城市公交客流量智能識別系統(tǒng)的研究
發(fā)布時間：2018-10-14 19:10
【摘要】：改革開放以來,我國的國民經濟發(fā)生了翻天覆地的變化,尤其是在城市建設方面,城市交通成為影響大中城市發(fā)展的關鍵因素。如今,隨著城市汽車的擁有量日益增多,城市汽車化速度迅速發(fā)展,導致城市中出現(xiàn)了許多阻礙城市發(fā)展的問題,諸如交通擁堵、能源匱乏、環(huán)境污染愈演愈烈以及交通事故頻繁發(fā)生等。如何提高城市交通資源的利用率成為解決上述城市交通問題的關鍵。鑒于城市公共交通與小汽車相比具有客運量大、投資相對少、資源占用率小、運營效率高、污染較少、人均占道少等優(yōu)勢,加大城市公共交通發(fā)展力度,達到城市交通管理的數字化和智能化的目標,并提高公共交通運營管理效率及社會服務水平成為改善城市交通的必經之路。本文旨在基于多傳感器陣列踏板獲取公交乘客的客流量數據,分析了公交車乘客上下車腳型變化規(guī)律,獲取了傳感器采集數據的特征,提出了基于腳型輪廓的客流數據判斷準則,通過人體運動學原理進行上下車方向識別,并采用BP神經網絡算法對原始數據進行預處理和智能識別,計算公交乘客上下車數量。文章對系統(tǒng)的硬件設計和識別軟件算法的實現(xiàn)方法作了詳盡闡述。最后對算法作了系統(tǒng)測試,準確率達到93%,具有很強的可靠性。
[Abstract]:Since the reform and opening up, the national economy of our country has undergone earth-shaking changes, especially in the aspect of urban construction, urban traffic has become a key factor affecting the development of large and medium-sized cities. Nowadays, with the increasing number of cars in cities and the rapid development of urban motorization, there are many problems that hinder the development of cities, such as traffic congestion and lack of energy. Environmental pollution is becoming more and more serious and traffic accidents occur frequently. How to improve the utilization rate of urban traffic resources becomes the key to solve the above urban traffic problems. In view of the fact that urban public transport has the advantages of large passenger traffic, relatively low investment, low utilization of resources, high operational efficiency, less pollution, less per capita traffic, and so on, the development of urban public transport should be strengthened. To achieve the goal of digitalization and intelligence of urban traffic management, and to improve the efficiency of public transportation management and the level of social service become the only way to improve urban traffic. The purpose of this paper is to obtain the passenger flow data of bus passengers based on multi-sensor array pedal, analyze the changing law of bus passengers' getting on and off feet, and obtain the characteristics of the data collected by the sensors. This paper presents a criterion for judging passenger flow data based on the profile of foot, and uses the principle of human kinematics to recognize the direction of boarding and disembarking, and uses BP neural network algorithm to preprocess and intelligently recognize the original data, and calculates the number of passengers on and off bus. In this paper, the hardware design of the system and the realization of recognition software algorithm are described in detail. Finally, the algorithm is tested systematically, and the accuracy is 93%, which has strong reliability.
【學位授予單位】：中國民航大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：U491.17;TP391.4;TP183
本文編號：2271373
[Abstract]:Since the reform and opening up, the national economy of our country has undergone earth-shaking changes, especially in the aspect of urban construction, urban traffic has become a key factor affecting the development of large and medium-sized cities. Nowadays, with the increasing number of cars in cities and the rapid development of urban motorization, there are many problems that hinder the development of cities, such as traffic congestion and lack of energy. Environmental pollution is becoming more and more serious and traffic accidents occur frequently. How to improve the utilization rate of urban traffic resources becomes the key to solve the above urban traffic problems. In view of the fact that urban public transport has the advantages of large passenger traffic, relatively low investment, low utilization of resources, high operational efficiency, less pollution, less per capita traffic, and so on, the development of urban public transport should be strengthened. To achieve the goal of digitalization and intelligence of urban traffic management, and to improve the efficiency of public transportation management and the level of social service become the only way to improve urban traffic. The purpose of this paper is to obtain the passenger flow data of bus passengers based on multi-sensor array pedal, analyze the changing law of bus passengers' getting on and off feet, and obtain the characteristics of the data collected by the sensors. This paper presents a criterion for judging passenger flow data based on the profile of foot, and uses the principle of human kinematics to recognize the direction of boarding and disembarking, and uses BP neural network algorithm to preprocess and intelligently recognize the original data, and calculates the number of passengers on and off bus. In this paper, the hardware design of the system and the realization of recognition software algorithm are described in detail. Finally, the algorithm is tested systematically, and the accuracy is 93%, which has strong reliability.
【學位授予單位】：中國民航大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：U491.17;TP391.4;TP183
【參考文獻】
相關期刊論文 前10條
1 武根友;李江;李曉輝;;基于物聯(lián)網的智能公交系統(tǒng)研究[J];河北省科學院學報;2011年03期
2 白子建;段緒斌;;智能公交系統(tǒng)設計方案分析研究[J];城市道橋與防洪;2011年08期
3 張娟;毛曉波;陳鐵軍;;運動目標跟蹤算法研究綜述[J];計算機應用研究;2009年12期
4 孫紅麗;;構建BP網絡結構方法及其在預測上應用[J];河南科學;2009年07期
5 鄭建湖;王明華;;動態(tài)交通信息采集技術比較分析[J];交通標準化;2009年07期
6 常新峰;沈連豐;胡靜;夏瑋瑋;;一種智能公交車載系統(tǒng)的研制及性能分析[J];東南大學學報(自然科學版);2009年02期
7 歐陽磊;黃友銳;黃宜慶;;基于模糊RBF神經網絡的PID及其應用[J];計算機工程;2008年22期
8 于洋;周學偉;楊青;趙亞威;;基于模糊神經網絡的鍋爐系統(tǒng)故障診斷研究[J];工業(yè)儀表與自動化裝置;2008年02期
9 杜友田;陳峰;徐文立;李永彬;;基于視覺的人的運動識別綜述[J];電子學報;2007年01期
10 王圣男,郁梅,蔣剛毅;智能交通系統(tǒng)中基于視頻圖像處理的車輛檢測與跟蹤方法綜述[J];計算機應用研究;2005年09期
相關碩士學位論文 前1條
1 邵媛媛;智能公交系統(tǒng)中車載終端的研究與開發(fā)[D];大連理工大學;2007年
，本文編號：2271373
本文鏈接：http://www.wukwdryxk.cn/kejilunwen/jiaotonggongchenglunwen/2271373.html
