WO2016045512A1 - 基于分布式框架的大规模实时交通指数服务方法与系统 - Google Patents
基于分布式框架的大规模实时交通指数服务方法与系统 Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
- G08G1/0141—Measuring and analyzing of parameters relative to traffic conditions for specific applications for traffic information dissemination
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
Definitions
- the invention relates to a traffic information service.
- the traditional traffic service information system can only provide users with three traffic situations: congestion, generality and smoothness. Such traffic information is not intuitive for users.
- an object of the present invention is to provide a large-scale real-time traffic index service method and system implemented by a distributed framework.
- a large-scale real-time traffic index service system based on distributed framework, which is divided into resource layer, index calculation layer, user service layer, application scheduling layer, information interaction and display layer.
- the resource layer provides infrastructure resources for the service system, including computing resources, structured databases, unstructured databases, and traffic index data sources.
- the computing resource is a computing node that implements distributed computing, a structured database is used to store structured data such as user paths, and an unstructured database is used to store unstructured data such as a traffic segment of a release segment.
- the traffic index data source is traffic. Real-time traffic flow data provided by the information center.
- the user service layer invokes user data stored in the resource layer structured database to complete the corresponding user service content.
- the layer includes a user management module, a path management module, and a data cache module, wherein: the user management module implements management tasks such as creating, modifying, and deleting system users.
- the path management module implements management of path information related data.
- the data caching module processes the cached data of the user path traffic index information to prevent repeated calculations requested by the user multiple times during a traffic index data source update period.
- the application scheduling layer receives various types of user requests sent by the information interaction and the display layer, invokes the index calculation layer and the user service layer, completes the user request, and feeds the request result to the information interaction and display layer.
- This layer it includes the index a data acquisition module, a user data acquisition module, a service request receiving and distribution module, wherein:
- the index data acquisition module mainly includes:
- General Traffic Index Acquisition Service Obtain traffic index information for a single road segment or release segment based on a specific query.
- the path index obtaining module obtains the calculated path traffic index information according to the maintained path information.
- the user data obtaining module acquires structured storage data of the user according to the query and the computing requirement, including user account information, user path information, and the like.
- the service request receiving and distributing module receives user requests and system requests from the information interaction and presentation layer, and distributes to distributed cluster nodes for specific service processing.
- the information interaction and display layer provides a real-time display of the user's map-based traffic information index, and performs traffic index information and management.
- This layer includes a map service module and an information display module, where:
- the map service module further includes:
- Map display module road map zoom in, zoom out, drag, display, etc.
- GIS service module Provides query of geographic information.
- the information display module further includes:
- Dynamic road condition display module real-time road condition based on traffic index (key road conditions, designated area, designated road section).
- the road condition display uses index information combined with color quantitative to indicate the road segment, red indicates congestion, yellow indicates crowded, and green indicates smooth.
- Traffic Index Query Module Provides real-time query of traffic indices for each road segment and release segment, and provides traffic index information for a certain number of most congested road segments in real time.
- Path Query Module Provides traffic index information for a specified path.
- a large-scale real-time traffic index service method based on distributed framework which adopts the above-mentioned system, which includes four steps of real-time calculation of traffic index, user service interface response, application service request and distribution, and information display service.
- Step 2 The user service interface responds, receives the user request information, invokes the index calculation layer, and the user service layer.
- Step 3 applying service request and distribution, distributing the user request to the index calculation layer and the user service layer to obtain feedback information, and the application service request type includes a release segment index query service, a path index query service, and a path management service.
- Step 4 information display, call information interaction and display layer display processing results, display services include map service, Web display service.
- the invention applies the traffic index to the transportation service system for the first time, calculates the traffic index of the massive path in real time through the distributed framework, realizes the traffic information display based on the traffic index through the Web mode, and provides more accurate and practical traffic information for the majority of travel users. service.
- the traffic index is a new technology that quantifies the three traffic situations of traditional blocking, squeezing and smoothing, so that the expression of road conditions is more precise.
