WO2019028809A1 - Traffic data processing method and vehicle-mounted client - Google Patents

Traffic data processing method and vehicle-mounted client Download PDF

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Publication number
WO2019028809A1
WO2019028809A1 PCT/CN2017/097019 CN2017097019W WO2019028809A1 WO 2019028809 A1 WO2019028809 A1 WO 2019028809A1 CN 2017097019 W CN2017097019 W CN 2017097019W WO 2019028809 A1 WO2019028809 A1 WO 2019028809A1
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Prior art keywords
traffic
data
adjacent road
node
traffic data
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PCT/CN2017/097019
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French (fr)
Chinese (zh)
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阳光
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深圳配天智能技术研究院有限公司
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Priority to CN201780092637.XA priority Critical patent/CN110800032A/en
Priority to PCT/CN2017/097019 priority patent/WO2019028809A1/en
Publication of WO2019028809A1 publication Critical patent/WO2019028809A1/en

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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
    • G08G1/0969—Systems involving transmission of navigation instructions to the vehicle having a display in the form of a map

Definitions

  • the present invention relates to the field of communications, and in particular, to a traffic data processing method and an in-vehicle client.
  • the cloud server refers to a database that is optimized or deployed into a virtual computing environment.
  • the cloud server stores all traffic data for the road on which the vehicle is currently traveling. But when the in-vehicle system gets traffic data through the cloud, there are two big problems:
  • the prior art utilizes the buffering method to cache the cloud data to the local database of the in-vehicle system, and then provides the vehicle to the vehicle, and the vehicle uses the data buffered by the cloud to travel.
  • the prior art uses the buffering method to cache the data of the cloud server to the local database of the in-vehicle system, and the cloud data of the local database cached to the in-vehicle system may be incorrect due to the sudden jump of the location, but the in-vehicle system cannot be known at this time. Whether the currently buffered data is correct.
  • the embodiment of the invention provides a traffic data processing method and an in-vehicle client, which are used for solving the problem of the correct rate of the in-vehicle system buffering from the cloud server to the local data.
  • a first aspect of the embodiments of the present invention provides a traffic data processing method, including:
  • the first traffic node being a nearest traffic node that the target vehicle has traveled
  • each of the first traffic data data is traffic data of a first road segment on each adjacent road segment, where the first road segment is the middle and the adjacent road segment a section where the distance of the first traffic node is a preset distance;
  • the second traffic data is traffic data collected by the first traffic node that the target vehicle has traveled to the current location of the target vehicle;
  • the traffic data of the corresponding adjacent road segment is acquired from the cloud server according to the probability that the target vehicle is in the adjacent road segments.
  • the at least two road segments connected to the first traffic node may be determined first, where A traffic node is located on one side of the at least two road segments, and the traffic nodes on the other side of each of the at least two road segments are determined as at least two second traffic nodes.
  • all the road segments connected to the first node may be determined, and the all road segments include at least two a road segment, acquiring all traffic nodes on the other side of all road sections connected to the first traffic node, acquiring driving direction data or destination data of the target vehicle, according to the driving direction data or the destination data according to preset rules At least two traffic nodes are selected from all traffic nodes.
  • the in-vehicle client may determine the target when acquiring the traffic data of the corresponding adjacent road segment from the cloud server according to the probability that the target vehicle is in each adjacent road segment.
  • the probability of the vehicle in each adjacent road segment acquires the traffic data of the adjacent road segment with the highest probability from the cloud server.
  • the traffic data of the adjacent road segment with the highest probability is determined as the traffic data of the corresponding adjacent road segment.
  • the in-vehicle client may determine the target when acquiring the traffic data of the responding adjacent road segment from the cloud server according to the probability that the target vehicle is in each adjacent road segment.
  • the visual data of the set adjacent road segments is determined as the traffic data of the corresponding adjacent road segments.
  • the in-vehicle client may use the traffic data of the corresponding adjacent road segment as the traffic data used by the target vehicle.
  • a second aspect of the embodiments of the present invention provides an in-vehicle client, including:
  • a central processing unit a storage medium, and an input and output interface
  • the program medium is stored on the storage medium, and the central processor is configured to invoke the program code to perform the following steps:
  • the first traffic node being a nearest traffic node that the target vehicle has traveled
  • each first traffic data is traffic data of a first road segment on each adjacent road segment, wherein the first road segment is in the adjacent road segment and the a section of the first traffic node whose distance is a preset distance;
  • the second traffic data is traffic data collected by the first traffic node that the target vehicle has traveled to the current location of the target vehicle;
  • the traffic data of the corresponding adjacent road segment is acquired from the cloud server according to the probability that the target vehicle is in the adjacent road segments.
  • the central processor is further configured to invoke the program code to perform the following steps:
  • a traffic node on the other side of each of the at least two road segments is determined as the at least two second traffic nodes.
  • the central processor is further configured to invoke the program code to perform the following steps:
  • the central processor is further configured to invoke the program code to perform the following steps:
  • the central processor is further configured to invoke the program code to perform the following steps:
  • the visual data of the adjacent road segments whose probability reaches a preset value is determined as the traffic data of the corresponding adjacent road segments.
  • the central processor is further configured to invoke the program code to perform the following steps:
  • the traffic data of the corresponding adjacent road segment is used as traffic data used by the target vehicle.
  • the vehicle-mounted client in the present invention uses the acquired traffic data and the collected traffic data to determine the target vehicle in each adjacent road segment.
  • the probability of obtaining the traffic data of the corresponding adjacent road segment from the cloud server according to the probability of the target vehicle in the adjacent road segment thereby improving the correctness of the traffic data used as the target vehicle, that is, improving the sudden jump at the positioning position When it is out of time, it is used as the correctness of the traffic data of the target vehicle.
  • FIG. 1 is a schematic diagram of an embodiment of a method for processing traffic data according to an embodiment of the present invention
  • FIG. 2 is a schematic diagram of an embodiment of an in-vehicle client according to an embodiment of the present invention
  • FIG. 3 is a schematic diagram of a first traffic point, a second traffic node, second traffic data, and a location of a target vehicle in an embodiment of the present invention
  • FIG. 4 is a schematic structural diagram of an in-vehicle client according to an embodiment of the present invention.
  • an embodiment of a method for processing traffic data in an embodiment of the present invention includes:
  • the vehicle-mounted client determines a first traffic node, the first traffic node is a traffic node that the target vehicle has traveled, and the traffic node connects at least three road segments. , that is, the road section that has already traveled and the two road sections that are not traveling.
  • the in-vehicle client may determine, according to the first traffic node, at least two second traffic nodes connected to the first traffic node.
  • the adjacent road segment refers to a road segment between the first traffic node and each of the second traffic nodes.
  • the traffic data of the first road segment on each adjacent road segment may be obtained from the cloud server, where the first road segment is a distance from the first traffic node in the adjacent road segment.
  • the distance segment is set, and the visual data of the first road segment on each adjacent road segment is used as the first traffic data of each adjacent road segment, and the cloud server includes the cloud database, and the cloud server and the target vehicle are connected by wireless.
  • the traffic data includes visual data and other data such as weather data, driving direction data, driving speed data, and altitude data of the current road section.
  • the target vehicle collects traffic data and saves it in real time during the running process.
  • the second traffic data refers to traffic data collected by the target vehicle traveling from the first traffic node to the current location of the target vehicle.
  • the in-vehicle client after determining the at least two first traffic data and the second traffic data, separately performs the similarity calculation on the second traffic data and each of the first traffic data to obtain the second traffic data and each The similarity of the first traffic data, thereby obtaining the matching degree of the second traffic data with each of the first traffic data, and then calculating the matching degree of the second traffic data and each of the first traffic data to calculate that the target vehicle is located in each neighborhood The probability in the road segment.
  • the similarity between the second traffic data and the first traffic data may be obtained by performing similarity calculation on the sub-data in the second traffic data and the corresponding sub-data in the first traffic data. That is, the second traffic data and some key data in each first traffic data may be extracted, and the key data in the second traffic data is compared with the key data in each first traffic data, and the comparison result may be Determining the probability of the target vehicle in each adjacent road segment, for example, the similarity between the picture of each location stored in the database of the cloud server and the picture collected by the target vehicle at a corresponding distance, and then integrating according to the similarities to determine the target vehicle is In each adjacent section Probability.
  • the vehicle-mounted client may acquire the probability of the corresponding adjacent road segment from the cloud server according to the probability of the target vehicle in each adjacent road segment, and may acquire the target vehicle in each neighborhood.
  • the traffic data corresponding to the road segment with the highest probability in the road segment can also obtain the traffic data corresponding to the road segment whose target vehicle has a preset probability value in each adjacent road segment.
