WO2011079681A1 - Method and apparatus for predicting travel time - Google Patents

Method and apparatus for predicting travel time Download PDF

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Publication number
WO2011079681A1
WO2011079681A1 PCT/CN2010/079358 CN2010079358W WO2011079681A1 WO 2011079681 A1 WO2011079681 A1 WO 2011079681A1 CN 2010079358 W CN2010079358 W CN 2010079358W WO 2011079681 A1 WO2011079681 A1 WO 2011079681A1
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Prior art keywords
road
target
unit
traffic
target road
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PCT/CN2010/079358
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French (fr)
Chinese (zh)
Inventor
胡健
魏俊华
杨承继
夏伟
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北京世纪高通科技有限公司
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Publication of WO2011079681A1 publication Critical patent/WO2011079681A1/en

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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions

Definitions

  • the present invention relates to the field of intelligent transportation, and in particular, to a method and apparatus for traveling time prediction.
  • Travel time prediction can facilitate travellers, traffic management personnel to conduct inquiries and various decision analysis.
  • the data analysis is performed by the clustering method, the feature values are extracted for matching, and then the line time is directly predicted, thereby obtaining the road. ⁇ Line time.
  • Embodiments of the present invention provide a method and apparatus for travel time prediction that enables travel time prediction based on road traffic conditions.
  • a method for predicting line time including:
  • a device for predicting travel time comprising:
  • a first acquiring unit configured to acquire a level of the target road and a traffic road condition
  • a determining unit configured to determine an average speed of the target road according to a grade of the target road and a traffic road condition
  • a calculating unit configured to divide the length of the target road by the average speed of the target road to obtain a line time of the target road.
  • the traffic road condition may be smooth, slow or congested by acquiring the level of the target road and the traffic road condition, and then determining the target road according to the grade of the target road and the traffic road condition. The average speed.
  • the travel time of the target road can be obtained by dividing the length of the target road by the average speed of the target road.
  • the travel time prediction is implemented by the traffic condition of the road, and the embodiment of the present invention is not limited by the data source provided by the city, compared with the travel time prediction of the road directly by the measured travel time data in the prior art. In the prior art, the problem of the road travel time cannot be predicted when only the traffic condition of the road can be obtained and the travel time data cannot be obtained.
  • 1 is a flow chart of a method for predicting time in the first embodiment
  • Embodiment 2 is a structural block diagram of an apparatus for predicting travel time in Embodiment 1;
  • Embodiment 3 is a flow chart of a method for predicting time in Embodiment 2;
  • Fig. 4 is a block diagram showing the structure of an apparatus for predicting travel time in the second embodiment.
  • Example 1 An embodiment of the present invention provides a method for predicting travel time. As shown in FIG. 1, the method includes the following steps:
  • the acquired traffic conditions include smooth, slow or congested, and the traffic conditions of each road can be obtained through the fusion of various data sources.
  • the various data sources include, but are not limited to, the following data types: Floating car data, since the floating car data contains time information, the travel time of the floating car data can be obtained, and the travel time can be obtained. The reliability is higher.
  • the road condition information, radio data, line data, etc. collected by the manual industry can only obtain the road condition information of the road through the data collected by the human industry, and there is no travel time information, and the road condition status is highly reliable.
  • traffic data collected by the artificial field There are also data sources such as traffic data collected by the artificial field or traffic data with video entry.
  • any combination of the above various data can be selected.
  • Multiple data source fusion processing methods are more, and can be weighted according to the reliability of different data sources to obtain a value, and also according to the DS evidence theory method. Fusion and more.
  • the coverage rate is very low, which requires data collected through artificial internal industry, data collected by the field, data collected by highways, or directly
  • the data of the traffic video input and other data are merged together, and then the historical traffic data is filled and the congestion point information is corrected, and finally the traffic road condition of the urban road can be obtained. For example, the traffic intersection of a certain road is smooth.
  • the average speed of the target road can be determined according to the grade of the target road and the traffic road condition.
  • an embodiment of the present invention further provides a device for predicting travel time.
  • the device includes: a first acquiring unit 21, a determining unit 22, and a calculating unit 23.
  • the first acquisition unit 21 is configured to acquire the level of the target road and the traffic condition.
  • the traffic conditions of the target road can be derived from the fusion of multiple data sources.
  • the determining unit 22 is then operative to determine an average speed of the target road based on the level of the target road and the traffic condition.
  • the calculation unit 23 is configured to divide the length of the target road by the average speed of the target road to derive the travel time of the target road. Since the device is the travel time of the target road obtained by obtaining the traffic road condition, the prior art also solves the problem that the prior art can only obtain the road traffic condition and can not obtain the travel time. The data sometimes cannot predict the travel time of the road.
  • a travel time prediction method of a road is taken as an example to describe a travel time prediction method. As shown in FIG. 3, the method includes the following steps:
  • the lengths of each road unit in the target road are sequentially acquired, and the total length of all road units in the target road is the length of the target road, according to the RTI C standard (Rea lT ime Informa ti on of Ch ina , China Real-time traffic information)
  • the target road includes at least one road unit. After sequentially obtaining the length of each road unit in the target road, the lengths of all the road units are summed to obtain the length of the target road.
  • each road unit in the target road is sequentially acquired.
  • Each of the road units has a corresponding rating.
  • each road list in the target road The traffic conditions of the yuan are the same as the traffic conditions of the target road.
