基于换乘的城市轨道交通网络流量分配建模及其实证研究
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摘要
随着国内几所大城市轨道交通线网的逐步形成,客流网络化特征已经开始显现,乘客在轨道交通网络中的出行时空分布特征及出行路径选择行为均发生了较大变化。在网络化运营及“无缝换乘”条件下,乘客在不同线路之间换乘时不需再刷卡付费,导致路径流量和换乘流量的不确定性和难以统计性,也对城市轨道交通运营组织与管理提出更高层次的要求。因此,从理论上深入研究乘客在轨道交通网络中的路径选择规律和流量分配方法,有助于准确地掌握轨道交通网络客流特征和进一步提高城市轨道交通运营管理水平。
本论文的研究主要围绕城市轨道交通网络的客流分配问题而展开。本论文充分考虑了影响城市轨道交通网络客流分配的主要因素,以及城市轨道交通网络的特有属性,从理论上分析和研究城市轨道交通网络客流分布规律,提出了不同的城市轨道交通网络客流分配模型及算法,并采用北京市轨道交通网络的实际数据对模型和算法进行了测算和分析。具体而言,论文进行了如下研究工作：
(1)城市轨道交通网络流量分配是所有乘客进行路径选择的聚集结果,因此,掌握乘客的路径选择心理是建立配流模型的基础。为了充分掌握乘客的路径选择行为,同时,为了给后续研究提供可靠的数据支持和相关参数估计,针对北京市轨道交通网络,进行了乘客路径选择行为调查对调查数据进行了统计分析。结果表明：不同年龄、职业、收入、出行目的被调查者对路径选择存在明显差异,乘车时间对不同类别出行群体的影响最为显著,其次为换乘次数和车内拥挤程度；不同属性乘客对上述影响因素的关注程度呈现明显的差异性,因此,在对配流模型建模与标定时,应在考虑乘车时间、换乘时间和换乘次数的基础上，应充分考虑不同乘客类别的差异性。
(2)充分考虑了影响乘客在轨道交通网络中路径选择的主要因素,包括乘车时间、换乘时间和换乘次数,构造了路径广义效用模型,基于随机效用理论分析了乘客的路径选择问题,提出了考虑换乘次数的基于改进Logit的城市轨道交通网络流量分配模型和算法。以2008年北京市轨道交通网络的实际数据为例,对模型和算法其进行了测算,案例研究表明考虑基于换乘次数的路径费用构建的Logit模型计算结果与实际数据的平均相对误差为31.22%,比没有考虑换乘次数时降低了16.44%,计算结果更加贴近实际情况。
对基于换乘次数的路径广义费用模型中参数α和β灵敏度分析表明,参数α和β取值相对于配流计算结果的灵敏程度较高,说明城市轨道交通网络OD对之间有效路径的换乘次数越多,其选择概率也越低；随着网络规模的扩大,网络中的换乘节点增加,乘客对换乘费用的考虑将成为影响路径选择的主要因素。
(3)在基于换乘次数的流量分配模型的基础上,统计分析了乘客属性对路径选择偏好的影响,根据影响因素对乘客进行交叉分类,分别对不同类别乘客的路径广义费用模型进行了参数标定。在此基础上构建了基于乘客类别的城市轨道交通网络流量分配模型；针对模型中考虑乘客类型因素所导致的计算复杂程度提高,在基于改进Dial算法的基础上,设计了基于区间的随机网络流量分配算法。对典型城市轨道交通网络的研究结果表明：相对传统的集计模型,基于乘客类别的流量分配方法更加细致地反映出乘客构成对流量分配结果的影响,对乘客出行路径选择偏好的建模更加精确。
(4)考虑了乘客在城市轨道交通网络中选择路径时的车内拥挤费用,提出了描述车内拥挤程度的非线性路径广义费用,构建了基于Probit模型的随机用户平衡客流分配模型,并提出使用MSWA算法对的随机用户平衡模型进行了求解。在具体案例的基础上,分析了单个OD下可变费用校正参数对计算结果收敛精度的影响,结果表明,当(α,β=(1,2)时,其计算结果优于其他组参数,相对误差接近10-4,并且经过多次迭代之后收敛的稳定性好；分析了多个OD对并存时对乘客路径选择的影响和算法的收敛效果,结果表明随着加载OD对数量的增加,MSWA算法的收敛速度将会持续降低,相对误差也会变大。
(5)针对北京市轨道交通网络,利用本文所提出的城市轨道交通客流分布模型及算法,基于利用Fratar模型的推算站间OD矩阵的方法,设计并开发了城市轨道交通客流分析系统,系统可以自动实现各项客流统计指标的计算,并已在北京交通信息发布方面得到应用。
Along with the construction of urban railway network, passenger flow displays network characteristic. The time-space distribution and path choice behavior greatly changes. Under the network operation and seamless transfer, passengers need not to pay for transfer, which results in the uncertainty and difficulties in the statistics of passenger volume both on path and in transfer station. And this gives rise to great difficulties for urban railway operation and management. Therefore, theoretic research on urban railway path choice and passenger assignment does great help to capture the passenger network pattern and enhance the management level of urban railway operation.