  • the in-vehicle client may determine the first traffic node, and determine, according to the first traffic node, at least two second traffic nodes connected to the first traffic node; The first traffic node and the at least two second traffic nodes determine at least two adjacent road segments; acquire at least two first traffic data; acquire second traffic data; determine the target according to the at least two first traffic data and the second traffic data The probability of the vehicle in each adjacent road segment; the visual data of the corresponding adjacent road segment is obtained according to the probability of the target vehicle in each adjacent road segment.
  • the vehicle-mounted client in the present invention uses the acquired traffic data and the collected traffic data to determine the target vehicle in each adjacent road segment.
  • the probability of obtaining the traffic data of the corresponding adjacent road segment from the cloud server according to the probability of the target vehicle in the adjacent road segment thereby improving the correctness of the traffic data used as the target vehicle, that is, improving the sudden jump at the positioning position When it is out of time, it is used as the correctness of the traffic data of the target vehicle.
  • another embodiment of a method for processing traffic data in an embodiment of the present invention includes:
  • the vehicle-mounted client may determine the first traffic node, the first traffic node is a traffic node that the target vehicle has traveled, and the traffic node is connected with at least three The road section, that is, the road section that has already traveled and the two road sections that are not traveling.
  • the in-vehicle client may first determine all the road segments (at least two) connected to the first traffic node, and determine the traffic nodes on the other side of all the road segments connected to the first traffic node. For the second traffic node, the second traffic node connects at least three road segments.
  • the in-vehicle client may first determine all the road segments (at least two) connected to the first traffic node, and acquire the traffic nodes on the other side of all the road segments connected to the first traffic node.
  • the in-vehicle client further acquires driving direction data or destination data of the target vehicle, and selects at least two of all the traffic nodes connected to the first traffic node according to the driving direction data or the destination data of the target vehicle.
  • the traffic node acts as a second traffic node. For example, at least two traffic nodes in one of the above-mentioned traffic nodes in one sector-shaped area are determined as second traffic nodes, which are sector-shaped regions whose axes of travel are the axes of the target vehicle.
  • the sector-shaped area being a sector-shaped area with the direction of the target vehicle's current position pointing to the destination as an axis.
  • the adjacent road segment refers to a road segment between the first traffic node and each of the second traffic nodes.
  • the traffic data of the first road segment on each adjacent road segment may be obtained from the cloud server, where the first road segment is a distance from the first traffic node in the adjacent road segment.
  • the distance segment is set, and the visual data of the first road segment on each adjacent road segment is used as the first traffic data of each adjacent road segment.
  • the traffic data includes visual data and other data such as weather data, driving direction data, driving speed data, and altitude data of the current road section.
  • the target vehicle collects traffic data and saves it in real time during the running process.
  • the second traffic data refers to visual data collected by the first traffic node that the target vehicle has traveled to the current location of the target vehicle.
  • FIG. 3 is the first traffic point, the second traffic node, and the second intersection.
  • a schematic diagram of the pass data and the location of the target vehicle wherein the target vehicle may be any location above any one of the first traffic node and the second traffic node, the first traffic node being the nearest one of the traffic nodes
  • the second traffic node is a traffic node connected to the first traffic node
  • the second traffic data is traffic data of the road segment between the first traffic node and the current location of the target vehicle, where the first traffic data is the first traffic node and the second traffic node. Traffic data of a section of the road between the traffic nodes that is a preset distance from the first traffic node.
  • the in-vehicle client after determining the at least two first traffic data and the second traffic data, separately performs the similarity calculation on the second traffic data and each of the first traffic data to obtain the second traffic data and each The similarity of the first traffic data, thereby obtaining the matching degree of the second traffic data with each of the first traffic data, and then calculating the matching degree of the second traffic data and each of the first traffic data to calculate that the target vehicle is located in each neighborhood The probability in the road segment.
  • the similarity between the second traffic data and the first traffic data may be obtained by performing similarity calculation on the sub-data in the second traffic data and the corresponding sub-data in the first traffic data. That is, the second traffic data and some key data in each first traffic data may be extracted, and the key data in the second traffic data is compared with the key data in each first traffic data, and the comparison result may be Determining the probability of the target vehicle in each adjacent road segment, for example, the similarity between the picture of each location stored in the database of the cloud server and the picture collected by the target vehicle at a corresponding distance, and then integrating according to the similarities to determine the target vehicle is Probability in each adjacent road segment.
  • the vehicle-mounted client may determine the adjacent road segment with the highest probability among the target vehicles in each adjacent road segment, and obtain the visual data corresponding to the adjacent road segment with the highest probability from the cloud server.
  • the visual data of the adjacent road segment with the highest probability is used as the target data of the target vehicle.
  • the vehicle client can also determine the probability of the target vehicle in each adjacent road segment. After that, the neighboring road segment whose target vehicle has a probability of reaching a preset value in each adjacent road segment can be obtained, and the visual data of the adjacent road segment whose probability reaches the preset value is acquired from the cloud server, and the visual data of the adjacent road segment whose probability reaches the preset value is obtained. As the target data of the target vehicle.
  • the vehicle-mounted client may use the traffic data of the corresponding adjacent road segment as the traffic data used by the target vehicle.
  • the in-vehicle client may determine the first traffic node, and determine, according to the first traffic node, at least two second traffic nodes connected to the first traffic node; The first traffic node and the at least two second traffic nodes determine at least two adjacent road segments; acquire at least two first traffic data; acquire second traffic data; determine the target vehicle according to the at least two first traffic data and the second traffic data The probability in each adjacent road segment; the visual data of the corresponding adjacent road segment is obtained according to the probability of the target vehicle in each adjacent road segment, and the traffic data of the corresponding adjacent road segment is used as the traffic data used by the target vehicle.
  • the vehicle-mounted client in the present invention uses the acquired traffic data and the collected traffic data to determine the target vehicle in each adjacent road segment.
  • the probability of obtaining the traffic data of the corresponding adjacent road segment from the cloud server according to the probability of the target vehicle in the adjacent road segment thereby improving the correctness of the traffic data used as the target vehicle, that is, improving the sudden jump at the positioning position When it is out of time, it is used as the correctness of the traffic data of the target vehicle.
  • FIG. 4 is a schematic structural diagram of an in-vehicle client according to an embodiment of the present invention.
  • the in-vehicle client 400 may generate a large difference due to different configurations or performances, and may include one or more central processing units ( Central processing units (CPU) 422 (eg, one or more processors), one or more storage media 430 for storing applications 442 or data 444 (the storage medium may be one or one storage device in Shanghai, or A temporary storage device such as one or more memories may also be used for one or one hard disk, or one or more memories and a hard disk, which are not limited herein.
  • the storage medium 430 may be short-term storage or persistent storage.
  • the program stored on the storage medium 430 can include a series of instruction operations in the onboard client.
  • central processor 422 can be configured to communicate with storage medium 430 to perform a series of instruction operations in storage medium 430 on vehicle-mounted client 400.
  • the in-vehicle client 400 may further include one or more input and output interfaces 458 (the input and output interfaces may be one or more wired or wireless network interfaces, or other input and output interfaces, which are not limited herein), and/or One or more operating systems 441, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, and the like.
  • the steps performed by the in-vehicle client in the above embodiments may be based on the in-vehicle client structure shown in FIG.
  • the disclosed system, apparatus, and method may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • there may be another division manner for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
  • the integrated unit if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium.
  • the storage medium includes instructions for causing a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention.
  • the foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like. .

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
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Abstract

Provided are a traffic data processing method and vehicle-mounted client, used for resolving the problem of correct rate of traffic data cached locally by a vehicle-mounted system from a cloud server. The method comprises: determining a first traffic node (101); according to the first traffic node, determining at least two second traffic nodes connected to the first traffic node (102); according to the first traffic node and the at least two second traffic nodes, determining at least two adjacent road sections (103); obtaining at least two first traffic data from the cloud server (104); obtaining second traffic data (105); according to the at least two first traffic data and second traffic data, determining the probability that a target vehicle is in each of the adjacent road sections (106); according to the probability that the target vehicle is in each of the adjacent road sections, obtaining from the cloud server the traffic data of a corresponding adjacent road section (107).

Description

一种交通数据处理方法及车载客户端Traffic data processing method and vehicle client 技术领域Technical field
本发明涉及通信领域，尤其涉及一种交通数据处理方法及车载客户端。The present invention relates to the field of communications, and in particular, to a traffic data processing method and an in-vehicle client.
