客运专线网络承载能力及其可靠性研究
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摘要
摘要：随着我国市场经济的快速发展,人口城镇化进程的加速,人民生活水平的提高和对时间价值观念的增强,对缩短旅行时间、提高服务质量的愿望也日益强烈。客运专线以其独有速度快、运量大、舒适性好、占地面积小、能耗低、正点可靠、社会经济效益好等优势越来越受到关注,我国规划了“四纵四横”的客运专线路网来满足人们对客运服务质量日益增长的需求,随着客运专线路网的逐步建成,可以预见其必然会成为承担着我国客运的骨干网络。
客运专线网络承载能力是一种综合考虑了网络结构、交通需求和服务水平条件下路网最大容量的研究方法,它是基于交通服务水平的标准对于交通网络容量和交通网络资源的能力利用状况的计算和评价。这不仅在理论上是对客运专线网络能力研究的有益补充,在实际中,有利于交通网络资源的合理高效利用,有利于为旅客提供高质量的客运服务。主要工作和结论如下：(1)针对以往的研究较少考虑服务水平的缺点,提出了客运专线路网承载能力的概念,将网络服务水平、运输资源能力综合进行了考虑。回顾了国内外研究的现状,根据与客运专线承载能力相关的研究内容,主要介绍了铁路通过能力研究现状,交通网络输送能力研究现状和交通网络可靠性研究现状。介绍了道路交通网络承载能力的研究方法,主要介绍了备用能力模型和网络区域备用能力模型,并比较了这两个模型的优缺点,并决定了采用网络区域备用能力模型进行研究。(2)在考虑客运专线路网特点的基础上,对道路承载能力模型进行改进并建立了基于物理网络的承载能力优化模型,采用包含二阶段算法的启发式算法进行求解,并根据起讫点选择方式的不同产生了OD非对称和OD对称两种客流分配模式。算例表明,在OD非对称模式中服务水平最优时,路网备用能力系数为1.63。服务水平最差时,路网备用能力系数为2.1。OD对称模式在服务水平最优时,路网备用能力系数为1.22。服务水平最差时,路网备用能力系数为1.72。研究了参数的灵敏度,结果表明：随着吸引度的增加,最大的承载能力逐渐减少,分配到不同级别节点的客流差别逐渐增加,部分弧段的利用率逐渐增加。随着拥挤阻抗系数的增加,最大的承载能力出现先增大后减少的趋势,最终选择使路网承载能力最大的拥挤阻抗系数。
(3)在研究基于物理网络承载能力的基础上研究了基于开行方案优化的路网承载能力模型。首先给出了开行方案优化模型,通过基于按流开车和备用路径集的方法得出初始方案,采用模拟退火算法进行优化得出了优化的开行方案。在优化开行方案的基础上,建立了基于开行方案的客运专线网络承载能力模型,并采用包含二阶段算法的启发式算法进行求解。根据第4章产生的最大客流需求,产生了OD非对称和OD对称的开行方案,OD非对称开行方案共有127种高、中等级列车,OD对称开行方案共有68种高、中等级列车。算例表明,OD非对称模式下在服务水平较优时,路网备用能力系数为1.52。服务水平最差时,路网备用能力系数为2.42。OD对称模式下在服务水平较优时,路网备用能力系数为1.3。服务水平最差时,路网备用能力系数为1.95。
(4)针对路网状态随机变化的特性,采用包含承载能力模型的Monte-Carlo模拟仿真系统研究了路网承载能力的可靠性。可靠性的研究主要包括在服务弧段能力退化和需求结构波动情况下路网容量的可靠性,在服务弧段能力退化和需求结构波动情况下服务水平的可靠性。结果表明,在随机状态下随着备用能力系数μ的增加路网容量可靠性逐渐减少,随着服务水平系数ρ的增加路网的服务水平可靠性逐渐增加。
ABSTRACT:With the rapid development of market economy in our country, the acceleration of population urbanization process, the improvement of people's living standard, the enhance of time value conception, the desire to shorten travel time and to improve service quality is growing. Passenger dedicate line (PDL) receiving more and more attention because of its advantage of high speed, large volume, comfortable, small occupation, low energy consumption, reliability, good socio-economic benefits. In our country "four vertical and four horizontal" high-speed railway passenger transport network is planned to satisfy people's growing desire of service quality. With the building of PDL network, this will be the backbone network in passenger railway transport.
PDL network carrying capacity is a research method of the network capacity, which comprehensively considers the network structure, traffic demand and service level. It calculates and evaluates the transport network capacity and transport network resources capacity utilization based on traffic service level. It will not only be a useful addition to theory of PDL network capacity, but also make the use of traffic network resources reasonable and efficiency and provide high service quality to railway passengers. The main work and conclusion of the dissertation:
(1) According the shortcomings of previous studies lack condition service level, the concept of PDL network carrying capacity is proposed, which take into account network service level and transportation resource capacity. Previous studies are reviewed, and capacity of through train traffic, traffic network transport capacity, transportation network reliability is introduced based on relationship with PDL network carrying capacity. The research method of road earring capacity is introduced, reserve capacity model and network zones reserve capacity model are introduce, whose merits and demerits are compared to determine the latter model in our research.