- the degree of congestion of the user's travel route can be quantified by mathematical models to provide users with an intuitive traffic situation.
- through high-performance computing it is possible to calculate the travel routes of massive users in real time, and provide more accurate and practical traffic information services for the majority of travel users.
- Figure 1 Schematic diagram of a large-scale real-time traffic index service system architecture
- Figure 2 Technical flow chart of a large-scale real-time traffic index service method based on distributed framework
- FIG. 3 Index Distributed Computing Service System
- a large-scale real-time traffic index service system based on a distributed framework, the system is divided into a resource layer, an index calculation layer, a user service layer, an application scheduling layer, an information interaction and a display layer,
- the resource layer provides infrastructure resources for the service system, including computing resources, structured databases, unstructured databases, and traffic index data sources.
- the computing resource is a computing node that implements distributed computing, a structured database is used to store structured data such as user paths, and an unstructured database is used to store unstructured data such as a traffic segment of a release segment.
- the traffic index data source is traffic. Real-time traffic flow data provided by the information center.
- the index calculation layer calls a plurality of computing nodes of the computing resources in the resource layer, and processes the traffic index data source data by using the distributed framework, and stores them in the unstructured database after calculation.
- the layer includes an exponent update module and a daemon thread module, wherein: the exponent update module completes update of real-time traffic flow data stored in the structured database in the resource layer according to the call of the daemon thread module, and is stored according to the structure
- the road publishing segment information in the database completes the traffic index calculation process of each road and each release segment through a distributed cluster composed of multiple computing nodes, and stores the result in the unstructured database.
- the daemon thread module periodically updates the data in the database in the resource layer according to the update period of the real-time data provided by the resource layer traffic index data source, and monitors the running status of the index update module to process the abnormal information.
- the user service layer invokes user data stored in the resource layer structured database to complete the corresponding user service content.
- the layer includes a user management module, a path management module, and a data cache module, wherein: the user management module implements management tasks such as creating, modifying, and deleting system users.
- the path management module implements management of path information related data.
- the data caching module processes the cached data of the user path traffic index information to prevent repeated calculations requested by the user multiple times during a traffic index data source update period.
- the application scheduling layer receives various types of user requests sent by the information interaction and the display layer, invokes the index calculation layer and the user service layer, completes the user request, and feeds the request result to the information interaction and display layer.
- the layer includes an index data acquisition module, a user data acquisition module, a service request receiving and distribution module, wherein:
- the index data acquisition module mainly includes:
- General Traffic Index Acquisition Service Obtain traffic index information for a single road segment or release segment based on a specific query.
- the path index obtaining module obtains the calculated path traffic index information according to the maintained path information.
- the user data obtaining module acquires structured storage data of the user according to the query and the computing requirement, including user account information, user path information, and the like.
- the service request receiving and distributing module receives user requests and system requests from the information interaction and presentation layer, and distributes to distributed cluster nodes for specific service processing.
- the information interaction and display layer provides a real-time display of the user's map-based traffic information index, and performs traffic index information management.
- This layer includes a map service module and an information display module, where:
- the map service module further includes:
- Map display module road map zoom in, zoom out, drag, display, etc.
- GIS service module Provides query of geographic information.
- the information display module further includes:
- Dynamic road condition display module real-time road condition based on traffic index (key road conditions, designated area, designated road section).
- the road condition display uses index information combined with color quantitative to indicate the road segment, red indicates congestion, yellow indicates crowded, and green indicates smooth.
- Traffic Index Query Module Provides real-time query of traffic indices for each road segment and release segment, and provides traffic index information for a certain number of most congested road segments in real time.
- Path Query Module Provides traffic index information for a specified path.
- a large-scale real-time traffic index service method based on a distributed framework calculates and integrates traffic index information to provide a large-scale real-time traffic index service, and the specific steps include:
- Step 1 The system starts. First start each computing resource node, initialize the database, form a service cluster;
- Step 2 Start the service, enter the URL, and request the web page.
