WO2020083399A1 - 基于交通流数据的协调干线线路规划方法及配置系统 - Google Patents
基于交通流数据的协调干线线路规划方法及配置系统 Download PDFInfo
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- the invention relates to a coordinated trunk line planning method and configuration system based on traffic flow data.
- intersections are close to each other.
- vehicles often encounter red lights and turn on and stop at a time, resulting in poor driving, and thus increasing environmental pollution.
- To reduce the parking time at each intersection it is necessary to connect a group of adjacent traffic signals on a trunk line to coordinate control.
- traffic signal control systems are being popularized, and traffic police departments at all levels are beginning to implement trunk lines on the city's main roads.
- the coordinated trunk line is empirically calibrated by the credit control professional team and the traffic police department policemen according to the current situation of urban intersection channelization characteristics, intersection traffic volume, traffic management rules, etc.
- the generally configured trunk line is the urban main road of multiple intersections , Highway trunk roads, long tunnels and long bridges, but in urban road networks, the trunk roads are not necessarily the trunk roads that really need to be coordinated; on the other hand, the coordination direction of the trunk road coordination of various intersections is determined according to the traffic flow of each intersection, but The flow direction data detected by the video number plate recognition device (electronic police / smart bay) at the intersection saturation state does not represent the real demand flow direction of the intersection, and the comparison of the whole-day traffic detection or the dynamic OD research is more complicated, so it is aimed at the current
- the planning and configuration of the traffic signal coordination trunk line lacks a set of standards for the rational analysis of trunk line configuration. An intelligent and automated trunk line planning and configuration method is needed to ensure the optimal efficiency of the coordinated trunk line configured by the traffic police brigade.
- the purpose of the present invention is to provide a coordinated trunk line planning method and configuration system based on traffic flow data, relying on Internet data and passing data identified by video number plates to identify the critical flow direction of the entrance road at the intersection during non-congested time periods, and then to Analyze the key flow directions of adjacent intersections, plan and configure coordinated trunk lines and their control time period, improve the accuracy of coordinated trunk lines, alleviate the problem of urban road congestion, and solve the current trunk line configuration existing in the existing technology according to the main road of traffic planning Such as the type of road, the problem of inaccurate direction of intersection coordination.
- a coordinated trunk route planning method based on traffic flow data integrating Internet data and passing data of video number plate recognition equipment, relying on traffic flow data in non-congested time periods to determine key flow directions, thereby identifying and configuring each control time period Coordination direction, and then plan to configure a coordination trunk; including the following steps,
- step S1 is specifically,
- each road segment includes uplink and downlink;
- step S13 Draw a time-congestion index line chart from the congestion index obtained in step S12, and determine the non-congestion time period of the road section.
- step S12 the congestion index per unit time in the statistical time period of each road segment divided in step S11 is calculated, specifically, it is connected with Internet data to extract the traffic state of each unit time of the entire day in the statistical time period, There are four types of smooth, slow, congested and severely congested, and then the total number of occurrences of this traffic state N i within the statistical time period is determined, where i represents the traffic state, specifically including four types, i.e. 1 represents unobstructed, i is 2 Represents slow travel, i is 3 for congestion, and i is 4 for severe congestion; then it is calculated according to the weight value ⁇ i of clear, slow, congested and severe congestion, that is, the congestion index is:
- step S2 is specifically,
- step S22 specifically is to calculate the passing traffic in the unit time period of each flow direction of the entrance based on the passing data, and further calculate the traffic demand ratio q mn of the flow direction of each entrance, namely:
- m is the entrance road
- n is the flow direction
- Q mn is the traffic flow of the entrance road m in the unit time period to n
- Q m is the total traffic flow of the entrance road m in the unit time period
- step S3 is specifically,
- step S31 specifically is,
- step S312 If the traffic demand balance ⁇ is greater than the set balance threshold, it is determined that the intersection cannot be associated; otherwise, the intersection is determined to be associated, and the downstream intersection is defaulted to the upstream intersection, and step S311 is repeated until the coordinated trunk configuration is completed within a unit time period.
- Intersection traffic flow recognition module access to Internet data and video number plates to identify the passing data collected to determine the key flow direction in each signal control time period of each intersection;
- Coordination trunk configuration module Based on the key flow direction identified by the intersection traffic flow identification module, the coordination trunk and its coordination control time period are configured.
- intersection traffic flow identification module includes a non-congestion time identification unit and an intersection key flow direction identification unit,
- Non-congestion time recognition unit traffic status data connected to the Internet, using step S1 in the coordinated trunk line planning method based on any of the above-mentioned traffic flow data to determine the non-congestion time period of each road segment in the road network The time period is transmitted to the key flow direction identification unit of the intersection;
- Intersection key flow direction identification unit docking with the video number plate identification device in the road network, using step S2 in the coordinated trunk line planning method based on any of the above-mentioned traffic flow data to determine the key flow direction of each intersection, and according to the selected time period
- the key flow directions of each entrance at the intersection are displayed and marked on the GIS electronic map.
