城市环境下无人驾驶车辆运动控制方法的研究
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摘要
无人驾驶车辆是一种移动机器人,其关键技术涉及到环境感知、模式识别、导航定位、智能决策、控制工程以及计算机技术等众多学科的前沿研究领域,是验证机器感知与认知理论和关键技术的最佳实验平台,同时其技术单元也可以帮助人类驾驶员进行车辆自主驾驶工作,并以此提高行车的安全和效率。
在无人驾驶车辆的单元技术中,在未知路况条件下的高速高精度轨迹跟踪自适应控制一直是研究的重点和难点。针对城市综合环境下无人驾驶车辆的运动控制问题,本文在传统方法的基础上,根据车辆控制模型的特殊性和城市环境的复杂多样性,提出了一些新的解决方案,以提高算法的适应性。具体的研究内容包括以下几个方面：
1)对无人驾驶车辆控制理论的相关概念,对国内外研究成果进行分析,了解汽车的运动特性及建模仿真方法,了解不同环境对车辆运动的影响,了解驾驶员的驾驶过程,从人对车辆的控制方式来思考无人驾驶控制所要面临问题。
2)对城市道路的分类和各自特点进行了归纳总结,明确了无人车在各种道路环境所要完成的任务；以“智能先锋”无人驾驶车辆平台为基础,介绍了平台的感知系统、决策系统、控制系统及执行机构。结合无人驾驶车辆在城市道路运动控制方面遇到的关键性问题提出控制系统采用的研究策略和设计思想。
3)分析车辆纵向动力学,研究车辆纵向控制方法。分析总结“智能先锋”动力传动特性和制动力学特性,参考实际驾驶员对车辆的速度控制行为,结合专家控制方法,提出专家PID控制算法,根据实际驾驶员的驾车经验建立专家规则,解决在传动系统高度非线性和复杂的纵向干扰条件下的控制精度的问题,提高速度控制的鲁棒性,实现无人驾驶车辆在城市道路行驶的速度控制。
4)研究基于车辆操作动力学的横向控制方法。建立车辆操纵动力学模型,进行车辆操纵动力学和轮胎侧向力学分析；在“预瞄—跟随”理论的控制模型和传统PID控制方法的基础上设计一种基于小脑模型神经网络与PID复合的无人驾驶车辆横向控制算法,使系统能够自动补偿被控模型和输入信号发生的非预知的变化,解决由于模型不精确或存在其他变化因素带来的控制不确定性问题,从而使无人车能够灵活的在各种道路环境实现稳定准确的道路跟踪行驶。
5)研究车辆高速行驶时的运动学特性,联合考虑纵向控制和横向控制之间相互制约关系,根据车辆操纵稳定性及舒适性的要求建立了最高速度和最大转向角的约束规则,以保障车辆行驶安全性。
本文最后在真实的城市道路环境中,以“智能先锋”无人驾驶车辆为实验平台,验证了上述研究内容的可行性和有效性,并根据实验结果总结了目前控制系统设计方法的优势和不足,也对进一步的研究提出了展望。
The autonomous vehicle is one kind of mobile robots, whose key technologies are related to frontier research fields of environmental perception, pattern recognition, navigation and positioning, intelligent decision-making, control engineering, computer technology, and many other disciplines. It is not only the best experimental platform to exam the cognitive theory and the critical technology, but also, at the same time, its unit technology can help humans drive cars automatically to improve the driving safety and efficiency.
In the technology of autonomous vehicle, the high speed and high precision self-adaptative control of trajectory tracking in unknown traffic conditions is always the key difficulty. To deal with the problems of autonomous vehicle's motion control in urban environment and to improve the known traditional method, this paper presents some new solutions dealing with the specific characteristics of vehicle control model and complex diversity of city environment, to enhance the adaptability of the algorithms. Our research includes the following several aspects, specifically:
1) We first briefly introduce the concept of vehicle control theory and the state-of-the-art international and domestic achievements. This includes the understanding of vehicle's kinetic characters with its modeling and simulation, the understanding of the environmental influence on the vehicle's and the understanding of the driving process upon considering the way that human drives.
2) This paper also summarizes the classification of urban streets and their respective characteristic, in a way that the tasks that the autonomous vehicle faced in various conditions clear. With the so-called "Intelligent Pioneer" as a basis platform of the autonomous vehicle, we introduce the platform of sensing systems, decision-making systems, control systems, and implementing agencies. We propose a control system's research strategy and design idea that combine the key problems of autonomous vehicle's motion control in urban environment.
3) We analyze the vehicle longitudinal dynamics and study the method of vehicle longitudinal control. The power transmission characteristics and brake mechanical properties of "Intelligent Pioneer" is analyzed and summarized, according to the behavior of driver's speed control, combining the expert control method. We develop the expert PID control algorithm, that establishes expert rules according to the driving experience, solves the problem of control accuracy when the transmission system is highly nonlinear and the longitudinal interference is too complex, so that the robustness of speed control system can be improved and the goal of speed control of autonomous vehicle's driving in urban road can be established.
4) We study the method of lateral control for vehicle operation dynamics. The model of vehicle operation dynamics is established for the research of vehicle operation dynamics and tire lateral mechanics. Upon the formally established theory and traditional PID control, this paper presents a new autonomous vehicle's lateral control algorithm based on a composite of the CMAC and PID control. This enables the system to compensate automatically when the model and input signal occur changes unpredictability, such that the autonomous vehicle can drive steadily and accurately in any kind of urban environments.
5) We study the kinematic characteristics when a car travels at a high speed. We consider the restricted relationship between vertical control and lateral control federatively and establish the constraint between the highest speed and biggest steering angle at the request of stability and comfort, to ensure the safety of the vehicles.