  • the traffic condition of each of the road units can be determined after the traffic road conditions of the target road are obtained.
  • the acquired traffic conditions include smooth, slow, or congested, and the traffic conditions of each road can be obtained through the fusion of multiple data sources.
  • the various data sources include, but are not limited to, the following data types: Floating car data, since the floating car data contains time information, the road travel time can be obtained by processing the floating car data, and the travel time can be The reliability is higher.
  • the road condition information, radio data, line data, etc. collected by the manual industry can only obtain the road condition information of the road through the data collected by the human industry, and there is no travel time information, and the road condition status is highly reliable.
  • traffic data collected by the artificial field There are also data sources such as traffic data collected by the artificial field or traffic data with video entry.
  • any combination of the above various data can be selected.
  • Multiple data source fusion processing methods are more, and can be weighted according to the reliability of different data sources to obtain a value, and also according to the DS evidence theory method. Fusion and more.
  • the coverage rate is very low, which requires data collected through artificial internal industry, data collected by the field, data collected by highways, or directly
  • the data of the traffic video input and other data are merged together, and then the historical traffic data is filled and the congestion point information is corrected, and finally the traffic road condition of the urban road can be obtained. For example, the traffic intersection of a certain road is smooth.
  • the level of the target road and the traffic road condition determine the average of the target road. If the target road includes a road unit, the obtained speed is obtained from the preset speed configuration information according to the grade of the road unit and the traffic road condition. The speed of the road unit, since the target road has only one road unit at this time, the acquired speed is the average speed of the target road.
  • the preset speed configuration information includes speeds of road units of each level under different traffic conditions. Due to the different characteristics of different grades of roads, and considering the speed limit standards of each type of road, the preset speed configuration information of different urban road units may be different in configuration.
  • the speed is 65 km/h when the traffic condition is unblocked; and the speed is slow when the traffic condition is slow. 44 km/h; speed is 24 km/h when traffic conditions are congested.
  • the preset speed configuration information the speed corresponding to different levels of single-channel units in different road conditions can be obtained.
  • the speed of each of the road units is obtained from the preset speed configuration information according to the level of each of the road units and the traffic condition. For example, if the target road includes three road units, and the obtained traffic road condition of the target road is slow, it can be known that the traffic condition of each of the road units is slow. Then, according to the respective ranks of the three road units obtained in sequence, it is assumed that the first road unit level obtained is Type l and the length is L1, the second road unit level is Type 2 and the length is L2, and the third The road unit level is Type 3 and the length is L 3 .
  • the first road unit level is selected as Type 1 from the preset speed configuration information, and the speed is VI when the traffic condition is slow, the second road unit level is Type 2, and when the traffic condition is slow, The speed is V2 and the third road unit level is Type 3 and the speed is V3 when the traffic condition is slow.
  • the embodiment of the present invention further provides a device for predicting travel time.
  • the device includes: a first obtaining unit 41, a determining unit 42, and a calculating unit 43.
  • the first obtaining unit 41 is configured to acquire the level of the target road and the traffic road condition.
  • the obtained traffic conditions include smooth, slow or congested, and the traffic conditions of each road can be obtained through the fusion of various data sources.
  • the target road includes at least one road unit, and the total length of all road units in the target road is the length of the target road.
  • the level of the acquired target road is the rank of each road unit in the target road sequentially acquired.
  • the determining unit 42 is then configured to determine an average speed of the target road based on the level of the target road and the traffic condition.
  • the determining unit includes: a first obtaining module 42A.
  • Each of the preset speed configuration information is acquired.
  • the first acquisition module 42A is configured to acquire the road from the preset speed configuration information according to the level of the road unit and the traffic road condition, when the target road includes at least one road unit.
  • the speed of the unit, the acquired speed is the average speed of the target road.
  • the determining unit may further include: a second obtaining module 42B and a calculating module 42C.
  • the second obtaining module 42B is configured to acquire the speed of each road unit from the preset speed configuration information according to the level of each road unit and the traffic road condition when the target road includes at least two road units. . Then, a calculation module 42C is configured to use the length of each road unit as the weight of the road unit speed, and weight the average of the speeds of all the road units to obtain an average speed of the target road.
  • the calculating unit 43 A travel time of the target road is obtained by dividing a length of the target road by an average speed of the target road. Therefore, the problem that the road cannot be predicted when the road condition of the road can only be obtained and the travel time data cannot be obtained is solved in the prior art;
  • the embodiments of the present invention are mainly applied to the field of intelligent transportation, and the travel time prediction of the road is realized by the acquired road traffic condition.
  • the present invention can be implemented by means of software plus necessary general hardware, and of course, by hardware, but in many cases, the former is a better implementation. .
  • the technical solution of the present invention which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a readable storage medium, such as a floppy disk of a computer.
  • a hard disk or optical disk or the like includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the methods described in various embodiments of the present invention.

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  • Analytical Chemistry (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Traffic Control Systems (AREA)

Abstract

A method for predicting travel time comprises following steps: obtaining the grade and the traffic condition of the target road (101); determining the average speed on the target road based on the grade and traffic condition of the target road (102); getting the travel time on the target road through dividing the length of the target road by the average speed on the target road (103). The application solves a problem that the travel time can not be predicted when only the traffic condition of the road can be obtained but the travel time can not.

