WO2020192120A1 - 一种基于出行结构的城市路网诱导方案发布方法和系统 - Google Patents
一种基于出行结构的城市路网诱导方案发布方法和系统 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
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
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- the invention belongs to the technical field of urban road network traffic operation guidance release, and specifically relates to a method and system for issuing urban road network guidance schemes based on a travel structure.
- traffic guidance issuance is one of the indispensable means of modern intelligent traffic operation and management. It mainly provides urban road network traffic guidance information or instructions for road vehicles, and adjusts the road traffic status through vehicle traffic guidance.
- the reasonable allocation of demand in the road network is the goal, so as to achieve the purpose of alleviating traffic congestion and facilitating motor vehicle travel; but based on the unpredictability and randomness of traffic operation data, it may lead to the problem of poor traffic guidance release effects, especially real-time Changes in traffic flow require a real-time and effective traffic guidance release method and a corresponding guidance release generation organization to realize an efficient and practical traffic guidance solution.
- the purpose of the present invention is to propose a method and system for issuing urban road network guidance plan based on travel structure, implement global optimal guidance route search based on real-time traffic flow data, and determine the road network by analyzing the traffic travel structure of the road network
- the internal guidance plan issuance strategy in order to achieve the effect of the balanced distribution of road network demand, so that travelers can avoid congested road sections and improve the overall traffic efficiency of the road network.
- a method for issuing an urban road network guidance plan based on a travel structure including:
- step S1 includes:
- the spatio-temporal characteristic index includes: trajectory repetition coefficient, daily average number of trips, average daily length of stay in the road network, and departure time similarity; wherein the trajectory point repetition coefficient is used to measure the similarity of the passing trajectory, and the calculation formula for:
- Track point repetition coefficient number of different track points/number of days of appearance, track points refer to the bayonet recording points in the original historical traffic trajectory, and days of appearance refer to the number of days that a motor vehicle has a travel trajectory;
- Average number of trips per day total number of trips/number of days of appearance
- Average daily staying time on the road network total driving time/number of days of appearance, the total driving time is calculated based on the transit time of the complete trajectory corresponding to each motor vehicle;
- Departure time similarity number of trajectory start time nodes located in different time intervals/number of days of appearance; where, time interval refers to dividing 24 hours a day into several time intervals of equal length, and each interval corresponds to a time interval.
- the travel mode label includes a rigid demand group and a non-rigid demand group.
- the rigid demand group is a group of motor vehicles with a specified regularity; and the non-rigid demand group is a group of motor vehicles that do not have a specified regularity. group.
- step S2 the method for determining the travel mode of each road segment in the travel path set described in step S2 is:
- step S3 includes: searching for the upstream road section of each congested road section in the congested road section set S according to the road network topology, and setting a threshold K, and calculating the real-time traffic flow and maximum traffic of the upstream road section The capacity ratio v/c, if v/c ⁇ K, the upstream road section is included in the congested road section's influence range set Z s , and the search is further upstream; otherwise, the search is stopped.
- step S4 generating multiple guidance routes according to the real-time traffic operation conditions of the entire road network and each of the OD points on the travel structure of each component of the travel route set includes:
- step S5 includes:
- a travel structure-based urban road network guidance plan publishing system which is applied to the above-mentioned travel structure-based urban road network guidance plan publishing method.
- the system includes a data access module, a demand structure analysis module, and congestion.
