本文關鍵詞：基于熱點載客區(qū)域的出租車應急調(diào)度方案研究　出處：《北京交通大學》2014年碩士論文　論文類型：學位論文

  更多相關文章： 出租車應急調(diào)度 GPS數(shù)據(jù)采集 K-Means聚類模型 熱點載客區(qū)域 遺傳算法工具箱 調(diào)度點配置

【摘要】：隨著人們對城市交通管理規(guī)劃的日益重視,作為城市公共交通重要方式之一的出租車,其數(shù)量也在不斷地增長,由于目前我國絕大部分城市的出租車管理缺乏高效、科學的智能調(diào)度,出租車行業(yè)面臨了越來越多的問題：空駛率高、分布不均衡、供不應求等等,從而嚴重影響了出租車行業(yè)便捷、高效、舒適等優(yōu)勢特性,這就更加迫切地體現(xiàn)了出租車調(diào)度管理對交通出行質(zhì)量的重要性。通過本文對城市熱點載客區(qū)域內(nèi)出租車調(diào)度點的配置方案,來提高城市出租車管理系統(tǒng)的科學、有效、合理性,提升市民出行的便捷度及出租車公司的運營效益；降低城市出租車的空駛率及運營成本；減少城市道路交通負荷及因乘客滯留導致的公共安全危害。 本文通過出租車GPS數(shù)據(jù)的采集,分析了GPS數(shù)據(jù)誤差的影響因素,并利用MATLAB軟件對原始數(shù)據(jù)中的冗余數(shù)據(jù)及錯誤數(shù)據(jù)進行處理,提高了數(shù)據(jù)精度；通過建立K-Means聚類模型,將有效出租車GPS數(shù)據(jù)分類劃分為出租車熱點載客區(qū)域,在考慮實際交通狀態(tài)對最短路徑的影響后,選擇用路段的行駛時間作為拓撲圖的最短時間權重,從而得到基于最短時間的載客熱點區(qū)域路網(wǎng)結構拓撲圖；在出租車GPS數(shù)據(jù)及簡化的路網(wǎng)拓撲賦權圖基礎上,采用圖論原理提出熱點載客區(qū)域應急出租車調(diào)度點配置模型,并用遺傳算法求解。通過該模型的求解可以得出應急出租車調(diào)度點的最優(yōu)配置,最終確立城市出租車應急調(diào)度方案,并結合實例對該模型進行驗證,結果表明本方案能夠滿足在有限調(diào)度點配置的情況下,出租車以最短時間到達熱點載客區(qū)域內(nèi)的突發(fā)客流產(chǎn)生地點,實現(xiàn)熱點載客區(qū)域突發(fā)需求的優(yōu)化調(diào)度,減少整個出租車調(diào)度管理的響應時間,進一步實現(xiàn)科學而高效的乘客疏散。
[Abstract]:With the increasing attention to urban traffic management planning, as an important way of urban public transport, the number of taxis is also increasing. Due to the lack of efficient taxi management and scientific intelligent dispatching in most cities in China, taxi industry is faced with more and more problems: high empty driving rate, uneven distribution, shortage of supply and so on. As a result, the taxi industry has a serious impact on the convenience, efficiency, comfort and other advantages of the characteristics. This is more urgent to reflect the importance of taxi scheduling management to the quality of traffic. To improve the city taxi management system science, effectiveness, rationality, improve the convenience of the public travel and taxi company operating efficiency; Reduce the empty driving rate and operating cost of city taxi; Reduce urban road traffic load and public safety hazards caused by passenger retention. This paper analyzes the influencing factors of GPS data error through the collection of taxi GPS data, and uses MATLAB software to deal with the redundant data and error data in the original data. The data precision is improved; Through the establishment of K-Means clustering model, the effective taxi GPS data classification is divided into taxi hot passenger carrying areas, after considering the actual traffic status on the shortest path. The shortest time weight of the topology graph is the driving time of the section, and the structure topology of the hot spot region is obtained based on the shortest time. Based on the GPS data of taxis and the simplified network topology weighting graph, the paper proposes a configuration model of emergency taxi dispatching points in hot passenger region by using the graph theory principle. Through the solution of the model, the optimal allocation of emergency taxi dispatch points can be obtained, and finally the urban taxi emergency scheduling scheme is established, and the model is verified by an example. The results show that the scheme can meet the situation of limited scheduling point configuration, the taxi in the shortest time to the hot passenger region in the area of sudden passenger flow generation location, to achieve the hot passenger areas of emergency demand optimization scheduling. Reduce the response time of the whole taxi dispatch management, and further realize the scientific and efficient passenger evacuation.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：U492.434

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本文編號：1427289