基于收费数据的高速公路旅行时间可靠性分析与应用
发布时间：2019-04-13 13:56
【摘要】：旅行时间是智能交通系统的重要基础性数据，交通流的动态、随机性及偶发事件等影响了车辆在高速公路网络中的旅行时间，，而旅行时间的可靠性会影响到出行者对出发时间、路径和出行方式的选择，因此旅行时间可靠性研究日益受到重视。旅行时间可靠性研究必须有长期的数据作为支撑，目前国外针对旅行时间的研究主要基于车辆检测器数据，但是全面安装检测器需要增加大量的投资且数据稳定性不高，很难收集到全面、完整的数据；我国的高速公路采用封闭式收费管理方式，收费管理系统记录了丰富的信息，这为高速公路的旅行时间可靠性研究提供了可能。因此，基于收费数据的高速公路旅行时间可靠性研究具有现实意义。然而，目前基于数据的研究还存在若干关键问题有待解决，主要包括：收费数据存在噪声干扰；收费数据只记录出入口信息，无法全程跟踪车辆的行驶过程。针对这些问题，本文完成了以下工作：（1）针对异常数据干扰问题，基于高速路限速和正态分布概率筛选性质，提出了一种两步数据预处理方法。在数据预处理的基础上，在一个较长时间跨度内，分别对一周之中每一天不同时间区间出发车辆的平均旅行时间进行分布拟合，证明其服从对数正态分布。（2）提出了一种依据轨迹法计算车辆时空坐标轨迹，以路段长度为权重进行路段速度修正的路段旅行时间估计算法。该算法较直接使用收费数据进行路段旅行时间估计的精度提高了30%以上，直接提高了路段断面流量估算的准确性。（3）选定缓冲指数作为本文中旅行时间可靠性测度指标。利用回归分析的方法，以缓冲指数为因变量，重车比、V/C和路段长度为自变量，建立不同车型的旅行时间可靠性经验方程，并分析各个影响因素的影响程度。（4）基于本文研究成果，提出了基于收费数据的路段断面流量估算方法的应用场景，并与其他几种基于车辆检测器的流量检测方法进行了全面比较，论证其在成本效益上较其他方法的优势。此外，介绍了旅行时间可靠性在先进交通管理系统中的应用。 此外，本文中以丰富的算例分析，验证了以上所提方法的可行性和准确性，算例分析中获得的众多有益结论不仅充实了研究成果，更为研究成果投入实际应用提供了思路和借鉴。研究成果的应用将为提高高速公路服务水平、降低运输成本做出重要的贡献。
[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.
【学位授予单位】：华南理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U495
本文编号：2457630
[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.
【学位授予单位】：华南理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U495
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