At last, this paper takes "Intelligent Pioneer" as the experimental platform to check the feasibility and to examine the research above in the real urban environment. We also summarize the advantages and shortages of control system's design procedures. Future research directions are also proposed.
在无人驾驶车辆的单元技术中,在未知路况条件下的高速高精度轨迹跟踪自适应控制一直是研究的重点和难点。针对城市综合环境下无人驾驶车辆的运动控制问题,本文在传统方法的基础上,根据车辆控制模型的特殊性和城市环境的复杂多样性,提出了一些新的解决方案,以提高算法的适应性。具体的研究内容包括以下几个方面：
1)对无人驾驶车辆控制理论的相关概念,对国内外研究成果进行分析,了解汽车的运动特性及建模仿真方法,了解不同环境对车辆运动的影响,了解驾驶员的驾驶过程,从人对车辆的控制方式来思考无人驾驶控制所要面临问题。
2)对城市道路的分类和各自特点进行了归纳总结,明确了无人车在各种道路环境所要完成的任务；以“智能先锋”无人驾驶车辆平台为基础,介绍了平台的感知系统、决策系统、控制系统及执行机构。结合无人驾驶车辆在城市道路运动控制方面遇到的关键性问题提出控制系统采用的研究策略和设计思想。
3)分析车辆纵向动力学,研究车辆纵向控制方法。分析总结“智能先锋”动力传动特性和制动力学特性,参考实际驾驶员对车辆的速度控制行为,结合专家控制方法,提出专家PID控制算法,根据实际驾驶员的驾车经验建立专家规则,解决在传动系统高度非线性和复杂的纵向干扰条件下的控制精度的问题,提高速度控制的鲁棒性,实现无人驾驶车辆在城市道路行驶的速度控制。
4)研究基于车辆操作动力学的横向控制方法。建立车辆操纵动力学模型,进行车辆操纵动力学和轮胎侧向力学分析；在“预瞄—跟随”理论的控制模型和传统PID控制方法的基础上设计一种基于小脑模型神经网络与PID复合的无人驾驶车辆横向控制算法,使系统能够自动补偿被控模型和输入信号发生的非预知的变化,解决由于模型不精确或存在其他变化因素带来的控制不确定性问题,从而使无人车能够灵活的在各种道路环境实现稳定准确的道路跟踪行驶。
5)研究车辆高速行驶时的运动学特性,联合考虑纵向控制和横向控制之间相互制约关系,根据车辆操纵稳定性及舒适性的要求建立了最高速度和最大转向角的约束规则,以保障车辆行驶安全性。
本文最后在真实的城市道路环境中,以“智能先锋”无人驾驶车辆为实验平台,验证了上述研究内容的可行性和有效性,并根据实验结果总结了目前控制系统设计方法的优势和不足,也对进一步的研究提出了展望。
The autonomous vehicle is one kind of mobile robots, whose key technologies are related to frontier research fields of environmental perception, pattern recognition, navigation and positioning, intelligent decision-making, control engineering, computer technology, and many other disciplines. It is not only the best experimental platform to exam the cognitive theory and the critical technology, but also, at the same time, its unit technology can help humans drive cars automatically to improve the driving safety and efficiency.
In the technology of autonomous vehicle, the high speed and high precision self-adaptative control of trajectory tracking in unknown traffic conditions is always the key difficulty. To deal with the problems of autonomous vehicle's motion control in urban environment and to improve the known traditional method, this paper presents some new solutions dealing with the specific characteristics of vehicle control model and complex diversity of city environment, to enhance the adaptability of the algorithms. Our research includes the following several aspects, specifically:
1) We first briefly introduce the concept of vehicle control theory and the state-of-the-art international and domestic achievements. This includes the understanding of vehicle's kinetic characters with its modeling and simulation, the understanding of the environmental influence on the vehicle's and the understanding of the driving process upon considering the way that human drives.
2) This paper also summarizes the classification of urban streets and their respective characteristic, in a way that the tasks that the autonomous vehicle faced in various conditions clear. With the so-called "Intelligent Pioneer" as a basis platform of the autonomous vehicle, we introduce the platform of sensing systems, decision-making systems, control systems, and implementing agencies. We propose a control system's research strategy and design idea that combine the key problems of autonomous vehicle's motion control in urban environment.
3) We analyze the vehicle longitudinal dynamics and study the method of vehicle longitudinal control. The power transmission characteristics and brake mechanical properties of "Intelligent Pioneer" is analyzed and summarized, according to the behavior of driver's speed control, combining the expert control method. We develop the expert PID control algorithm, that establishes expert rules according to the driving experience, solves the problem of control accuracy when the transmission system is highly nonlinear and the longitudinal interference is too complex, so that the robustness of speed control system can be improved and the goal of speed control of autonomous vehicle's driving in urban road can be established.
4) We study the method of lateral control for vehicle operation dynamics. The model of vehicle operation dynamics is established for the research of vehicle operation dynamics and tire lateral mechanics. Upon the formally established theory and traditional PID control, this paper presents a new autonomous vehicle's lateral control algorithm based on a composite of the CMAC and PID control. This enables the system to compensate automatically when the model and input signal occur changes unpredictability, such that the autonomous vehicle can drive steadily and accurately in any kind of urban environments.
5) We study the kinematic characteristics when a car travels at a high speed. We consider the restricted relationship between vertical control and lateral control federatively and establish the constraint between the highest speed and biggest steering angle at the request of stability and comfort, to ensure the safety of the vehicles.
At last, this paper takes "Intelligent Pioneer" as the experimental platform to check the feasibility and to examine the research above in the real urban environment. We also summarize the advantages and shortages of control system's design procedures. Future research directions are also proposed.
引文
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