Description

旅行时间预测的方法及装置 本申请要求于 2 009 年 1 2 月 3 0 日提交中国专利局、 申请号为 2 009 1 0244 148. 9 . 发明名称为 "；^行时间预测的方法及装置" 的中 国专利申请的优先权， 其全部内容通过引用结合在本申请中。  Method and device for predicting travel time The application is filed on January 30, 2010 in the Chinese Patent Office, and the application number is 2 009 1 0244 148. 9 . The invention is entitled "Method and Apparatus for Time Prediction" Priority of the Chinese Patent Application, the entire contents of which is incorporated herein by reference.
技术领域 Technical field
本发明涉及智能交通领域， 尤其涉及一种旅行时间预测的方法 及装置。  The present invention relates to the field of intelligent transportation, and in particular, to a method and apparatus for traveling time prediction.
背景技术 Background technique
旅行时间预测可以方便出行者、 交通管理人员进行查询和各种 决策分析。 现有技术中在进行; ^行时间预测时， 以大量^行时间数 据作为基础， 通过聚类方法进行数据分析， 提取特征值进行匹配， 然后直接对所述 行时间进行预测， 从而得到道路的 ^行时间。  Travel time prediction can facilitate travellers, traffic management personnel to conduct inquiries and various decision analysis. In the prior art; when performing line time prediction, based on a large amount of time data, the data analysis is performed by the clustering method, the feature values are extracted for matching, and then the line time is directly predicted, thereby obtaining the road. ^ Line time.
发明人发现现有技术中釆用的算法往往都需要大量的实测旅行 时间数据来进行辨识， 如果缺乏大量的旅行时间数据作为支持， 则 算法的效果不是很理想。 如： 由于一些城市根本就没有浮动车数据， 或者浮动车数据很少， 覆盖率很低时， 这时只能通过浮动车数据外 的其它种类数据， 比如人工内业釆集到的路况信息、 电台数据、 线 圈数据等进行数据融合来获得交通状态， 但这种情况下得不到旅行 发明内容  The inventors have found that algorithms used in the prior art often require a large amount of measured travel time data for identification. If a large amount of travel time data is lacking as support, the algorithm is not very effective. For example, since some cities do not have floating car data at all, or there are few floating car data, and the coverage rate is very low, only other types of data other than floating car data, such as road conditions collected by manual industry, can be used. Radio data, coil data, etc. are fused to obtain traffic status, but in this case, the invention content is not obtained.
本发明的实施例提供一种旅行时间预测的方法及装置，实现了基于道 路的交通状态来进行旅行时间的预测。  Embodiments of the present invention provide a method and apparatus for travel time prediction that enables travel time prediction based on road traffic conditions.
为达到上述目的， 本发明的实施例釆用如下技术方案：  In order to achieve the above object, embodiments of the present invention use the following technical solutions:
一种 ^行时间预测的方法， 包括：  A method for predicting line time, including:
获取目标道路的等级和交通路况；  Obtain the grade of the target road and traffic conditions;
根据所述目标道路的等级和交通路况确定所述目标道路的平均速度； 将所述目标道路的长度除以所述目标道路的平均速度得出所述目标 道路的;^行时间。 Determining an average speed of the target road according to a grade of the target road and a traffic road condition; and dividing the length of the target road by an average speed of the target road to obtain the target The time of the road;
一种旅行时间预测的装置， 包括：  A device for predicting travel time, comprising:
第一获取单元， 用于获取目标道路的等级和交通路况；  a first acquiring unit, configured to acquire a level of the target road and a traffic road condition;
确定单元，用于根据所述目标道路的等级和交通路况确定所述目标道 路的平均速度；  a determining unit, configured to determine an average speed of the target road according to a grade of the target road and a traffic road condition;
计算单元，用于将所述目标道路的长度除以所述目标道路的平均速度 得出所述目标道路的 行时间。  And a calculating unit, configured to divide the length of the target road by the average speed of the target road to obtain a line time of the target road.
由上述技术方案所描述的本发明实施例，通过获取目标道路的等级和 交通路况， 所述交通路况可以为畅通、 緩慢或者拥堵， 然后根据所述目标 道路的等级和交通路况确定所述目标道路的平均速度。最后通过所述将所 述目标道路的长度除以所述目标道路的平均速度就可以得出所述目标道 路的旅行时间。 实现了通过道路的交通路况来进行旅行时间的预测 , 与现 有技术中直接通过实测的旅行时间数据进行道路的旅行时间预测相比，本 发明实施例不受城市提供的数据源的限制，解决了现有技术中当只能获得 道路的交通路况并且获取不到旅行时间数据时而无法预测道路旅行时间 的问题。  According to the embodiment of the present invention described in the above technical solution, the traffic road condition may be smooth, slow or congested by acquiring the level of the target road and the traffic road condition, and then determining the target road according to the grade of the target road and the traffic road condition. The average speed. Finally, the travel time of the target road can be obtained by dividing the length of the target road by the average speed of the target road. The travel time prediction is implemented by the traffic condition of the road, and the embodiment of the present invention is not limited by the data source provided by the city, compared with the travel time prediction of the road directly by the measured travel time data in the prior art. In the prior art, the problem of the road travel time cannot be predicted when only the traffic condition of the road can be obtained and the travel time data cannot be obtained.
