智能停车管理与引导系统研究

发布时间：2019-03-11 09:07

【摘要】：伴随我国良好的经济发展态势与城市化进程的加快推进,交通运输行业蓬勃发展,汽车保有量逐年提升,我国已进入私家车时代。与年均15%-20%的汽车保有量增长率相对应的是城市道路交通压力的加剧,改善城市的交通条件和设施的利用效率已成为迫切之举,乃至城市经济发展的重要保障手段。面对停车场数量不足且运行低效的现状与巨大的停车需求间的突出矛盾,由于城市用地紧张短期内停车设施数量提升有限,应当通过提升停车场运行效率以缓解供需矛盾。而目前停车场运行低效的主要原因为:场内泊位信息获取度较低,入场车辆无明确引导,所以有必要开发一套有效且具有普及价值的停车管理与引导系统。本文基于成熟的传感器检测技术与网络通信技术应用,针对停车场内信息获取与泊车引导流程优化主要完成以下工作:(1)研究了停车场状态信息获取与泊位选择算法。首先,基于地磁传感器检测数据提出了相应数据处理方法与车辆状态判别方法。其次,通过车辆状态判别结果提出针对不同停车场规模布局下的停车特征参数获取算法,实现了停车场管理信息与泊位状态信息的有效获取。最后,通过分析不同引导方式下的泊车流程与泊位选择影响因素提出了基于灰熵模型的最优泊位选择算法与优化方案,并通过模拟实例进行计算验证。(2)研究了智能停车管理与引导系统的开发实现。首先,通过分析智能停车管理系统的功能需求与相应的业务流程,明确开发过程的侧重点,并论证了系统实现的可行性。其次,通过分析系统中数据传输层次,完成了系统网络拓扑结构的框架搭建。最后,在相应开发环境下,根据构建的停车场模型实例,完成了对应的数据库搭建与最终的引导界面可视化实现。
[Abstract]:With the development of China's economy and the acceleration of urbanization, the transportation industry has developed vigorously, and the number of cars has been increased year by year. China has entered the era of private cars. Corresponding to the growth rate of 15% / 20% vehicle ownership per year, the urban road traffic pressure is increasing. It has become an urgent task to improve the traffic conditions and utilization efficiency of the facilities in the city, and even an important means to guarantee the development of the city economy. In the face of the contradiction between the shortage of parking lot and the low efficiency of parking and the huge demand for parking, the contradiction between supply and demand should be alleviated by improving the operation efficiency of parking lot, because the quantity of parking facilities is limited in the short term due to the shortage of urban land use. At present, the main reasons for the low efficiency of parking are: the access to parking information is low, and there is no clear guidance for entering vehicles, so it is necessary to develop a set of effective and universal parking management and guidance system. Based on the mature sensor detection technology and network communication technology, this paper focuses on the optimization of parking information acquisition and parking guidance flow. (1) the algorithm of parking state information acquisition and parking selection is studied. First, based on the geomagnetic sensor detection data, the corresponding data processing method and vehicle status discrimination method are proposed. Secondly, according to the result of vehicle status discrimination, a parking characteristic parameter acquisition algorithm for different parking lot size layout is put forward, which realizes the effective acquisition of parking lot management information and parking state information. Finally, the optimal parking selection algorithm and optimization scheme based on grey entropy model are put forward by analyzing the parking flow and the influencing factors of parking choice under different guiding modes. (2) the development and realization of intelligent parking management and guidance system are studied. Firstly, by analyzing the functional requirements and the corresponding business processes of the intelligent parking management system, the emphasis of the development process is defined, and the feasibility of the implementation of the system is demonstrated. Secondly, through the analysis of the data transmission level of the system, the framework of the network topology of the system is completed. Finally, under the corresponding development environment, according to the parking lot model example, the corresponding database construction and the final visual implementation of the guide interface are completed.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：U491.7

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