle speed is converted into energy according to the energy loss characteristics reflected by the dissipative system of the system. The storage function is the H infinity control problem for the optimization target. A gamma dissipation criterion for speed regulation is established. The HJI method (Hamilton-Jacobi-Issacs) is used to transform the design of the control law into a energy storage function for constructing the compensation cost of the excitation cost and speed of the ramp and the variation of the longitudinal acceleration. The Backstepping method is used. Along the forward speed control system of the integrator chain signal, the speed adaptive control law is designed by gradually approaching the gamma dissipation inequality. In the MATLAB environment, the intelligent speed control simulation experiment of the autonomous driving on the slope is carried out. The change of the traction force of the lower ramp is analyzed. The results show that the geometric characteristics of the ramp are taken into consideration. The speed adaptive control law can not only automatically adjust the speed according to the gradient angle of the downhill slope, but also has the advantages of high driving safety and low energy consumption.
The calculation formula of curve curvature and its rate of change is deduced under the condition of bend, and the criterion of speed regulation is set up. The optimal control problem is transformed into the optimal control problem with the minimum square sum of deviation. The LMI method is used to convert the control law design into the solution of the positive definite matrix which satisfies the Hurwitz stability of the lateral deviation control system. To realize the optimal control of the longitudinal and transverse direction of the autonomous driving of the bend, the optimal control law of the longitudinal and transverse direction of the curve is not only to automatically adjust the speed and lateral deviation according to the curvature of the bend, but also to adjust the optimal control law of the MATLAB. During the curve, the angle of the front wheel is smaller and the energy consumption is lower, which can enhance the safety of the vehicle running in the curve.
Finally, the intelligent control simulation experiment of the micro vehicle under different road conditions is carried out, including the intelligent speed control of the ramp and the optimal control of the longitudinal and transverse direction of the bend. The feasibility and effectiveness of the adaptive speed control and the lateral deviation self adjustment method on the road traffic simulation platform are verified.
【學(xué)位授予單位】：武漢理工大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：U495;U463.6

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 馬國成;劉昭度;裴曉飛;葉陽;;汽車自適應(yīng)巡航控制主動(dòng)制動(dòng)實(shí)現(xiàn)方法[J];北京理工大學(xué)學(xué)報(bào);2012年02期

2 王榮本;郭烈;金立生;顧柏園;余天洪;;智能車輛安全輔助駕駛技術(shù)研究近況[J];公路交通科技;2007年07期

3 宋_g,張貴文,黨星海;相似理論內(nèi)容的擴(kuò)充與分析[J];蘭州理工大學(xué)學(xué)報(bào);2004年05期

4 任殿波;張京明;崔勝民;張繼業(yè);;車輛換道縱橫向耦合控制[J];交通運(yùn)輸工程學(xué)報(bào);2009年03期

5 古志鵬;;道路線形對行車安全的影響[J];山西建筑;2009年14期

6 張德兆;秦立峰;王建強(qiáng);李克強(qiáng);;基于電子真空助力器的汽車駕駛輔助系統(tǒng)制動(dòng)壓力控制[J];汽車工程;2011年12期

7 張德兆;王建強(qiáng);劉佳熙;李克強(qiáng);連小珉;;加速度連續(xù)型自適應(yīng)巡航控制模式切換策略[J];清華大學(xué)學(xué)報(bào)(自然科學(xué)版);2010年08期

8 王浩;馬壽峰;;適用于彎度與坡度的跟馳模型及其仿真研究[J];土木工程學(xué)報(bào);2005年11期

9 常促宇;向勇;史美林;;車載自組網(wǎng)的現(xiàn)狀與發(fā)展[J];通信學(xué)報(bào);2007年11期

10 李朋;魏民祥;侯曉利;;自適應(yīng)巡航控制系統(tǒng)的建模與聯(lián)合仿真[J];汽車工程;2012年07期

相關(guān)博士學(xué)位論文 前2條

1 羅莉華;汽車自適應(yīng)巡航控制及相應(yīng)宏觀交通流模型研究[D];浙江大學(xué);2011年

2 冀杰;基于自動(dòng)駕駛系統(tǒng)的車輛縱橫向運(yùn)動(dòng)綜合控制研究[D];重慶大學(xué);2010年

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