附图说明 DRAWINGS
图 1为实施例 1 中;^行时间预测的方法的流程图；  1 is a flow chart of a method for predicting time in the first embodiment;
图 2为实施例 1 中旅行时间预测的装置的结构框图；  2 is a structural block diagram of an apparatus for predicting travel time in Embodiment 1;
图 3为实施例 2 中;^行时间预测的方法的流程图；  3 is a flow chart of a method for predicting time in Embodiment 2;
图 4为实施例 2 中旅行时间预测的装置的结构框图。  Fig. 4 is a block diagram showing the structure of an apparatus for predicting travel time in the second embodiment.
具体实施方式 detailed description
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。 基于本发明中的实施例， 本领域普通技术人员在没 有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的 范围。  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 of the embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts are within the scope of the present invention.
实施例 1： 本发明实施例提供一种旅行时间预测的方法， 如图 1所示， 该方法包 括如下步骤： Example 1: An embodiment of the present invention provides a method for predicting travel time. As shown in FIG. 1, the method includes the following steps:
1 01、 获取目标道路的等级和交通路况。 所述获取到的交通路况包括 畅通、 緩慢或者拥堵， 可以通过多种数据源的融合获得每条道路的交通路 况。 该多种数据源包括但不限于以下几种数据种类： 浮动车数据， 由于浮 动车数据是包含时间信息的，所以通过对浮动车数据的处理是可以得到道 路旅行时间的， 而且旅行时间的可信度较高。  1 01. Obtain the grade of the target road and traffic conditions. The acquired traffic conditions include smooth, slow or congested, and the traffic conditions of each road can be obtained through the fusion of various data sources. The various data sources include, but are not limited to, the following data types: Floating car data, since the floating car data contains time information, the travel time of the floating car data can be obtained, and the travel time can be obtained. The reliability is higher.
人工内业釆集到的路况信息、 电台数据、 线圏数据等， 通过人工业釆 集到的数据只能得到道路的路况信息， 没有旅行时间信息， 路况状态的可 信度较高。  The road condition information, radio data, line data, etc. collected by the manual industry can only obtain the road condition information of the road through the data collected by the human industry, and there is no travel time information, and the road condition status is highly reliable.
高速公路中通过收费站等釆集到的交通信息。  Traffic information collected by toll stations in highways.
另外还有人工外业采集到的交通数据或者有视频录入的交通数据等 数据源。  There are also data sources such as traffic data collected by the artificial field or traffic data with video entry.
多种数据源在融合时可以选择上述各种数据的任意组合，多种数据源 融合处理方法比较多， 可以按照不同数据源的可信度进行加权得到一个 值， 也有按照基于 D-S证据理论方法进行融合等等。  When multiple data sources are merged, any combination of the above various data can be selected. Multiple data source fusion processing methods are more, and can be weighted according to the reliability of different data sources to obtain a value, and also according to the DS evidence theory method. Fusion and more.
比如， 当一些城市没有浮动车数据时， 或者浮动车数据很少， 覆盖率 很低， 这就需要将通过人工内业采集的数据、 外业采集的数据、 高速公路 采集到的数据或者直接由交通视频录入的数据等多种数据融合在一起，然 后加上历史交通数据的填补和拥堵点信息修正，最终就可以得到城市道路 的交通路况， 比如说得到某条道路的交通路口为畅通。  For example, when some cities do not have floating car data, or floating car data is very small, the coverage rate is very low, which requires data collected through artificial internal industry, data collected by the field, data collected by highways, or directly The data of the traffic video input and other data are merged together, and then the historical traffic data is filled and the congestion point information is corrected, and finally the traffic road condition of the urban road can be obtained. For example, the traffic intersection of a certain road is smooth.
1 02、 艮据所述目标道路的等级和交通路况确定所述目标道路的平均 速度。 通过多种数据源的融合得到上述目标道路的交通路况之后， 就可以 根据所述目标道路的等级和交通路况确定所述目标道路的平均速度。  1 02. Determine an average speed of the target road according to the grade of the target road and the traffic road condition. After obtaining the traffic road condition of the target road by the fusion of the plurality of data sources, the average speed of the target road can be determined according to the grade of the target road and the traffic road condition.
1 03、 将所述目标道路的长度除以所述目标道路的平均速度得出所述 目标道路的旅行时间。由于是根据所述目标道路的交通路况获得的平均速 度进而又计算出了所述目标道路的旅行时间，这就解决了现有技术中当只 能获得道路的交通路况并且获取不到旅行时间数据时而无法预测道路^ 行时间的问题。并且该方法在进行旅行时间预测时通过多种数据源的融合 得到所述目标道路的交通路况，然后又通过所述交通路况计算出所述目标 道路的旅行时间，因而与现有技术中直接通过实测旅行时间进行旅行时间 的预测相比， 本发明实施例不受城市提供的数据源的限制。 1 03. Divide the length of the target road by the average speed of the target road to obtain a travel time of the target road. Since the average speed obtained from the traffic road condition of the target road is further calculated as the travel time of the target road, this solves the prior art when only It is impossible to predict the road time when the road traffic conditions are available and the travel time data is not available. And the method obtains the traffic road condition of the target road by the fusion of the plurality of data sources during the travel time prediction, and then calculates the travel time of the target road by using the traffic road condition, and thus directly passes the prior art. Embodiments of the present invention are not limited by the data sources provided by the city as compared to the prediction of the travel time for the travel time.
为了实现上述方法本发明实施例还提供一种旅行时间预测的装置，如 图 2所示， 该装置包括： 第一获取单元 21、 确定单元 22和计算单元 23。  In order to achieve the above method, an embodiment of the present invention further provides a device for predicting travel time. As shown in FIG. 2, the device includes: a first acquiring unit 21, a determining unit 22, and a calculating unit 23.
