In order to obtain the trend of urban rail transit traffic flow and grasp the fluctuation range of passenger flow better,this paper proposes a combined forecasting model of passenger flow fluctuation range based on fu...In order to obtain the trend of urban rail transit traffic flow and grasp the fluctuation range of passenger flow better,this paper proposes a combined forecasting model of passenger flow fluctuation range based on fuzzy information granulation and least squares support vector machine(LS-SVM)optimized by chaos particle swarm optimization(CPSO).Due to the nonlinearity and fluctuation of the passenger flow,firstly,fuzzy information granulation is used to extract the valid data from the window according to the requirement.Secondly,CPSO that has strong global search ability is applied to optimize the parameters of the LS-SVM forecasting model.Finally,the combined model is used to forecast the fluctuation range of early peak passenger flow at Tiyu Xilu Station of Guangzhou Metro Line 3 in 2014,and the results are compared and analyzed with other models.Simulation results demonstrate that the combined forecasting model can effectively track the fluctuation of passenger flow,which provides an effective method for predicting the fluctuation range of short-term passenger flow in the future.展开更多
在信号系统失效的情况下,调度人员无法获悉列车位置,现有后备模式和电话闭塞法指挥行车存在效率低下的问题,且具有一定的安全隐患。通过列车速度传感器、加速度传感器提供速度信息,持续计算列车位移,并通过PIS(passenger information sy...在信号系统失效的情况下,调度人员无法获悉列车位置,现有后备模式和电话闭塞法指挥行车存在效率低下的问题,且具有一定的安全隐患。通过列车速度传感器、加速度传感器提供速度信息,持续计算列车位移,并通过PIS(passenger information system,乘客信息系统)网络通道传送给车载定位服务器;车载定位服务器再结合信号系统故障时刻的位置信息,计算出列车的最新位置信息,以实现列车实时定位。该系统在合肥轨道交通1号线上进行验证,结果表明该系统在全线及个别列车信号系统故障情况下,均能实现列车实时定位,站间平均误差小于1 m,全线定位误差率小于1‰,全线单程累计误差距离小于20 m。展开更多
为推进智慧城市轨道交通的发展,车载乘客信息系统(PIS,Passenger Information System)亟需提供更贴合乘客出行需求、能够与运营动态自适应的信息服务。文章在分析车载PIS发展趋势、城市轨道交通乘客服务情景感知信息源的基础上,提出PIS...为推进智慧城市轨道交通的发展,车载乘客信息系统(PIS,Passenger Information System)亟需提供更贴合乘客出行需求、能够与运营动态自适应的信息服务。文章在分析车载PIS发展趋势、城市轨道交通乘客服务情景感知信息源的基础上,提出PIS情景感知服务技术方案,采用基于云边端融合的开放架构搭建系统,利用边缘端设备完成乘客服务情景感知信息的采集、传输、分析、调度处理能力,形成伸缩性强、性能更佳的弹性云平台,有助于提升车载PIS的自适应性,为乘客提供更人性化的服务体验。展开更多
基金National Natural Science Foundation of China(No.61663021)Science and Technology Support Project of Gansu Province(No.1304GKCA023)Scientific Research Project in University of Gansu Province(No.2017A-025)
文摘In order to obtain the trend of urban rail transit traffic flow and grasp the fluctuation range of passenger flow better,this paper proposes a combined forecasting model of passenger flow fluctuation range based on fuzzy information granulation and least squares support vector machine(LS-SVM)optimized by chaos particle swarm optimization(CPSO).Due to the nonlinearity and fluctuation of the passenger flow,firstly,fuzzy information granulation is used to extract the valid data from the window according to the requirement.Secondly,CPSO that has strong global search ability is applied to optimize the parameters of the LS-SVM forecasting model.Finally,the combined model is used to forecast the fluctuation range of early peak passenger flow at Tiyu Xilu Station of Guangzhou Metro Line 3 in 2014,and the results are compared and analyzed with other models.Simulation results demonstrate that the combined forecasting model can effectively track the fluctuation of passenger flow,which provides an effective method for predicting the fluctuation range of short-term passenger flow in the future.
文摘在信号系统失效的情况下,调度人员无法获悉列车位置,现有后备模式和电话闭塞法指挥行车存在效率低下的问题,且具有一定的安全隐患。通过列车速度传感器、加速度传感器提供速度信息,持续计算列车位移,并通过PIS(passenger information system,乘客信息系统)网络通道传送给车载定位服务器;车载定位服务器再结合信号系统故障时刻的位置信息,计算出列车的最新位置信息,以实现列车实时定位。该系统在合肥轨道交通1号线上进行验证,结果表明该系统在全线及个别列车信号系统故障情况下,均能实现列车实时定位,站间平均误差小于1 m,全线定位误差率小于1‰,全线单程累计误差距离小于20 m。
文摘为推进智慧城市轨道交通的发展,车载乘客信息系统(PIS,Passenger Information System)亟需提供更贴合乘客出行需求、能够与运营动态自适应的信息服务。文章在分析车载PIS发展趋势、城市轨道交通乘客服务情景感知信息源的基础上,提出PIS情景感知服务技术方案,采用基于云边端融合的开放架构搭建系统,利用边缘端设备完成乘客服务情景感知信息的采集、传输、分析、调度处理能力,形成伸缩性强、性能更佳的弹性云平台,有助于提升车载PIS的自适应性,为乘客提供更人性化的服务体验。