The core of this dissertation is transit assignment of urban railway network. Major factors impacting the transit are taken into account and the urban railway flow distribution pattern is analyzed. On base of these, some mathematical models are presented for urban railway traffic network flow assignment problem. The application of these models and algorithms are illustrated with Beijing urban railway traffic network. The contents of this paper are summarized as follows:
(1) In practice, the flow assignment pattern through urban rail transport network is resulted with the aggregation of all passengers' combined choices. Therefore, understanding and mastering the passenger's choice psychology is the foundation of modeling the passenger's route choice and flow assignment through whole network. In order to fully grasp the characteristics of the passenger route choice behavior, meanwhile, in order to provide reliable data for future research support and related parameter estimation, this paper designed a questionnaire of passengers' choice behavior and gives fully data statistical analysis of Beijing urban railway. The result proves that age, gender, income level, occupation and trip purpose have great influence on path choice. Travel time is the most significant factor while time of transfer and crowdedness follows. Passengers with different attribute have different response to these factors so that the presented model gives fully consideration to this besides the time in cars, transfer time and numbers needed of transfer.
(2) The major factors (including travel time and transfer) that influence passenger flow pattern in URTS are taken into account. The general cost function for generalized urban rail transit network is presented and corresponding route choice behavior of passengers is analyzed. On base of these, an improved logit-based model is then presented for URTS flow assignment problem which is tested by Beijing urban railway data in2008. The relative error of this transfer-considered model is31.22%, which is16.44%lower than the no-transfer model.
And sensitivity study of general cost model shows the result is very high sensitive which means that the more number of transfer needed, the lower chance the path be selected. This is partially because that the enlargement of urban railway network and increase of transfer station make number of transfer a critical factor for passenger's path choice.
(3) According to survey data, the passengers with different socio-economic attributes will have different standards and preferences of traffic choices. This paper considers the different choice behaviors between different passengers fully and establishes the generalized travel cost functions for different types of passengers. Then the urban railway flow assignment model is built considering the passenger classification. And improved Dial algorithm based on random network assignment is proposed to solve the model rapidly. And the result indicates that the assignment model based on passenger classification can demonstrate the influence of passenger attributes on assignment result and is more precisely on passenger's preference on path choice.
(4) This paper gives full consideration of the crowdedness factor in the passenger's route choice and proposes crowdedness-based generalized travel cost function and Probit based assignment model which is solved by MSWA algorithm. And a case study is done based on this model. With one pair of OD, the effect of parameter on result precision is analyzed which shows that (α,β)=(1,2) gives the best result and reliability and lowest relative error. With multipaire of OD, the effect of parameter on result precision is analyzed and the analysis proves that MSWA algorithm gives lower speed and larger relative error with more OD pair.
(5) Based on the proposed model and Fratar model based OD, the design and development of network passenger flow analysis software for Beijing URTS are introduced in this paper, which can calculate statistical index of railway flow automatically.
本论文的研究主要围绕城市轨道交通网络的客流分配问题而展开。本论文充分考虑了影响城市轨道交通网络客流分配的主要因素,以及城市轨道交通网络的特有属性,从理论上分析和研究城市轨道交通网络客流分布规律,提出了不同的城市轨道交通网络客流分配模型及算法,并采用北京市轨道交通网络的实际数据对模型和算法进行了测算和分析。具体而言,论文进行了如下研究工作：
(1)城市轨道交通网络流量分配是所有乘客进行路径选择的聚集结果,因此,掌握乘客的路径选择心理是建立配流模型的基础。为了充分掌握乘客的路径选择行为,同时,为了给后续研究提供可靠的数据支持和相关参数估计,针对北京市轨道交通网络,进行了乘客路径选择行为调查对调查数据进行了统计分析。结果表明：不同年龄、职业、收入、出行目的被调查者对路径选择存在明显差异,乘车时间对不同类别出行群体的影响最为显著,其次为换乘次数和车内拥挤程度；不同属性乘客对上述影响因素的关注程度呈现明显的差异性,因此,在对配流模型建模与标定时,应在考虑乘车时间、换乘时间和换乘次数的基础上，应充分考虑不同乘客类别的差异性。
(2)充分考虑了影响乘客在轨道交通网络中路径选择的主要因素,包括乘车时间、换乘时间和换乘次数,构造了路径广义效用模型,基于随机效用理论分析了乘客的路径选择问题,提出了考虑换乘次数的基于改进Logit的城市轨道交通网络流量分配模型和算法。以2008年北京市轨道交通网络的实际数据为例,对模型和算法其进行了测算,案例研究表明考虑基于换乘次数的路径费用构建的Logit模型计算结果与实际数据的平均相对误差为31.22%,比没有考虑换乘次数时降低了16.44%,计算结果更加贴近实际情况。
对基于换乘次数的路径广义费用模型中参数α和β灵敏度分析表明,参数α和β取值相对于配流计算结果的灵敏程度较高,说明城市轨道交通网络OD对之间有效路径的换乘次数越多,其选择概率也越低；随着网络规模的扩大,网络中的换乘节点增加,乘客对换乘费用的考虑将成为影响路径选择的主要因素。
(3)在基于换乘次数的流量分配模型的基础上,统计分析了乘客属性对路径选择偏好的影响,根据影响因素对乘客进行交叉分类,分别对不同类别乘客的路径广义费用模型进行了参数标定。在此基础上构建了基于乘客类别的城市轨道交通网络流量分配模型；针对模型中考虑乘客类型因素所导致的计算复杂程度提高,在基于改进Dial算法的基础上,设计了基于区间的随机网络流量分配算法。对典型城市轨道交通网络的研究结果表明：相对传统的集计模型,基于乘客类别的流量分配方法更加细致地反映出乘客构成对流量分配结果的影响,对乘客出行路径选择偏好的建模更加精确。
