多自主车辆系统安全控制与分布式优化策略研究

发布时间：2018-07-18 15:54

【摘要】：论文题目：多自主车辆系统安全控制与分布式优化策略研究多自主车辆系统因其能够释放繁杂交通工作对人的束缚，为交通路网提供及时的服务，成为近年来智能交通领域研究的热点之一。本文以多自主车辆系统控制与优化策略为切入点，通过对多自主车辆系统建模分析，着重研究了自主车辆在典型路况的安全控制策略、分布式环境中的优化配置以及多自主车辆系统的任务分配方法。具体如下： 1)建立了多自主车辆系统模型，设计滤波器估计自主车辆运动状态。分别对自主车辆纵向动力学、操纵动力学和多自主车辆系统进行建模，分析了风阻对自主车纵向车速的影响，从操纵稳定性角度出发，分析自主车设计合理性，不同频率响应下的稳定性等，通过混合自动机模型描述多自主车辆系统协作模式。设计卡尔曼滤波器估计自主车运动状态。仿真结果验证了所建模型的合理性。 2)研究了针对典型交通路况的柔性跟驰、路口高效协作安全控制策略。考虑急刹给车辆带来的损伤，通过引入以自然指数函数为原型的安全控制策略模型，解决了跟驰安全控制问题。针对T形路口安全问题，提出安全系数估计方法，结合人工势场思想，，估计车辆期望加速度、速度，利用改进的增量型数字PI控制器实现自主车纵向车速的准确控制，实现自主车辆协作避碰。仿真结果验证了跟驰安全控制策略和采用安全系数估计自主车辆T形路口协作避碰规划的可行性与有效性。 3)解决了交通路网中多自主车辆系统通过优化配置、任务规划满足指定覆盖率、减少平均时间代价的问题。利用先“静”后“动”的思想，通过模拟退火算法求解数量不同的自主车能够达到的静态优化覆盖率，进而求得满足指定覆盖率的自主车配置数量。以此为依据，进一步求解动态情况下满足指定覆盖率的自主车配置数量。对任务分配问题，给出基于BDI模型的决策模块结构，利用Hungary算法给出任务分配方案。仿真结果通过覆盖率统计值证明了优化配置的可行性，通过平均到达比例、完成率估计值、平均时间代价证明任务分配的有效性。 4)设计多自主车辆仿真实验平台，分析系统模块性能。搭建多自主车辆系统仿真平台，给出多自主车辆系统结构。对平台上的室内定位子系统模块进行了准确性测试。在一组合理的参数配置下，对定位系统性能进行了分析。通过软件实验平台对通信子系统进行了组网，实现对自主车辆位置信息的发送与控制。综上所述，本文就多自主车辆系统的安全控制和分布式优化策略进行了相对完整的理论研究，主要目的是实现自主车辆的安全控制与多自主车辆系统的分布式优化，通过仿真实验进行了相应的验证与分析，并搭建仿真实验平台，分析系统性能。
[Abstract]:Topic: multi autonomous vehicle system security control and distributed optimization strategy research
The multi autonomous vehicle system has become one of the hotspots in the field of Intelligent Transportation Research in recent years because of its ability to release the bondage of complex traffic work and provide timely service to the traffic network. This paper focuses on the multi autonomous vehicle system control and optimization strategy, and focuses on the research of autonomous vehicles through the modeling and analysis of the multi autonomous vehicle system. In the typical road safety control strategy, the optimal allocation in the distributed environment and the task allocation method of the multi autonomous vehicle system are as follows:
1) the multi autonomous vehicle system model is established and the filter is designed to estimate the motion state of the autonomous vehicle. The longitudinal dynamics, the control dynamics and the multi autonomous vehicle system are modeled respectively. The influence of the wind resistance on the longitudinal vehicle speed is analyzed. From the angle of control stability, the design rationality and the different frequency of the autonomous vehicle are analyzed. In response to the stability, a hybrid automaton model is used to describe the cooperative model of the multi autonomous vehicle system. The Calman filter is designed to estimate the motion state of the autonomous vehicle. The simulation results verify the reasonableness of the model.
2) the efficient cooperative safety control strategy for the intersection of typical traffic conditions is studied. Considering the damage caused by emergency brake, the safety control problem is solved by introducing the model of natural exponential function as the prototype of safety control strategy, and the safety factor estimation method is proposed for the safety problem of the T intersection. The idea of the potential field is used to estimate the desired acceleration and speed of the vehicle. The improved incremental digital PI controller is used to realize the accurate control of the longitudinal speed of the autonomous vehicle and realize the cooperative collision avoidance of the autonomous vehicle. The simulation results verify the feasibility and effectiveness of the following safety control strategy and the use of the safety factor to estimate the cooperative collision avoidance planning for the T intersection of the autonomous vehicle. Sex.
3) to solve the problem that the multi autonomous vehicle system in the traffic network is optimized through the optimization configuration, the task planning satisfies the specified coverage rate and reduces the average time cost. By using the idea of "static" after the "motion", the simulated annealing algorithm is used to solve the static optimal coverage rate that the number of different autonomous vehicles can reach, and then to meet the specified coverage rate. On the basis of this, we further solve the number of autonomous vehicles that meet the specified coverage in the dynamic situation. The decision module structure based on the BDI model is given to the task allocation problem, and the task allocation scheme is given by the Hungary algorithm. The simulation results prove the feasibility of the optimized configuration through the coverage rate statistics. Over average arrival ratio, completion rate estimate and average time cost prove the effectiveness of task allocation.
4) design the multi autonomous vehicle simulation experiment platform, analyze the performance of the system module, build the multi autonomous vehicle system simulation platform, give the multi autonomous vehicle system structure. The accuracy test of the indoor positioning subsystem module on the platform is carried out. The performance of the positioning system is analyzed under a set of reasonable parameters configuration. The software experiment is carried out through the software experiment. The communication network is organized by the platform to realize the transmission and control of the location information of the autonomous vehicle.
To sum up, this paper makes a relatively complete theoretical study on the security control and distributed optimization strategy of the multi autonomous vehicle system. The main purpose is to realize the safety control of the autonomous vehicle and the distributed optimization of the multi autonomous vehicle system. The corresponding verification and analysis are carried out through the simulation experiment, and the simulation experiment platform and the analysis system are set up. Unified performance.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U495

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