基于车联网车载终端及车辆侧翻预警系统设计

发布时间：2018-08-03 16:41

【摘要】：随着我国经济的发展,交通管理压力以及交通安全问题日趋明显,如何更有效地保障车辆的安全运行变得尤其重要。及时获取车辆实时信息以及相关参数预测信息,对于防止交通事故的发生有着重要的现实意义。针对这一现象,本文基于嵌入式技术、无线网络通信技术、车辆实时定位技术以及车辆侧翻预警算法,设计了具有数据中心控制平台、无线通信模块、车联网车载终端模块以车辆侧翻预警模块的综合系统。本文主要完成了以下工作：(1)设计了一种车辆综合信息管理系统。该系统主要包括：车主及车辆信息管理、车辆定位信息管理、车辆状态数据信息管理等。系统主要从数据中心控制平台以及车联网车载终端两部分进行设计。在数据中心控制平台中,系统实现对车主以及车辆的基本信息进行查询以及修改、显示并保存车辆的实时位置信息、以及与车载平台进行信息交互等功能。在车联网车载终端中,系统除了能实现数据中心的功能外,还可以显示并保存车辆状态数据信息等功能。(2)设计了一种车辆侧翻预警系统。系统选择内含ARM11处理器的S3C6410作为侧翻预警系统主控制器的处理器,利用MPU6050六自由度传感器采集车辆实时运行参数并输送给主控制器。使用定位通信一体模块SIM908模块实现车辆的实时定位,以及车联网车载终端与数据中心控制平台的无线通信。(3)为了达到车辆侧翻预警的目的,本文选取车辆的横向载荷转载转移率(LTR, Lateral-Load Transfer Ratio)作为车辆侧翻预警算法的判别侧翻指示。选用多层递阶(MLR, Multi-level Recursive)建模预测方法作为预警算法,可以实现在线预测侧翻判别指标的数值,根据预测得到的数值,车载系统对车辆侧翻危险程度进行判断,当预测LTR值超过设定的阈值后发出报警信号。本系统基于软硬件平台以及实车模拟实验完成了系统的综合测试,实现了数据中心与车载终端进行信息的查询、储存、更改、交互等功能。为验证系统算法的有效性,将本文所提MLR建模预测方法与自回归模型(AR, Autoregressive Model)预测方法在未来1到2秒的LTR预测值并与车辆实际LTR值作对比,实验结果显示,本文所提车辆侧翻预警系统有较高的适用性和预测精度。
[Abstract]:With the development of our country's economy, traffic management pressure and traffic safety problems become more and more obvious. How to ensure the safe operation of vehicles becomes more and more important. It is of great practical significance to obtain real-time vehicle information and related parameter prediction information in time to prevent traffic accidents. Aiming at this phenomenon, based on embedded technology, wireless network communication technology, vehicle real-time positioning technology and vehicle rollover early warning algorithm, a data center control platform and wireless communication module are designed. The vehicle network vehicle terminal module is a comprehensive system of vehicle rollover warning module. The main work of this paper is as follows: (1) A vehicle integrated information management system is designed. The system mainly includes: owner and vehicle information management, vehicle positioning information management, vehicle status information management and so on. The system is mainly designed from data center control platform and vehicular terminal. In the data center control platform, the system can query and modify the basic information of the owner and the vehicle, display and save the real-time position information of the vehicle, and exchange information with the vehicle platform. In the vehicle network vehicle terminal, the system can not only realize the function of data center, but also display and save the information of vehicle status. (2) A vehicle rollover warning system is designed. The S3C6410 with ARM11 processor is selected as the processor of the main controller of the rollover warning system. The real-time running parameters of the vehicle are collected by using the MPU6050 six-degree-of-freedom sensor and transmitted to the main controller. The SIM908 module is used to realize the real-time positioning of vehicles and the wireless communication between the vehicle terminal and the data center control platform. (3) in order to achieve the purpose of early warning of vehicle rollover, In this paper, the lateral load transfer rate (Lateral-Load Transfer Ratio) of vehicles is selected as the discriminant rollover indication of the early warning algorithm of vehicle rollover. The multilevel hierarchical (Multi-level Recursive) modeling and prediction method is chosen as the early warning algorithm, which can realize the on-line prediction of the value of the rollover discriminant index. According to the predicted value, the vehicle system can judge the dangerous degree of the vehicle rollover. An alarm signal is issued when the predicted LTR value exceeds the set threshold. The system is based on the hardware and software platform and the real vehicle simulation experiment to complete the comprehensive test of the system, the data center and the vehicle terminal for information query, storage, change, interaction and other functions. In order to verify the effectiveness of the system algorithm, the proposed MLR modeling and prediction method and the autoregressive model (AR, Autoregressive Model) prediction method are compared with the actual LTR values of the vehicle in the next 1 to 2 seconds. The experimental results show that, The vehicle rollover warning system proposed in this paper has high applicability and prediction accuracy.
【学位授予单位】：昆明理工大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：U463.6

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