第一获取单元 21用于获取目标道路的等级和交通路况。 所述目标道 路的交通路况可以通过多种数据源的融合得出。 然后确定单元 22用于根 据所述目标道路的等级和交通路况确定所述目标道路的平均速度。计算单 元 23用于将所述目标道路的长度除以所述目标道路的平均速度得出所述 目标道路的旅行时间。由于本装置是通过获取交通路况进而得出的所述目 标道路的旅行时间，因而也解决了现有技术中这就解决了现有技术中当只 能获得道路的交通路况并且获取不到旅行时间数据时而无法预测道路旅 行时间的问题。  The first acquisition unit 21 is configured to acquire the level of the target road and the traffic condition. The traffic conditions of the target road can be derived from the fusion of multiple data sources. The determining unit 22 is then operative to determine an average speed of the target road based on the level of the target road and the traffic condition. The calculation unit 23 is configured to divide the length of the target road by the average speed of the target road to derive the travel time of the target road. Since the device is the travel time of the target road obtained by obtaining the traffic road condition, the prior art also solves the problem that the prior art can only obtain the road traffic condition and can not obtain the travel time. The data sometimes cannot predict the travel time of the road.
实施例 2:  Example 2:
本发明实施例以一条道路的旅行时间预测为例详细介绍一种旅行时 间预测的方法， 如图 3所示， 该方法包括以下步骤：  In the embodiment of the present invention, a travel time prediction method of a road is taken as an example to describe a travel time prediction method. As shown in FIG. 3, the method includes the following steps:
301、 依次获取所述目标道路中每条道路单元的长度， 目标道路中所 有道路单元的长度总和即为所述目 标道路的长度， 按 RTI C 标准 ( Rea l-T ime Informa t i on of Ch ina , 中国实时交通信息） 进行道路划分 时， 所述目标道路包括至少一条道路单元。 当依次获取所述目标道路中每 条道路单元的长度之后，将所述所有道路单元的长度进行加和从而就可以 得出所述目标道路的长度。  301. The lengths of each road unit in the target road are sequentially acquired, and the total length of all road units in the target road is the length of the target road, according to the RTI C standard (Rea lT ime Informa ti on of Ch ina , China Real-time traffic information) When performing road division, the target road includes at least one road unit. After sequentially obtaining the length of each road unit in the target road, the lengths of all the road units are summed to obtain the length of the target road.
同时依次获取目标道路中每条道路单元的等级。所述每条道路单元都 有对应的等级。  At the same time, the ranks of each road unit in the target road are sequentially acquired. Each of the road units has a corresponding rating.
302、 获取目标道路的等级和交通路况； 所述目标道路中每条道路单 元的交通路况与所述目标道路的交通路况相同。当得到目标道路的交通路 况之后就可以确定所述每个道路单元的交通路况。 302. Obtain a grade of a target road and a traffic road condition; each road list in the target road The traffic conditions of the yuan are the same as the traffic conditions of the target road. The traffic condition of each of the road units can be determined after the traffic road conditions of the target road are obtained.
所述获取到的交通路况包括畅通、 緩慢或者拥堵， 可以通过多种数据 源的融合获得每条道路的交通路况。该多种数据源包括但不限于以下几种 数据种类： 浮动车数据， 由于浮动车数据是包含时间信息的， 所以通过对 浮动车数据的处理是可以得到道路旅行时间的，而且旅行时间的可信度较 高。  The acquired traffic conditions include smooth, slow, or congested, and the traffic conditions of each road can be obtained through the fusion of multiple data sources. The various data sources include, but are not limited to, the following data types: Floating car data, since the floating car data contains time information, the road travel time can be obtained by processing the floating car data, and the travel time can be The reliability is higher.
人工内业釆集到的路况信息、 电台数据、 线圏数据等， 通过人工业釆 集到的数据只能得到道路的路况信息， 没有旅行时间信息， 路况状态的可 信度较高。  The road condition information, radio data, line data, etc. collected by the manual industry can only obtain the road condition information of the road through the data collected by the human industry, and there is no travel time information, and the road condition status is highly reliable.
高速公路中通过收费站等釆集到的交通信息。  Traffic information collected by toll stations in highways.
另外还有人工外业采集到的交通数据或者有视频录入的交通数据等 数据源。  There are also data sources such as traffic data collected by the artificial field or traffic data with video entry.
多种数据源在融合时可以选择上述各种数据的任意组合，多种数据源 融合处理方法比较多， 可以按照不同数据源的可信度进行加权得到一个 值， 也有按照基于 D-S证据理论方法进行融合等等。  When multiple data sources are merged, any combination of the above various data can be selected. Multiple data source fusion processing methods are more, and can be weighted according to the reliability of different data sources to obtain a value, and also according to the DS evidence theory method. Fusion and more.
比如， 当一些城市没有浮动车数据时， 或者浮动车数据很少， 覆盖率 很低， 这就需要将通过人工内业采集的数据、 外业采集的数据、 高速公路 采集到的数据或者直接由交通视频录入的数据等多种数据融合在一起，然 后加上历史交通数据的填补和拥堵点信息修正，最终就可以得到城市道路 的交通路况， 比如说得到某条道路的交通路口为畅通。  For example, when some cities do not have floating car data, or floating car data is very small, the coverage rate is very low, which requires data collected through artificial internal industry, data collected by the field, data collected by highways, or directly The data of the traffic video input and other data are merged together, and then the historical traffic data is filled and the congestion point information is corrected, and finally the traffic road condition of the urban road can be obtained. For example, the traffic intersection of a certain road is smooth.