- the user first enters the URL of the traffic index service and enters the website page;
- Step 3 Start the index calculation daemon thread. Performing scheduled scheduling of traffic index updates
- Step 4 The traffic index data source is updated. Completing the update of real-time traffic flow data stored in the structured database in the resource layer;
- Step 5 Calculation of traffic index.
- the traffic index calculation process of each road and each release section is completed by distributed clustering, and the result is stored in a distributed database;
- Step 6 The user selects the service.
- the user chooses to publish a segment index query service, a path index query service, a path management service, and the like;
- Step 7 User Service Request Distribution. Distribute user requests to each node of the service cluster in a load-balanced manner for index data and user data acquisition;
- Step 8 User data acquisition. Return user management related data, including user information, etc. according to service request requirements;
- Step 9 Path data acquisition. Return the path information stored by the user according to the service request requirement;
- Step 10 Index data acquisition. According to the service request requirement, the index calculation service is invoked to obtain the relevant index information data;
- Step 11 Cache the data.
- the return data of each service request is cached according to the period of the index update
- Step 12 Map service acquisition. Return the road network address data of the specified area according to the service request requirement;
- Step 13 Dynamic road condition display. According to the service request, the data is returned, and the index information is combined with the color quantitative display mode to display the real-time road condition of the traffic index;
- Step 14 Traffic index query display. Returning data according to the service request, displaying the traffic index information of the specified query, and simultaneously giving a certain amount of traffic index information of the most congested road sections in real time;
- Step 16 The service ends.
