本文選題：智能車輛　切入點：自主換道　出處：《中國人民解放軍軍事醫(yī)學科學院》2014年博士論文

【摘要】：智能車輛從根本上改變了傳統(tǒng)的車輛駕駛方式,將駕駛員從“駕駛員一車輛-道路”的閉環(huán)系統(tǒng)中解放出來,利用先進的電子與信息技術控制車輛行駛,讓駕駛活動中常規(guī)的、持久且易疲勞的操作自動完成,能夠極大地提高交通系統(tǒng)的效率和人員的安全性。研究智能車輛的自主換道關鍵技術,最終能夠實現(xiàn)多車的自主交互協(xié)同,提高部隊人員、裝備的使用效率和戰(zhàn)場環(huán)境的適應能力；同時,通過準確的環(huán)境信息感知,加上科學、合理的決策分析與穩(wěn)定可靠的控制算法,使車輛自主換道的安全性比充滿不確定因素的駕駛員換道更具優(yōu)越性,有效地控制人為因素造成的交通事故。 本文通過分析駕駛員的駕駛行為過程,研究了駕駛員換道意圖的產(chǎn)生及階段,分析了影響駕駛員換道的因素,進而深入研究了駕駛員換道的決策機制,并針對智能車輛的結構特點,模擬駕駛員換道的決策過程,解析了智能車輛自主換道的決策機制。通過分析人體器官在駕駛員駕駛車輛過程中的功能,建立了“駕駛員-車輛-道路”的系統(tǒng)模型,從控制論的角度分別研究了駕駛員、車輛和道路在系統(tǒng)中的功能與作用,并提出了系統(tǒng)控制的評價指標；通過試驗數(shù)據(jù),得出了誘發(fā)車輛換道的主要原因是本車道前方有慢車,而駕駛員對時間與空間的追求是影響車輛換道的主要因素；本文將車輛的換道過程分為換道意圖的產(chǎn)生、換道時機的決策、換道軌跡的規(guī)劃和換道軌跡的跟蹤控制四個階段；建立了“駕駛員-車輛-道路”系統(tǒng)的高速公路典型場景,得出了駕駛員的換道過程是以駕駛員行為特性為主導的信息感知、決策與操控的三個模塊相互作用的行為決策與控制過程；分析了駕駛員換道決策階段的表征參數(shù),選取了車道線信息、車道邊緣信息、交互車輛信息等作為智能車輛自主換道研究的特征參數(shù)；根據(jù)智能車輛的結構特點,模擬駕駛員換道決策過程,建立了“機器-車輛-道路”的系統(tǒng)模型,解析了智能車輛自主換道的決策機制。 通過建立路權雷達圖進行信息融合,對換道過程中換道意圖的產(chǎn)生、換道時機的決策、換道軌跡的規(guī)劃三個階段進行分析,建立了智能車輛自主換道的決策模型,并針對換道過程出現(xiàn)的突發(fā)異常情況,建立了靜、動態(tài)障礙車輛的避障模型。模擬人類認知行為的注意力分配機制,根據(jù)路權的概念,建立了變粒度路權雷達圖,使用較少的存儲空間和計算資源完成對人類認知行為的模擬和計算,通過路權雷達圖實現(xiàn)了信息融合、仿真分析和路徑規(guī)劃等功能；定義了智能車輛的最小行車安全距離,在此基礎上確定了智能車輛產(chǎn)生換道意圖的期望值。通過選取2名熟練駕駛員、選擇典型高速公路路線、制定試驗控制條件等設計試驗方案,采集影響駕駛員換道的特征參數(shù)311組,其中,車道保持數(shù)據(jù)97組,換道行駛數(shù)據(jù)214組；采用v-支持向量機進行訓練,選取(δ,v)=(0.12,0.03)作為v-支持向量機的模型參數(shù),判斷換道行為的準確率為91.05%；從換道時間、換道橫向加速度、曲率突變等方面分析比較了智能車輛常用的換道軌跡規(guī)劃方法,根據(jù)本文研究的對象,確定了梯形加速度換道軌跡的方法；針對換道過程的突發(fā)意外事件,建立了靜、動態(tài)障礙車輛的避障模型；為了滿足實時性要求,在環(huán)境建模中設計了變尺度柵格圖,當車輛高速行駛時,變尺度柵格圖比傳統(tǒng)柵格的CPU占用降低約34%；將變尺度柵格圖與路權雷達圖進行融合,通過靜態(tài)選擇式避障模塊和動態(tài)障礙避障策略,實現(xiàn)對突發(fā)意外障礙車輛的躲避。 通過分析智能車輛縱橫向耦合系統(tǒng)的建模與控制方法,建立了智能車輛縱橫向耦合運動學模型,該模型考慮縱向、橫向以及橫擺運動狀態(tài),可以更為精確地對智能車輛換道軌跡與換道完成后的車道保持進行控制。分析了車輛行駛過程中的縱橫向耦合影響,提出了智能車輛縱橫向耦合建模與控制問題,建立了智能車輛縱橫耦合控制系統(tǒng),包括縱向運動、橫向運動以及橫擺運動模型；采用指數(shù)型滑模變結構方法設計換道軌跡跟蹤控制器,使智能車輛系統(tǒng)在車輛換道過程中滿足期望的動靜態(tài)性能指標；針對換道完成后的車道保持問題,建立智能車輛的橫向偏差模型,采用Terminal滑模變結構方法設計車道保持控制器,將橫向運動與橫擺運動結合起來,使得橫向偏差可以隨著車道曲率變化而自動調節(jié),同時,可以提高車道保持過程中縱橫向運動的穩(wěn)定性；采用MATLAB仿真工具對智能車輛換道軌跡跟蹤控制以及換道完成后的車道保持控制進行仿真,驗證了控制器設計的有效性和穩(wěn)定性。 針對某型越野車的結構特點,進行了智能車輛平臺的機械改造,搭建了智能車輛的硬件和軟件平臺,并進行了實際高速公路的試驗,驗證了系統(tǒng)的可靠性和穩(wěn)定性。根據(jù)智能車輛自主換道技術驗證的需要,對原車進行了智能化改造,采用電動轉向方案設計了車輛的轉向機構,在原車制動系統(tǒng)中加裝一套液壓閥組改造了制動機構,通過并聯(lián)安裝一套電控拉線盤實現(xiàn)油門機構的智能控制；搭建了智能車輛的硬件平臺,優(yōu)化儀器設備；采用多線程技術進行軟件設計,將系統(tǒng)分為主線程、控制線程、道路信息采集線程和串口通訊線程四個部分:進行了智能車輛高速公路自主駕駛試驗,完成我國首次在權威機構、測試機構和新聞媒體三方共同監(jiān)督下的智能車輛高速公路自主駕駛試驗,測試公里數(shù)達到1500公里以上,共計完成自主換道95次,試驗數(shù)據(jù)證明了智能車輛在高速公路環(huán)境下的自主換道具有較好的穩(wěn)定性和可靠性。
