本文選題：動(dòng)態(tài)交通誘導(dǎo) + 浮動(dòng)車數(shù)據(jù)　； 參考：《長(zhǎng)安大學(xué)》2014年碩士論文

【摘要】：動(dòng)態(tài)交通誘導(dǎo)系統(tǒng)對(duì)提高車輛出行效率、增加道路使用效率、緩解交通擁堵具有十分重要的意義。傳統(tǒng)的交通誘導(dǎo)系統(tǒng)多基于靜態(tài)交通信息構(gòu)建，沒(méi)有結(jié)合實(shí)時(shí)動(dòng)態(tài)交通信息、實(shí)用性不高。針對(duì)該問(wèn)題，論文開發(fā)了一種基于浮動(dòng)車數(shù)據(jù)的動(dòng)態(tài)交通誘導(dǎo)系統(tǒng)，對(duì)系統(tǒng)中動(dòng)態(tài)路網(wǎng)自動(dòng)生成、動(dòng)態(tài)道路阻值估算、動(dòng)態(tài)交通誘導(dǎo)等多個(gè)關(guān)鍵技術(shù)進(jìn)行了研究。論文主要工作如下： 1．提出了一種基于關(guān)系型數(shù)據(jù)的動(dòng)態(tài)路網(wǎng)自動(dòng)生成算法。該算法針對(duì)基于GIS（Geographic Information System）空間實(shí)體數(shù)據(jù)進(jìn)行誘導(dǎo)存在的搜索冗余度大、效率低等問(wèn)題，，對(duì)GIS數(shù)據(jù)進(jìn)行重新分析，剔除冗余數(shù)據(jù)，并將結(jié)果存儲(chǔ)在關(guān)系型數(shù)據(jù)庫(kù)中，根據(jù)用戶輸入的起訖點(diǎn)動(dòng)態(tài)構(gòu)造搜索空間，提高了路網(wǎng)生成效率。 2．研究了浮動(dòng)車數(shù)據(jù)預(yù)處理算法。針對(duì)原始浮動(dòng)車數(shù)據(jù)存在誤差、屬性信息不足等問(wèn)題，設(shè)計(jì)了數(shù)據(jù)清洗規(guī)則，對(duì)錯(cuò)誤數(shù)據(jù)進(jìn)行過(guò)濾，同時(shí)采用ST地圖匹配算法對(duì)有誤差的浮動(dòng)車數(shù)據(jù)進(jìn)行修正。 3．建立了一種基于交叉口延誤與空間拓?fù)潢P(guān)系的道路阻值估算模型。動(dòng)態(tài)道路阻值估算是交通誘導(dǎo)系統(tǒng)的核心，該模型通過(guò)浮動(dòng)車數(shù)據(jù)預(yù)估交叉口延誤時(shí)間，同時(shí)融合道路拓?fù)潢P(guān)系信息，實(shí)現(xiàn)了道路阻值的實(shí)時(shí)估算。 4．提出了一種基于改進(jìn)蟻群算法的交通誘導(dǎo)算法，該算法針對(duì)傳統(tǒng)蟻群算法在大規(guī)模路網(wǎng)中效率低的問(wèn)題提出了三條改進(jìn)規(guī)則，克服了傳統(tǒng)蟻群算法在大規(guī)模路網(wǎng)下效率較低的不足，同時(shí)更能適應(yīng)浮動(dòng)車數(shù)據(jù)離散但又相互關(guān)聯(lián)的特性。 論文對(duì)上述算法進(jìn)行了系統(tǒng)集成，并基于西安市6000多輛出租車60天運(yùn)營(yíng)數(shù)據(jù)對(duì)系統(tǒng)進(jìn)行了測(cè)試，測(cè)試結(jié)果表明：系統(tǒng)運(yùn)行穩(wěn)定、實(shí)用性強(qiáng)，浮動(dòng)車數(shù)據(jù)匹配準(zhǔn)確率高達(dá)93%，系統(tǒng)生成的動(dòng)態(tài)誘導(dǎo)路徑比基于靜態(tài)信息生成的路徑平均節(jié)省20%出行時(shí)間，提高了出行效率。
[Abstract]:Dynamic traffic guidance system plays an important role in improving vehicle travel efficiency, increasing road use efficiency and alleviating traffic congestion. The traditional traffic guidance system is based on static traffic information and has no real-time dynamic traffic information. To solve this problem, a dynamic traffic guidance system based on floating vehicle data is developed in this paper. Several key technologies, such as automatic generation of dynamic road network, dynamic road resistance estimation, dynamic traffic guidance and so on, are studied. The main work of the thesis is as follows: 1. A dynamic road network automatic generation algorithm based on relational data is proposed. In order to solve the problems of large redundancy and low efficiency in search induced by spatial entity data based on GIS(Geographic Information system, the algorithm reanalyzes GIS data, removes redundant data, and stores the results in relational database. The search space is constructed dynamically according to the starting point of user input, and the efficiency of road network generation is improved. 2. The data preprocessing algorithm of floating vehicle is studied. Aiming at the problems of errors in original floating vehicle data and insufficient attribute information, the data cleaning rules are designed, the error data is filtered, and the St map matching algorithm is used to correct the error floating vehicle data. 3. A road resistance estimation model based on the relationship between intersection delay and spatial topology is established. Dynamic road resistance estimation is the core of traffic guidance system. The model estimates the delay time of intersection by floating vehicle data and integrates the road topology information to realize the real-time estimation of road resistance value. 4. A traffic guidance algorithm based on improved ant colony algorithm is proposed. The algorithm proposes three improved rules to solve the problem of low efficiency of traditional ant colony algorithm in large-scale road network. It overcomes the shortcoming of the traditional ant colony algorithm which is low efficiency under the large-scale road network and adapts to the discrete but interrelated characteristics of floating vehicle data at the same time. The system is integrated and tested based on the 60 days operation data of more than 6000 taxis in Xi'an. The test results show that the system is stable and practical. The accuracy rate of floating vehicle data matching is as high as 93%. The dynamic induced path generated by the system saves an average of 20% travel time and improves the travel efficiency compared with the path generated based on static information.
【學(xué)位授予單位】：長(zhǎng)安大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U495

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本文編號(hào)：1991496