本文選題：占道停車　切入點(diǎn)：智能管理　出處：《北京郵電大學(xué)》2015年碩士論文

【摘要】：隨著經(jīng)濟(jì)的發(fā)展和人們消費(fèi)能力的提高,家用小汽車的數(shù)量日漸增長,城市中“停車難”問題越來越嚴(yán)重�，F(xiàn)有的大型停車場難以滿足停車需求,增加占道停車的方式可以大大緩解這一難題。然而因為占道停車場分布的不規(guī)律性及管理體系的不健全,存在個人私行收取費(fèi)用的狀況,且無嚴(yán)格統(tǒng)一的收費(fèi)準(zhǔn)則,管理部門沒法及時掌握泊車信息及停車費(fèi)用,駕駛員無法及時獲取所在位置附近的停車場及車位占用情況信息,所以需要構(gòu)建統(tǒng)一的智能管理系統(tǒng)。此外,國內(nèi)的大多數(shù)停車管理系統(tǒng)中的信息發(fā)布模塊,僅能顯示車位的實時信息,未能提供對短時間內(nèi)車位變化情況的預(yù)測,導(dǎo)致駕駛員到達(dá)停車場后的實際車位占用情況可能與在停車場外看到或者查詢到的信息差別很大,甚至只能到其他停車場尋找車位,帶來諸多不便。 首先,本文針對當(dāng)前國內(nèi)外普遍使用的停車場系統(tǒng)的情況進(jìn)行了調(diào)研,指出了當(dāng)前工作中存在的問題并予以剖析。進(jìn)而討論了時間序列預(yù)測的相關(guān)方法,重點(diǎn)討論了基于神經(jīng)網(wǎng)絡(luò)預(yù)測的方法,針對BP神經(jīng)網(wǎng)絡(luò)預(yù)測算法進(jìn)行了深入的研究。 然后,本文對城區(qū)占道停車智能管理系統(tǒng)的功能需求進(jìn)行了分析,并完成了整體的設(shè)計工作。第一,為了使管理系統(tǒng)智能化,將系統(tǒng)劃分為四個子系統(tǒng)：分別是車位信息采集子系統(tǒng),手持終端收費(fèi)子系統(tǒng),中心管理子系統(tǒng)以及停車誘導(dǎo)及車位預(yù)測子系統(tǒng)。在各子系統(tǒng)之間定義了通信格式及交互協(xié)議,實現(xiàn)了數(shù)據(jù)的采集、傳輸、處理及應(yīng)用。第二,在停車誘導(dǎo)子系統(tǒng)中引入了車位信息的預(yù)測功能,目的是對未來車位的變化情況實現(xiàn)短時預(yù)測。通過對時間序列預(yù)測的傳統(tǒng)方法、時間序列的非線性預(yù)測方法以及神經(jīng)網(wǎng)絡(luò)預(yù)測方法的比較,最終創(chuàng)建了基于BP神經(jīng)網(wǎng)絡(luò)的車位信息預(yù)測模型,并用實際數(shù)據(jù)對該模型進(jìn)行了驗證。 最后,結(jié)合實際項目需求,完成了對本系統(tǒng)的開發(fā)和實現(xiàn)。
[Abstract]:With the development of economy and the improvement of people's consumption power, the number of household cars is increasing day by day, and the problem of "parking difficulty" is becoming more and more serious.The existing large parking lot is difficult to meet the parking demand, increasing the parking on the road can greatly alleviate this problem.However, due to the irregular distribution of parking lots and the unsound management system, there is a situation in which private individuals collect fees, and there are no strict and uniform charging criteria, so the management can not grasp parking information and parking fees in a timely manner.The driver can not get the information of parking lot and parking space in time, so it is necessary to construct a unified intelligent management system.In addition, the information release modules in most parking management systems in China can only display the real-time information of parking spaces, and fail to predict the changes of parking spaces in a short period of time.As a result, the actual parking space occupation after the driver arrives in the parking lot may be very different from the information seen or inquired outside the parking lot, even can only look for the parking space in other parking lot, which brings a lot of inconvenience.Firstly, this paper investigates the situation of parking lot system which is widely used at home and abroad, points out the problems existing in the current work and analyzes it.Then, the related methods of time series prediction are discussed, and the methods based on neural network prediction are discussed, and the BP neural network prediction algorithm is studied deeply.Then, this paper analyzes the functional requirements of urban parking intelligent management system, and completes the overall design work.First, in order to make the management system intelligent, the system is divided into four subsystems: parking information collection subsystem, handheld terminal charge subsystem, central management subsystem and parking guidance and parking prediction subsystem.The communication format and interactive protocol are defined among the subsystems, and the data collection, transmission, processing and application are realized.Secondly, the prediction function of parking space information is introduced in the parking guidance subsystem, in order to predict the future parking space changes in a short time.Through the comparison of the traditional methods of time series prediction, the nonlinear prediction methods of time series and the neural network forecasting methods, the vehicle parking information prediction model based on BP neural network is established.The model is validated with actual data.Finally, according to the actual project requirements, the development and implementation of the system is completed.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：U491.7;TP18

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