城市轨道交通与接运公交换乘模型优化研究

发布时间：2018-09-08 09:38

【摘要】：目前，随着城市规模不断发展，城市人口的逐渐增加，城市交通问题日益凸显。大力发展公共交通已成为城市“缓堵保畅”，降低交通污染的重要途径。城市轨道交通作为城市公共交通的组成部分，具有快速、准时、运量大、无污染等优点，目前国内许多大中型城市都已建或在建，城市轨道交通在我国发展前景广阔；常规公交作为现状我国城市公共交通的主体部分，具有线路设置灵活、方便等优点。随着智能交通系统在我国不断的发展，在构建一体化城市公共交通的进程中有效结合这两种交通的技术经济优势，扬长避短，实现有效的接驳协调，是提高城市公共交通体系整体效率的重要举措。本文在网络运营条件下，以城市轨道交通与常规公交的特例——接运公交之间的换乘接驳为研究内容，着重对接运公交发车间隔进行了研究，通过使用概率论和数理统计的方法，，对该问题构建了相关模型，并对模型进行了启发式算法的建立。在模型构建之前，陈述了轨道交通与接运公交换乘接驳的理论方法，研究了乘客换乘走行时间的分布规律，为建模构建了数据和理论方面的支撑。文章首先对轨道交通与接运公交网络中的换乘理论进行了分析，并根据换乘类型，指出两种交通方式发车间隔较小情况下，一般不用进行发车间隔优化。然后对乘客换乘走行时间进行了抽样调查，从累积分布函数的角度，运用Weibull函数对换乘走行时间的分布进行了描述，并进行参数估计和参数检验。在此研究基础上，确定本文研究平峰时段内城市轨道交通与接运公交之间的运营协调。基于接运公交采用不等间隔发车的思想，以研究时段内最小乘客总换乘时间为优化目标，建立了相关的模型，并对模型求解的启发式算法进行设计。最后，把西安地铁2号线换乘接运公交162路作为算例，对模型进行了验证。经过本文的分析，发现Weibull分布对于乘客换乘走行时间的分布规律的描述性能较为优良；平峰时段对接运公交的发车间隔进行优化计算更有意义；接运公交在平峰时段采用不等间隔发车比较容易实现且优化效果明显。会展中心站的换乘在优化计算以后，平均每一个乘客在研究时段内换乘时间缩减了104.7秒，所有乘客的总换乘时间缩减了27365秒，折合7小时36分钟。因此，本文设计的乘客总换乘时间模型和遗传算法对两种交通方式之间的换乘接驳优化是有效的，具有一定的实用性。
[Abstract]:At present, with the continuous development of urban scale and the increasing of urban population, urban traffic problems become increasingly prominent. The development of public transportation has become an important way to reduce traffic pollution. As a part of urban public transportation, urban rail transit has the advantages of fast, punctual, large volume, no pollution and so on. At present, many large and medium-sized cities in China have been built or are under construction, and urban rail transit has a broad development prospect in China. As the main part of urban public transport in our country, bus routine has the advantages of flexible and convenient route setting. With the continuous development of intelligent transportation system in our country, in the process of constructing integrated urban public transportation, we can effectively combine the technical and economic advantages of these two kinds of traffic, exploit the advantages and avoid the disadvantages, and realize effective connection and coordination. It is an important measure to improve the overall efficiency of urban public transport system. In this paper, under the condition of network operation, taking the special case of urban rail transit and conventional public transport as the research content, the paper focuses on the study of the bus departure interval. By using the methods of probability theory and mathematical statistics, the related models are constructed and the heuristic algorithms are established. Before the model is constructed, the theory and method of rail transit and transit transfer connection are stated, the distribution of passenger transfer and departure time is studied, and the data and theoretical support are constructed for the modeling. In this paper, firstly, the transfer theory in rail transit and transit network is analyzed, and according to the type of transfer, it is pointed out that there is no need to optimize the departure interval in the case of small departure interval between the two modes of transportation. Then a sampling survey is carried out on the passenger transfer travel time. From the angle of cumulative distribution function, the distribution of transfer travel time is described by using Weibull function, and the parameter estimation and parameter test are carried out. On the basis of this study, this paper studies the operation coordination between urban rail transit and transit during peak time. Based on the idea of using unequal interval for bus delivery and taking the minimum passenger transfer time as the optimization objective, the relevant model is established and the heuristic algorithm for solving the model is designed. Finally, the model is verified by taking the transfer bus 162 of Xi'an Metro Line 2 as an example. Through the analysis of this paper, it is found that the Weibull distribution has a good performance in describing the distribution law of passenger transfer and departure time, and it is more meaningful to optimize the departure interval of docking public transportation in the flat peak time. It is easy to realize the bus transportation at different intervals and the effect of optimization is obvious. After optimization calculation, the average transfer time of each passenger was reduced by 104.7 seconds, and the total transfer time of all passengers was reduced by 27365 seconds, equivalent to 7 hours and 36 minutes. Therefore, the total passenger transfer time model and genetic algorithm designed in this paper are effective and practical for the optimization of the transfer connection between the two traffic modes.
【学位授予单位】：长安大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：U12

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