本文選題：車路協(xié)同　切入點(diǎn)：智能車　出處：《大連理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著全球城市的大力發(fā)展,土地資源越來越緊張,汽車保有量持續(xù)增加,城市交通擁堵問題日益突出,智能交通運(yùn)輸系統(tǒng)的相關(guān)研究越來越受到各國(guó)的重視。作為智能交通運(yùn)輸系統(tǒng)的重要組成部分,車路協(xié)同系統(tǒng)將車輛與道路通過計(jì)算機(jī)互聯(lián)網(wǎng)連接起來,旨在解決交通擁堵,提高道路利用率等問題。隨著現(xiàn)代計(jì)算機(jī)及互聯(lián)網(wǎng)科技的持續(xù)革新,智能無人駕駛車技術(shù)越來越成熟。本文研究的智能車輛調(diào)度系統(tǒng),旨在為車路協(xié)同系統(tǒng)與智能車兩者提供一種可行的合作方案,在未來車路協(xié)同大環(huán)境下,實(shí)現(xiàn)智能車的自動(dòng)無沖突安全行駛,減少交通擁堵,提高道路交通利用率。 本文研究了基于改進(jìn)Dijkstra算法的單元目標(biāo)最優(yōu)路徑規(guī)劃方法,為每個(gè)運(yùn)行目標(biāo)提供一條初始的最優(yōu)運(yùn)行路線,使得車輛的行駛路徑長(zhǎng)度最短。本改進(jìn)算法針對(duì)經(jīng)典Dijkstra算法在任務(wù)節(jié)點(diǎn)增加時(shí)時(shí)間復(fù)雜度增加、實(shí)時(shí)性降低這一問題,提出了一種動(dòng)態(tài)路徑規(guī)劃算法,它能動(dòng)態(tài)地添加需求的任務(wù)節(jié)點(diǎn),剔除冗余的任務(wù)節(jié)點(diǎn),從而保持路網(wǎng)總節(jié)點(diǎn)數(shù)不變,進(jìn)而降低了算法的時(shí)間復(fù)雜度。采用VC編寫了算法仿真軟件,對(duì)兩種算法進(jìn)行了比較,證明了改進(jìn)算法的高效性。 在單元目標(biāo)路徑規(guī)劃的基礎(chǔ)上,本文提出了基于全局離線規(guī)劃和局部在線相結(jié)合的綜合路徑?jīng)_突解決方案,當(dāng)多目標(biāo)初始運(yùn)行時(shí)采用全局規(guī)劃,為每個(gè)目標(biāo)提供一條初始的最優(yōu)運(yùn)行路線,在運(yùn)行過程中采用Petri網(wǎng)建立沖突模型進(jìn)行沖突車輛的局部規(guī)劃,并開發(fā)了相關(guān)的測(cè)試軟件驗(yàn)證了方案的可行性。最后,搭建和設(shè)計(jì)了硬件試驗(yàn)平臺(tái),采用STM32微處理器設(shè)計(jì)了路面基站模型,并采用相應(yīng)的無線收發(fā)模塊發(fā)送和接收來自模型智能車輛的數(shù)據(jù)信息并處理,證明了基于車路協(xié)同的智能車調(diào)度的可行性。為未來智能交通運(yùn)輸系統(tǒng)的發(fā)展提供了參考。
[Abstract]:With the rapid development of global cities, land resources are becoming more and more tight, the number of cars is increasing, and the problem of urban traffic congestion is becoming increasingly prominent. As an important part of intelligent transportation system, vehicle-road cooperative system connects vehicles and roads through the computer Internet to solve traffic congestion. With the continuous innovation of modern computer and Internet technology, the technology of intelligent driverless vehicle becomes more and more mature. The purpose of this paper is to provide a feasible cooperative scheme for the vehicle-road coordination system and intelligent vehicle. In the future environment of vehicle-road coordination, the intelligent vehicle can drive automatically and safely without conflict, reduce traffic congestion and improve the utilization ratio of road traffic. In this paper, we study the optimal path planning method based on improved Dijkstra algorithm, which provides an initial optimal path for each target. In order to solve the problem of increasing the time complexity and reducing the real-time performance of the classical Dijkstra algorithm, a dynamic path planning algorithm is proposed. It can dynamically add the required task nodes, eliminate redundant task nodes, so as to keep the total nodes of the road network unchanged, and then reduce the time complexity of the algorithm. The algorithm simulation software is programmed with VC, and the two algorithms are compared. The efficiency of the improved algorithm is proved. On the basis of cell objective path planning, a comprehensive path conflict solution based on the combination of global off-line planning and local online planning is proposed in this paper. When the multi-objective is in initial operation, the global planning is adopted. This paper provides an initial optimal running route for each target. In the course of operation, Petri net is used to build a conflict model for local planning of conflicting vehicles, and relevant test software is developed to verify the feasibility of the scheme. The hardware test platform is built and designed, and the road base station model is designed with STM32 microprocessor, and the corresponding wireless transceiver module is used to send and receive the data information from the model intelligent vehicle and process it. The feasibility of intelligent vehicle scheduling based on vehicle-road coordination is proved, which provides a reference for the development of intelligent transportation system in the future.
【學(xué)位授予單位】：大連理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U495

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 陳余慶;莊嚴(yán);王偉;;基于Petri網(wǎng)的多機(jī)器人協(xié)作任務(wù)分配與導(dǎo)航研究[J];大連理工大學(xué)學(xué)報(bào);2008年04期

2 卜登立;;VC++編程中Unicode編碼的使用研究[J];電腦學(xué)習(xí);2009年02期

3 張亮;;基于雙緩沖技術(shù)的VC++圖形刷新技術(shù)的原理和實(shí)現(xiàn)[J];福建電腦;2010年06期

4 芮新芳;朱朝霞;牛耀國(guó);;使用Altium Designer Winter 09設(shè)計(jì)印刷電路板之常見問題及使用技巧[J];電腦與電信;2011年09期

5 王建彬;馬芷薔;許金元;疏達(dá);;基于Petri網(wǎng)的多智能體制造系統(tǒng)建模[J];安徽工程大學(xué)學(xué)報(bào);2013年04期

6 龍毅,蔣成環(huán),張亮,周衛(wèi);電子地圖的基礎(chǔ)理論與框架體系[J];現(xiàn)代測(cè)繪;2005年03期

7 李洪波;王茂波;;Floyd最短路徑算法的動(dòng)態(tài)優(yōu)化[J];計(jì)算機(jī)工程與應(yīng)用;2006年34期

8 車忠志;孫雪雁;;MFC應(yīng)用程序基本框架分析[J];農(nóng)業(yè)網(wǎng)絡(luò)信息;2010年09期

9 饒萬成;;VC++訪問Excel的應(yīng)用技巧[J];計(jì)算機(jī)與現(xiàn)代化;2007年04期

10 王莉麗;李萍;;一種基于VC的靜態(tài)圖像特征整合方法[J];計(jì)算機(jī)與現(xiàn)代化;2010年01期

，

本文編號(hào)：1628393