基于物聯(lián)網(wǎng)的城市停車誘導(dǎo)系統(tǒng)的研究

2.2萬字
自己原創(chuàng)的畢業(yè)設(shè)計(jì)，今年最新的，僅在本站獨(dú)家提交，大家放心使用

摘要 目前城市交通中的“停車難”問題日益成為影響我國大中城市經(jīng)濟(jì)發(fā)展的難題,雖然最近各地修建了不少新的停車場,但是由于停車誘導(dǎo)信息的不完善,人們?nèi)匀恍枰ㄙM(fèi)大量時(shí)間尋找合適的停車位,既增加了道路交通擁堵,又浪費(fèi)大量的寶貴時(shí)間。經(jīng)過對現(xiàn)有泊車誘導(dǎo)系統(tǒng)以及城市停車管理現(xiàn)實(shí)情況的分析發(fā)現(xiàn)，停車場內(nèi)部泊位誘導(dǎo)主要存在以下問題：一是如何確保誘導(dǎo)信息的實(shí)時(shí)性和準(zhǔn)確性，二是如何確保停車者對誘導(dǎo)信息的滿意度。針對這些問題，本文將物聯(lián)網(wǎng)思想應(yīng)用到大城市的停車誘導(dǎo)系統(tǒng)中，建立實(shí)時(shí)、準(zhǔn)確的泊車誘導(dǎo)信息體系，實(shí)現(xiàn)城市內(nèi)部停車場的停車位信息的網(wǎng)絡(luò)互聯(lián)，提供準(zhǔn)確實(shí)時(shí)的信息，方便停車者停車。
本文首先針對我國停車泊位誘導(dǎo)系統(tǒng)方面存在的問題及不足，分析國內(nèi)外物聯(lián)網(wǎng)和停車誘導(dǎo)系統(tǒng)方面的發(fā)展現(xiàn)狀，并對物聯(lián)網(wǎng)在停車誘導(dǎo)方面的應(yīng)用情況進(jìn)行論述，在此基礎(chǔ)上提出了基于物聯(lián)網(wǎng)的泊位誘導(dǎo)系統(tǒng)，明確了論文的研究目的和意義，擬定論文的研究思路和總體框架。文中同時(shí)還討論和分析了基于物聯(lián)網(wǎng)技術(shù)的停車誘導(dǎo)系統(tǒng)的總體要求、設(shè)計(jì)原則、功能需求等應(yīng)用需求，并描述了各功能模塊的架構(gòu)和實(shí)現(xiàn)流程。本文重點(diǎn)分析并提出了在物聯(lián)網(wǎng)環(huán)境下的最優(yōu)車位選擇算法,論述了算法的基本原理和改進(jìn)，使客戶停車更加方便快捷。
本文成功的將蟻群算法引入到了最優(yōu)停車位的模型中來,以此來解決車位預(yù)定中的最優(yōu)車位選擇問題,并且根據(jù)現(xiàn)實(shí)中的駕駛員停車特點(diǎn),對蟻群算法進(jìn)行了部分改進(jìn), 使其更加符合物聯(lián)網(wǎng)環(huán)境下的最優(yōu)車位選擇問題。用戶可以準(zhǔn)確快速的尋找自己合適的停車車位，節(jié)省了時(shí)間并且有利于緩解在停車高峰期的堵車問題。
關(guān)鍵詞：
物聯(lián)網(wǎng) 泊位誘導(dǎo) 蟻群算法 泊位選擇


Key technology research things on the parking
guidance system
Abstract Currently urban transport in the "parking difficult" issues affecting our cities are increasingly becoming the economic development problems, although recently a lot of new construction around the parking lot, but because of imperfect information, parking guidance, people still need to spend a lot of time looking for suitable parking spaces, not only increasing the road traffic congestion, but also waste a lot of valuable time.After analysis of the existing parking guidance systems and parking management urban realities found inside parking spaces induced following major issues: First, how to ensure the timeliness and accuracy of the guidance information, the second is how to ensure that those on the parking guidance information satisfaction. To solve these problems, we thought things would apply to metropolitan parking guidance system, create real-time, accurate parking guidance information system, to achieve network interconnection inner city parking parking information, providing accurate real-time information to facilitate parkers parking.
Firstly, for the problems and shortcomings of parking spaces induction systems, analyzing the current development of domestic and foreign things and parking guidance systems, and parking guidance and networking in terms of the application are discussed, on this basis, based on the proposed things berth induction system, a clear purpose and significance of research papers, research ideas and develop the overall framework of the paper. The paper also discusses and analyzes the application of networking technology needs of the general requirements of parking guidance systems, design principles, based on functional requirements, etc., and describes the structure of the functional modules and the implementation process. This article focuses on the analysis and proposed parking spaces in optimal networking environment selection algorithm, discusses the basic principle of the algorithm and implementation of process improvement, enabling customers faster and more convenient parking.
The success of the ant colony algorithm is introduced in this article to model the optimal parking spaces in the past, in order to solve the optimal parking spaces predetermined selection problem, and depending on the characteristics of the reality of the driver to stop, to improve the ant colony algorithm part to make it more in line with the best parking IOT environment choice. Users can quickly and accurately find their suitable parking spaces, saving time and help alleviate the problem of traffic jams in the parking peak.

Key words:
Internet of Things Berth Guidance Ant Colony Algorithm Berth Selection


目錄
第一章 緒論 1
1.1 研究背景 1
1.2 物聯(lián)網(wǎng)發(fā)展現(xiàn)狀 2
1.2.1 國外物聯(lián)網(wǎng)發(fā)展?fàn)顩r 2
1.2.2 國內(nèi)物聯(lián)網(wǎng)發(fā)展?fàn)顩r 3
1.3 停車泊位誘導(dǎo)系統(tǒng)發(fā)展現(xiàn)狀 4
1.3.1國外城市停車誘導(dǎo)系統(tǒng)發(fā)展現(xiàn)狀 4
1.3.2國內(nèi)城市停車誘導(dǎo)系統(tǒng)發(fā)展?fàn)顩r 5
1.4 研究目的及意義 6
第二章 基于物聯(lián)網(wǎng)技術(shù)的停車誘導(dǎo)系統(tǒng)研究 7
2.1 基于物聯(lián)網(wǎng)技術(shù)的城市停車誘導(dǎo)系統(tǒng)模型 7
2.1.1總體要求 7
2.1.2 設(shè)計(jì)原則 8
2.1.3 功能需求分析 8
2.1.4 系統(tǒng)架構(gòu) 8
2.1.5 系統(tǒng)功能描述 14
2.2 基于物聯(lián)網(wǎng)技術(shù)的城市停車誘導(dǎo)系統(tǒng)優(yōu)勢 19
2.2.1系統(tǒng)應(yīng)用價(jià)值 19
2.2.2 系統(tǒng)的特點(diǎn) 20
第三章 停車位預(yù)定模塊的算法 22
3.1最優(yōu)車位選擇算法提出的背景 22
3.2蟻群算法的基本原理 23
3.3 最優(yōu)停車位模型 26
3.4 物聯(lián)網(wǎng)環(huán)境..