- the steps of performing distributed calculation on the traffic index in the present invention are as shown in FIG. 3, and the specific steps include:
- Step 1 Get the data source. Obtaining traffic index data source information
- Step 2 Data source storage.
- the traffic index raw data is unpacked and stored in the structured database
- Step 3 Update the index. Update traffic index information data
- Step 4 Index calculation and storage. Through the distributed cluster, the traffic index calculation process of each road and each release section is completed, and the result is stored in the unstructured database.
- the steps of the distributed processing for the user request in the present invention are as shown in FIG. 4, and the specific steps include:
- Step 1 User connection. Users request different index services
- Step 2 Request distribution. Distribute user requests to each node of the service cluster in a load-balanced manner
- Step 3 Web service response. Corresponding to user service requests through the web server;
- Step 4 Obtain index data, user data, and map.
- the traffic index data and the user data required for the request are obtained through the index calculation layer and the user service layer, and the required map data is acquired through the information interaction and the presentation layer.
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Abstract
基于分布式框架的大规模实时交通指数服务方法与系统, 其为广大出行用户提供更为准确、实用的交通信息服务。系统分为资源层、指数计算层、用户服务层、应用调度层、信息交互与展示层；资源层提供了基础设施资源；指数计算层调用资源层中计算资源的多个计算节点，利用分布式框架处理交通指数数据源数据，经过计算后存储到非结构化数据库中；用户服务层调用资源层存储的用户数据，完成相应的用户服务内容；应用调度层接收信息交互与展示层发送的各类用户请求，调用指数计算层以及用户服务层，完成用户请求，将请求结果反馈给信息交互与展示层。方法包括交通指数实时计算、用户服务接口响应、应用服务请求与分发、信息展示服务四个步骤。
Description
本发明涉及一种交通信息服务。
目前，以私家车和出租车为代表的个体出行用户逐渐发展成为城市交通的主力军，与公共交通相比，个体用户对于交通信息服务系统的需求更加旺盛。我国十五ITS发展规划已经把面向个体用户的交通服务系统作为试点，重点发展利用大众传媒的交通信息服务系统，体现以人为本的交通理念。
传统的交通服务信息系统仅能向用户提供拥堵、一般和畅通三种交通态势，这类交通信息对于用户来说缺乏直观性。
发明内容
针对现有技术的上述特点，本发明的目的在于提供一种用分布式框架实现的大规模实时交通指数服务方法与系统。
为达上述目的，本发明采用如下技术方案：
(1)一种基于分布式框架的大规模实时交通指数服务系统，所述系统分为资源层、指数计算层、用户服务层、应用调度层、信息交互与展示层，
所述资源层提供了服务系统的基础设施资源，包括计算资源、结构化数据库、非结构化数据库以及交通指数数据源。其中，计算资源是实现分布式计算的计算节点、结构化数据库用于存储用户路径等结构化数据、非结构化数据库用于存储发布段交通指数等非结构化数据，交通指数数据源是由交通信息中心提供的实时交通流量数据。