(2) According to the characteristics of PDL network, carrying capacity model based on physical network is proposed with the improvement of the road carrying capacity model, a heuristic algorithm containing two-stage algorithm is designed to solve the problem. OD asymmetric mode and OD symmetric mode are proposed based on different choice of Origin-Destination. Example indicate:when the service level is optimal the network coefficient of reserve capacity is1.63, when the service level is worst the network coefficient of reserve capacity is2.1in OD asymmetric mode; when the service level is optimal the coefficient of network reserve capacity is1.22, when the service level is worst the coefficient of network reserve capacity is1.72in OD symmetric mode. Parameters sensitivity is researched, the result show that:with the point attraction increasing, the maximum multiplying factor decline, the difference of passenger volume between different rating point increase, some arc capacity use ratio increase; with the crowed parameters increasing, the maximum multiplying factor increases firstly and then decreases, the crowed parameters are selected which make the the maximum multiplying factor largest.
(3) Network carrying capacity model based on train plan is proposed after the research of carrying capacity based on physical network. The train plan optimize model is proposed, whose initial plan is obtained based on according to passenger volume and alternate route collection, optimize plan is obtained using simulated annealing algorithm. Network carrying capacity model based on train plan is proposed according to optimize train plan, a heuristic algorithm containing two-stage algorithm is designed to solve the problem. OD asymmetric train plan and OD symmetric train plan are generated according to the maximum passenger need in chapter4. OD asymmetric train plan has127different kinds of high and middle class trains. OD symmetric train plan has68different kinds of high and middle class trains. Example indicate:when the service level is better the network coefficient of reserve capacity is1.52, when the service level is worst the network coefficient of reserve capacity is2.42in OD asymmetric mode; when the service level is better the network coefficient of reserve capacity is1.3, when the service level is worst the network coefficient of reserve capacity is1.95in OD symmetric mode.
(4) According to features of network state random fluctuation, network carrying capacity reliability is researched based on the Monte-Carlo simulation system containing carrying capacity models. Reliability research contains:network capacity volume reliability with service arc capacity deterioration, passenger demand structure fluctuation; service level reliability with passenger demand structure fluctuation and arc capacity deterioration. The results show that:network capacity volume reliability decrease with coefficient of reserve capacity μincrease, network stability increase with coefficient of service level ρ increase.
客运专线网络承载能力是一种综合考虑了网络结构、交通需求和服务水平条件下路网最大容量的研究方法,它是基于交通服务水平的标准对于交通网络容量和交通网络资源的能力利用状况的计算和评价。这不仅在理论上是对客运专线网络能力研究的有益补充,在实际中,有利于交通网络资源的合理高效利用,有利于为旅客提供高质量的客运服务。主要工作和结论如下：(1)针对以往的研究较少考虑服务水平的缺点,提出了客运专线路网承载能力的概念,将网络服务水平、运输资源能力综合进行了考虑。回顾了国内外研究的现状,根据与客运专线承载能力相关的研究内容,主要介绍了铁路通过能力研究现状,交通网络输送能力研究现状和交通网络可靠性研究现状。介绍了道路交通网络承载能力的研究方法,主要介绍了备用能力模型和网络区域备用能力模型,并比较了这两个模型的优缺点,并决定了采用网络区域备用能力模型进行研究。(2)在考虑客运专线路网特点的基础上,对道路承载能力模型进行改进并建立了基于物理网络的承载能力优化模型,采用包含二阶段算法的启发式算法进行求解,并根据起讫点选择方式的不同产生了OD非对称和OD对称两种客流分配模式。算例表明,在OD非对称模式中服务水平最优时,路网备用能力系数为1.63。服务水平最差时,路网备用能力系数为2.1。OD对称模式在服务水平最优时,路网备用能力系数为1.22。服务水平最差时,路网备用能力系数为1.72。研究了参数的灵敏度,结果表明：随着吸引度的增加,最大的承载能力逐渐减少,分配到不同级别节点的客流差别逐渐增加,部分弧段的利用率逐渐增加。随着拥挤阻抗系数的增加,最大的承载能力出现先增大后减少的趋势,最终选择使路网承载能力最大的拥挤阻抗系数。
(3)在研究基于物理网络承载能力的基础上研究了基于开行方案优化的路网承载能力模型。首先给出了开行方案优化模型,通过基于按流开车和备用路径集的方法得出初始方案,采用模拟退火算法进行优化得出了优化的开行方案。在优化开行方案的基础上,建立了基于开行方案的客运专线网络承载能力模型,并采用包含二阶段算法的启发式算法进行求解。根据第4章产生的最大客流需求,产生了OD非对称和OD对称的开行方案,OD非对称开行方案共有127种高、中等级列车,OD对称开行方案共有68种高、中等级列车。算例表明,OD非对称模式下在服务水平较优时,路网备用能力系数为1.52。服务水平最差时,路网备用能力系数为2.42。OD对称模式下在服务水平较优时,路网备用能力系数为1.3。服务水平最差时,路网备用能力系数为1.95。
(4)针对路网状态随机变化的特性,采用包含承载能力模型的Monte-Carlo模拟仿真系统研究了路网承载能力的可靠性。可靠性的研究主要包括在服务弧段能力退化和需求结构波动情况下路网容量的可靠性,在服务弧段能力退化和需求结构波动情况下服务水平的可靠性。结果表明,在随机状态下随着备用能力系数μ的增加路网容量可靠性逐渐减少,随着服务水平系数ρ的增加路网的服务水平可靠性逐渐增加。
ABSTRACT:With the rapid development of market economy in our country, the acceleration of population urbanization process, the improvement of people's living standard, the enhance of time value conception, the desire to shorten travel time and to improve service quality is growing. Passenger dedicate line (PDL) receiving more and more attention because of its advantage of high speed, large volume, comfortable, small occupation, low energy consumption, reliability, good socio-economic benefits. In our country "four vertical and four horizontal" high-speed railway passenger transport network is planned to satisfy people's growing desire of service quality. With the building of PDL network, this will be the backbone network in passenger railway transport.