背景技术Background technique
随着汽车的普及，越来越多的汽车开始配备车载***。当汽车在行驶过程中，车载***需要从云端服务器获取交通数据，帮助车载***提供准确的地图，地理信息，清晰的行进路线，云端服务器是指被优化或部署到一个虚拟计算环境中的数据库，云端服务器存储有车辆当前所行驶道路的所有交通数据。但是当车载***通过云端获取交通数据时，有两个大问题：With the popularity of automobiles, more and more cars are beginning to be equipped with in-vehicle systems. When the car is in motion, the in-vehicle system needs to obtain traffic data from the cloud server to help the in-vehicle system provide accurate maps, geographic information, and clear travel routes. The cloud server refers to a database that is optimized or deployed into a virtual computing environment. The cloud server stores all traffic data for the road on which the vehicle is currently traveling. But when the in-vehicle system gets traffic data through the cloud, there are two big problems:
1、当定位不够准确时，云端服务器提供的数据无法当成可供参考的数据；1. When the positioning is not accurate enough, the data provided by the cloud server cannot be regarded as data for reference;
2、数据传输延时，导致即使获取准确的位置也无法有效使用云端数据。2, data transmission delay, resulting in the use of cloud data can not be effectively used even if the location is accurate.
针对这两个问题，现有技术利用缓冲方式，将云端数据先缓存至车载***本地数据库，然后提供给车辆，车辆使用该云端缓冲的数据进行行驶。For these two problems, the prior art utilizes the buffering method to cache the cloud data to the local database of the in-vehicle system, and then provides the vehicle to the vehicle, and the vehicle uses the data buffered by the cloud to travel.
但是，现有技术利用缓冲方式将云端服务器的数据缓存到车载***本地数据库，有可能由于定位位置突然跳离，导致缓存到车载***本地数据库的云端数据不正确，但是此时车载***是无法获知当前缓冲的数据是否正确。However, the prior art uses the buffering method to cache the data of the cloud server to the local database of the in-vehicle system, and the cloud data of the local database cached to the in-vehicle system may be incorrect due to the sudden jump of the location, but the in-vehicle system cannot be known at this time. Whether the currently buffered data is correct.
发明内容Summary of the invention
本发明实施例提供了一种交通数据处理方法及车载客户端，用于解决车载***从云端服务器缓存到本地的数据的正确率问题。The embodiment of the invention provides a traffic data processing method and an in-vehicle client, which are used for solving the problem of the correct rate of the in-vehicle system buffering from the cloud server to the local data.
本发明实施例的第一方面提供一种交通数据处理方法，包括：A first aspect of the embodiments of the present invention provides a traffic data processing method, including:
确定第一交通节点，所述第一交通节点是目标车辆行驶过的最近的交通节点；Determining a first traffic node, the first traffic node being a nearest traffic node that the target vehicle has traveled;
根据所述第一交通节点确定与所述第一交通节点相连的至少两个第二交通节点；Determining, according to the first traffic node, at least two second traffic nodes connected to the first traffic node;
根据所述第一交通节点以及所述至少两个第二交通节点确定至少两个邻近路段，所述至少两个邻近路段为所述第一交通节点与每个第二交通节点之间的路段； Determining at least two adjacent road segments according to the first traffic node and the at least two second traffic nodes, the at least two adjacent road segments being a road segment between the first traffic node and each second traffic node;
从云端服务器获取至少两个第一交通数据，每个第一交通数据数据为相应的每个邻近路段上的第一路段的交通数据，所述第一路段为所述每个邻近路段中与所述第一交通节点的距离为预设距离的路段；Obtaining at least two first traffic data from the cloud server, each of the first traffic data data is traffic data of a first road segment on each adjacent road segment, where the first road segment is the middle and the adjacent road segment a section where the distance of the first traffic node is a preset distance;
获取第二交通数据，所述第二交通数据为所述目标车辆行驶过的所述第一交通节点至所述目标车辆当前位置的路段所采集的交通数据；Acquiring second traffic data, the second traffic data is traffic data collected by the first traffic node that the target vehicle has traveled to the current location of the target vehicle;
根据所述至少两个第一交通数据以及所述第二交通数据确定所述目标车辆在各邻近路段中的概率；Determining, according to the at least two first traffic data and the second traffic data, a probability that the target vehicle is in each adjacent road segment;
根据所述目标车辆在所述各邻近路段中的概率从所述云端服务器获取相应的邻近路段的交通数据。The traffic data of the corresponding adjacent road segment is acquired from the cloud server according to the probability that the target vehicle is in the adjacent road segments.
结合第一方面，在第一方面的第一种可能的实现方式中，当车载客户端需要确定至少两个交通节点时，可以先确定与第一交通节点相连接的至少两个路段，该第一交通节点位于至少两个路段的一侧，将至少两个路段中的每个路段另一侧的交通节点确定为至少两个第二交通节点。With reference to the first aspect, in a first possible implementation manner of the first aspect, when the in-vehicle client needs to determine the at least two traffic nodes, the at least two road segments connected to the first traffic node may be determined first, where A traffic node is located on one side of the at least two road segments, and the traffic nodes on the other side of each of the at least two road segments are determined as at least two second traffic nodes.
结合第一方面，在第一方面的第二种可能的实现方式中，当车载客户端需要确定至少两个交通节点时，可以确定与第一节点相连接的所有路段，该所有路段包含至少两个路段，获取与第一交通节点相连接的所有路段的另一侧的所有交通节点，获取目标车辆的行驶方向数据或者目的地数据，根据所述行驶方向数据或者目的地数据按照预置的规则从所有交通节点中筛选出至少两个交通节点。With reference to the first aspect, in a second possible implementation manner of the first aspect, when the in-vehicle client needs to determine at least two traffic nodes, all the road segments connected to the first node may be determined, and the all road segments include at least two a road segment, acquiring all traffic nodes on the other side of all road sections connected to the first traffic node, acquiring driving direction data or destination data of the target vehicle, according to the driving direction data or the destination data according to preset rules At least two traffic nodes are selected from all traffic nodes.
结合第一方面，在第一方面的第三种可能的实现方式中，车载客户端在根据目标车辆在各邻近路段中的概率从云端服务器获取相应的邻近路段的交通数据时，可以先确定目标车辆在各邻近路段中的概率，从云端服务器获取概率最高的邻近路段的交通数据，此时，即确定将概率最高的邻近路段的交通数据作为相应的邻近路段的交通数据。In combination with the first aspect, in a third possible implementation manner of the first aspect, the in-vehicle client may determine the target when acquiring the traffic data of the corresponding adjacent road segment from the cloud server according to the probability that the target vehicle is in each adjacent road segment. The probability of the vehicle in each adjacent road segment acquires the traffic data of the adjacent road segment with the highest probability from the cloud server. At this time, the traffic data of the adjacent road segment with the highest probability is determined as the traffic data of the corresponding adjacent road segment.
结合第一方面，在第一方面的第四种可能的实现方式中，车载客户端在根据目标车辆在各邻近路段中的概率从云端服务器获取响应的邻近路段的交通数据时，还可以确定目标车辆在各邻近路段中的概率达到预设值的邻近路段，并且从云端服务器获取概率达到预设值的邻近路段的交通数据，将概率达到预 设值的邻近路段的视觉数据确定为相应的邻近路段的交通数据。In conjunction with the first aspect, in a fourth possible implementation manner of the first aspect, the in-vehicle client may determine the target when acquiring the traffic data of the responding adjacent road segment from the cloud server according to the probability that the target vehicle is in each adjacent road segment. The probability that the probability of the vehicle in each adjacent road segment reaches a preset value, and the traffic data of the adjacent road segment whose probability reaches the preset value is obtained from the cloud server, and the probability is reached. The visual data of the set adjacent road segments is determined as the traffic data of the corresponding adjacent road segments.
结合第一方面以及第一方面的第一种可能的实现方式至第一方面的第四种可能的实现方式中的任一项实现方式，在第一方面的第五种可能的实现方式中，当车载客户端根据目标车辆在各邻近路段中的概率从云端服务器获取相应的邻近路段的交通数据之后，车载客户端可以将相应的邻近路段的交通数据作为目标车辆使用的交通数据。In conjunction with the first aspect, and the first possible implementation of the first aspect, to any one of the fourth possible implementations of the first aspect, in a fifth possible implementation of the first aspect, After the in-vehicle client acquires the traffic data of the corresponding adjacent road segment from the cloud server according to the probability that the target vehicle is in each adjacent road segment, the in-vehicle client may use the traffic data of the corresponding adjacent road segment as the traffic data used by the target vehicle.
