The high peak hour demand in Urban Rail Transport (URT) is usually met by supply side measures such as pushing more number of trains/cars in peak hour by the operator. This additional capacity generates more demand du...The high peak hour demand in Urban Rail Transport (URT) is usually met by supply side measures such as pushing more number of trains/cars in peak hour by the operator. This additional capacity generates more demand due to a positive elasticity of demand with respect to services. Delhi Metro Rail Corporation (DMRC), India has converted its fleet from 4 cars per train to 6 cars per train and finally to 8 cars per train on its Broad Gauge section. The ridership of the system has also witnessed double digit growth during this conversion period. The demand elasticity w.r.t services for the passengers of DMRC has been estimated as 0.512 on the basis of growth of demand and increase in capacity after adjusting for natural growth. So a 10% increase in supply results into 5% increase in capacity. A simple service elasticity model has been developed to estimate demand with increase in supply. The model has been applied to Line 2 (yellow line), the busiest line of DMRC, to estimate the demand for different level of services (trains/hour). The efficacy of supply side measures is limited by the design capacity of the system beyond which any increase in supply would require disproportionate investment. An optimum combination of supply and demand side measures would perhaps be the best way to address peak hour congestion in Urban Rail Transport.展开更多
Urban rail transit loops are essential in urban rail transit systems and transportation networks.However,precise requirements and reference standards for rail transit loop design have yet to be established.There are c...Urban rail transit loops are essential in urban rail transit systems and transportation networks.However,precise requirements and reference standards for rail transit loop design have yet to be established.There are certain areas for improvement in planning,construction,and operation.In the planning and design of urban rail transit loops,the scale of the city and the relationship between line operations should be considered to ensure that the line conforms to the city’s operating traffic conditions and can effectively cater to peak passenger flow requirements.This article presents strategies for planning,constructing,and operating urban rail transit loops,laying the foundation for the healthy operation of urban rail transit.展开更多
The discrete choice model is used to estimate the walking access area of rail transit stations while considering the influence of existing competition from other traffic modes. The acceptable walking access area is de...The discrete choice model is used to estimate the walking access area of rail transit stations while considering the influence of existing competition from other traffic modes. The acceptable walking access area is determined according to the willingness of passengers to walk who prefer rail transit compared with bus and automobile. Empirical studies were conducted using the survey data of six stations from the rail transit in Nanjing, China. The results indicate that the rail transit is more preferable compared with bus and private automobile in this case when excluding the influence of individual and environmental factors. It is found that passengers tend to underestimate their willingness to walk. The acceptable walking access area of every rail transit station is different from each other. Suburban stations generally have a larger walking access area than downtown stations. In addition, a better walking environment and a scarcer surrounding traffic environment can also lead to a larger walking area. The model was confirmed to be effective and reasonable according to the model validation. This study can be of benefit to the passenger transportation demand estimation in the location planning and evaluation of rail transit stations.展开更多
With the increase of Beijing urban rail transport network, the structure of the road network is becoming more complex, and passengers have more travel options. Together with the complex paths and different timetables,...With the increase of Beijing urban rail transport network, the structure of the road network is becoming more complex, and passengers have more travel options. Together with the complex paths and different timetables, taking the last train is becoming much more difficult and unsuccessful. To avoid losses, we propose feasible suggestions to the last train with reasonable selling tickets system.展开更多
[目的]通过总结上海城市轨道交通既有线运能提升改造项目的实施经验,为其提出有效的运能提升方法及具体案例。[方法]深入分析上海轨道交通既有线运能不足的主要原因及其影响因素;基于这些分析,提出运能提升的技术路线及5大核心策略;详...[目的]通过总结上海城市轨道交通既有线运能提升改造项目的实施经验,为其提出有效的运能提升方法及具体案例。[方法]深入分析上海轨道交通既有线运能不足的主要原因及其影响因素;基于这些分析,提出运能提升的技术路线及5大核心策略;详细介绍了上海轨道交通9号线实现1 min 50 s最小行车间隔、3号线与4号线增能改造、5号线从4节编组扩编至6节编组、6号线增能改造及增设复线等成功案例。[结果及结论]影响线路运能的主要因素包括车辆基地规模、区间通过能力、出入场能力,以及供电能力等。针对这些因素,确定了运能提升的技术路线,即从客流预测及客流特征分析入手,进行设施设备能力评估,设计行车交路方案,最终形成科学的改造方案。同时,提出了5大策略:运营管理优化、既有系统能力挖潜及改造、信号系统升级或土建局部改造、系统规模性改造及线网整体优化。展开更多
城市轨道交通起讫点(origin-destination,OD)客流短时预测在智能交通系统中意义重大,它为交通管控策略实施以及出行者出行选择提供了重要的决策依据。卷积神经网络被广泛用于交通数据空间相关性提取,但其平移不变性与局部敏感性导致该...城市轨道交通起讫点(origin-destination,OD)客流短时预测在智能交通系统中意义重大,它为交通管控策略实施以及出行者出行选择提供了重要的决策依据。卷积神经网络被广泛用于交通数据空间相关性提取,但其平移不变性与局部敏感性导致该方法更重视局部特征而忽视全局特征。本研究构建了基于注意力机制的异构数据特征提取机模型(heterogeneous data feature extraction machine,HDFEM)以实现OD矩阵空间相关性的全局感知。该模型从时空特征和用地属性特征出发,构造异构数据OD时空张量与地理信息张量,依托模型张量编码层对异构数据张量进行分割与编码,通过注意力机制连接各张量块特征,提取OD矩阵中各个部分间的空间相关性。该方法不仅实现了异构数据与OD客流数据的融合,还兼顾了卷积神经网络模型未能处理的OD矩阵远距离特征,进而帮助模型更全面地学习OD客流的空间特征。对于OD时序特性,该模型使用了长短时记忆网络来处理。在杭州地铁自动售检票系统(auto fare collection,AFC)数据集上的实验结果表明:HDFEM模型相对于基于卷积神经网络的预测模型,其均方误差、平均绝对误差与标准均方根误差分别下降了4.1%,2.5%,2%,验证了全局OD特征感知对于城市轨道交通OD客流预测的重要性。展开更多
文摘The high peak hour demand in Urban Rail Transport (URT) is usually met by supply side measures such as pushing more number of trains/cars in peak hour by the operator. This additional capacity generates more demand due to a positive elasticity of demand with respect to services. Delhi Metro Rail Corporation (DMRC), India has converted its fleet from 4 cars per train to 6 cars per train and finally to 8 cars per train on its Broad Gauge section. The ridership of the system has also witnessed double digit growth during this conversion period. The demand elasticity w.r.t services for the passengers of DMRC has been estimated as 0.512 on the basis of growth of demand and increase in capacity after adjusting for natural growth. So a 10% increase in supply results into 5% increase in capacity. A simple service elasticity model has been developed to estimate demand with increase in supply. The model has been applied to Line 2 (yellow line), the busiest line of DMRC, to estimate the demand for different level of services (trains/hour). The efficacy of supply side measures is limited by the design capacity of the system beyond which any increase in supply would require disproportionate investment. An optimum combination of supply and demand side measures would perhaps be the best way to address peak hour congestion in Urban Rail Transport.