- the coordinated trunk configuration module includes a trunk drawing unit and a control period division unit,
- Trunk drawing unit Determine a certain intersection of the coordinated trunk based on the GIS electronic map, display the key flow directions of each entrance of the signal and the key flow directions of adjacent signal-controlled intersections according to the selected time period, determine the coordination direction of the intersection, and in turn Configure the downstream intersection to complete the trunk drawing, and send the drawn trunk information to the control time period dividing unit; according to any of the above, based on the traffic flow data-based coordinated trunk route planning method, step S3 warns the unconnected intersection;
- Control time period division unit integrate the time period of the coordinated trunk line drawn by the trunk line drawing unit, and use step S3 in the coordinated trunk line planning method based on the traffic flow data described above to determine the coordinated trunk line controllable time period And display the list.
- this coordinated trunk line planning method and configuration system based on traffic flow data
- the Internet-based traffic status data identifies a non-congested time period, that is, a non-saturated time period, and analyzes the trunk line configuration for this time period
- the invention performs configuration identification analysis on trunks in different time periods, improves the implementation efficiency of coordinated trunks, and provides auxiliary support for regional signal coordination and optimization.
- FIG. 1 is a schematic flowchart of a coordinated trunk line planning method based on traffic flow data according to an embodiment of the present invention.
- FIG. 2 is an explanatory block diagram of a coordinated trunk line planning and configuration system based on traffic flow data in an embodiment.
- a coordinated trunk route planning method based on traffic flow data integrating Internet data and passing data of video number plate recognition equipment, relying on traffic flow data in non-congested time periods to determine key flow directions, thereby identifying and configuring each control time period Coordination direction, and then plan to configure a coordination trunk; as shown in Figure 1, the specific steps are as follows:
- each road segment includes both uplink and downlink. Specifically, it is connected with Internet data to extract the traffic state (including four types of smooth, slow, congested and severe congestion) of each unit time of the whole day in the statistical time period, and then determine the total number of such traffic states during the statistical time period Number of times N i , where i represents the traffic state, specifically including four types, namely 1 (clear), 2 (slow), 3 (congested), 4 (severe congestion); then according to the weight value of smooth, slow, congested and severe congested ⁇ i is calculated, that is, the congestion index is:
- the road segment has multiple traffic states, for example, the road segment displays "congestion-free-congestion"
- the statistical time period is week / month / quarter, and the whole-day unit time period is 15min / 30min / 1hour.
- the congestion index per unit time of the road section draw a line chart of the up and down time of the whole day road section-congestion index, find its inflection point based on the trend of the line chart, and default it to the start time and end time of the congestion time period , So as to determine the congestion time period within the whole day, and further exclude all-day non-congestion time period of the found road section, that is, the time period other than the congestion time period.
- the inflection point can be found by the slope or standard deviation.
- the total number of congestion time periods throughout the day is generally dominated by two periods, that is, the morning peak period and the evening peak period.
- the trunk line coordination scheme cannot be configured during this period.
- the passing traffic is basically the actual traffic demand, and the traffic demand for each direction of the entrance of the intersection is identified for the non-congested undersaturated traffic flow.
- m is the entrance road
- n is the flow direction
- Q mn is the traffic flow of the entrance road m to n in the unit time period
- Q m is the total traffic flow of the entrance road m in the unit time period.
- the flow direction threshold is configured by the user according to the channelization characteristics of the intersection. If there are three flow directions of left turn, straight travel, and right turn at the intersection entrance, the flow direction threshold can be 45% -55%, and the intersection entrance only has left turn and straight travel 2. Two flow directions in the right turn, that is, the flow threshold can be 55% -65%.
- S23 Integrate to establish a key flow schedule. Specifically, integrate the key flow directions within the unit time period of each entrance of the intersection to establish a key flow direction schedule.
- the table contains the time period, intersection number, entrance road, and key flow direction. For the congestion time period, the key flow direction is air.
- step S312 If the traffic demand balance ⁇ is greater than the set balance threshold, the intersection is determined not to be associated, otherwise the intersection is determined to be associated, and the downstream intersection is defaulted to the upstream intersection, repeating step S311 until the coordinated trunk configuration is completed within a unit time period.
- the balance threshold is configured by the user, and the value can be between 120% and 180%. If it is greater than the balance threshold, it means that the key flow direction of the downstream intersection not only comes from the flow of the inlet of the upstream intersection, but also includes the other inlets of the upstream intersection. For traffic flow, the coordination trunk cannot be configured.
- the coordinated trunk line is reasonable, and the coordinated control time period is 9: 00-16: 00; If the key flow direction of the southern entrance of junction A is 9: 00-10: 00 and 10: 00-11: 00, the coordinated trunk line is unreasonable.
- the embodiment also provides a coordinated trunk line planning and configuration system based on traffic flow data, as shown in FIG. 2, which includes an intersection traffic flow identification module and a coordinated trunk line configuration module to implement the configuration of the coordinated trunk line and its control time period.
- Intersection traffic flow recognition module This module accesses Internet data and video number plate to identify the passing data collected, and determines the key flow direction in each signal control time period of each intersection, specifically including the non-congestion time recognition unit and the intersection key flow direction recognition unit.