本发明实施例第二方面提供了一种车载客户端，包括：A second aspect of the embodiments of the present invention provides an in-vehicle client, including:
中央处理器、存储介质以及输入输出接口；a central processing unit, a storage medium, and an input and output interface;
所述存储介质上存储有程序代码，所述中央处理器，用于调用所述程序代码执行如下步骤：The program medium is stored on the storage medium, and the central processor is configured to invoke the program code to perform the following steps:
确定第一交通节点，所述第一交通节点是目标车辆行驶过的最近的交通节点；Determining a first traffic node, the first traffic node being a nearest traffic node that the target vehicle has traveled;
根据所述第一交通节点确定与所述第一交通节点相连的至少两个第二交通节点；Determining, according to the first traffic node, at least two second traffic nodes connected to the first traffic node;
根据所述第一交通节点以及所述至少两个第二交通节点确定至少两个邻近路段，所述至少两个邻近路段为所述第一交通节点与每个第二交通节点之间的路段；Determining at least two adjacent road segments according to the first traffic node and the at least two second traffic nodes, the at least two adjacent road segments being a road segment between the first traffic node and each second traffic node;
从云端服务器获取至少两个第一交通数据，每个第一交通数据为相应的每个邻近路段上的第一路段的交通数据，所述第一路段为所述每个邻近路段中与所述第一交通节点的距离为预设距离的路段；Acquiring at least two first traffic data from the cloud server, each first traffic data is traffic data of a first road segment on each adjacent road segment, wherein the first road segment is in the adjacent road segment and the a section of the first traffic node whose distance is a preset distance;
获取第二交通数据，所述第二交通数据为所述目标车辆行驶过的所述第一交通节点至所述目标车辆当前位置的路段所采集的交通数据；Acquiring second traffic data, the second traffic data is traffic data collected by the first traffic node that the target vehicle has traveled to the current location of the target vehicle;
根据所述至少两个第一交通数据以及所述第二交通数据确定所述目标车辆在各邻近路段中的概率；Determining, according to the at least two first traffic data and the second traffic data, a probability that the target vehicle is in each adjacent road segment;
根据所述目标车辆在所述各邻近路段中的概率从所述云端服务器获取相应的邻近路段的交通数据。The traffic data of the corresponding adjacent road segment is acquired from the cloud server according to the probability that the target vehicle is in the adjacent road segments.
可选地，所述中央处理器还用于调用所述程序代码执行如下步骤：Optionally, the central processor is further configured to invoke the program code to perform the following steps:
确定与所述第一交通节点相连接的至少两个路段，所述第一交通节点位于 所述至少两个路段的一侧；Determining at least two road segments connected to the first traffic node, the first traffic node being located One side of the at least two sections;
将所述至少两个路段中的每个路段另一侧的交通节点确定为所述至少两个第二交通节点。A traffic node on the other side of each of the at least two road segments is determined as the at least two second traffic nodes.
可选地，所述中央处理器还用于调用所述程序代码执行如下步骤：Optionally, the central processor is further configured to invoke the program code to perform the following steps:
确定与所述第一交通节点相连接的所有路段，所述所有路段包含至少两个路段；Determining all road segments connected to the first traffic node, the all road segments comprising at least two road segments;
获取与所述第一交通节点相连接的所有路段的另一侧的所有交通节点；Obtaining all traffic nodes on the other side of all road sections connected to the first traffic node;
获取所述目标车辆的行驶方向数据或者目的地数据；Obtaining driving direction data or destination data of the target vehicle;
根据所述行驶方向数据或者目的地数据按照预置的规则从所述所有交通节点筛选出所述至少两个交通节点。And filtering the at least two traffic nodes from the all traffic nodes according to the driving direction data or the destination data according to a preset rule.
可选地，所述中央处理器还用于调用所述程序代码执行如下步骤：Optionally, the central processor is further configured to invoke the program code to perform the following steps:
确定所述目标车辆在所述各邻近路段中概率最高的邻近路段；Determining, by the target vehicle, a probabilistic adjacent road segment among the adjacent road segments;
从所述云端服务器获取所述概率最高的邻近路段的交通数据；Obtaining traffic data of the probabilistic adjacent road segment from the cloud server;
确定将所述概率最高的邻近路段的视觉数据作为所述相应的邻近路段的交通数据。Determining visual data of the adjacent road segments with the highest probability as traffic data of the corresponding adjacent road segments.
可选地，所述中央处理器还用于调用所述程序代码执行如下步骤：Optionally, the central processor is further configured to invoke the program code to perform the following steps:
确定所述目标车辆在所述各邻近路段中的概率达到预设值的邻近路段；Determining a neighboring road segment whose probability of the target vehicle in the adjacent road segments reaches a preset value;
从所述云端服务器获取所述概率达到预设值的邻近路段的交通数据；Obtaining, from the cloud server, traffic data of the adjacent road segment whose probability reaches a preset value;
将所述概率达到预设值的邻近路段的视觉数据确定为所述相应的邻近路段的交通数据。The visual data of the adjacent road segments whose probability reaches a preset value is determined as the traffic data of the corresponding adjacent road segments.
可选地，所述中央处理器还用于调用所述程序代码执行如下步骤：Optionally, the central processor is further configured to invoke the program code to perform the following steps:
将所述相应的邻近路段的交通数据作为所述目标车辆使用的交通数据。The traffic data of the corresponding adjacent road segment is used as traffic data used by the target vehicle.
由此可见，相对于现有的直接根据定位位置而使用相应的交通数据作为目标车辆的交通数据，本发明中的车载客户端利用获取的交通数据以及采集的交通数据确定目标车辆在各邻近路段中的概率，根据目标车辆在邻近路段中的概率从云端服务器获取相应的邻近路段的交通数据，从而提高了被用做目标车辆的交通数据的正确性，也即，提高了在定位位置突然跳离时，被用做目标车辆的交通数据的正确性。 It can be seen that, compared with the existing traffic data directly using the corresponding traffic data as the target vehicle according to the positioning position, the vehicle-mounted client in the present invention uses the acquired traffic data and the collected traffic data to determine the target vehicle in each adjacent road segment. The probability of obtaining the traffic data of the corresponding adjacent road segment from the cloud server according to the probability of the target vehicle in the adjacent road segment, thereby improving the correctness of the traffic data used as the target vehicle, that is, improving the sudden jump at the positioning position When it is out of time, it is used as the correctness of the traffic data of the target vehicle.
附图说明DRAWINGS
图1为本发明实施例中交通数据处理方法的一个实施例示意图；1 is a schematic diagram of an embodiment of a method for processing traffic data according to an embodiment of the present invention;
图2为本发明实施例中车载客户端的一个实施例示意图；2 is a schematic diagram of an embodiment of an in-vehicle client according to an embodiment of the present invention;
图3为本发明实施例中的第一交通点、第二交通节点、第二交通数据以及目标车辆所处位置的示意图；3 is a schematic diagram of a first traffic point, a second traffic node, second traffic data, and a location of a target vehicle in an embodiment of the present invention;
图4为本发明实施例中车载客户端的结构示意图。FIG. 4 is a schematic structural diagram of an in-vehicle client according to an embodiment of the present invention.
具体实施方式Detailed ways
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。The technical solutions in the embodiments of the present invention are clearly and completely described in the following with reference to the accompanying drawings in the embodiments of the present invention. It is obvious that the described embodiments are only a part of the embodiments of the present invention, but not all embodiments.
本发明的说明书和权利要求书及上述附图中的术语“第一”、“第二”、“第三”和“第四”等(如果存在)是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的实施例能够以除了在这里图示或描述的内容以外的顺序实施。此外，术语“包括”和“具有”以及他们的任何变形，意图在于覆盖不排他的包含，例如，包含了一系列步骤或单元的过程、方法、***、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。The terms "first", "second", "third" and "fourth", etc. (if present) in the specification and claims of the present invention and the above figures are used to distinguish similar objects without having to use To describe a specific order or order. It is to be understood that the data so used may be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than what is illustrated or described herein. In addition, the terms "comprises" and "comprises" and "the" and "the" are intended to cover a non-exclusive inclusion, for example, a process, method, system, product, or device that comprises a series of steps or units is not necessarily limited to Those steps or units may include other steps or units not explicitly listed or inherent to such processes, methods, products or devices.
请参阅图1，本发明实施例中交通数据处理方法的一个实施例包括：Referring to FIG. 1, an embodiment of a method for processing traffic data in an embodiment of the present invention includes:
101、确定第一交通节点，第一交通节点是目标车辆行驶过的最近的交通节点。101. Determine a first traffic node, where the first traffic node is the nearest traffic node that the target vehicle has traveled.
本实施例中，当目标车辆行驶中需要获取交通数据进行行驶时，车载客户端确定第一交通节点，该第一交通节点为目标车辆已经行驶过的交通节点，且该交通节点至少连接三条路段，即已经行驶过的路段以及未行驶的两条路段。In this embodiment, when the target vehicle needs to obtain traffic data for traveling, the vehicle-mounted client determines a first traffic node, the first traffic node is a traffic node that the target vehicle has traveled, and the traffic node connects at least three road segments. , that is, the road section that has already traveled and the two road sections that are not traveling.
102、根据第一交通节点确定与第一交通节点相连的至少两个第二交通节点。102. Determine, according to the first traffic node, at least two second traffic nodes connected to the first traffic node.
在本实施例中，车载客户端在确定第一交通节点之后，可以根据该第一交通节点确定与第一交通节点相连的至少两个第二交通节点。 In this embodiment, after determining the first traffic node, the in-vehicle client may determine, according to the first traffic node, at least two second traffic nodes connected to the first traffic node.
