本文選題：智能汽車　切入點(diǎn)：復(fù)雜交通環(huán)境　出處：《吉林大學(xué)》2017年博士論文

【摘要】：汽車智能化是當(dāng)今世界汽車工業(yè)的重點(diǎn)發(fā)展方向。經(jīng)過多年的研究推動,針對簡單工況的智能輔助駕駛技術(shù)日益成熟,諸如車道偏離預(yù)警、自適應(yīng)巡航控制、車道保持輔助等先進(jìn)駕駛輔助系統(tǒng)已經(jīng)在工業(yè)界得到廣泛應(yīng)用,半自動駕駛和有條件自動駕駛的智能汽車也已經(jīng)進(jìn)入測試階段。各國研究人員正致力于高度自動化智能汽車的攻關(guān),其中,針對復(fù)雜交通環(huán)境的方向與速度綜合決策模型是當(dāng)前的難點(diǎn)問題之一。駕駛員控制汽車行駛方向與速度的綜合決策行為本質(zhì)上是一個多目標(biāo)優(yōu)化問題,通常需要考慮兩類因素:一類是可采用連續(xù)目標(biāo)函數(shù)進(jìn)行評價的因素,諸如工效性、易操縱性等;另一類是不連續(xù)的二值邏輯因素,諸如安全性、合法性等�，F(xiàn)有模型大多基于控制理論和力學(xué)原理等機(jī)理進(jìn)行建模,將不連續(xù)取值的因素也納入目標(biāo)函數(shù),與連續(xù)取值的因素一起進(jìn)行多目標(biāo)優(yōu)化,導(dǎo)致難以確定加權(quán)系數(shù),求解過程可能收斂到局部解而產(chǎn)生發(fā)散,表現(xiàn)為緊急轉(zhuǎn)彎時汽車沖出道路邊界等危險情況。針對上述問題,本文提出一種基于機(jī)理與規(guī)則混合決策的智能汽車駕駛員建模方法。在課題組原有的方向與速度綜合控制的駕駛員最優(yōu)預(yù)瞄加速度模型基礎(chǔ)上,將安全性與合法性基于規(guī)則建模,作為約束條件縮減預(yù)瞄加速度的可行域;將工效性、易操縱性等基于機(jī)理建模,作為目標(biāo)函數(shù)優(yōu)化求解最優(yōu)預(yù)瞄加速度。在目前查閱到的相關(guān)文獻(xiàn)中尚未見到同樣做法。本文重點(diǎn)研究了以下幾個方面的內(nèi)容:首先,預(yù)瞄加速度可行域縮減方法研究。本文探索了在預(yù)瞄縱向加速度和預(yù)瞄側(cè)向加速度構(gòu)成的平面上,依次根據(jù)道路可行駛區(qū)域、障礙物等約束的行駛安全性,以及法規(guī)限速、車道線、交通信號燈與停止線等約束的行駛合法性,逐步縮減預(yù)瞄加速度的可行域,進(jìn)而保證最優(yōu)預(yù)瞄加速度符合汽車行駛安全與交通規(guī)則要求。研究了汽車輪廓分別與道路可行駛區(qū)域、障礙物、車道線相對位置關(guān)系的判定方法,并且提出了一種針對交通信號燈與停止線的合法性分相判定方法。仿真和試驗(yàn)表明有效解決了現(xiàn)有模型難以確定加權(quán)系數(shù)以及優(yōu)化求解過程可能發(fā)散的問題。其次,預(yù)瞄加速度綜合評價方法研究。在經(jīng)過安全性判定與合法性判定縮減之后的可行域內(nèi),根據(jù)工效性、易操縱性等評價指標(biāo)對預(yù)瞄加速度進(jìn)行綜合評價,優(yōu)化求解最優(yōu)預(yù)瞄加速度。原有模型主要依靠側(cè)方安全性指標(biāo)來促使汽車靠近車道中心線行駛。然而,由于側(cè)方安全性指標(biāo)基本上只在車道線或道路邊界附近區(qū)域起作用,而在車道中心線附近區(qū)域作用很小,導(dǎo)致汽車行駛軌跡的收斂性欠佳,在移線或轉(zhuǎn)彎之后難以穩(wěn)定地沿車道中心線行駛,呈現(xiàn)出持續(xù)的左右擺動。安全性基于規(guī)則建模會進(jìn)一步加劇這個問題。因此,本文提出增加一個橫向跟隨性評價指標(biāo),用于描述駕駛員期望靠近車道中心線行駛的心理特征。仿真和試驗(yàn)表明有效解決了軌跡收斂性欠佳的問題。再次,汽車非線性動力學(xué)動態(tài)校正方法研究。在經(jīng)典的最優(yōu)預(yù)瞄加速度模型中,采用被控車輛的低階等效逆系統(tǒng)模型對汽車動力學(xué)進(jìn)行開環(huán)校正,通過精確標(biāo)定逆模型來保證實(shí)際加速度與最優(yōu)預(yù)瞄加速度的一致性。由于汽車動力學(xué)除線性區(qū)外還有中心區(qū)和大滑移區(qū),呈現(xiàn)強(qiáng)非線性,要精確獲取其逆模型參數(shù),通常需要在由車速、加速度和路面條件構(gòu)成的三維空間的大量工作點(diǎn)做標(biāo)定試驗(yàn),標(biāo)定工作量非常大。針對這一問題,本文根據(jù)復(fù)合校正控制原理,提出以基于逆系統(tǒng)原理的開環(huán)校正為主體,代表駕駛員對汽車動力學(xué)特性的掌握程度,在此基礎(chǔ)上增加一個閉環(huán)校正環(huán)節(jié),用于描述人的補(bǔ)償修正能力。仿真和試驗(yàn)表明提高了系統(tǒng)魯棒性,可以有效減少標(biāo)定工作量。最后,在Simulink仿真環(huán)境下建立了基于機(jī)理與規(guī)則混合決策的智能汽車駕駛員最優(yōu)預(yù)瞄加速度模型。一方面,以車輛動力學(xué)仿真軟件Car Sim中的C級樣車模型作為控制對象,進(jìn)行了諸如雙移線路段、直角轉(zhuǎn)彎路段、“8”字形路段、3D循環(huán)賽道、巡航、超車、交通信號燈路段等多種工況的人-車-路閉環(huán)系統(tǒng)仿真;另一方面,以開發(fā)型駕駛模擬器作為試驗(yàn)平臺,進(jìn)行了典型ACC工況的試驗(yàn)驗(yàn)證。仿真和試驗(yàn)結(jié)果表明:基于機(jī)理與規(guī)則混合決策的智能汽車駕駛員模型,只需對各評價指標(biāo)的加權(quán)系數(shù)進(jìn)行簡單地設(shè)定,就能較好地適應(yīng)上述各種工況,沒有出現(xiàn)任何不安全或違反交通規(guī)則的現(xiàn)象,有效解決了現(xiàn)有模型優(yōu)化求解過程可能發(fā)散的問題;汽車在移線和通過彎道之后,可以穩(wěn)定地沿車道中心線行駛,沒有出現(xiàn)軌跡持續(xù)擺動的現(xiàn)象,有效解決了原有模型汽車軌跡收斂性欠佳的問題;通過對被控車輛的主特性進(jìn)行快速標(biāo)定,就可以保證實(shí)際加速度與最優(yōu)預(yù)瞄加速度具有較高的一致性,有效解決了標(biāo)定工作量大的問題。
[Abstract]:The intelligent car is the focus of the development direction of the automotive industry in the world today. After many years of research to promote, in an intelligent driver assistance technology simple conditions increasingly mature, such as lane departure warning, adaptive cruise control, auxiliary and other advanced driver assistance system has been widely used in lane keeping, semi automatic driving and intelligent vehicle condition the autopilot has entered the testing stage. The