(4)考虑了乘客在城市轨道交通网络中选择路径时的车内拥挤费用,提出了描述车内拥挤程度的非线性路径广义费用,构建了基于Probit模型的随机用户平衡客流分配模型,并提出使用MSWA算法对的随机用户平衡模型进行了求解。在具体案例的基础上,分析了单个OD下可变费用校正参数对计算结果收敛精度的影响,结果表明,当(α,β=(1,2)时,其计算结果优于其他组参数,相对误差接近10-4,并且经过多次迭代之后收敛的稳定性好；分析了多个OD对并存时对乘客路径选择的影响和算法的收敛效果,结果表明随着加载OD对数量的增加,MSWA算法的收敛速度将会持续降低,相对误差也会变大。
(5)针对北京市轨道交通网络,利用本文所提出的城市轨道交通客流分布模型及算法,基于利用Fratar模型的推算站间OD矩阵的方法,设计并开发了城市轨道交通客流分析系统,系统可以自动实现各项客流统计指标的计算,并已在北京交通信息发布方面得到应用。
Along with the construction of urban railway network, passenger flow displays network characteristic. The time-space distribution and path choice behavior greatly changes. Under the network operation and seamless transfer, passengers need not to pay for transfer, which results in the uncertainty and difficulties in the statistics of passenger volume both on path and in transfer station. And this gives rise to great difficulties for urban railway operation and management. Therefore, theoretic research on urban railway path choice and passenger assignment does great help to capture the passenger network pattern and enhance the management level of urban railway operation.
The core of this dissertation is transit assignment of urban railway network. Major factors impacting the transit are taken into account and the urban railway flow distribution pattern is analyzed. On base of these, some mathematical models are presented for urban railway traffic network flow assignment problem. The application of these models and algorithms are illustrated with Beijing urban railway traffic network. The contents of this paper are summarized as follows:
(1) In practice, the flow assignment pattern through urban rail transport network is resulted with the aggregation of all passengers' combined choices. Therefore, understanding and mastering the passenger's choice psychology is the foundation of modeling the passenger's route choice and flow assignment through whole network. In order to fully grasp the characteristics of the passenger route choice behavior, meanwhile, in order to provide reliable data for future research support and related parameter estimation, this paper designed a questionnaire of passengers' choice behavior and gives fully data statistical analysis of Beijing urban railway. The result proves that age, gender, income level, occupation and trip purpose have great influence on path choice. Travel time is the most significant factor while time of transfer and crowdedness follows. Passengers with different attribute have different response to these factors so that the presented model gives fully consideration to this besides the time in cars, transfer time and numbers needed of transfer.
(2) The major factors (including travel time and transfer) that influence passenger flow pattern in URTS are taken into account. The general cost function for generalized urban rail transit network is presented and corresponding route choice behavior of passengers is analyzed. On base of these, an improved logit-based model is then presented for URTS flow assignment problem which is tested by Beijing urban railway data in2008. The relative error of this transfer-considered model is31.22%, which is16.44%lower than the no-transfer model.
And sensitivity study of general cost model shows the result is very high sensitive which means that the more number of transfer needed, the lower chance the path be selected. This is partially because that the enlargement of urban railway network and increase of transfer station make number of transfer a critical factor for passenger's path choice.
(3) According to survey data, the passengers with different socio-economic attributes will have different standards and preferences of traffic choices. This paper considers the different choice behaviors between different passengers fully and establishes the generalized travel cost functions for different types of passengers. Then the urban railway flow assignment model is built considering the passenger classification. And improved Dial algorithm based on random network assignment is proposed to solve the model rapidly. And the result indicates that the assignment model based on passenger classification can demonstrate the influence of passenger attributes on assignment result and is more precisely on passenger's preference on path choice.
(4) This paper gives full consideration of the crowdedness factor in the passenger's route choice and proposes crowdedness-based generalized travel cost function and Probit based assignment model which is solved by MSWA algorithm. And a case study is done based on this model. With one pair of OD, the effect of parameter on result precision is analyzed which shows that (α,β)=(1,2) gives the best result and reliability and lowest relative error. With multipaire of OD, the effect of parameter on result precision is analyzed and the analysis proves that MSWA algorithm gives lower speed and larger relative error with more OD pair.
(5) Based on the proposed model and Fratar model based OD, the design and development of network passenger flow analysis software for Beijing URTS are introduced in this paper, which can calculate statistical index of railway flow automatically.
引文
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