PDL network carrying capacity is a research method of the network capacity, which comprehensively considers the network structure, traffic demand and service level. It calculates and evaluates the transport network capacity and transport network resources capacity utilization based on traffic service level. It will not only be a useful addition to theory of PDL network capacity, but also make the use of traffic network resources reasonable and efficiency and provide high service quality to railway passengers. The main work and conclusion of the dissertation:
(1) According the shortcomings of previous studies lack condition service level, the concept of PDL network carrying capacity is proposed, which take into account network service level and transportation resource capacity. Previous studies are reviewed, and capacity of through train traffic, traffic network transport capacity, transportation network reliability is introduced based on relationship with PDL network carrying capacity. The research method of road earring capacity is introduced, reserve capacity model and network zones reserve capacity model are introduce, whose merits and demerits are compared to determine the latter model in our research.
(2) According to the characteristics of PDL network, carrying capacity model based on physical network is proposed with the improvement of the road carrying capacity model, a heuristic algorithm containing two-stage algorithm is designed to solve the problem. OD asymmetric mode and OD symmetric mode are proposed based on different choice of Origin-Destination. Example indicate:when the service level is optimal the network coefficient of reserve capacity is1.63, when the service level is worst the network coefficient of reserve capacity is2.1in OD asymmetric mode; when the service level is optimal the coefficient of network reserve capacity is1.22, when the service level is worst the coefficient of network reserve capacity is1.72in OD symmetric mode. Parameters sensitivity is researched, the result show that:with the point attraction increasing, the maximum multiplying factor decline, the difference of passenger volume between different rating point increase, some arc capacity use ratio increase; with the crowed parameters increasing, the maximum multiplying factor increases firstly and then decreases, the crowed parameters are selected which make the the maximum multiplying factor largest.
(3) Network carrying capacity model based on train plan is proposed after the research of carrying capacity based on physical network. The train plan optimize model is proposed, whose initial plan is obtained based on according to passenger volume and alternate route collection, optimize plan is obtained using simulated annealing algorithm. Network carrying capacity model based on train plan is proposed according to optimize train plan, a heuristic algorithm containing two-stage algorithm is designed to solve the problem. OD asymmetric train plan and OD symmetric train plan are generated according to the maximum passenger need in chapter4. OD asymmetric train plan has127different kinds of high and middle class trains. OD symmetric train plan has68different kinds of high and middle class trains. Example indicate:when the service level is better the network coefficient of reserve capacity is1.52, when the service level is worst the network coefficient of reserve capacity is2.42in OD asymmetric mode; when the service level is better the network coefficient of reserve capacity is1.3, when the service level is worst the network coefficient of reserve capacity is1.95in OD symmetric mode.
(4) According to features of network state random fluctuation, network carrying capacity reliability is researched based on the Monte-Carlo simulation system containing carrying capacity models. Reliability research contains:network capacity volume reliability with service arc capacity deterioration, passenger demand structure fluctuation; service level reliability with passenger demand structure fluctuation and arc capacity deterioration. The results show that:network capacity volume reliability decrease with coefficient of reserve capacity μincrease, network stability increase with coefficient of service level ρ increase.
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