所述指数计算层调用资源层中计算资源的多个计算节点，利用分布式框架处理交通指数数据源数据，经过计算后存储到非结构化数据库中。该层包括指数更新模块、和守护线程模块，其中：所述指数更新模块，根据守护线程模块的调用完成资源层中存储于结构化数据库中的实时交通流量数据的更新，同时根据存储于结构化数据库中的道路发布段信息，通过多个计算节点组成的分布式集群完成各条道路及各发布段交通指数计算过程，将结果存储于非结构化数据库中。所述守护线程模块，根据资源层交通指数数据源提供的实时数据的更新周期，定时调用指数更新模块更新资源层中数据库中数据，同时监控指数更新模块的运行状态，处理异常信息。
所述用户服务层调用资源层结构化数据库中存储的用户数据，完成相应的用户服务内容。该层它包括用户管理模块、路径管理模块、数据缓存模块，其中：所述用户管理模块，实现对系统用户的创建、修改、删除等管理工作。所述路径管理模块，实现对于路径信息相关数据的管理。所述数据缓存模块，处理用户路径交通指数信息的缓存数据，防止在一次交通指数数据源更新周期内用户多次请求的重复计算。
所述应用调度层接收信息交互与展示层发送的各类用户请求，调用指数计算层以及用户服务层，完成用户请求，同时将请求结果反馈给信息交互与展示层。该层它包括指数
数据获取模块、用户数据获取模块、服务请求接收与分发模块，其中：
所述指数数据获取模块，主要包括：
通用交通指数获取服务：根据具体查询获取单一路段或者发布段的交通指数信息。
所述路径指数获取模块，根据维护的路径信息，获取计算后的路径交通指数信息。
所述用户数据获取模块，根据查询和计算需求获取用户的结构化存储数据，包括用户的账户信息，用户路径信息等。
所述服务请求接收与分发模块，接收来自信息交互与展示层的用户请求和系统请求，分发到分布式集群节点进行具体的服务处理过程。
所述信息交互与展示层提供用户基于地图的交通信息指数的实时展示，进行交通指数信息、管理。该层它包括地图服务模块、信息展示模块，其中：
所述地图服务模块，又包括：
地图展示模块：道路地图放大、缩小、拖动、显示等。
GIS服务模块：提供地理信息的查询。
所述信息展示模块，又包括：
动态路况展示模块：基于交通指数的实时路况(重点路况、指定区域、指定路段)，路况显示采用指数信息结合颜色定量表示路段，红色表示拥塞，黄色表示拥挤，绿色表示畅通。
交通指数查询模块：提供各个路段及发布段的交通指数实时查询，同时实时给出一定数量的最为拥堵的路段的交通指数信息。
路径查询模块：提供指定路径的交通指数信息。
(2)一种基于分布式框架的大规模实时交通指数服务方法，采用上述系统，依次包括交通指数实时计算、用户服务接口响应、应用服务请求与分发、信息展示服务四个步骤，
步骤1交通指数实时计算，接收资源层交通指数数据源的实时数据分发到由计算资源节点组成的分布式集群进行高性能交通指数计算，将结果保存到非结构化数据库中，
步骤2用户服务接口响应，接收用户请求信息调用指数计算层以及用户服务层
步骤3应用服务请求与分发，将用户请求分发到指数计算层和用户服务层取得反馈信息，应用服务请求类型包括发布段指数查询服务、路径指数查询服务、路径管理服务，
步骤4信息展示，调用信息交互和展示层展示处理结果，展示服务包括地图服务，Web展示服务。
本发明首次将交通指数应用到交通服务系统中，通过分布式框架实时计算海量路径的交通指数，通过Web方式实现基于交通指数的交通信息展示，为广大出行用户提供更为准确、实用的交通信息服务。
交通指数是一种将传统的堵、挤、畅三种交通态势量化，从而使路况的表达更为精准的一种新技术。将交通指数这一新概念拓展到交通指数服务系统中，能够将用户出行路线的拥堵程度通过数学模型加以量化，提供用户直观的交通态势感受。同时，通过高性能计算，能够实时计算海量用户的出行路线，为广大出行用户提供更为准确、实用的交通信息服务。
图1：大规模实时交通指数服务系统体系结构示意图
图2：基于分布式框架的大规模实时交通指数服务方法的技术流程图
图3：指数分布式计算服务体系
图4：用户请求分布式处理服务体系
如图1所示，一种基于分布式框架的大规模实时交通指数服务系统，所述系统分为资源层、指数计算层、用户服务层、应用调度层、信息交互与展示层，
所述资源层提供了服务系统的基础设施资源，包括计算资源、结构化数据库、非结构化数据库以及交通指数数据源。其中，计算资源是实现分布式计算的计算节点、结构化数据库用于存储用户路径等结构化数据、非结构化数据库用于存储发布段交通指数等非结构化数据，交通指数数据源是由交通信息中心提供的实时交通流量数据。
所述指数计算层调用资源层中计算资源的多个计算节点，利用分布式框架处理交通指数数据源数据，经过计算后存储到非结构化数据库中。该层包括指数更新模块、和守护线程模块，其中：所述指数更新模块，根据守护线程模块的调用完成资源层中存储于结构化数据库中的实时交通流量数据的更新，同时根据存储于结构化数据库中的道路发布段信息，通过多个计算节点组成的分布式集群完成各条道路及各发布段交通指数计算过程，将结果存储于非结构化数据库中。所述守护线程模块，根据资源层交通指数数据源提供的实时数据的更新周期，定时调用指数更新模块更新资源层中数据库中数据，同时监控指数更新模块的运行状态，处理异常信息。