[Abstract]:Intelligent vehicle has changed the traditional vehicle driving way fundamentally, the closed-loop system driver from "the driver of a vehicle - road of liberation, the use of advanced electronic and information technology to control the vehicle, that conventional driving activities, durable and easy fatigue operation automatically, can greatly improve the safety efficiency and personnel transportation system. The Research of intelligent vehicle autonomous switching technology, autonomous interaction can eventually realize multi vehicle cooperation, improve personnel, equipment efficiency and battlefield environment; at the same time, through the accurate perception of environmental information, and scientific and reasonable control algorithm of decision analysis and stability reliable, safety of the vehicle lane change ratio of uncertainty the lane change is more superiority and effective control of traffic accidents caused by human factors.
Through the process analysis of driver's driving behavior of driver, change and stage intention, analyzes the influencing factors of the lane change, and then in-depth study of the decision-making mechanism for the driver, and according to the structure characteristics of intelligent vehicle, decision process simulation of the lane change, analyzes the decision-making mechanism for autonomous intelligent vehicle Tao. Through the analysis of human organs in the process of driving the vehicle in the driver, the establishment of a system model of driver vehicle road, the driver was studied from the perspective of control theory, the function and role of vehicle and road in the system, and puts forward the evaluation index system control; through the experimental data. The main cause of lane change is a slow lane in front of the driver, and the pursuit of space and time are the main factors influencing the vehicle lane change; the car A lane change process is divided into the lane change intention, change the timing of the decision, changing path planning and trajectory tracking control in four stages; establish "highway typical scene driver - vehicle - road system, the driver's lane changing process of information perception to the driver behavior oriented, behavior decision and control process of the three modules and control decision interaction; analysis of the parameters characterizing the lane change decision stage, select the lane information, lane edge information, vehicle information such as the characteristic parameters of interactive intelligent vehicle autonomous lane change research; according to the structural characteristics of intelligent vehicle the lane change decision making process, simulation, system model is established for the" machine - vehicle - Road ", analyzes the decision-making mechanism of intelligent vehicle autonomous lane change.