103、根据第一交通节点以及至少两个第二交通节点确定至少两个邻近路段。所述邻近路段指的是所述第一交通节点与每个第二交通节点之间的路段。103. Determine at least two adjacent road segments according to the first traffic node and the at least two second traffic nodes. The adjacent road segment refers to a road segment between the first traffic node and each of the second traffic nodes.
104、从云端服务器获取至少两个第一交通数据。104. Obtain at least two first traffic data from the cloud server.
本实施例中，当车载客户端确定至少两个邻近路段之后，可以从云端服务器获取每个邻近路段上第一路段的交通数据，第一路段为邻近路段中与第一交通节点的距离为预设距离的路段，将每个邻近路段上第一路段的视觉数据作为每个邻近路段的第一交通数据，云端服务器中包括云端数据库，云端服务器与目标车辆通过无线方式连接。In this embodiment, after the in-vehicle client determines at least two adjacent road segments, the traffic data of the first road segment on each adjacent road segment may be obtained from the cloud server, where the first road segment is a distance from the first traffic node in the adjacent road segment. The distance segment is set, and the visual data of the first road segment on each adjacent road segment is used as the first traffic data of each adjacent road segment, and the cloud server includes the cloud database, and the cloud server and the target vehicle are connected by wireless.
需要说明的是，交通数据包括视觉数据以及其他一些数据，例如天气数据、行驶方向数据、行驶速度数据以及当前路段的海拔高度数据等数据。It should be noted that the traffic data includes visual data and other data such as weather data, driving direction data, driving speed data, and altitude data of the current road section.
105、获取第二交通数据。105. Obtain second traffic data.
在本实施例中，所述目标车辆在行驶的过程中会实时的采集交通数据并保存。第二交通数据指的是目标车辆行驶过第一交通节点至目标车辆当前位置的路段所采集的交通数据。In this embodiment, the target vehicle collects traffic data and saves it in real time during the running process. The second traffic data refers to traffic data collected by the target vehicle traveling from the first traffic node to the current location of the target vehicle.
106、根据至少两个第一交通数据以及第二交通数据确定目标车辆在各邻近路段中的概率。106. Determine, according to the at least two first traffic data and the second traffic data, a probability that the target vehicle is in each adjacent road segment.
本实施例中，车载客户端在确定至少两个第一交通数据以及第二交通数据之后，将第二交通数据与每个第一交通数据分别进行相似度计算，得到第二交通数据与每个第一交通数据的相似度，进而得到第二交通数据与每个第一交通数据的匹配度，然后通过第二交通数据与每个第一交通数据的匹配度来计算该目标车辆位于每个邻近路段中的概率。In this embodiment, after determining the at least two first traffic data and the second traffic data, the in-vehicle client separately performs the similarity calculation on the second traffic data and each of the first traffic data to obtain the second traffic data and each The similarity of the first traffic data, thereby obtaining the matching degree of the second traffic data with each of the first traffic data, and then calculating the matching degree of the second traffic data and each of the first traffic data to calculate that the target vehicle is located in each neighborhood The probability in the road segment.
需要说明的是，具体可以通过将第二交通数据中的子数据与第一交通数据中相应的子数据进行相似度计算，从而得到所述第二交通数据与第一交通数据的相似度。也即可以提取第二交通数据以及每个第一交通数据中的某些关键数据，将第二交通数据中的关键数据与每个第一交通数据中的关键数据进行对比，通过对比结果即可以确定目标车辆在各邻近路段中的概率，例如云端服务器的数据库中存储的各个位置的图片与目标车辆在相应的距离采集的图片的相似度，然后根据这些相似度进行整合即可以确定目标车辆在各邻近路段中的 概率。It should be noted that the similarity between the second traffic data and the first traffic data may be obtained by performing similarity calculation on the sub-data in the second traffic data and the corresponding sub-data in the first traffic data. That is, the second traffic data and some key data in each first traffic data may be extracted, and the key data in the second traffic data is compared with the key data in each first traffic data, and the comparison result may be Determining the probability of the target vehicle in each adjacent road segment, for example, the similarity between the picture of each location stored in the database of the cloud server and the picture collected by the target vehicle at a corresponding distance, and then integrating according to the similarities to determine the target vehicle is In each adjacent section Probability.
107、根据目标车辆在各邻近路段中的概率从云端服务器获取相应的邻近路段的交通数据。107. Acquire traffic data of the corresponding adjacent road segment from the cloud server according to the probability that the target vehicle is in each adjacent road segment.
本实施例中，车载客户端在确定目标车辆在各邻近路段中的概率后，可以根据目标车辆在各邻近路段中的概率从云端服务器获取相应的邻近路段的概率，可以获取目标车辆在各邻近路段中的概率最高的路段对应的交通数据，也可以获取目标车辆在各邻近路段中的概率达到预设值的路段对应的交通数据。In this embodiment, after determining the probability of the target vehicle in each adjacent road segment, the vehicle-mounted client may acquire the probability of the corresponding adjacent road segment from the cloud server according to the probability of the target vehicle in each adjacent road segment, and may acquire the target vehicle in each neighborhood. The traffic data corresponding to the road segment with the highest probability in the road segment can also obtain the traffic data corresponding to the road segment whose target vehicle has a preset probability value in each adjacent road segment.
综上所述，当目标车辆需要从云端服务器缓存视觉数据的时候，车载客户端可以确定第一交通节点，根据第一交通节点确定与第一交通节点相连的至少两个第二交通节点；根据第一交通节点以及至少两个第二交通节点确定至少两个邻近路段；获取至少两个第一交通数据，；获取第二交通数据；根据至少两个第一交通数据以及第二交通数据确定目标车辆在各邻近路段中的概率；根据目标车辆在各邻近路段中的概率获取相应的邻近路段的视觉数据。由此可见，相对于现有的直接根据定位位置而使用相应的交通数据作为目标车辆的交通数据，本发明中的车载客户端利用获取的交通数据以及采集的交通数据确定目标车辆在各邻近路段中的概率，根据目标车辆在邻近路段中的概率从云端服务器获取相应的邻近路段的交通数据，从而提高了被用做目标车辆的交通数据的正确性，也即，提高了在定位位置突然跳离时，被用做目标车辆的交通数据的正确性。In summary, when the target vehicle needs to cache the visual data from the cloud server, the in-vehicle client may determine the first traffic node, and determine, according to the first traffic node, at least two second traffic nodes connected to the first traffic node; The first traffic node and the at least two second traffic nodes determine at least two adjacent road segments; acquire at least two first traffic data; acquire second traffic data; determine the target according to the at least two first traffic data and the second traffic data The probability of the vehicle in each adjacent road segment; the visual data of the corresponding adjacent road segment is obtained according to the probability of the target vehicle in each adjacent road segment. It can be seen that, compared with the existing traffic data directly using the corresponding traffic data as the target vehicle according to the positioning position, the vehicle-mounted client in the present invention uses the acquired traffic data and the collected traffic data to determine the target vehicle in each adjacent road segment. The probability of obtaining the traffic data of the corresponding adjacent road segment from the cloud server according to the probability of the target vehicle in the adjacent road segment, thereby improving the correctness of the traffic data used as the target vehicle, that is, improving the sudden jump at the positioning position When it is out of time, it is used as the correctness of the traffic data of the target vehicle.
请参阅图2，本发明实施例中交通数据处理方法的另一实施例包括：Referring to FIG. 2, another embodiment of a method for processing traffic data in an embodiment of the present invention includes:
201、确定第一交通节点，所述第一交通节点是目标车辆行驶过的最近的交通节点。201. Determine a first traffic node, where the first traffic node is a nearest traffic node that the target vehicle has traveled.
本实施例中，当目标车辆行驶中需要获取交通数据进行行驶时，车载客户端可以确定第一交通节点，该第一交通节点为目标车辆已经行驶过的交通节点，且该交通节点至少连接三条路段，即已经行驶过的路段以及未行驶的两条路段。In this embodiment, when the target vehicle needs to obtain traffic data for traveling, the vehicle-mounted client may determine the first traffic node, the first traffic node is a traffic node that the target vehicle has traveled, and the traffic node is connected with at least three The road section, that is, the road section that has already traveled and the two road sections that are not traveling.
202、根据第一交通节点确定与第一交通节点相连的至少两个第二交通节点。 202. Determine, according to the first traffic node, at least two second traffic nodes connected to the first traffic node.
在本实施例中，车载客户端可以先确定与第一交通节点相连接的所有路段(至少两个)，并将与该第一交通节点相连接的所有路段的另一侧的交通节点均确定为第二交通节点，所述第二交通节点至少连接三条路段。In this embodiment, the in-vehicle client may first determine all the road segments (at least two) connected to the first traffic node, and determine the traffic nodes on the other side of all the road segments connected to the first traffic node. For the second traffic node, the second traffic node connects at least three road segments.