- Non-congestion time identification unit traffic status data connected to the Internet, based on step S1 of the above-described coordinated trunk line planning method based on the traffic flow data of the embodiment to determine the non-congestion time period of each road segment in the road network, and transmit the non-congestion time period To the key flow direction identification unit of the intersection.
- Intersection key flow direction identification unit docking with the video number plate identification device in the road network, and determining the key flow direction of each intersection based on step S2 of the above-mentioned coordinated trunk line planning method based on the traffic flow data of the embodiment, and showing the intersection according to the selected time period
- the key flow directions of each entrance are marked on the GIS electronic map.
- Coordinated main line configuration module This module configures a coordinated main line and its coordinated control time period based on the key flow direction identified by the intersection traffic flow identification module, which specifically includes a main line drawing unit and a control time period dividing unit.
- Trunk drawing unit Determine a certain intersection of the coordinated trunk based on the GIS electronic map, display the key flow directions of each entrance of the signal and the key flow directions of adjacent signal-controlled intersections according to the selected time period, determine the coordination direction of the intersection, and in turn Configure the downstream intersection to complete the trunk line drawing, and send the drawn trunk line information to the control time period dividing unit; at the same time, the system can perform early warning for the uncorrelated intersection according to step S3 of the coordinated trunk line planning method based on the traffic flow data described above in the embodiment.
- Control time period division unit integrate the time period of the coordinated trunk line drawn by the trunk line drawing unit, based on the step S3 of the coordinated trunk line planning method based on the traffic flow data described above in the embodiment, determine the coordinated trunk line coordinated and controllable time period, and perform List display.
- the coordinated trunk line planning method and configuration system based on the traffic flow data of the embodiment recognizes the non-congested time period based on the traffic data of the Internet data, and then extracts the passing data of the non-congested time period of each entrance of the intersection to effectively identify The accurate key flow direction is determined, and further analysis is performed on adjacent intersections to determine the coordinated trunk line.