30 3、 # 居所述目标道路的等级和交通路况确定所述目标道路的平均 如果所述目标道路包括一条道路单元时，根据道路单元的等级和交通 路况从预设速度配置信息中获取所述道路单元的速度，由于此时该目标道 路只有一个道路单元，因而所述获取到的速度即为所述目标道路的平均速 度。 所述预设速度配置信息包括每种等级的道路单元在不同交通路况下 的速度。 由于不同等级道路具有不同的特点， 同时考虑到每种道路的限速 标准，不同城市道路单元的预设速度配置信息在配置时可能不一样。比如， 某城市的预设速度配置信息中当某条道路的其中一条道路单元等级为 1 级时， 在交通路况为畅通时对于的速度为 65km/h ; 在交通路况为緩慢时 对于的速度为 44 km/h; 在交通路况为拥堵时对于的速度为 24 km/h。 根 据所述预设速度配置信息就可以的到不同等级的单路单元在不同路况下 对应的速度。 30 3. The level of the target road and the traffic road condition determine the average of the target road. If the target road includes a road unit, the obtained speed is obtained from the preset speed configuration information according to the grade of the road unit and the traffic road condition. The speed of the road unit, since the target road has only one road unit at this time, the acquired speed is the average speed of the target road. The preset speed configuration information includes speeds of road units of each level under different traffic conditions. Due to the different characteristics of different grades of roads, and considering the speed limit standards of each type of road, the preset speed configuration information of different urban road units may be different in configuration. For example, in a city's preset speed configuration information, when one of the road units of a certain road has a level of 1 level, the speed is 65 km/h when the traffic condition is unblocked; and the speed is slow when the traffic condition is slow. 44 km/h; speed is 24 km/h when traffic conditions are congested. According to the preset speed configuration information, the speed corresponding to different levels of single-channel units in different road conditions can be obtained.
或者， 如果所述目标道路包括至少两条道路单元时， 依次根据所述每 条道路单元的等级和交通路况从预设速度配置信息中获取所述每条道路 单元的速度。 如， 假设所述目标道路包括 3个道路单元， 获取到的所述目 标道路的交通路况为緩慢时，可以知道所述每个道路单元的交通路况均为 緩慢。 然后再根据依次获取到的所述 3个道路单元各自的等级， 假设获取 到的第一个道路单元等级为 Type l 并且长度为 L1 , 第二个道路单元等级 为 Type2并且长度为 L2 , 第三个道路单元等级为 Type 3并且长度为 L 3。 然后从上述预设速度配置信息中依次取出第一个道路单元等级为 Type l 并且在交通路况为緩慢时对于的速度为 VI ,第二个道路单元等级为 Type 2 并且在交通路况为緩慢时对于的速度为 V2 和第三个道路单元等级为 Type 3并且在交通路况为缓慢时对于的速度为 V 3。  Alternatively, if the target road includes at least two road units, the speed of each of the road units is obtained from the preset speed configuration information according to the level of each of the road units and the traffic condition. For example, if the target road includes three road units, and the obtained traffic road condition of the target road is slow, it can be known that the traffic condition of each of the road units is slow. Then, according to the respective ranks of the three road units obtained in sequence, it is assumed that the first road unit level obtained is Type l and the length is L1, the second road unit level is Type 2 and the length is L2, and the third The road unit level is Type 3 and the length is L 3 . Then, the first road unit level is selected as Type 1 from the preset speed configuration information, and the speed is VI when the traffic condition is slow, the second road unit level is Type 2, and when the traffic condition is slow, The speed is V2 and the third road unit level is Type 3 and the speed is V3 when the traffic condition is slow.
然后将所述每条道路单元的长度作为该道路单元速度的权数，对所述 所有道路单元的速度进行加权平均得出所述目标道路的平均速度。具体如 下： 假设计算的出的所述目标道路的平均速度用 V 表示， 那么 V = ( V 1 *L 1 +V2 *L2+V 3 *L 3 ) / ( )。  The length of each road unit is then used as the weight of the road unit speed, and the average speed of the target road is obtained by weighting the speeds of the all road units. Specifically as follows: Assuming that the calculated average speed of the target road is expressed by V, then V = (V 1 *L 1 +V2 *L2+V 3 *L 3 ) / ( ).
304、 将所述目标道路的长度除以所述目标道路的平均速度得出所述 目标道路的旅行时间。将依次获取到的所述目标道路中每条道路单元的长 度进行加和就可以得出所述目标道路的长度。将该长度除于步驟 303得出 的平均速度就可以算出所述目标道路的旅行时间。从而也解决了现有技术 中当只能获得道路的交通路况并且获取不到旅行时间数据时而无法预测 道路旅行时间的问题。并且该方法在进行旅行时间预测时通过多种数据源 的融合得到所述目标道路的交通路况，然后又通过所述交通路况计算出所 述目标道路的旅行时间，因而与现有技术中直接通过实测旅行时间进行旅 行时间的预测相比， 本发明实施例不受到城市提供的数据源的限制。 304. Divide the length of the target road by the average speed of the target road to obtain a travel time of the target road. The length of the target road can be obtained by summing the lengths of each road unit in the target road sequentially acquired. The travel time of the target road can be calculated by dividing the length by the average speed obtained in step 303. Thereby solving the prior art The problem of road travel time cannot be predicted when the traffic conditions of the road can only be obtained and the travel time data cannot be obtained. And the method obtains the traffic road condition of the target road by the fusion of the plurality of data sources during the travel time prediction, and then calculates the travel time of the target road by using the traffic road condition, and thus directly passes the prior art. Compared to the prediction of travel time for measured travel time, embodiments of the present invention are not limited by data sources provided by the city.