- Recognition module, inducement path search module, inducement strategy generation module, inducement release module including:
- the data access module connects the smart bayonet system and the database through a designated interface to obtain the bayonet passing records, dynamically synchronize the real-time passing records of the smart bayonet system, and interact with the database;
- the demand structure analysis module which retrieves the original historical traffic trajectory from the data access module, is used to reconstruct the trajectory of motor vehicles, analyze the OD point-to-travel path set of the road network, and analyze the OD travel structure and the travel mode of the road section;
- a congestion identification module which reads real-time synchronization data from the access data access module, is used to identify congested road sections in the road network, generates the congested road section set S, and analyzes the impact range of the congested road sections;
- the guidance path search module obtains the real-time vehicle passing records of the smart bayonet system from the data access module, obtains the OD travel structure and the travel mode analysis results of the road section from the demand structure analysis module, and receives from the congestion recognition module Into the set of congested road sections; used to calculate the real-time remaining bearing capacity of the road section and the road section travel time; simultaneously generate multiple guidance paths for each of the OD point pairs; and the guidance path search model is set in the guidance path search module ;
- Guidance strategy generation module from the demand structure analysis module to access the OD point to analyze the results of the travel path set, OD travel structure, and road travel mode, from the congestion identification module to the congested road set and its influence range, and from the guidance path search module Enter the optimal plan, the sub-optimal plan and the remaining bearing capacity of the road section, determine the release location and the content of the optimal guidance plan, the sub-optimal guidance plan, and pass them to the guidance release module;
- the guidance release module is connected to the guidance strategy generation module and docked with the road guidance screen control card, and is used to publish the guidance plan output position and content of the guidance strategy generation module; transmit the guidance plan to the corresponding control card of the road section, Realize the release of the induction program.
- the system is composed of a data access module, a demand structure analysis module, a congestion recognition module, a guidance path search module, a guidance strategy generation module, and a guidance release module.
- the data access module reads the smart bayonet system to obtain the bayonet passing record of the motor vehicle, and dynamically synchronizes the real-time passing record of the smart bayonet system; at the same time, the data access module is also connected to the database and passes through each other Set up the interface for data interaction; the demand structure analysis module will reconstruct the trajectory of the motor vehicle, analyze the OD point of the road network to travel path set, and analyze the OD travel structure and the travel mode of the road section; identify the congestion in the road network by the congestion recognition module Road section, and analyze the impact range of the congested road section according to the congested road section; the guidance path search module calculates the real-time remaining bearing capacity of the road section and the road section travel time, and generates multiple guidance paths corresponding to each OD point pair; the guidance path is generated by the guidance strategy module The search module accesses the optimal plan, the sub-optimal plan and the remaining bearing capacity of the road section, determines the release position and the content of the optimal guide plan, the sub-optimal guide plan, and transmit
- FIG. 1 is a schematic flowchart of a method for issuing an urban road network guidance plan based on a travel structure in an embodiment of the present invention
- Fig. 2 is a schematic structural block diagram of the urban road network guidance plan issuing system based on the travel structure in an embodiment of the present invention.
- a method and system for issuing an urban road network guidance plan based on a travel structure are provided.
- the method provided by the present invention specifically includes the following steps:
- Step 1 Obtain the vehicle bayonet passing records of the entire road network within a specified time period, extract the original historical passing trajectory corresponding to each vehicle based on the bayonet passing record, and complete the original historical passing trajectory to obtain a complete history
- the traffic trajectory, and the travel mode label corresponding to each motor vehicle is obtained according to the complete historical traffic trajectory; specifically, the present invention also needs to determine whether the original historical traffic trajectory corresponding to each motor vehicle is complete in the actual operation process, if not complete , Reconstruction operation is performed through particle swarm algorithm to generate a complete historical traffic trajectory; at the same time, the spatial collection of a complete historical traffic trajectory is carried out for each vehicle one by one, and the historical travel time and space characteristic indexes of the EMU in a specified time period are calculated based on the spatial collection; Then, taking the spatio-temporal characteristic index as the attribute of each motor vehicle, the Gaussian mixture model is used to determine the travel mode label of the motor vehicle for all attributes in the specified time period.
- the unit of the bayonet passing record in the present invention is recorded in a unit of motor vehicle.
- the spatio-temporal characteristic indicators include: trajectory repetition coefficient, daily average number of trips, average daily length of stay in the road network, and departure time similarity; wherein the trajectory point repetition coefficient is used to measure the similarity of the passage trajectory, and each time and space
- the travel mode label includes rigid demand groups and non-rigid demand groups.
- the travel time and travel space range of motor vehicles have obvious constancy, that is, regularity.
- this group of motor vehicles constitutes a rigid demand group; on the contrary, the corresponding motor vehicle group constitutes a non-rigid demand group.
- Step 2 Construct the road network topology, determine the road network OD point pair set C according to the road network topology; determine the travel path set of the OD point pair based on the complete historical traffic trajectory; and determine the travel path according to the travel mode label corresponding to the motor vehicle Collect the travel mode of each component road section; specifically, obtain the traffic demand structure of each OD point pair according to the trajectory space collection and travel mode label corresponding to the vehicle, that is, the ratio of the sample size of the rigid group to the sample size of the non-rigid demand group;
- the sample size includes the daily average sample size and the average sample size in a short interval.