- This kind of coordinated trunk line planning method and configuration system based on traffic flow data can freely configure coordinated trunks according to the key flow directions of each entrance of the intersection during the time period, and innovatively judged whether the configured coordinated trunks are reasonable, so as to propose trunks in different time periods coordination.
- the coordinated trunk line planning method and configuration system based on the traffic flow data of the embodiment, according to the current situation of the trunk line planning and configuration of the urban road traffic signal control coordinated trunk line, identifies non-congested time periods based on Internet data, thereby extracting the non-congested time periods Passing data, identifying the key flow direction of the entrance road of the intersection, analyzing the correlation between the intersections, thereby configuring the coordinated trunk line and its control time period, which improves the efficiency of the coordinated trunk line configuration and avoids the coordination efficiency of the traditional trunk road planning configuration method
- the low problem provides effective support for regional signal coordination.
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Abstract
一种基于交通流数据的协调干线线路规划方法及配置系统，将互联网数据和视频号牌识别设备的过车数据进行整合，依托非拥堵时间段内交通流数据确定关键流向，从而识别配置出各控制时间段的协调方向，进而规划配置出协调干线；基于互联网的交通状态数据识别出非拥堵时间段，针对该时间段进行干线配置分析，避免了传统干线配置根据路网交通规划以及针对饱和时间段和非饱和时间段综合考虑各路口的协调方向，导致的协调干线效率低下的问题，从而提高了协调干线不同时间段的准确性，达到协调最优。对不同时间段的干线进行配置识别分析，提高了协调干线实施效率，为区域信号协调优化提供了辅助支撑。
Description
本发明涉及一种基于交通流数据的协调干线线路规划方法及配置系统。
在城市道路中，交叉口相距较近，各交叉口分别设置单点信号控制时，车辆经常遇到红灯，时停时开，造成行车不畅，也因而使环境污染加重，因此为使车辆减少在各个交叉口上的停车时间，需要把一条干线上一批相邻的交通信号连接起来，加以协调控制。目前随着机动车保有量的日趋增长，交通拥堵问题日渐严重，交通信号控制系统不断被普及，各级交警部门均开始在本城市主干道实施干线。
现阶段的协调干线是由信控专业团队和交警部门警员根据城市路口渠化特征、路口交通量、交通管理规则等现状进行经验式标定，一般配置的干线为多个交叉口的城市主干道、高速公路干道、长隧道和长桥，但在城市路网中，主干道不一定为真正需要协调的干线；另一方面，目前干线协调各路口的协调方向根据各路口的交通流量确定，但是视频号牌识别设备(电子警察/智能卡口)在路口饱和状态下检测的流向数据并不能代表为路口真正的需求流向，而对全天流量的检测对比或基于动态OD研究较为复杂，因此针对目前交通信号协调干线的规划和配置缺乏一套干线配置合理性分析的标准，需要一套智能化、自动化的干线规划配置方法，从而确保交警大队配置的协调干线效率最优。
发明内容
本发明的目的是提供一种基于交通流数据的协调干线线路规划方法及配置系统，依托互联网数据和视频号牌识别的过车数据对非拥堵时间段内路口进口道关键流向进行判别，进而对相邻路口关键流向进行分析，规划配置出协调干线及其控制时间段，提高了协调干线的准确性，缓解了城市道路拥堵问题，解决现有技术中存在的现阶段干线配置依据交通规划主干道等道路类型，路口协调方向不准确的问题。
本发明的技术解决方案是：
一种基于交通流数据的协调干线线路规划方法，将互联网数据和视频号牌识别设备的过车数据进行整合，依托非拥堵时间段内交通流数据确定关键流向，从而识别配置出各控制时间段的协调方向，进而规划配置出协调干线；包括以下步骤，
S1、基于互联网数据对路段上行与下行的拥堵指数进行求解，识别出路段的非拥堵时间段；
S2、提取出非拥堵时间段内的过车数据，对路口进口各单位时间段内的关键流向进行识 别，建立关键流向时间表；
S3、基于关键流向配置出协调干线，确定干线的协调控制时间段。