所述用户服务层调用资源层结构化数据库中存储的用户数据，完成相应的用户服务内容。该层它包括用户管理模块、路径管理模块、数据缓存模块，其中：所述用户管理模块，实现对系统用户的创建、修改、删除等管理工作。所述路径管理模块，实现对于路径信息相关数据的管理。所述数据缓存模块，处理用户路径交通指数信息的缓存数据，防止在一次交通指数数据源更新周期内用户多次请求的重复计算。
所述应用调度层接收信息交互与展示层发送的各类用户请求，调用指数计算层以及用户服务层，完成用户请求，同时将请求结果反馈给信息交互与展示层。该层它包括指数数据获取模块、用户数据获取模块、服务请求接收与分发模块，其中：
所述指数数据获取模块，主要包括：
通用交通指数获取服务：根据具体查询获取单一路段或者发布段的交通指数信息。
所述路径指数获取模块，根据维护的路径信息，获取计算后的路径交通指数信息。
所述用户数据获取模块，根据查询和计算需求获取用户的结构化存储数据，包括用户的账户信息，用户路径信息等。
所述服务请求接收与分发模块，接收来自信息交互与展示层的用户请求和系统请求，分发到分布式集群节点进行具体的服务处理过程。
所述信息交互与展示层提供用户基于地图的交通信息指数的实时展示，进行交通指数信息管理。该层它包括地图服务模块、信息展示模块，其中：
所述地图服务模块，又包括：
地图展示模块：道路地图放大、缩小、拖动、显示等。
GIS服务模块：提供地理信息的查询。
所述信息展示模块，又包括：
动态路况展示模块：基于交通指数的实时路况(重点路况、指定区域、指定路段)，路况显示采用指数信息结合颜色定量表示路段，红色表示拥塞，黄色表示拥挤，绿色表示畅通。
交通指数查询模块：提供各个路段及发布段的交通指数实时查询，同时实时给出一定数量的最为拥堵的路段的交通指数信息。
路径查询模块：提供指定路径的交通指数信息。
如图2所示，一种基于分布式框架的大规模实时交通指数服务方法，计算并整合交通指数信息用以提供大规模实时交通指数服务，具体步骤包括：
步骤1：系统启动。首先启动各个计算资源节点，初始化数据库，形成服务集群；
步骤2：服务开始，输入网址，请求网页。用户首先输入交通指数服务的网址，进入网站页面；
步骤3：启动指数计算守护线程。进行交通指数更新的定时调度；
步骤4：交通指数数据源更新。完成资源层中存储于结构化数据库中的实时交通流量数据的更新；
步骤5：交通指数计算。通过分布式集群完成各条道路及各发布段交通指数计算过程，将结果存储于分布式数据库中；
步骤6：用户选择服务。用户选择发布段指数查询服务、路径指数查询服务、路径管理服务等；
步骤7：用户服务请求分发。将用户请求按照负载均衡的方式分发到服务集群的各个节点中进行指数数据及用户数据的获取；
步骤8：用户数据获取。按照服务请求需求，返回用户管理相关数据，包括用户信息等；
步骤9：路径数据获取。按照服务请求需求，返回用户存储的路径信息；
步骤10：指数数据获取。按照服务请求需求，调用指数计算服务，获取相关指数信息数据；
步骤11：缓存数据。按照指数更新的周期将每次服务请求的返回数据进行缓存；
步骤12：地图服务获取。按照服务请求需求，返回指定区域的路网地址数据；
步骤13：动态路况展示。根据服务请求返回数据，采用指数信息结合颜色定量展示方式，显示交通指数的实时路况；
步骤14：交通指数查询展示。根据服务请求返回数据，展示指定查询的交通指数信息，同时实时给出一定数量的最为拥堵的路段的交通指数信息；
步骤15：路径指数展示。根据服务请求返回数据，展示路径指数信息；
步骤16：服务结束。
本发明中对于交通指数进行分布式计算的步骤如图3所示，具体步骤包括：
步骤1：获取数据源。获取交通指数数据源信息；
步骤2：数据源存储。交通指数原始数据解包后存入结构化数据库；
步骤3：更新指数。更新交通指数信息数据；
步骤4：指数计算和存储。通过分布式集群完成各条道路及各发布段交通指数计算过程，将结果存储于非结构化数据库中。
本发明中对于用户请求进行分布式处理的步骤如图4所示，具体步骤包括：
步骤1：用户连接。用户请求不同指数服务；
步骤2：请求分发。将用户请求按照负载均衡的方式分发到服务集群的各个节点；
步骤3：Web服务响应。通过Web服务器对用户服务请求进行相应；
步骤4：获取指数数据、用户数据、地图。通过指数计算层和用户服务层获取请求所需的交通指数数据以及用户数据，通过信息交互与展示层获取请求所需地图数据。
Claims (2)