research, researchers are working on highly automated intelligent vehicle in complex traffic environment, the speed and direction of the comprehensive decision model is one of the difficult problems in current. The driver control decision behavior essence vehicle speed and direction is a multi-objective optimization problem. Usually need to consider two factors: one is the factors that can adopt continuous objective function evaluation, such as efficiency, easy operation etc. ; another kind is the two valued logic factor is not continuous, such as safety, legality and so on. The existing models are based on control theory and mechanics principle of mechanism modeling, the factors of continuous values are included in the objective function of multi-objective optimization with continuous value factors, difficult to determine the weighted coefficient the solving process may converge to a local solution for emergency caused divergence, turning out of the car. The dangerous situation of road boundary according to the above problems, this paper presents an intelligent rule-based decision mechanism and the driver of the car. The driver optimal modeling method based on pre research group of the original direction and velocity integrated control based on tracking acceleration model the safety, validity and rule based modeling, as constraints reduce the feasible domain previewacceleration; the work efficiency, easy handling based on mechanism modeling, as. Standard function optimization of optimal preview acceleration. The same has not been seen in the literature at present refer to. This article focuses on the following aspects: firstly, previewacceleration feasible domain reduction method research. This paper explores in the preview plane longitudinal acceleration and lateral acceleration of the preview, in turn according to the road the driving region, driving safety barriers and regulatory constraints, speed, lane, traffic lights and stop line constraints such as driving legitimacy, gradually reduce the feasible acceleration, so as to ensure the optimal preview acceleration to meet the requirements of safety and traffic rules of the car. The car and road profile respectively. The driving region, obstacles, method to determine the relative position between the lane line, and put forward a set of traffic lights and the method of judging legality phase of the stop line. The simulation and test results show that the effective solution of the existing model is difficult to determine the weighted coefficient and optimization to solve the potential divergence problem. Secondly, research on the comprehensive evaluation method of acceleration preview. After determine the security and legitimacy to determine feasible domain reduction after, according to ergonomic, easy manipulation of the evaluation index of previewacceleration comprehensive the evaluation and optimization of optimal preview acceleration. The original model mainly depends on the lateral safety index to make the car near the center line of the lane. However, due to the lateral safety index basically only in the region near the lane or road boundary effect, and in the center line of the lane near the area of effect is very small, resulting in convergence of the vehicle trajectory the poor, after driving in the lane change or turn to steadily along the center line of the