进一步地，步骤S1具体为，
S11、基于路网内的信控路口划分路段，即相邻信控路口之间为一路段；
S12、对步骤S11中划分的各路段统计时间段内单位时间的拥堵指数进行计算；其中，每条路段均包括上行和下行；
S13、由步骤S12所得拥堵指数来绘制时间-拥堵指数折线图，确定路段非拥堵时间段。
进一步地，步骤S12中，对步骤S11中划分的各路段统计时间段内单位时间的拥堵指数进行计算，具体为，与互联网数据对接，提取出统计时间段内全天各单位时间的交通状态，包括畅通、缓行、拥堵和严重拥堵四种，进而确定统计时间段内出现此种交通状态的总次数N
i，其中i表示交通状态，具体包括四种，即i为1代表畅通，i为2代表缓行，i为3代表拥堵，i为4代表严重拥堵；进而根据畅通、缓行、拥堵和严重拥堵的权重数值α
i进行计算，即拥堵指数为：
进一步地，步骤S2具体为，
S21、基于路口号牌识别设备提取出路口各进口道非拥堵时间段内的过车数据；
S22、识别出进口道各单位时间段内的关键流向；
S23、整合路口各进口道单位时间段内的关键流向，建立关键流向时间表。
进一步地，步骤S22具体为，基于过车数据统计出进口道各流向的单位时间段内的过车流量，进一步计算出各进口道内流向的交通需求比值q
mn，即：
式中：m为进口道，n为流向；Q
mn为单位时间段内进口道m流向n的交通流量；Q
m为单位时间段内进口道m总交通流量；同时若某一流向比例大于设定的流向阈值，则选定该流向为关键流向。
进一步地，步骤S3具体为，
S31、基于确定的路口方向识别上下游关联路口，判别交通需求平衡度，配置出单位时间段内的协调干线；
S32、整合各单位时间段内路口进口道关键流向和配置的协调干线，识别协调干线的合理性，确定协调干线的控制时间段；具体为，根据协调干线开始路口进口道的关键流向进行时 间段划分，若连续多个单位时间段内的存在一个路口的进口道关键流向不一，即配置的干线均为不同，则默认为该协调干线不适合配置，否则默认协调干线合理，且基于整合的时间段确定其协调控制时间段。
进一步地，步骤S31具体为，
S311、求解出交通需求平衡度γ，具体为，基于筛选的单位时间段，通过路口进口道的关键流向确定其在此流向的下游路口进口道，根据关键流向时间表确定该路口进口道的关键流向；进一步依托上游路口进口道关键流向的交通流量数值Q
mn上和下游关联进口道的关键流向交通流量数值Q
mn下，求解出交通需求平衡度γ：
S312、若交通需求平衡度γ大于设定的平衡阈值，则判定路口不可关联，否则判别路口可关联，将下游路口默认为上游路口，重复步骤S311直至单位时间段内协调干线配置完成。
一种采用上述任一项所述基于交通流数据的协调干线线路规划方法的基于交通流数据的协调干线线路规划配置系统，包括路口交通流识别模块和协调干线配置模块，
路口交通流识别模块：接入互联网数据和视频号牌识别采集的过车数据，确定各路口各信控时间段内的关键流向；
协调干线配置模块：基于路口交通流识别模块识别的关键流向，配置出协调干线及其协调控制时间段。
进一步地，路口交通流识别模块包括非拥堵时间识别单元和路口关键流向识别单元，
非拥堵时间识别单元：接入互联网的交通状态数据，采用上述任一项所述基于交通流数据的协调干线线路规划方法中步骤S1确定路网内各路段的非拥堵时间段，并将非拥堵时间段传输至路口关键流向识别单元；
路口关键流向识别单元：与路网内视频号牌识别设备对接，采用上述任一项所述基于交通流数据的协调干线线路规划方法中步骤S2确定各路口的关键流向，同时根据筛选的时间段展现出路口各进口道的关键流向，并在GIS电子地图中标注。
进一步地，协调干线配置模块包括干线绘制单元和控制时间段划分单元，
干线绘制单元：基于GIS电子地图确定协调干线的某一路口，根据筛选的时间段展示出该信号各进口道的关键流向及其相邻信控路口的关键流向，确定路口的协调方向，并依次配置出下游路口完成干线绘制，并将绘制的干线信息发送至控制时间段划分单元；根据上述任一项所述基于交通流数据的协调干线线路规划方法中步骤S3针对无法关联的路口进行预警；
控制时间段划分单元：将干线绘制单元绘制的协调干线存在的时间段进行整合，采用上述任一项所述基于交通流数据的协调干线线路规划方法中步骤S3确定协调干线协调可控的时间段，并进行列表展示。
本发明的有益效果是：该种基于交通流数据的协调干线线路规划方法及配置系统，基于互联网的交通状态数据识别出非拥堵时间段，即非饱和时间段，针对该时间段进行干线配置分析，避免了传统干线配置根据路网交通规划以及针对饱和时间段和非饱和时间段综合考虑各路口的协调方向，导致的协调干线效率低下的问题，从而提高了协调干线不同时间段的准确性，达到协调最优。本发明对不同时间段的干线进行配置识别分析，提高了协调干线实施效率，为区域信号协调优化提供了辅助支撑。
图1是本发明实施例基于交通流数据的协调干线线路规划方法的流程示意图。
图2是实施例中基于交通流数据的协调干线线路规划配置系统的说明框图。
下面结合附图详细说明本发明的优选实施例。
实施例
一种基于交通流数据的协调干线线路规划方法，将互联网数据和视频号牌识别设备的过车数据进行整合，依托非拥堵时间段内交通流数据确定关键流向，从而识别配置出各控制时间段的协调方向，进而规划配置出协调干线；如图1，具体步骤如下所示：
S1.基于互联网数据对路段上行与下行的拥堵指数进行求解，识别出路段的非拥堵时间段。
S11.基于路网内的信控路口划分路段，即相邻信控路口之间为一路段。
S12.对各路段(每条路段均包括上行和下行)统计时间段内单位时间的拥堵指数进行计算。具体来说，与互联网数据对接，提取出统计时间段内全天各单位时间的交通状态(包括畅通、缓行、拥堵和严重拥堵四种)，进而确定统计时间段内出现此种交通状态的总次数N
i，其中i表示交通状态，具体包括四种，即1(畅通)、2(缓行)、3(拥堵)、4(严重拥堵)；进而根据畅通、缓行、拥堵和严重拥堵的权重数值α
i进行计算，即拥堵指数为：
同时若路段有多种交通状态，如路段显示“拥堵-畅通-拥堵”则根据交通状态将路段划分为若干个小路段，分别对各小路段的拥堵指数进行求解，进而得到路段的拥堵指数，即 k＝∑k
j，其中j为若干小路段的数目。