- 一种基于分布式框架的大规模实时交通指数服务系统，所述系统分为资源层、指数计算层、用户服务层、应用调度层、信息交互与展示层，所述资源层提供了服务系统的基础设施资源，包括计算资源、结构化数据库、非结构化数据库以及交通指数数据源。其中，计算资源是实现分布式计算的计算节点、结构化数据库用于存储用户路径等结构化数据、非结构化数据库用于存储发布段交通指数等非结构化数据，交通指数数据源是由交通信息中心提供的实时交通流量数据；所述指数计算层调用资源层中计算资源的多个计算节点，利用分布式框架处理交通指数数据源数据，经过计算后存储到非结构化数据库中。该层包括指数更新模块、和守护线程模块，其中：所述指数更新模块，根据守护线程模块的调用完成资源层中存储于结构化数据库中的实时交通流量数据的更新，同时根据存储于结构化数据库中的道路发布段信息，通过多个计算节点组成的分布式集群完成各条道路及各发布段交通指数计算过程，将结果存储于非结构化数据库中。所述守护线程模块，根据资源层交通指数数据源提供的实时数据的更新周期，定时调用指数更新模块更新资源层中数据库中数据，同时监控指数更新模块的运行状态，处理异常信息；所述用户服务层调用资源层结构化数据库中存储的用户数据，完成相应的用户服务内容。该层它包括用户管理模块、路径管理模块、数据缓存模块，其中：所述用户管理模块，实现对系统用户的创建、修改、删除等管理工作。所述路径管理模块，实现对于路径信息相关数据的管理。所述数据缓存模块，处理用户路径交通指数信息的缓存数据，防止在一次交通指数数据源更新周期内用户多次请求的重复计算；所述应用调度层接收信息交互与展示层发送的各类用户请求，调用指数计算层以及用户服务层，完成用户请求，同时将请求结果反馈给信息交互与展示层。该层它包括指数数据获取模块、用户数据获取模块、服务请求接收与分发模块，其中：所述指数数据获取模块，主要包括：通用交通指数获取服务：根据具体查询获取单一路段或者发布段的交通指数信息；所述路径指数获取模块，根据维护的路径信息，获取计算后的路径交通指数信息；所述用户数据获取模块，根据查询和计算需求获取用户的结构化存储数据，包括用户的账户信息，用户路径信息等；所述服务请求接收与分发模块，接收来自信息交互与展示层的用户请求和系统请求，分发到分布式集群节点进行具体的服务处理过程；所述信息交互与展示层提供用户基于地图的交通信息指数的实时展示，进行交通指数信息管理。该层它包括地图服务模块、信息展示模块，其中：所述地图服务模块，又包括：地图展示模块：道路地图放大、缩小、拖动、显示等。GIS服务模块：提供地理信息的查询；所述信息展示模块，又包括：动态路况展示模块：基于交通指数的实时路况(重点路况、指定区域、指定路段)，路况显示采用指数信息结合颜色定量表示路段，红色表示拥塞，黄色表示拥挤，绿色表示畅通；交通指数查询模块：提供各个路段及发布段的交通指数实时查询，同时实时给出一定数量的最为拥堵的路段的交通指数信息；路径查询模块：提供指定路径的交通指数信息。
- 一种基于分布式框架的大规模实时交通指数服务方法，采用上述系统，依次包括交通指数实时计算、用户服务接口响应、应用服务请求与分发、信息展示服务四个步骤，步骤1交通指数实时计算，接收资源层交通指数数据源的实时数据分发到由计算资源节点组成的分布式集群进行高性能交通指数计算，将结果保存到非结构化数据库中，步骤2用户服务接口响应，接收用户请求信息调用指数计算层以及用户服务层步骤3应用服务请求与分发，将用户请求分发到指数计算层和用户服务层取得反馈信息，应用服务请求类型包括发布段指数查询服务、路径指数查询服务、路径管理服务，步骤4信息展示，调用信息交互和展示层展示处理结果，展示服务包括地图服务，Web展示服务。
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107026909A (zh) * | 2017-04-17 | 2017-08-08 | 衢州市江氏电子科技有限公司 | 一种基于云服务的防洪e‑监测数据调度管理系统 |
| CN111460012A (zh) * | 2020-04-26 | 2020-07-28 | 国家气象信息中心 | 基于Spark的气象历史台站沿革数据可视化方法及系统 |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104282140B (zh) * | 2014-09-22 | 2016-06-15 | 同济大学 | 基于分布式框架的大规模实时交通指数服务方法与系统 |
| CN105741548A (zh) * | 2016-04-19 | 2016-07-06 | 上海理工大学 | 一种生成交通状态云图的方法 |
| CN105890609B (zh) * | 2016-06-02 | 2019-01-25 | 同济大学 | 一种基于分布式动态路网的路径规划方法及系统 |
| CN107066483A (zh) * | 2016-12-25 | 2017-08-18 | 北京通途永久科技有限公司 | 一种交通行业指标数据编码及存储方法 |
| CN107832369B (zh) * | 2017-10-27 | 2020-02-04 | 北京世纪高通科技有限公司 | 一种道路路况动态粒子流生成方法及装置 |