文摘Urban rail transit loops are essential in urban rail transit systems and transportation networks.However,precise requirements and reference standards for rail transit loop design have yet to be established.There are certain areas for improvement in planning,construction,and operation.In the planning and design of urban rail transit loops,the scale of the city and the relationship between line operations should be considered to ensure that the line conforms to the city’s operating traffic conditions and can effectively cater to peak passenger flow requirements.This article presents strategies for planning,constructing,and operating urban rail transit loops,laying the foundation for the healthy operation of urban rail transit.
基金The Scientific Research Foundation of Graduate School of Southeast University(No.YBJJ1838)the Fundamental Research Funds for the Central Universities(No.KYLX16_0270)the Foundation of China Scholarship Council(No.201606090240)
文摘The discrete choice model is used to estimate the walking access area of rail transit stations while considering the influence of existing competition from other traffic modes. The acceptable walking access area is determined according to the willingness of passengers to walk who prefer rail transit compared with bus and automobile. Empirical studies were conducted using the survey data of six stations from the rail transit in Nanjing, China. The results indicate that the rail transit is more preferable compared with bus and private automobile in this case when excluding the influence of individual and environmental factors. It is found that passengers tend to underestimate their willingness to walk. The acceptable walking access area of every rail transit station is different from each other. Suburban stations generally have a larger walking access area than downtown stations. In addition, a better walking environment and a scarcer surrounding traffic environment can also lead to a larger walking area. The model was confirmed to be effective and reasonable according to the model validation. This study can be of benefit to the passenger transportation demand estimation in the location planning and evaluation of rail transit stations.
文摘With the increase of Beijing urban rail transport network, the structure of the road network is becoming more complex, and passengers have more travel options. Together with the complex paths and different timetables, taking the last train is becoming much more difficult and unsuccessful. To avoid losses, we propose feasible suggestions to the last train with reasonable selling tickets system.
文摘[目的]通过总结上海城市轨道交通既有线运能提升改造项目的实施经验,为其提出有效的运能提升方法及具体案例。[方法]深入分析上海轨道交通既有线运能不足的主要原因及其影响因素;基于这些分析,提出运能提升的技术路线及5大核心策略;详细介绍了上海轨道交通9号线实现1 min 50 s最小行车间隔、3号线与4号线增能改造、5号线从4节编组扩编至6节编组、6号线增能改造及增设复线等成功案例。[结果及结论]影响线路运能的主要因素包括车辆基地规模、区间通过能力、出入场能力,以及供电能力等。针对这些因素,确定了运能提升的技术路线,即从客流预测及客流特征分析入手,进行设施设备能力评估,设计行车交路方案,最终形成科学的改造方案。同时,提出了5大策略:运营管理优化、既有系统能力挖潜及改造、信号系统升级或土建局部改造、系统规模性改造及线网整体优化。
文摘城市轨道交通起讫点(origin-destination,OD)客流短时预测在智能交通系统中意义重大,它为交通管控策略实施以及出行者出行选择提供了重要的决策依据。卷积神经网络被广泛用于交通数据空间相关性提取,但其平移不变性与局部敏感性导致该方法更重视局部特征而忽视全局特征。本研究构建了基于注意力机制的异构数据特征提取机模型(heterogeneous data feature extraction machine,HDFEM)以实现OD矩阵空间相关性的全局感知。该模型从时空特征和用地属性特征出发,构造异构数据OD时空张量与地理信息张量,依托模型张量编码层对异构数据张量进行分割与编码,通过注意力机制连接各张量块特征,提取OD矩阵中各个部分间的空间相关性。该方法不仅实现了异构数据与OD客流数据的融合,还兼顾了卷积神经网络模型未能处理的OD矩阵远距离特征,进而帮助模型更全面地学习OD客流的空间特征。对于OD时序特性,该模型使用了长短时记忆网络来处理。在杭州地铁自动售检票系统(auto fare collection,AFC)数据集上的实验结果表明:HDFEM模型相对于基于卷积神经网络的预测模型,其均方误差、平均绝对误差与标准均方根误差分别下降了4.1%,2.5%,2%,验证了全局OD特征感知对于城市轨道交通OD客流预测的重要性。