一般情况下，统计时间段为周/月/季度，全天单位时间段为15min/30min/1hour，畅通、缓行、拥堵和严重拥堵的权重比值按固定比值确定。如选取周为统计单位，单位时间段内为15min，则基于物联网数据对每周内各15min的交通状态进行读取，畅通、缓行、拥堵和严重拥堵的权重α
i分别取0、0.5、1和2，以8:00-8:15为例，一周内，畅通的次数为1次、缓行次数为3次、拥堵为3次，严重拥堵为0次，则拥堵指数k＝10.5。
S13.绘制时间-拥堵指数折线图，确定路段非拥堵时间段(非饱和时间段)。
具体来说，整合路段单位时间内的拥堵指数，绘制出全日路段上行与下行时间-拥堵指数折线图，基于折线图趋势找出其拐点，并将其默认为拥堵时间段的开始时刻和结束时刻，从而确定出全日内的拥堵时间段，进一步剔除找到路段全天非拥堵时间段，即除了拥堵时间段以外的时间段。
一般情况下，可通过斜率或者标准差找寻拐点，同时全天的拥堵时间段总数一般以两段为主，即为早高峰时间段和晚高峰时间段，该时间段内无法配置干线协调方案。
S2.提取出非拥堵时间段内的过车数据，对路口进口各单位时间段内的关键流向进行识别，建立关键流向时间表。
S21.基于路口号牌识别设备提取出路口各进口道非拥堵时间段内的过车数据。具体来说，对接路网内号牌识别视频设备，提取出路口绑定号牌视频设备采集的过车数据，提取出路口各进口道非拥堵时间段的过车数据。
一般情况下，路口欠饱和状态(非拥堵)下，过车流量基本为实际交通需求，针对非拥堵欠饱和的交通流量识别出路口进口道各流向的交通需求。
S22.识别出进口道各单位时间段内的关键流向。具体来说，基于过车数据统计出进口道各流向的单位时间段内的过车流量，进一步计算出各进口道内流向的交通需求比值q
mn，即：
式中：m为进口道，n为流向；Q
mn为单位时间段内，进口道m流向n的交通流量；Q
m为单位时间段内，进口道m总交通流量。同时若某一流向比例大于设定的流向阈值，则选定该流向为关键流向。
一般情况下，流向阈值根据路口渠化特征由用户自行配置，如路口进口道存在左转、直行、右转三个流向，则流向阈值可取45％-55％，路口进口道只有左转、直行、右转中两个流向，即流向阈值可取55％-65％。
S23.整合建立关键流向时间表。具体来说，整合路口各进口道单位时间段内的关键流向，建立关键流向时间表，表中包含时间段、路口编号、进口道、关键流向方向，其中对于拥堵时间段，则关键流向方向为空。
如单位时间为15min时，其表格式样如下所示：
S3.基于关键流向配置出协调干线，确定干线的协调控制时间段。
S31.基于确定的路口方向识别上下游关联路口，判别交通需求平衡度，配置出单位时间段内的协调干线。
S311.求解出交通需求平衡度γ。具体来说，基于筛选的单位时间段，通过路口进口道的关键流向确定其在此流向的下游路口进口道，根据关键流向时间表确定该路口进口道的关键流向；进一步依托上游路口进口道关键流向的交通流量数值Q
mn上和下游关联进口道的关键流向交通流量数值Q
mn下，求解出交通需求平衡度γ，即：
S312.若交通需求平衡度γ大于设定的平衡阈值，则判定路口不可关联，否则判别路口可关联，将下游路口默认为上游路口，重复S311步骤直至单位时间段内协调干线配置完成。
一般情况下，平衡阈值由用户配置，数值可为120％-180％之间，若大于该平衡阈值，说明下游路口的关键流向不仅来自上游路口进口道的流量，还包括上游路口其他进口道的车流，则不可配置协调干线。
S32.整合各单位时间段内路口进口道关键流向和配置的协调干线，识别协调干线的合理性，确定协调干线的控制时间段。具体来说，根据协调干线开始路口进口道的关键流向进行时间段划分，若连续多个单位时间段内的存在一个路口的进口道关键流向不一，即配置的干线均为不同，则默认为该协调干线不适合配置，否则默认协调干线合理，且基于整合的时间 段确定其协调控制时间段。
如A路口南进口道自9:00-16:00的关键流向均为直行，且基于S31步骤配置的协调干线一致，则该条协调干线合理，且协调控制时间段为9:00-16:00；如A路口南进口道9:00-10:00与10:00-11:00的关键流向不一，则协调干线不合理。
实施例还提供一种基于交通流数据的协调干线线路规划配置系统，如图2，包括路口交通流识别模块和协调干线配置模块，实现协调干线及其控制时间段的配置。
路口交通流识别模块：该模块接入互联网数据和视频号牌识别采集的过车数据，确定各路口各信控时间段内的关键流向，具体包括非拥堵时间识别单元和路口关键流向识别单元。
非拥堵时间识别单元：接入互联网的交通状态数据，基于实施例上述基于交通流数据的协调干线线路规划方法的步骤S1确定路网内各路段的非拥堵时间段，并将非拥堵时间段传输至路口关键流向识别单元。
路口关键流向识别单元：与路网内视频号牌识别设备对接，依托实施例上述基于交通流数据的协调干线线路规划方法的步骤S2确定各路口的关键流向，同时根据筛选的时间段展现出路口各进口道的关键流向，并在GIS电子地图中标注。
协调干线配置模块：该模块基于路口交通流识别模块识别的关键流向，配置出协调干线及其协调控制时间段，具体包括干线绘制单元和控制时间段划分单元。
干线绘制单元：基于GIS电子地图确定协调干线的某一路口，根据筛选的时间段展示出该信号各进口道的关键流向及其相邻信控路口的关键流向，确定路口的协调方向，并依次配置出下游路口完成干线绘制，并将绘制的干线信息发送至控制时间段划分单元；同时系统可根据实施例上述基于交通流数据的协调干线线路规划方法的步骤S3针对无法关联的路口进行预警。
控制时间段划分单元：将干线绘制单元绘制的协调干线存在的时间段进行整合，基于实施例上述基于交通流数据的协调干线线路规划方法的步骤S3确定协调干线协调可控的时间段，并进行列表展示。
实施例的基于交通流数据的协调干线线路规划方法及配置系统，基于互联网数据的交通状态数据识别出非拥堵时间段，进而提取出路口各进口道非拥堵时间段的过车数据，从而有效识别出准确的关键流向，进一步对相邻路口进行关联分析，确定协调干线。
该种基于交通流数据的协调干线线路规划方法及配置系统，可根据时间段内路口各进口的关键流向自由配置协调干线，创新的评判了配置的协调干线是否合理，从而提出不同时间段的干线协调。