Information fusion is carried out through the establishment of road radar map, lane change intention generation road in the process of change the timing of decisions, for trajectory planning of three stages analysis, set up the decision-making model of intelligent vehicle autonomous lane change, sudden abnormal situation and the change process of a static, obstacle avoidance the model of dynamic obstacles vehicle. Attention allocation mechanism simulation of human cognitive behavior, according to the concept of right of way, the establishment of the right size radar map, storage space and computing resources using less complete simulation of human cognitive behavior and counted by row radar map through information fusion, simulation analysis and path planning and other functions; the definition of the minimum safety distance of intelligent vehicle, based on the intelligent vehicle change intention. The value of expected tract sample of 2 skilled driver, select the typical highway road Line, make the test control conditions of design, characteristic parameters of impact of the acquisition of the lane change of the 311 groups, among them, lane keeping data of 97 groups, 214 groups of lane changing data; using v- training support vector machine, select (Delta, V) = (0.12,0.03) v- as the model parameters of support vector machine. The accuracy rate of lane changing is 91.05%; from the time of lane change, change lateral acceleration, curvature mutation analysis and comparison of the changing path planning method of intelligent vehicle used, according to the research object in this paper, the method of determining the trapezoidal acceleration changing path; the sudden and unexpected event change process, set up the static and dynamic model of vehicle obstacle avoidance; in order to meet the real-time requirements, design a variable scale grid in environment modeling, when the vehicle is traveling at a high speed variable scale grid than the traditional grid CPU occupancy is reduced about 34%; variable With the right scale grid radar map are fused by static selection and dynamic obstacle avoidance module obstacle avoidance strategy, to escape the vehicle sudden unexpected obstacles.
Through the analysis of intelligent vehicle longitudinal modeling and control method of coupling system, established intelligent vehicle longitudinal kinematic model, the model considering the longitudinal, lateral and yaw motion, can be more accurately on the changing path of intelligent vehicle and the lane change after the completion of the lane keeping control. Analysis of the vehicle in the vertical and horizontal coupling influence, proposed intelligent vehicle longitudinal modeling and control problems of coupling, established and coupling control system of intelligent vehicle, including longitudinal motion, lateral motion and yaw motion model; the exponential sliding mode variable structure design method for trajectory tracking controller, the intelligent vehicle system satisfies the desired dynamic and static performance the index in the vehicle lane change process; to change after the completion of the lane keeping, lateral deviation model of intelligent vehicle, using Terminal sliding mode variable structure The design method of lane keeping controller, the lateral motion and yaw motion combined with lateral deviation can make lane curvature change and automatic adjustment, at the same time, can improve the lane keeping process vertical movement stability; the intelligent vehicle lane changing trajectory tracking control and lane change after the completion of the lane keeping control using MATLAB simulation the simulation tool to verify the effectiveness of the controller design and stability.
According to the structure characteristics of a certain type of off-road vehicle, the mechanical transformation of intelligent vehicle platform, build intelligent vehicle platform of hardware and software, and test the actual highway is carried out and verified the reliability and stability of the system. According to the requirements of intelligent vehicle autonomous lane changing technology verification, the intelligent transformation of the original car the design of electric power steering, the steering mechanism of the vehicle, a hydraulic valve group reformed braking mechanism installed in the original brake system, by installing a set of parallel implementation of intelligent electric cable disc throttle body control; build intelligent vehicle hardware platform, optimization of equipment; software design adopts the multi thread technology the system is divided into the main thread, the thread of control, the four part of the road information acquisition thread and the serial communication thread: the intelligent vehicle autonomous highway driving test, I finished For the first time in the country authority, intelligent vehicle highway testing institutions and the media of all the three parties under the supervision of the autonomous driving test, test the number of kilometers to 1500 kilometers above, completed a total of 95 independent change, test data to prove that the autonomy in the highway environment for intelligent vehicle has good stability and reliability.

【學位授予單位】：中國人民解放軍軍事醫(yī)學科學院
【學位級別】：博士
【學位授予年份】：2014
【分類號】：U463.6;U495

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