| CN109064747A (zh) * | 2018-08-31 | 2018-12-21 | 司振国 | 基于实时移动地图的行车路线规划与到站时间上报的方法 |
| CN109669965A (zh) * | 2018-11-13 | 2019-04-23 | 广州欧赛斯信息科技有限公司 | 一种支持非结构化数据的采集分析系统和方法 |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1904935A (zh) * | 2005-07-26 | 2007-01-31 | 同济大学 | 用网格技术实现交通信息服务的系统和方法 |
| CN101075227A (zh) * | 2007-06-28 | 2007-11-21 | 上海交通大学 | 基于海量交通信息的融合系统 |
| US20100023253A1 (en) * | 2008-07-22 | 2010-01-28 | Samsung Electronics Co., Ltd. | Navigation apparatus and method |
| CN102638588A (zh) * | 2012-05-10 | 2012-08-15 | 北京邮电大学 | 基于物联网Web数据平台的用户可定制的交通服务信息获取方法 |
| CN103886739A (zh) * | 2014-03-05 | 2014-06-25 | 同济大学 | 基于大规模实时交通指数系统的个性化服务平台 |
| CN104282140A (zh) * | 2014-09-22 | 2015-01-14 | 同济大学 | 基于分布式框架的大规模实时交通指数服务方法与系统 |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100965662B1 (ko) * | 2003-01-11 | 2010-06-24 | 삼성전자주식회사 | 페이징 채널을 이용한 네비게이션 시스템 및 그 교통정보제공 방법 |
| US20090062975A1 (en) * | 2007-02-28 | 2009-03-05 | Henryk Strzeletz | Display system |
| CN103000039B (zh) * | 2012-11-26 | 2014-12-03 | 余姚德诚科技咨询有限公司 | 路况拥堵提示装置 |
| CN104021672B (zh) * | 2014-06-09 | 2016-09-07 | 北京世纪高通科技有限公司 | 一种获取交通拥堵指数的方法和装置 |
-
2014
- 2014-09-22 CN CN201410486663.9A patent/CN104282140B/zh active Active
-
2015
- 2015-09-14 WO PCT/CN2015/089507 patent/WO2016045512A1/zh active Application Filing
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1904935A (zh) * | 2005-07-26 | 2007-01-31 | 同济大学 | 用网格技术实现交通信息服务的系统和方法 |
| CN101075227A (zh) * | 2007-06-28 | 2007-11-21 | 上海交通大学 | 基于海量交通信息的融合系统 |
| US20100023253A1 (en) * | 2008-07-22 | 2010-01-28 | Samsung Electronics Co., Ltd. | Navigation apparatus and method |
| CN102638588A (zh) * | 2012-05-10 | 2012-08-15 | 北京邮电大学 | 基于物联网Web数据平台的用户可定制的交通服务信息获取方法 |
| CN103886739A (zh) * | 2014-03-05 | 2014-06-25 | 同济大学 | 基于大规模实时交通指数系统的个性化服务平台 |
| CN104282140A (zh) * | 2014-09-22 | 2015-01-14 | 同济大学 | 基于分布式框架的大规模实时交通指数服务方法与系统 |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107026909A (zh) * | 2017-04-17 | 2017-08-08 | 衢州市江氏电子科技有限公司 | 一种基于云服务的防洪e‑监测数据调度管理系统 |
| CN111460012A (zh) * | 2020-04-26 | 2020-07-28 | 国家气象信息中心 | 基于Spark的气象历史台站沿革数据可视化方法及系统 |
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