本发明实施例还提供一种旅行时间预测的装置， 如图 4所示， 该装置 包括： 第一获取单元 41 , 确定单元 42， 计算单元 4 3。  The embodiment of the present invention further provides a device for predicting travel time. As shown in FIG. 4, the device includes: a first obtaining unit 41, a determining unit 42, and a calculating unit 43.
其中， 第一获取单元 41用于获取目标道路的等级和交通路况。 所述 获取到的交通路况包括畅通、 緩慢或者拥堵， 可以通过多种数据源的融合 获得每条道路的交通路况。 所述目标道路包括至少一条道路单元， 所述目 标道路中所有道路单元的长度总和即为所述目标道路的长度。所述获取到 的目标道路的等级为依次获取到的所述目标道路中每个道路单元的等级。  The first obtaining unit 41 is configured to acquire the level of the target road and the traffic road condition. The obtained traffic conditions include smooth, slow or congested, and the traffic conditions of each road can be obtained through the fusion of various data sources. The target road includes at least one road unit, and the total length of all road units in the target road is the length of the target road. The level of the acquired target road is the rank of each road unit in the target road sequentially acquired.
然后确定单元 42， 用于根据所述目标道路的等级和交通路况确定所 述目标道路的平均速度。 所述确定单元包括： 第一获取模块 42A。 每种等 预设速度配置信息获取到。 由于所述目标道路包括至少一条道路单元， 第 一获取模块 42A用于在所述目标道路包括一条道路单元时，根据所述道路 单元的等级和交通路况从预设速度配置信息中获取所述道路单元的速度， 所述获取到的速度即为所述目标道路的平均速度。  The determining unit 42 is then configured to determine an average speed of the target road based on the level of the target road and the traffic condition. The determining unit includes: a first obtaining module 42A. Each of the preset speed configuration information is acquired. The first acquisition module 42A is configured to acquire the road from the preset speed configuration information according to the level of the road unit and the traffic road condition, when the target road includes at least one road unit. The speed of the unit, the acquired speed is the average speed of the target road.
或者， 可选的， 所述确定单元也可以包括： 第二获取模块 42B和计算 模块 42C。  Alternatively, the determining unit may further include: a second obtaining module 42B and a calculating module 42C.
第二获取模块 42B , 用于在所述目标道路包括至少两条道路单元时， 依次根据所述每条道路单元的等级和交通路况从预设速度配置信息中获 取所述每条道路单元的速度。 然后计算模块 42C , 用于将所述每条道路单 元的长度作为该道路单元速度的权数，对所述所有道路单元的速度进行加 权平均得出所述目标道路的平均速度。  The second obtaining module 42B is configured to acquire the speed of each road unit from the preset speed configuration information according to the level of each road unit and the traffic road condition when the target road includes at least two road units. . Then, a calculation module 42C is configured to use the length of each road unit as the weight of the road unit speed, and weight the average of the speeds of all the road units to obtain an average speed of the target road.
所述确定单元 42 确定所述目标道路的平均速度之后， 计算单元 4 3 用于将所述目标道路的长度除以所述目标道路的平均速度得出所述目标 道路的旅行时间。从而解决了现有技术中当只能获得道路的交通路况并且 获取不到旅行时间数据时而无法预测道路; j良行时间的问题。 After the determining unit 42 determines the average speed of the target road, the calculating unit 43 A travel time of the target road is obtained by dividing a length of the target road by an average speed of the target road. Therefore, the problem that the road cannot be predicted when the road condition of the road can only be obtained and the travel time data cannot be obtained is solved in the prior art;
本发明实施例主要应用于智能交通领域，通过获取到的道路交通路况 实现了道路的旅行时间预测。  The embodiments of the present invention are mainly applied to the field of intelligent transportation, and the travel time prediction of the road is realized by the acquired road traffic condition.
通过以上的实施方式的描述，所属领域的技术人员可以清楚地了解到 本发明可借助软件加必需的通用硬件的方式来实现， 当然也可以通过硬 件， 但很多情况下前者是更佳的实施方式。 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可读取的存储介质中， 如计算机的软 盘， 硬盘或光盘等， 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的方法。 以上所述， 仅为本发明的具体实施方式， 但本发明的保护范围并不局限于 此， 任何熟悉本技术领域的技术人员在本发明揭露的技术范围内， 可轻易 想到变化或替换， 都应涵盖在本发明的保护范围之内。 因此， 本发明的保 护范围应以所述权利要求的保护范围为准。  Through the description of the above embodiments, those skilled in the art can clearly understand that the present invention can be implemented by means of software plus necessary general hardware, and of course, by hardware, but in many cases, the former is a better implementation. . Based on such understanding, the technical solution of the present invention, which is essential or contributes to the prior art, may be embodied in the form of a software product stored in a readable storage medium, such as a floppy disk of a computer. A hard disk or optical disk or the like includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform the methods described in various embodiments of the present invention. The above is only the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily think of changes or substitutions within the technical scope of the present invention. It should be covered by the scope of the present invention. Accordingly, the scope of the invention should be determined by the scope of the appended claims.