在另一实施例中，车载客户端可以先确定与第一交通节点相连接的所有路段(至少两个)，并获取与所述第一交通节点相连接的所有路段的另一侧的交通节点；所述车载客户端进一步获取目标车辆的行驶方向数据或者目的地数据，并根据所述目标车辆的行驶方向数据或者目的地数据从与第一交通节点相连的所有交通节点中筛选出至少两个交通节点作为第二交通节点。例如，将上述所有交通节点中处于一个扇形区域内的至少两个交通节点确定为第二交通节点，所述扇形区域是以目标车辆的行驶方向为轴的扇形区域。或者将上述所有交通节点中处于一个扇形区域内的至少两个交通节点确定为第二交通节点，所述扇形区域是以目标车辆的当前位置指向目的地的方向为轴的扇形区域。In another embodiment, the in-vehicle client may first determine all the road segments (at least two) connected to the first traffic node, and acquire the traffic nodes on the other side of all the road segments connected to the first traffic node. The in-vehicle client further acquires driving direction data or destination data of the target vehicle, and selects at least two of all the traffic nodes connected to the first traffic node according to the driving direction data or the destination data of the target vehicle. The traffic node acts as a second traffic node. For example, at least two traffic nodes in one of the above-mentioned traffic nodes in one sector-shaped area are determined as second traffic nodes, which are sector-shaped regions whose axes of travel are the axes of the target vehicle. Or determining at least two traffic nodes in one of the above-mentioned traffic nodes in a sector-shaped area as a second traffic node, the sector-shaped area being a sector-shaped area with the direction of the target vehicle's current position pointing to the destination as an axis.
需要说明的是，上述只是根据第一交通节点确定与第一交通节点相连的至少两个交通节点的两种方式，也可以有其他方式，具体此处不做限定。It should be noted that the foregoing is only two ways of determining the at least two traffic nodes connected to the first traffic node according to the first traffic node, and there may be other manners, which are not limited herein.
203、根据第一交通节点以及至少两个第二交通节点确定至少两个邻近路段。所述邻近路段指的是所述第一交通节点与每个第二交通节点之间的路段。203. Determine at least two adjacent road segments according to the first traffic node and the at least two second traffic nodes. The adjacent road segment refers to a road segment between the first traffic node and each of the second traffic nodes.
204、从云端服务器获取至少两个第一交通数据。204. Obtain at least two first traffic data from the cloud server.
本实施例中，当车载客户端确定至少两个邻近路段之后，可以从云端服务器获取每个邻近路段上第一路段的交通数据，第一路段为邻近路段中与第一交通节点的距离为预设距离的路段，将每个邻近路段上第一路段的视觉数据作为每个邻近路段的第一交通数据。In this embodiment, after the in-vehicle client determines at least two adjacent road segments, the traffic data of the first road segment on each adjacent road segment may be obtained from the cloud server, where the first road segment is a distance from the first traffic node in the adjacent road segment. The distance segment is set, and the visual data of the first road segment on each adjacent road segment is used as the first traffic data of each adjacent road segment.
需要说明的是，交通数据包括视觉数据以及其他一些数据，例如天气数据、行驶方向数据、行驶速度数据以及当前路段的海拔高度数据等数据。It should be noted that the traffic data includes visual data and other data such as weather data, driving direction data, driving speed data, and altitude data of the current road section.
205、获取第二交通数据。205. Acquire second traffic data.
在本实施例中，所述目标车辆在行驶的过程中会实时的采集交通数据并保存。第二交通数据指的是目标车辆行驶过的第一交通节点至目标车辆当前位置的路段所采集的视觉数据。In this embodiment, the target vehicle collects traffic data and saves it in real time during the running process. The second traffic data refers to visual data collected by the first traffic node that the target vehicle has traveled to the current location of the target vehicle.
为了便于理解，请参阅图3，图3为第一交通点、第二交通节点、第二交 通数据以及目标车辆所处位置的示意图，其中目标车辆可以为第一交通节点与第二交通节点之间的任何一条路段上面的任意位置，第一交通节点为车辆行驶过的最近的一个交通节点，第二交通节点为与第一交通节点相连接的交通节点，第二交通数据为第一交通节点至目标车辆当前位置中间的路段的交通数据，第一交通数据为第一交通节点与第二交通节点之间的路段中距离第一交通交通节点为预设距离的路段的交通数据。For ease of understanding, please refer to FIG. 3, which is the first traffic point, the second traffic node, and the second intersection. A schematic diagram of the pass data and the location of the target vehicle, wherein the target vehicle may be any location above any one of the first traffic node and the second traffic node, the first traffic node being the nearest one of the traffic nodes The second traffic node is a traffic node connected to the first traffic node, and the second traffic data is traffic data of the road segment between the first traffic node and the current location of the target vehicle, where the first traffic data is the first traffic node and the second traffic node. Traffic data of a section of the road between the traffic nodes that is a preset distance from the first traffic node.
206、根据至少两个第一交通数据以及第二交通数据确定目标车辆在各邻近路段中的概率。206. Determine, according to the at least two first traffic data and the second traffic data, a probability that the target vehicle is in each adjacent road segment.
本实施例中，车载客户端在确定至少两个第一交通数据以及第二交通数据之后，将第二交通数据与每个第一交通数据分别进行相似度计算，得到第二交通数据与每个第一交通数据的相似度，进而得到第二交通数据与每个第一交通数据的匹配度，然后通过第二交通数据与每个第一交通数据的匹配度来计算该目标车辆位于每个邻近路段中的概率。In this embodiment, after determining the at least two first traffic data and the second traffic data, the in-vehicle client separately performs the similarity calculation on the second traffic data and each of the first traffic data to obtain the second traffic data and each The similarity of the first traffic data, thereby obtaining the matching degree of the second traffic data with each of the first traffic data, and then calculating the matching degree of the second traffic data and each of the first traffic data to calculate that the target vehicle is located in each neighborhood The probability in the road segment.
需要说明的是，具体可以通过将第二交通数据中的子数据与第一交通数据中相应的子数据进行相似度计算，从而得到所述第二交通数据与第一交通数据的相似度。也即可以提取第二交通数据以及每个第一交通数据中的某些关键数据，将第二交通数据中的关键数据与每个第一交通数据中的关键数据进行对比，通过对比结果即可以确定目标车辆在各邻近路段中的概率，例如云端服务器的数据库中存储的各个位置的图片与目标车辆在相应的距离采集的图片的相似度，然后根据这些相似度进行整合即可以确定目标车辆在各邻近路段中的概率。It should be noted that the similarity between the second traffic data and the first traffic data may be obtained by performing similarity calculation on the sub-data in the second traffic data and the corresponding sub-data in the first traffic data. That is, the second traffic data and some key data in each first traffic data may be extracted, and the key data in the second traffic data is compared with the key data in each first traffic data, and the comparison result may be Determining the probability of the target vehicle in each adjacent road segment, for example, the similarity between the picture of each location stored in the database of the cloud server and the picture collected by the target vehicle at a corresponding distance, and then integrating according to the similarities to determine the target vehicle is Probability in each adjacent road segment.
207、根据目标车辆在各邻近路段中的概率从云端服务器获取相应的邻近路段的交通数据。207. Acquire traffic data of the corresponding adjacent road segment from the cloud server according to the probability that the target vehicle is in each adjacent road segment.
本实施例中，车载客户端在确定目标车辆在各邻近路段中的概率后，可以确定目标车辆在各邻近路段中概率最高的邻近路段，从云端服务器获取该概率最高的邻近路段对应的视觉数据，将该概率最高的邻近路段的视觉数据作为目标车辆的目标数据。In this embodiment, after determining the probability of the target vehicle in each adjacent road segment, the vehicle-mounted client may determine the adjacent road segment with the highest probability among the target vehicles in each adjacent road segment, and obtain the visual data corresponding to the adjacent road segment with the highest probability from the cloud server. The visual data of the adjacent road segment with the highest probability is used as the target data of the target vehicle.
需要说明的是，车载客户端也可以在确定目标车辆在各邻近路段中的概率 后，可以获取目标车辆在各邻近路段中的概率达到预设值的邻近路段，从云端服务器获取概率达到预设值的邻近路段的视觉数据，将该概率达到预设值的邻近路段的视觉数据作为目标车辆的目标数据。It should be noted that the vehicle client can also determine the probability of the target vehicle in each adjacent road segment. After that, the neighboring road segment whose target vehicle has a probability of reaching a preset value in each adjacent road segment can be obtained, and the visual data of the adjacent road segment whose probability reaches the preset value is acquired from the cloud server, and the visual data of the adjacent road segment whose probability reaches the preset value is obtained. As the target data of the target vehicle.
208、将获取的相应的邻近路段的交通数据作为目标车辆使用的交通数据。208. Use the acquired traffic data of the adjacent adjacent road segment as the traffic data used by the target vehicle.