实施例的基于交通流数据的协调干线线路规划方法及配置系统，针对城市道路交通信号控制协调干线的干线规划配置问题现状，基于互联网数据识别出非拥堵时间段，从而提取出非拥堵时间段的过车数据，判别出路口进口道关键流向，分析出各路口之间关联关系，从而配置出协调干线及其控制时间段，提高了协调干线的配置效率，避免了传统主干道规划配置方法协调效率低下的问题，为区域信号协调提供了有效支撑。
Claims (10)
- 一种基于交通流数据的协调干线线路规划方法，其特征在于：将互联网数据和视频号牌识别设备的过车数据进行整合，依托非拥堵时间段内交通流数据确定关键流向，从而识别配置出各控制时间段的协调方向，进而规划配置出协调干线；包括以下步骤，S1、基于互联网数据对路段上行与下行的拥堵指数进行求解，识别出路段的非拥堵时间段；S2、提取出非拥堵时间段内的过车数据，对路口进口各单位时间段内的关键流向进行识别，建立关键流向时间表；S3、基于关键流向配置出协调干线，确定干线的协调控制时间段。
- 如权利要求1所述的基于交通流数据的协调干线线路规划方法，其特征在于：步骤S1具体为，S11、基于路网内的信控路口划分路段，即相邻信控路口之间为一路段；S12、对步骤S11中划分的各路段统计时间段内单位时间的拥堵指数进行计算；其中，每条路段均包括上行和下行；S13、由步骤S12所得拥堵指数来绘制时间-拥堵指数折线图，确定路段非拥堵时间段。
- 如权利要求2所述的基于交通流数据的协调干线线路规划方法，其特征在于：步骤S12中，对步骤S11中划分的各路段统计时间段内单位时间的拥堵指数进行计算，具体为，与互联网数据对接，提取出统计时间段内全天各单位时间的交通状态，包括畅通、缓行、拥堵和严重拥堵四种，进而确定统计时间段内出现此种交通状态的总次数N i，其中i表示交通状态，具体包括四种，即i为1代表畅通，i为2代表缓行，i为3代表拥堵，i为4代表严重拥堵；进而根据畅通、缓行、拥堵和严重拥堵的权重数值α i进行计算，即拥堵指数为：
- 如权利要求1所述的基于交通流数据的协调干线线路规划方法，其特征在于：步骤S2具体为，S21、基于路口号牌识别设备提取出路口各进口道非拥堵时间段内的过车数据；S22、识别出进口道各单位时间段内的关键流向；S23、整合路口各进口道单位时间段内的关键流向，建立关键流向时间表。
- 如权利要求4所述的基于交通流数据的协调干线线路规划方法，其特征在于：步骤S22具体为，基于过车数据统计出进口道各流向的单位时间段内的过车流量，进一步计算出 各进口道内流向的交通需求比值q mn，即：
式中：m为进口道，n为流向；Q mn为单位时间段内进口道m流向n的交通流量；Q m为单位时间段内进口道m总交通流量；同时若某一流向比例大于设定的流向阈值，则选定该流向为关键流向。 - 如权利要求1所述的基于交通流数据的协调干线线路规划方法，其特征在于：步骤S3具体为，S31、基于确定的路口方向识别上下游关联路口，判别交通需求平衡度，配置出单位时间段内的协调干线；S32、整合各单位时间段内路口进口道关键流向和配置的协调干线，识别协调干线的合理性，确定协调干线的控制时间段；具体为，根据协调干线开始路口进口道的关键流向进行时间段划分，若连续多个单位时间段内的存在一个路口的进口道关键流向不一，即配置的干线均为不同，则默认为该协调干线不适合配置，否则默认协调干线合理，且基于整合的时间段确定其协调控制时间段。
- 如权利要求6所述的基于交通流数据的协调干线线路规划方法，其特征在于：步骤S31具体为，S311、求解出交通需求平衡度γ，具体为，基于筛选的单位时间段，通过路口进口道的关键流向确定其在此流向的下游路口进口道，根据关键流向时间表确定该路口进口道的关键流向；进一步依托上游路口进口道关键流向的交通流量数值Q mn上和下游关联进口道的关键流向交通流量数值Q mn下，求解出交通需求平衡度γ：
S312、若交通需求平衡度γ大于设定的平衡阈值，则判定路口不可关联，否则判别路口可关联，将下游路口默认为上游路口，重复步骤S311直至单位时间段内协调干线配置完成。 - 一种采用权利要求1-7任一项所述基于交通流数据的协调干线线路规划方法的基于交通流数据的协调干线线路规划配置系统，其特征在于：包括路口交通流识别模块和协调干线配置模块，路口交通流识别模块：接入互联网数据和视频号牌识别采集的过车数据，确定各路口各信控时间段内的关键流向；协调干线配置模块：基于路口交通流识别模块识别的关键流向，配置出协调干线及其协调控制时间段。
- 如权利要求8所述的基于交通流数据的协调干线线路规划配置系统，其特征在于：路口交通流识别模块包括非拥堵时间识别单元和路口关键流向识别单元，非拥堵时间识别单元：接入互联网的交通状态数据，采用权利要求1-7任一项所述基于交通流数据的协调干线线路规划方法中步骤S1确定路网内各路段的非拥堵时间段，并将非拥堵时间段传输至路口关键流向识别单元；路口关键流向识别单元：与路网内视频号牌识别设备对接，采用权利要求1-7任一项所述基于交通流数据的协调干线线路规划方法中步骤S2确定各路口的关键流向，同时根据筛选的时间段展现出路口各进口道的关键流向，并在GIS电子地图中标注。
- 如权利要求8所述的基于交通流数据的协调干线线路规划配置系统，其特征在于：协调干线配置模块包括干线绘制单元和控制时间段划分单元，干线绘制单元：基于GIS电子地图确定协调干线的某一路口，根据筛选的时间段展示出该信号各进口道的关键流向及其相邻信控路口的关键流向，确定路口的协调方向，并依次配置出下游路口完成干线绘制，并将绘制的干线信息发送至控制时间段划分单元；根据权利要求1-7任一项所述基于交通流数据的协调干线线路规划方法中步骤S3针对无法关联的路口进行预警；控制时间段划分单元：将干线绘制单元绘制的协调干线存在的时间段进行整合，采用权利要求1-7任一项所述基于交通流数据的协调干线线路规划方法中步骤S3确定协调干线协调可控的时间段，并进行列表展示。
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| CN115063988A (zh) * | 2022-05-05 | 2022-09-16 | 北京联合大学 | 一种应急车辆优先的跨交通子区信号协同控制方法 |
| CN117593891A (zh) * | 2024-01-19 | 2024-02-23 | 长安大学 | 一种基于高速公路交通大数据的车流量分析系统及方法 |
Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109345031B (zh) * | 2018-10-26 | 2021-07-20 | 江苏智通交通科技有限公司 | 基于交通流数据的协调干线线路规划方法及配置系统 |
| CN109544925B (zh) * | 2018-11-30 | 2021-07-20 | 江苏智通交通科技有限公司 | 协调干线合理性分析及协调方式配置方法 |
| CN109859503B (zh) * | 2019-03-15 | 2021-07-13 | 公安部交通管理科学研究所 | 一种全网绿波协调线路自动识别方法、装置及系统 |
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| CN111986483A (zh) * | 2020-08-28 | 2020-11-24 | 上海宝康电子控制工程有限公司 | 基于电警数据碰撞实现道路拥堵状态研判处理的方法、装置及存储介质 |
| CN113345230B (zh) * | 2021-06-02 | 2023-01-03 | 江苏智通交通科技有限公司 | 一种协调干线管控问题研判的优化方法与优化系统 |
| CN114120647B (zh) * | 2021-11-26 | 2023-01-24 | 阿波罗智联(北京)科技有限公司 | 交通数据处理方法、装置、电子设备和介质 |
| CN116013083B (zh) * | 2023-01-10 | 2024-03-12 | 合肥工业大学 | 一种基于电子地图数据的路网常发性交通状态识别方法 |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102346964A (zh) * | 2010-08-05 | 2012-02-08 | 王学鹰 | 道路交通网络区域拥堵实时预测与智能管理系统 |
| WO2015159251A1 (en) * | 2014-04-16 | 2015-10-22 | Syntell Proprietary Limited | Method and system for adaptive traffic control |
| CN106856049A (zh) * | 2017-01-20 | 2017-06-16 | 东南大学 | 基于卡口号牌识别数据的关键交叉口需求集聚分析方法 |
| CN107730882A (zh) * | 2017-09-08 | 2018-02-23 | 上海电科市政工程有限公司 | 基于人工智能的道路拥堵预测系统及方法 |
| CN109345031A (zh) * | 2018-10-26 | 2019-02-15 | 江苏智通交通科技有限公司 | 基于交通流数据的协调干线线路规划方法及配置系统 |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN100543796C (zh) * | 2007-07-12 | 2009-09-23 | 公安部交通管理科学研究所 | 交通信号控制系统多关键路口优化方法 |
| CN103559795B (zh) * | 2013-11-07 | 2015-07-15 | 青岛海信网络科技股份有限公司 | 一种多策略多目标的自适应交通控制方法 |
| CN104835335A (zh) * | 2015-06-03 | 2015-08-12 | 常州市蓝涛物联网科技有限公司 | 路网交通优化控制系统和方法 |
| CN107316472B (zh) * | 2017-07-28 | 2020-05-01 | 广州市交通规划研究院 | 一种面向干道双向不同需求的动态协调控制方法 |
-
2018
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2019
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102346964A (zh) * | 2010-08-05 | 2012-02-08 | 王学鹰 | 道路交通网络区域拥堵实时预测与智能管理系统 |
| WO2015159251A1 (en) * | 2014-04-16 | 2015-10-22 | Syntell Proprietary Limited | Method and system for adaptive traffic control |
| CN106856049A (zh) * | 2017-01-20 | 2017-06-16 | 东南大学 | 基于卡口号牌识别数据的关键交叉口需求集聚分析方法 |
| CN107730882A (zh) * | 2017-09-08 | 2018-02-23 | 上海电科市政工程有限公司 | 基于人工智能的道路拥堵预测系统及方法 |
| CN109345031A (zh) * | 2018-10-26 | 2019-02-15 | 江苏智通交通科技有限公司 | 基于交通流数据的协调干线线路规划方法及配置系统 |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115063988A (zh) * | 2022-05-05 | 2022-09-16 | 北京联合大学 | 一种应急车辆优先的跨交通子区信号协同控制方法 |
| CN115063988B (zh) * | 2022-05-05 | 2023-06-02 | 北京联合大学 | 一种应急车辆优先的跨交通子区信号协同控制方法 |
| CN117593891A (zh) * | 2024-01-19 | 2024-02-23 | 长安大学 | 一种基于高速公路交通大数据的车流量分析系统及方法 |
| CN117593891B (zh) * | 2024-01-19 | 2024-05-07 | 长安大学 | 一种基于高速公路交通大数据的车流量分析系统及方法 |
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