- the short interval refers to a number of time intervals divided within 24 hours a day.
- it can be an equal interval interval, such as 24 hours divided into 24 Equally spaced intervals: [0:00,1:00), [1:00,2:00),...; can also be non-equal spaced intervals: peak hours [6:00,11:00), [16: 30,19:30), flat peak time [0:00,6:00), [11:00,16:30), [19:30,24:00), the specific division can be set according to the actual situation, There are no restrictions and fixes here; then, analyze the daily change of the traffic demand structure of each OD point and the change pattern of each time interval within 24 hours a day; obtain the OD travel structure based on the travel path set, and then calculate the OD point The number of the right rigid demand groups and the number of non-rigid groups are allocated to the composition road sections in the travel route concentration, and the number of rigid demand groups and the number ratio of non-rigid demand groups in each composition road section are calculated, and the number of road sections is determined based on the number ratio. Travel mode, the induced release strategy formulated in this way can be more adapted to the traffic
- Step 3 Obtain real-time traffic flow data including flow, speed, and headway corresponding to the travel path set, and based on the traffic flow data to correspond to the congested road sections in the travel path set, and generate a congested road section set S and the impact of each congested road section Range set Z s , where s refers to any element in the congested road section set S; specifically search for the upstream road section of each congested road section in the congested road section set S according to the road network topology, and set a threshold K, and calculate the upstream road section
- the specific traffic flow of each section of the road in the future can be used as a basis for formulating guidance and release strategies for motor vehicles traveling on the road network.
- Step 4 Construct a globally optimal guidance route search model based on the congested road section set S, and generate multiple guidance routes based on the real-time traffic operation of the entire road network and the travel structure of each component road section of the travel route set of each OD point pair; Among them, the specific steps of generating multiple induction paths for each OD point pair are as follows:
- the corresponding paths are selected in the effective path set P in turn, and the traffic flow is accumulated for each path Set the cumulative upper limit of traffic flow to 0.9Q ⁇ , if the cumulative value of route traffic flow Then the ending path is selected into the effective path set P, and all paths in the effective path set are determined; then, based on the effective path set
- Step 5 Determine the guidance release strategy according to the travel structure, and screen the optimal path guidance plan among the multiple guidance paths between OD point pairs; specifically, filter out all OD point pair sets that contain congested road sections in the effective path set P Calculate the corresponding number of rigid demand groups for each OD point pair according to the ratio of the number of rigid demand groups to the number of non-rigid demand groups in the travel structure, and select the OD point pair corresponding to the highest number of rigid demand groups to release the optimal guidance Calculate the number of real-time rigid demand groups and the number of non-rigid demand groups on the road segment according to the travel mode of each road segment in the set Z s of the impact range of the congested road segment; select the remaining number of each road segment For sections with low carrying capacity and a high number of rigid demand groups, the optimal guidance route will be released, and the remaining sections will be issued with the sub-optimal guidance route.
- the present invention also proposes a travel structure-based urban road network guidance plan publishing system, which is applied to the urban road network guidance plan publishing method based on the travel structure. See Figure 2.
- the system includes a data access module, a demand structure analysis module, a congestion recognition module, an induction path search module, an induction strategy generation module, and an induction release module; among them, the data access module connects the smart bayonet system and the database through a designated interface for Acquire the bayonet passing record, dynamically synchronize the real-time passing record of the smart bayonet system, and interact with the database;
- the demand structure analysis module retrieves the original historical passing trajectory from the data access module for checking the vehicle trajectory Reconstruction, road network OD point-to-travel path set analysis, and OD travel structure and travel mode analysis of road sections; congestion recognition module, read real-time synchronization data from the access data access module, used to identify congested road sections in the road network , Generate the set S of congested road sections, and analyze
- the system is composed of a data access module, a demand structure analysis module, a congestion recognition module, a guidance path search module, a guidance strategy generation module, and a guidance release module.