Claims

权 利 要 求 书 Claim
1、 一种旅行时间预测的方法， 其特征在于， 包括：  A method for predicting travel time, characterized in that it comprises:
获取目标道路的等级和交通路况；  Obtain the grade of the target road and traffic conditions;
根据所述目标道路的等级和交通路况确定所述目标道路的平均速度； 将所述目标道路的长度除以所述目标道路的平均速度得出所述目标道 路的旅行时间。  And determining an average speed of the target road according to a grade of the target road and a traffic road condition; and dividing a length of the target road by an average speed of the target road to obtain a travel time of the target road.
2、 根据权利要求 1所述的旅行时间预测的方法， 其特征在于， 所述目 标道路包括至少一条道路单元， 所述获取到的目标道路的等级为依次获取 到的所述目标道路中每个道路单元的等级；  The method for predicting travel time according to claim 1, wherein the target road includes at least one road unit, and the level of the acquired target road is each of the target roads sequentially acquired. The grade of the road unit;
所述目标道路中每条道路单元的交通路况与所述获取到的目标道路的 交通路况相同， 所述目标道路中所有道路单元的长度总和即为所述目标道 路的长度。  The traffic road condition of each road unit in the target road is the same as the traffic road condition of the acquired target road, and the total length of all road units in the target road is the length of the target road.
3、 根据权利要求 2所述的旅行时间预测的方法， 其特征在于， 所述目 标道路包括一条道路单元时， 所述根据所述目标道路的等级和交通路况确 定所述目标道路的平均速度为：  The method for predicting travel time according to claim 2, wherein when the target road includes a road unit, the determining an average speed of the target road according to a grade of the target road and a traffic road condition is :
根据所述道路单元的等级和交通路况获取所述道路单元的速度， 所述 获取到的速度即为所述目标道路的平均速度。  Acquiring the speed of the road unit according to the level of the road unit and the traffic road condition, and the obtained speed is the average speed of the target road.
4、 根据权利要求 2所述的旅行时间预测的方法， 其特征在于， 所述目 标道路包括至少两条道路单元时， 所述 居所述目标道路的等级和交通路 况确定所述目标道路的平均速度包括：  The method for predicting travel time according to claim 2, wherein when the target road includes at least two road units, the rank of the target road and the traffic road condition determine an average of the target road Speeds include:
依次根据所述每条道路单元的等级和交通路况获取所述每条道路单元 的速度；  Obtaining, according to the grade of each road unit and the traffic condition, the speed of each of the road units;
将所述每条道路单元的长度作为该道路单元速度的权数， 对所述所有 道路单元的速度进行加权平均得出所述目标道路的平均速度。  Using the length of each road unit as the weight of the road unit speed, weighting the speeds of all the road units to obtain an average speed of the target road.
5、 根据权利要求 3或 4所述的旅行时间预测的方法， 其特征在于， 所 述道路单元的速度为根据道路单元的等级和交通路况从预设速度配置信息 中获取到的速度， 所述预设速度配置信息包括每种等级的道路在不同交通 路况下的速度。  The method for predicting travel time according to claim 3 or 4, wherein the speed of the road unit is a speed obtained from preset speed configuration information according to a grade of a road unit and a traffic road condition, The preset speed configuration information includes the speed of each grade of road under different traffic conditions.
6、 一种旅行时间预测的装置， 其特征在于， 包括： 第一获取单元， 用于获取目标道路的等级和交通路况； 确定单元， 用于根据所述目标道路的等级和交通路况确定所述目标道 路的平均速度； 6. A device for predicting travel time, comprising: a first acquiring unit, configured to acquire a level of the target road and a traffic road condition; and a determining unit, configured to determine an average speed of the target road according to the level of the target road and the traffic road condition;
计算单元， 用于将所述目标道路的长度除以所述目标道路的平均速度 得出所述目标道路的 行时间。  And a calculating unit, configured to divide a length of the target road by an average speed of the target road to obtain a line time of the target road.
7、 根据权利要求 6所述的旅行时间预测的装置， 其特征在于， 所述确 定单元包括：  The apparatus for predicting travel time according to claim 6, wherein the determining unit comprises:
第一获取模块， 用于在所述目标道路包括一条道路单元时， 根据所述 道路单元的等级和交通路况获取所述道路单元的速度， 所述获取到的速度 即为所述目标道路的平均速度。  a first obtaining module, configured to acquire a speed of the road unit according to a level of the road unit and a traffic road condition when the target road includes a road unit, where the acquired speed is an average of the target road speed.
8、 根据权利要求 6所述的旅行时间预测的装置， 其特征在于， 所述确 定单元包括：  8. The apparatus for predicting travel time according to claim 6, wherein the determining unit comprises:
第二获取模块， 用于在所述目标道路包括至少两条道路单元时， 依次 根据所述每条道路单元的等级和交通路况获取所述每条道路单元的速度； 计算模块， 用于将所述每条道路单元的长度作为该道路单元速度的权 数， 对所述所有道路单元的速度进行加权平均得出所述目标道路的平均速 度。  a second obtaining module, configured to acquire, according to the level of each road unit and the traffic road condition, the speed of each road unit in sequence when the target road includes at least two road units; The length of each road unit is used as the weight of the road unit speed, and the average speed of the target road is obtained by weighting the speeds of all the road units.
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