本实施例中，车载客户端在得到相应的邻近路段的交通数据之后，可以将该相应的邻近路段的交通数据作为目标车辆使用的交通数据。In this embodiment, after obtaining the traffic data of the corresponding adjacent road segment, the vehicle-mounted client may use the traffic data of the corresponding adjacent road segment as the traffic data used by the target vehicle.
综上所述，当目标车辆需要从云端服务器缓存视觉数据的时候，车载客户端可以确定第一交通节点，根据第一交通节点确定与第一交通节点相连的至少两个第二交通节点；根据第一交通节点以及至少两个第二交通节点确定至少两个邻近路段；获取至少两个第一交通数据；获取第二交通数据；根据至少两个第一交通数据以及第二交通数据确定目标车辆在各邻近路段中的概率；根据目标车辆在各邻近路段中的概率获取相应的邻近路段的视觉数据，将相应的邻近路段的交通数据作为目标车辆使用的交通数据。由此可见，相对于现有的直接根据定位位置而使用相应的交通数据作为目标车辆的交通数据，本发明中的车载客户端利用获取的交通数据以及采集的交通数据确定目标车辆在各邻近路段中的概率，根据目标车辆在邻近路段中的概率从云端服务器获取相应的邻近路段的交通数据，从而提高了被用做目标车辆的交通数据的正确性，也即，提高了在定位位置突然跳离时，被用做目标车辆的交通数据的正确性。In summary, when the target vehicle needs to cache the visual data from the cloud server, the in-vehicle client may determine the first traffic node, and determine, according to the first traffic node, at least two second traffic nodes connected to the first traffic node; The first traffic node and the at least two second traffic nodes determine at least two adjacent road segments; acquire at least two first traffic data; acquire second traffic data; determine the target vehicle according to the at least two first traffic data and the second traffic data The probability in each adjacent road segment; the visual data of the corresponding adjacent road segment is obtained according to the probability of the target vehicle in each adjacent road segment, and the traffic data of the corresponding adjacent road segment is used as the traffic data used by the target vehicle. It can be seen that, compared with the existing traffic data directly using the corresponding traffic data as the target vehicle according to the positioning position, the vehicle-mounted client in the present invention uses the acquired traffic data and the collected traffic data to determine the target vehicle in each adjacent road segment. The probability of obtaining the traffic data of the corresponding adjacent road segment from the cloud server according to the probability of the target vehicle in the adjacent road segment, thereby improving the correctness of the traffic data used as the target vehicle, that is, improving the sudden jump at the positioning position When it is out of time, it is used as the correctness of the traffic data of the target vehicle.
请参阅图4，图4是本发明实施例提供的一种车载客户端的结构示意图，该车载客户端400可因配置或性能不同而产生比较大的差异，可以包括一个或一个以***处理器(central processing units，CPU)422(例如，一个或一个以上处理器)，一个或一个以上用于存储应用程序442或数据444的存储介质430(存储介质可以为一个或一个以上海量存储设备，也可以为一个或一个以上内存等临时存储设备，也可以为一个或一个硬盘，也可以是一个或一个以上的内存以及硬盘共同使用，具体此处不作限定)。其中，存储介质430可以是短暂存储或持久存储。存储在存储介质430的程序可以包括对车载客户端中的一系列指令操作。更进一步地，中央处理器422可以设置为与存储介质430通信，在车载客户端400上执行存储介质430中的一系列指令操作。 Please refer to FIG. 4. FIG. 4 is a schematic structural diagram of an in-vehicle client according to an embodiment of the present invention. The in-vehicle client 400 may generate a large difference due to different configurations or performances, and may include one or more central processing units ( Central processing units (CPU) 422 (eg, one or more processors), one or more storage media 430 for storing applications 442 or data 444 (the storage medium may be one or one storage device in Shanghai, or A temporary storage device such as one or more memories may also be used for one or one hard disk, or one or more memories and a hard disk, which are not limited herein. The storage medium 430 may be short-term storage or persistent storage. The program stored on the storage medium 430 can include a series of instruction operations in the onboard client. Still further, central processor 422 can be configured to communicate with storage medium 430 to perform a series of instruction operations in storage medium 430 on vehicle-mounted client 400.
车载客户端400还可以包括一个或一个以上输入输出接口458(输入输出接口可以为一个或一个以上有线或无线网络接口，也可以为其他输入输出接口，具体此处不作限定)，和/或，一个或一个以上操作***441，例如Windows ServerTM，Mac OS XTM，UnixTM，LinuxTM，FreeBSDTM等等。The in-vehicle client 400 may further include one or more input and output interfaces 458 (the input and output interfaces may be one or more wired or wireless network interfaces, or other input and output interfaces, which are not limited herein), and/or One or more operating systems 441, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, and the like.
上述实施例中由车载客户端所执行的步骤可以基于该图4所示的车载客户端结构。The steps performed by the in-vehicle client in the above embodiments may be based on the in-vehicle client structure shown in FIG.
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的***，装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。A person skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working process of the system, the device and the unit described above can refer to the corresponding process in the foregoing method embodiment, and details are not described herein again.
在本申请所提供的几个实施例中，应该理解到，所揭露的***，装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个***，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。In the several embodiments provided by the present application, it should be understood that the disclosed system, apparatus, and method may be implemented in other manners. For example, the device embodiments described above are merely illustrative. For example, the division of the unit is only a logical function division. In actual implementation, there may be another division manner, for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
另外，在本发明各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本发明的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个 存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本发明各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。The integrated unit, if implemented in the form of a software functional unit and sold or used as a standalone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may contribute to the prior art or all or part of the technical solution may be embodied in the form of a software product stored in a software product. The storage medium includes instructions for causing a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like. .
以上所述，以上实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的精神和范围。 The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to be limiting; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will understand that The technical solutions described in the embodiments are modified, or the equivalents of the technical features are replaced by the equivalents of the technical solutions of the embodiments of the present invention.

Claims (12)

  1. 一种交通数据处理方法，其特征在于，包括：A traffic data processing method, comprising:
    确定第一交通节点，所述第一交通节点是目标车辆行驶过的最近的交通节点；Determining a first traffic node, the first traffic node being a nearest traffic node that the target vehicle has traveled;
    根据所述第一交通节点确定与所述第一交通节点相连的至少两个第二交通节点；Determining, according to the first traffic node, at least two second traffic nodes connected to the first traffic node;
    根据所述第一交通节点以及所述至少两个第二交通节点确定至少两个邻近路段，所述至少两个邻近路段为所述第一交通节点与每个第二交通节点之间的路段；Determining at least two adjacent road segments according to the first traffic node and the at least two second traffic nodes, the at least two adjacent road segments being a road segment between the first traffic node and each second traffic node;
    从云端服务器获取至少两个第一交通数据，每个第一交通数据为相应的每个邻近路段上的第一路段的交通数据，所述第一路段为所述每个邻近路段中与所述第一交通节点的距离为预设距离的路段；Acquiring at least two first traffic data from the cloud server, each first traffic data is traffic data of a first road segment on each adjacent road segment, wherein the first road segment is in the adjacent road segment and the a section of the first traffic node whose distance is a preset distance;
    获取第二交通数据，所述第二交通数据为所述目标车辆行驶过的所述第一交通节点至所述目标车辆当前位置的路段所采集的交通数据；Acquiring second traffic data, the second traffic data is traffic data collected by the first traffic node that the target vehicle has traveled to the current location of the target vehicle;
    根据所述至少两个第一交通数据以及所述第二交通数据确定所述目标车辆在各邻近路段中的概率；Determining, according to the at least two first traffic data and the second traffic data, a probability that the target vehicle is in each adjacent road segment;
    根据所述目标车辆在所述各邻近路段中的概率从所述云端服务器获取相应的邻近路段的交通数据。The traffic data of the corresponding adjacent road segment is acquired from the cloud server according to the probability that the target vehicle is in the adjacent road segments.
  2. 根据权利要求1所述的交通数据处理方法，其特征在于，所述根据所述第一交通节点确定与所述第一交通节点相连的至少两个第二交通节点包括：The traffic data processing method according to claim 1, wherein the determining, according to the first traffic node, the at least two second traffic nodes connected to the first traffic node comprises:
    确定与所述第一交通节点相连接的至少两个路段，所述第一交通节点位于所述至少两个路段的一侧；Determining at least two road segments connected to the first traffic node, the first traffic node being located at one side of the at least two road segments;
    将所述至少两个路段中的每个路段另一侧的交通节点确定为所述至少两个第二交通节点。A traffic node on the other side of each of the at least two road segments is determined as the at least two second traffic nodes.