- the data access module reads the smart bayonet system to obtain the bayonet passing record of the motor vehicle, and dynamically synchronizes the real-time passing record of the smart bayonet system; at the same time, the data access module is also connected to the database and passes through each other Set up the interface for data interaction; the demand structure analysis module will reconstruct the trajectory of the motor vehicle, analyze the OD point of the road network to travel path set, and analyze the OD travel structure and the travel mode of the road section; identify the congestion in the road network by the congestion recognition module Road section, and analyze the impact range of the congested road section according to the congested road section; the guidance path search module calculates the real-time remaining bearing capacity of the road section and the road section travel time, and generates multiple guidance paths corresponding to each OD point pair; the guidance path is generated by the guidance strategy module The search module accesses the optimal plan, the sub-optimal plan and the remaining bearing capacity of the road section, determines the release position and the content of the optimal guide plan, the sub-optimal guide plan, and transmit
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Abstract
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Claims (9)
- 一种基于出行结构的城市路网诱导方案发布方法,其特征在于,所述方法包括:S1、获取指定时间段内全路网机动车卡口过车记录,基于所述卡口过车记录提取对应每一机动车的原始历史通行轨迹,对原始历史通行轨迹进行完整性重构得到完整历史通行轨迹,并根据所述完整历史通行轨迹得到与每一机动车对应的出行模式标签;S2、构建路网拓扑结构,根据所述路网拓扑结构确定路网OD点对集合C;并基于所述完整历史通行轨迹确定所述OD点对的出行路径集,并根据机动车对应的出行模式标签确定出行路径集各组成路段的出行模式;S3、获取与所述出行路径集对应的包含流量、速度、车头时距的实时交通流量数据,基于所述交通流量数据对应所述出行路径集中的拥堵路段,并生成拥堵路段集合S以及所述每一个拥堵路段对应的影响范围集合Z s,其中s指代拥堵路段集合S中的任一个元素;S4、基于所述拥堵路段集合S构建全局最优的诱导路径搜索模型,并根据全路网实时的交通运行情况及每一所述OD点对的所述出行路径集的各组成路段出行结构生成多条诱导路径;S5、根据所述出行结构确定诱导发布策略,并筛选所述OD点对间的多条诱导路径中的最优路径诱导方案。
- 如权利要求1所述的基于出行结构的城市路网诱导方案发布方法,其特征在于,步骤S1包括:S11、判断每一机动车对应的所述原始历史通行轨迹是否完整,若不完整,通过粒子群算法进行重构操作,生成完整的通行轨迹;S12、对每一机动车逐一进行所述完整历史通行轨迹的空间汇集,基于所述空间汇集计算机动车在所述指定时间段内的历史出行时空特征指标;S13、将所述时空特征指标作为每一机动车的属性,采用高斯混合模型对 所述指定时间段内所有所述属性确定机动车的出行模式标签。
