【摘要】：旅行時(shí)間是智能交通系統(tǒng)的重要基礎(chǔ)性數(shù)據(jù)，交通流的動(dòng)態(tài)、隨機(jī)性及偶發(fā)事件等影響了車輛在高速公路網(wǎng)絡(luò)中的旅行時(shí)間，，而旅行時(shí)間的可靠性會(huì)影響到出行者對(duì)出發(fā)時(shí)間、路徑和出行方式的選擇，因此旅行時(shí)間可靠性研究日益受到重視。旅行時(shí)間可靠性研究必須有長(zhǎng)期的數(shù)據(jù)作為支撐，目前國(guó)外針對(duì)旅行時(shí)間的研究主要基于車輛檢測(cè)器數(shù)據(jù)，但是全面安裝檢測(cè)器需要增加大量的投資且數(shù)據(jù)穩(wěn)定性不高，很難收集到全面、完整的數(shù)據(jù)；我國(guó)的高速公路采用封閉式收費(fèi)管理方式，收費(fèi)管理系統(tǒng)記錄了豐富的信息，這為高速公路的旅行時(shí)間可靠性研究提供了可能。因此，基于收費(fèi)數(shù)據(jù)的高速公路旅行時(shí)間可靠性研究具有現(xiàn)實(shí)意義。然而，目前基于數(shù)據(jù)的研究還存在若干關(guān)鍵問(wèn)題有待解決，主要包括：收費(fèi)數(shù)據(jù)存在噪聲干擾；收費(fèi)數(shù)據(jù)只記錄出入口信息，無(wú)法全程跟蹤車輛的行駛過(guò)程。針對(duì)這些問(wèn)題，本文完成了以下工作：（1）針對(duì)異常數(shù)據(jù)干擾問(wèn)題，基于高速路限速和正態(tài)分布概率篩選性質(zhì)，提出了一種兩步數(shù)據(jù)預(yù)處理方法。在數(shù)據(jù)預(yù)處理的基礎(chǔ)上，在一個(gè)較長(zhǎng)時(shí)間跨度內(nèi)，分別對(duì)一周之中每一天不同時(shí)間區(qū)間出發(fā)車輛的平均旅行時(shí)間進(jìn)行分布擬合，證明其服從對(duì)數(shù)正態(tài)分布。（2）提出了一種依據(jù)軌跡法計(jì)算車輛時(shí)空坐標(biāo)軌跡，以路段長(zhǎng)度為權(quán)重進(jìn)行路段速度修正的路段旅行時(shí)間估計(jì)算法。該算法較直接使用收費(fèi)數(shù)據(jù)進(jìn)行路段旅行時(shí)間估計(jì)的精度提高了30%以上，直接提高了路段斷面流量估算的準(zhǔn)確性。（3）選定緩沖指數(shù)作為本文中旅行時(shí)間可靠性測(cè)度指標(biāo)。利用回歸分析的方法，以緩沖指數(shù)為因變量，重車比、V/C和路段長(zhǎng)度為自變量，建立不同車型的旅行時(shí)間可靠性經(jīng)驗(yàn)方程，并分析各個(gè)影響因素的影響程度。（4）基于本文研究成果，提出了基于收費(fèi)數(shù)據(jù)的路段斷面流量估算方法的應(yīng)用場(chǎng)景，并與其他幾種基于車輛檢測(cè)器的流量檢測(cè)方法進(jìn)行了全面比較，論證其在成本效益上較其他方法的優(yōu)勢(shì)。此外，介紹了旅行時(shí)間可靠性在先進(jìn)交通管理系統(tǒng)中的應(yīng)用。 此外，本文中以豐富的算例分析，驗(yàn)證了以上所提方法的可行性和準(zhǔn)確性，算例分析中獲得的眾多有益結(jié)論不僅充實(shí)了研究成果，更為研究成果投入實(shí)際應(yīng)用提供了思路和借鑒。研究成果的應(yīng)用將為提高高速公路服務(wù)水平、降低運(yùn)輸成本做出重要的貢獻(xiàn)。
[Abstract]:Travel time is an important basic data of intelligent transportation system. The dynamics of traffic flow, randomness and random events affect the travel time of vehicles in highway network, and the reliability of travel time will affect the departure time of travelers. Because of the choice of route and travel mode, more and more attention has been paid to the study of travel time reliability. The research of travel time reliability must be supported by long-term data. At present, the research of travel time abroad is mainly based on vehicle detector data, but the complete installation of detectors needs to increase a lot of investment and the data stability is not high. It is difficult to collect comprehensive and complete data; In our country, the closed toll management mode is adopted, and the toll management system records abundant information, which makes it possible to study the reliability of highway travel time. Therefore, the study of highway travel time reliability based on toll data has practical significance. However, at present, there are still some key problems to be solved in the data-based research, such as: there is noise interference in the charging data; the charging data only records the information of the entrance and exit, and can not track the driving process of the vehicle in the whole course. To solve these problems, this paper has completed the following work: (1) aiming at the abnormal data interference problem, a two-step data preprocessing method is proposed based on the property of high speed limit and normal distribution probability screening. On the basis of data pre-processing, the average travel time of vehicles starting from different time intervals of each day in a week is fitted in a long time span. It is proved that it obeys log-normal distribution. (2) A road travel time estimation algorithm based on trajectory method to calculate the vehicle space-time coordinate trajectory and to modify the road section speed based on the length of the road section is proposed. This algorithm improves the accuracy of road section travel time estimation by more than 30% compared with the direct use of toll data. (3) the buffer index is selected as the measure index of travel time reliability in this paper. Taking buffer index as dependent variable, heavy-to-vehicle ratio, V / C and length of road section as independent variables, the empirical equations of travel time reliability of different models are established by using regression analysis method. And analyze the influence degree of each influence factor. (4) based on the research results of this paper, put forward the application scenario of section flow estimation method based on toll data. Compared with other flow detection methods based on vehicle detector, the cost-effectiveness of this method is proved to be better than that of other methods. In addition, the application of travel time reliability in advanced traffic management system is introduced. In addition, the feasibility and accuracy of the above-mentioned method are verified by a wealth of examples in this paper, and many useful conclusions obtained in the case analysis not only enrich the research results, but also prove the feasibility and accuracy of the proposed method. More research results are put into practical application to provide ideas and reference. The application of the research results will make an important contribution to the improvement of highway service level and the reduction of transportation cost.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：U495

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