  3. 根据权利要求1所述的交通数据处理方法，其特征在于，所述根据所述第一交通节点确定与所述第一交通节点相连的至少两个第二交通节点包括：The traffic data processing method according to claim 1, wherein the determining, according to the first traffic node, the at least two second traffic nodes connected to the first traffic node comprises:
    确定与所述第一交通节点相连接的所有路段，所述所有路段包含至少两个路段； Determining all road segments connected to the first traffic node, the all road segments comprising at least two road segments;
    获取与所述第一交通节点相连接的所有路段的另一侧的所有交通节点；Obtaining all traffic nodes on the other side of all road sections connected to the first traffic node;
    获取所述目标车辆的行驶方向数据或者目的地数据；Obtaining driving direction data or destination data of the target vehicle;
    根据所述行驶方向数据或者目的地数据按照预置的规则从所述所有交通节点筛选出所述至少两个交通节点。And filtering the at least two traffic nodes from the all traffic nodes according to the driving direction data or the destination data according to a preset rule.
  4. 根据权利要求1所述的交通数据处理方法，其特征在于，所述根据所述目标车辆在所述各邻近路段中的概率从所述云端服务器获取相应的邻近路段的交通数据包括：The traffic data processing method according to claim 1, wherein the obtaining the traffic data of the corresponding adjacent road segment from the cloud server according to the probability that the target vehicle is in the adjacent road segments comprises:
    确定所述目标车辆在所述各邻近路段中概率最高的邻近路段；Determining, by the target vehicle, a probabilistic adjacent road segment among the adjacent road segments;
    从所述云端服务器获取所述概率最高的邻近路段的交通数据；Obtaining traffic data of the probabilistic adjacent road segment from the cloud server;
    确定将所述概率最高的邻近路段的视觉数据作为所述相应的邻近路段的交通数据。Determining visual data of the adjacent road segments with the highest probability as traffic data of the corresponding adjacent road segments.
  5. 根据权利要求1所述的交通数据处理方法，其特征在于，所述根据所述目标车辆在所述各邻近路段中的概率从所述云端服务器获取相应的邻近路段的交通数据包括：The traffic data processing method according to claim 1, wherein the obtaining the traffic data of the corresponding adjacent road segment from the cloud server according to the probability that the target vehicle is in the adjacent road segments comprises:
    确定所述目标车辆在所述各邻近路段中的概率达到预设值的邻近路段；Determining a neighboring road segment whose probability of the target vehicle in the adjacent road segments reaches a preset value;
    从所述云端服务器获取所述概率达到预设值的邻近路段的交通数据；Obtaining, from the cloud server, traffic data of the adjacent road segment whose probability reaches a preset value;
    将所述概率达到预设值的邻近路段的视觉数据确定为所述相应的邻近路段的交通数据。The visual data of the adjacent road segments whose probability reaches a preset value is determined as the traffic data of the corresponding adjacent road segments.
  6. 根据权利要求1至5中任一项所述的交通数据处理方法，其特征在于，所述根据所述目标车辆在所述各邻近路段中的概率从所述云端服务器获取相应的邻近路段的交通数据之后，所述方法还包括：The traffic data processing method according to any one of claims 1 to 5, wherein the obtaining the traffic of the corresponding adjacent road segment from the cloud server according to the probability that the target vehicle is in the adjacent road segments After the data, the method further includes:
    将所述相应的邻近路段的交通数据作为所述目标车辆使用的交通数据。The traffic data of the corresponding adjacent road segment is used as traffic data used by the target vehicle.
  7. 一种车载客户端，其特征在于，包括：An in-vehicle client, comprising:
    中央处理器、存储介质以及输入输出接口；a central processing unit, a storage medium, and an input and output interface;
    所述存储介质上存储有程序代码，所述中央处理器，用于调用所述程序代码执行如下步骤：The program medium is stored on the storage medium, and the central processor is configured to invoke the program code to perform the following steps:
    确定第一交通节点，所述第一交通节点是目标车辆行驶过的最近的交通节点； Determining a first traffic node, the first traffic node being a nearest traffic node that the target vehicle has traveled;
    根据所述第一交通节点确定与所述第一交通节点相连的至少两个第二交通节点；Determining, according to the first traffic node, at least two second traffic nodes connected to the first traffic node;
    根据所述第一交通节点以及所述至少两个第二交通节点确定至少两个邻近路段，所述至少两个邻近路段为所述第一交通节点与每个第二交通节点之间的路段；Determining at least two adjacent road segments according to the first traffic node and the at least two second traffic nodes, the at least two adjacent road segments being a road segment between the first traffic node and each second traffic node;
    从云端服务器获取至少两个第一交通数据，每个第一交通数据为相应的每个邻近路段上的第一路段的交通数据，所述第一路段为所述每个邻近路段中与所述第一交通节点的距离为预设距离的路段；Acquiring at least two first traffic data from the cloud server, each first traffic data is traffic data of a first road segment on each adjacent road segment, wherein the first road segment is in the adjacent road segment and the a section of the first traffic node whose distance is a preset distance;
    获取第二交通数据，所述第二交通数据为所述目标车辆行驶过的所述第一交通节点至所述目标车辆当前位置的路段所采集的交通数据；Acquiring second traffic data, the second traffic data is traffic data collected by the first traffic node that the target vehicle has traveled to the current location of the target vehicle;
    根据所述至少两个第一交通数据以及所述第二交通数据确定所述目标车辆在各邻近路段中的概率；Determining, according to the at least two first traffic data and the second traffic data, a probability that the target vehicle is in each adjacent road segment;
    根据所述目标车辆在所述各邻近路段中的概率从所述云端服务器获取相应的邻近路段的交通数据。The traffic data of the corresponding adjacent road segment is acquired from the cloud server according to the probability that the target vehicle is in the adjacent road segments.
  8. 根据权利要求7所述的车载客户端，其特征在于，所述中央处理器还用于调用所述程序代码执行如下步骤：The in-vehicle client according to claim 7, wherein the central processor is further configured to invoke the program code to perform the following steps:
    确定与所述第一交通节点相连接的至少两个路段，所述第一交通节点位于所述至少两个路段的一侧；Determining at least two road segments connected to the first traffic node, the first traffic node being located at one side of the at least two road segments;
    将所述至少两个路段中的每个路段另一侧的交通节点确定为所述至少两个第二交通节点。A traffic node on the other side of each of the at least two road segments is determined as the at least two second traffic nodes.
  9. 根据权利要求7所述的车载客户端，其特征在于，所述中央处理器还用于调用所述程序代码执行如下步骤：The in-vehicle client according to claim 7, wherein the central processor is further configured to invoke the program code to perform the following steps:
    确定与所述第一交通节点相连接的所有路段，所述所有路段包含至少两个路段；Determining all road segments connected to the first traffic node, the all road segments comprising at least two road segments;
    获取与所述第一交通节点相连接的所有路段的另一侧的所有交通节点；Obtaining all traffic nodes on the other side of all road sections connected to the first traffic node;
    获取所述目标车辆的行驶方向数据或者目的地数据；Obtaining driving direction data or destination data of the target vehicle;
    根据所述行驶方向数据或者目的地数据按照预置的规则从所述所有交通节点筛选出所述至少两个交通节点。 And filtering the at least two traffic nodes from the all traffic nodes according to the driving direction data or the destination data according to a preset rule.
  10. 根据权利要求7所述的车载客户端，其特征在于，所述中央处理器还用于调用所述程序代码执行如下步骤：The in-vehicle client according to claim 7, wherein the central processor is further configured to invoke the program code to perform the following steps:
    确定所述目标车辆在所述各邻近路段中概率最高的邻近路段；Determining, by the target vehicle, a probabilistic adjacent road segment among the adjacent road segments;
    从所述云端服务器获取所述概率最高的邻近路段的交通数据；Obtaining traffic data of the probabilistic adjacent road segment from the cloud server;
    确定将所述概率最高的邻近路段的视觉数据作为所述相应的邻近路段的交通数据。Determining visual data of the adjacent road segments with the highest probability as traffic data of the corresponding adjacent road segments.
  11. 根据权利要求7所述的车载客户端，其特征在于，所述中央处理器还用于调用所述程序代码执行如下步骤：The in-vehicle client according to claim 7, wherein the central processor is further configured to invoke the program code to perform the following steps:
    确定所述目标车辆在所述各邻近路段中的概率达到预设值的邻近路段；Determining a neighboring road segment whose probability of the target vehicle in the adjacent road segments reaches a preset value;
    从所述云端服务器获取所述概率达到预设值的邻近路段的交通数据；Obtaining, from the cloud server, traffic data of the adjacent road segment whose probability reaches a preset value;
    将所述概率达到预设值的邻近路段的视觉数据确定为所述相应的邻近路段的交通数据。The visual data of the adjacent road segments whose probability reaches a preset value is determined as the traffic data of the corresponding adjacent road segments.
  12. 根据权利要求7至11中任一项所述的车载客户端，其特征在于，所述中央处理器还用于调用所述程序代码执行如下步骤：The vehicle-mounted client according to any one of claims 7 to 11, wherein the central processor is further configured to call the program code to perform the following steps:
    将所述相应的邻近路段的交通数据作为所述目标车辆使用的交通数据。 The traffic data of the corresponding adjacent road segment is used as traffic data used by the target vehicle.
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