- 如权利要求2所述的基于出行结构的城市路网诱导方案发布方法,其特征在于,所述时空特征指标包括:轨迹重复系数、日均出行次数、路网日均逗留时长和出发时刻相似度;其中,所述轨迹点重复系数用于衡量通行轨迹的相似性,计算公式为:轨迹点重复系数=不同轨迹点数量/出现天数,轨迹点是指所述原始历史通行轨迹中的卡口记录点,出现天数指机动车存在出行轨迹的天数;日均出行次数=总出行次数/出现天数;路网日均逗留时长=总行驶时长/出现天数,总行驶时长依据每一机动车对应的完整轨迹的通行时长统计得到;出发时刻相似度=位于不同时间间隔内的轨迹起始时间节点数量/出现天数;其中,时间间隔是指将一日24小时划分为等长的若干时间区间,每一区间对应一个时间间隔。
- 如权利要求2所述的基于出行结构的城市路网诱导方案发布方法,其特征在于,所述出行模式标签包括刚性需求群体和非刚性需求群体,所述刚性需求群体为具有指定规律性的出行机动车群体;所述非刚性需求群体为不具有指定规律性的出行机动车群体。
- 如权利要求4所述的基于出行结构的城市路网诱导方案发布方法,其特征在于,步骤S2所述的确定出行路径集各组成路段的出行模式方法为:S21、根据机动车对应的所述轨迹空间汇集和所述出行模式标签得到每一所述OD点对的交通需求结构;S22、基于所述交通需求结构将所述OD点对的所述刚性需求群体的数量和非刚性群体的数量分配至所述出行路径集中的组成路段,并计算每一所述组成路段中所述刚性需求群体的数量和所述非刚性需求群体的数量比例,得到所述出行路段的出行模式。
- 如权利要求1所述的基于出行结构的城市路网诱导方案发布方法,其特征在于,步骤S3包括:根据所述路网拓扑结构搜索所述拥堵路段集合S中每一拥堵路段的上游路段,并设定一阈值K,并计算所述上游路段的实时交通流量与最大通行能力的比值v/c,若v/c<K,则将所述上游路段纳入所述拥堵路段的影响范围集合Z s,并进一步向上游搜索;否则,停止搜索。
- 如权利要求5所述的基于出行结构的城市路网诱导方案发布方法,其特征在于,步骤S4中所述根据全路网实时的交通运行情况及每一所述OD点对所述出行路径集的各组成路段出行结构生成多条诱导路径,包括:S42、根据所述完整历史通行轨迹从所述出行路径集中筛选出有效路径集P:S421、计算每一所述OD点对对应路径的流量q r,以及总流量Q δ=∑q r,δ表示所述OD点对的序号,且δ∈C;S43、基于所述有效路径集P,从所述卡口过车记录中调取设定时间间隔内所述路径的过车记录,并计算机动车在每一所述OD点对的平均行使时间T δ;S45、采用所述诱导路径搜索模型针对每一所述OD点对同时生成多条诱导路径。
- 如权利要求7所述的基于出行结构的城市路网诱导方案发布方法,其特征在于,步骤S5包括:S51、在所述有效路径集P中筛选出包含拥堵路段的所有所述OD点对集合,根据所述出行结构中所述刚性需求群体的数量与所述非刚性需求群体的数量比例计算每一所述OD点对的所述刚性需求群体对应数量,并筛选出所述刚性需求群体的数量最高所对应的所述OD点对发布最优诱导路径,其余所述OD点对发布次优诱导路径;S52、根据所述拥堵路段的影响范围集合Z s中各路段的出行模式,计算路段实时的所述刚性需求群体的数量与所述非刚性需求群体的数量;选择各路段的所述剩余承载力低且所述刚性需求群体数量高的路段,发布最优诱导路径,其余路段发布次优诱导路径。
- 一种基于出行结构的城市路网诱导方案发布系统,应用于权利要求1-8任一项所述的基于出行结构的城市路网诱导方案发布方法,其特征在于,所述系统包括数据接入模块、需求结构分析模块、拥堵识别模块、诱导路径搜索模块、诱导策略生成模块、诱导发布模块,其中:数据接入模块,通过指定接口连接智能卡口系统与数据库,用于获取卡口过车记录,动态同步所述智能卡口系统实时的过车记录,并与数据库进行数据交互;需求结构分析模块,从所述数据接入模块调取原始历史通行轨迹,用于对机动车轨迹重构、路网OD点对出行路径集分析,以及OD出行结构与路段的出行模式分析;拥堵识别模块,从所述接入数据接入模块读取实时同步数据,用于识别路网内的拥堵路段,生成所述拥堵路段集S,并分析拥堵路段影响范围;诱导路径搜索模块,从所述数据接入模块获取所述智能卡口系统实时的过车记录,从所述需求结构分析模块获取OD出行结构与路段的出行模式分析结果,从所述拥堵识别模块接入拥堵路段集;用于计算实时的路段剩余承载力与路段行程时间;针对每一个所述OD点对同时生成多条诱导路径;且所述诱导路径搜索模型设置在所述诱导路径搜索模块内;诱导策略生成模块,从需求结构分析模块接入OD点对出行路径集以及OD出行结构、路段出行模式的分析结果,从拥堵识别模块接入拥堵路段集及其影响范围,从诱导路径搜索模块接入诱导路径的最优方案、次优方案以及路段剩余承载力,确定最优诱导方案、次优诱导方案的发布位置以及发布内容,并传递至所述诱导发布模块;诱导发布模块,连接所述诱导策略生成模块,并与道路诱导屏控制卡对接,用于将所述诱导策略生成模块输出的诱导方案发布位置、内容;将诱导方案传输至路段相应的控制卡,实现诱导方案的发布。
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