lane, showing a swing continuously. Based on the security rules into modeling This problem is exacerbated in one step. Therefore, this paper proposes to add a transverse follow evaluation index for describing the psychological characteristics of the driver's desired driving lanes near the center line. The simulation and test results show that effectively solves the problem of poor convergence trajectory. Thirdly, vehicle nonlinear dynamics dynamic correction method. The optimal pre classical tracking acceleration in the model, the low order equivalent controlled vehicle inverse system model of vehicle dynamics of open loop correction, the accurate calibration of the inverse model to ensure that the actual acceleration and consistency of optimal preview acceleration. The vehicle dynamics in linear region and the central area and the large slip area, showing the strong nonlinearity, to accurately obtain the inverse model the parameters, usually require a lot of work in the speed, acceleration and three-dimensional space composition of road condition to do the calibration test, the calibration for the workload is very large. This problem, based on the composite correction control principle, put forward to the open-loop inverse system based on the principle of correction as the main representative of the driver master degree of vehicle dynamics, based on a closed loop correction link is used to describe the compensation ability. The simulation and test results show that improve the robustness of the system, can be effective to reduce calibration workload. Finally, established in Simulink simulation environment of intelligent vehicle driver optimal decision rules and mechanism of pre mixed tracking model based on acceleration. On the one hand, with the C prototype vehicle dynamics simulation software Car Sim as a control object, such as the double shift line section, turn Road, "8" cross section, 3D cycle track, cruise, overtaking, traffic lights and other road conditions of driver vehicle road closed-loop simulation; on the other hand, the driving simulator for As the test platform, test of typical ACC conditions. Simulation and experimental results indicate that the intelligent driver model based on hybrid decision mechanism and rules, only weighting coefficient of each index to set up a simple, can better adapt to the various working conditions, without any unsafe or violate traffic regulations the phenomenon, effectively solve the existing optimization model to solve the potential divergence problem; in the car lane and through the corners, can be stably along the center line of the lane road, no track continuous swing phenomenon, effective solution to the original model of vehicle track convergence problem of poor; fast through the calibration on the main characteristics of the controlled vehicle. You can ensure the consistency of the actual acceleration and optimal preview acceleration is high, effectively solve the calibration workload big problem.

【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2017
【分類號】：U463.6

【相似文獻(xiàn)】

相關(guān)期刊論文 前10條

1 顏世宗;智能汽車向我們駛來[J];電子科技;2000年10期

2 熊和金;智能汽車系統(tǒng)研究的若干問題[J];交通運(yùn)輸工程學(xué)報;2001年02期

3 添藝;智能汽車──21世紀(jì)的新型交通工具[J];汽車工藝與材料;2001年03期

4 ;智能汽車走近你我[J];甘肅科技縱橫;2003年03期

5 高山;;智能汽車指日可待[J];科學(xué)時代;2003年09期

6 曉魚;形式各異的智能汽車[J];安全與健康;2004年24期

7 田原Z，

本文編號：1682400