CN102496279B - Method and device for system configuration of floating car - Google Patents

Method and device for system configuration of floating car Download PDF

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CN102496279B
CN102496279B CN 201110412813 CN201110412813A CN102496279B CN 102496279 B CN102496279 B CN 102496279B CN 201110412813 CN201110412813 CN 201110412813 CN 201110412813 A CN201110412813 A CN 201110412813A CN 102496279 B CN102496279 B CN 102496279B
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floating
road network
configuration
model
floating car
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CN102496279A (en
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贾学力
李建军
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北京世纪高通科技有限公司
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Abstract

本发明公开了一种浮动车系统配置方法及装置,涉及智能交通技术领域,用于解决现有技术中无法对浮动车系统进行配置的问题。 The present invention discloses a method and an apparatus arranged floating car system, intelligent transportation technical field relates, for solving the problems of the prior art can not be configured for floating car system. 本发明提供的方法包括:建立浮动车系统配置模型;获取所述浮动车系统配置模型的限定参数;根据所述限定参数对所述浮动车系统配置模型进行处理,得到浮动车系统的配置结果。 The present invention provides a method comprising: establishing a floating car system configuration model; acquiring the parameters defining the model floating vehicle system; processing the floating car system configuration model according to the parameters defined, to give the configuration of floating car system. 本发明适用于智能交通技术领域,用于对浮动车系统进行配置。 The present invention is applicable to the field of intelligent transportation technology, for floating car system configuration.

Description

浮动车系统配置方法及装置 Floating car system configuration method and apparatus

技术领域 FIELD

[0001] 本发明涉及智能交通技术领域,尤其涉及一种浮动车系统配置方法及装置。 [0001] The present invention relates to the field of intelligent transportation technology, particularly to a method and apparatus arranged floating vehicle systems.

背景技术 Background technique

[0002] 在智能交通领域,通过浮动车系统采集交通信息已成为获取道路交通信息的主要技术手段。 [0002] In the field of intelligent transportation by floating car traffic information collection system has become the main road traffic information acquisition technology. 浮动车系统以搭载有GPS(Global Positioning System,全球定位系统)车载装置和无线通信设备的浮动车(一般为出租车)作为采集工具,以获取实时交通信息。 Floating car system equipped with GPS (Global Positioning System, GPS) vehicle device and wireless communication devices floating car (usually a taxi) as a collection tool to obtain real-time traffic information. 浮动车系统具有建设周期短、投资少、覆盖范围广、实时性强等优点。 Floating car system has a short construction period, low investment, covering a wide range of real-time and other advantages. 近年来,随着浮动车上GPS装置的广泛应用、通信传输技术的快速发展,基于浮动车系统的交通信息数据的处理技术日趋成熟,并已应用到一些经济发达的城市。 In recent years, with the rapid development of a wide range of applications floating car GPS devices, communications transmission technology based on processing traffic information data floating car system matures, and has been applied to some economically developed cities. 由于各城市地理特征、经济⑶P、人口等因素互不相同,导致在交通信息质量指标一致的情况下,各城市所需的浮动车的数量、浮动车数据采集周期不同。 As the cities geographical characteristics, economic ⑶P, demographic and other factors different from each other, resulting in the same traffic information quality indicators, the number of cities required for floating cars, different floating car data acquisition cycle.

[0003] 在实现本发明的过程中,发明人发现现有技术中至少存在如下问题: [0003] During the implementation of the present invention, the inventor finds at least the following problems in the prior art:

[0004]目前,智能交通系统中并没有一种明确的计算方法能够使得浮动车运营商根据交通信息服务质量对浮动车系统进行配置(主要包括对浮动车数量和数据车数据采集周期进行配置),使得浮动车运营商无法对浮动车系统进行管理,导致浮动车系统的成本过高,或者是浮动车系统提供的交通信息的服务质量较低,严重阻碍了智能交通技术的发展。 [0004] At present, intelligent transportation system is not a clear calculation method enables the floating vehicle operator to configure the floating car traffic information system based on quality of service (including the number of floating car data and vehicle data acquisition cycle configuration) so that the floating car operators can not manage the floating car system, leading to the cost of floating car system is too high, or low quality traffic information service provided by floating car system, a serious impediment to the development of intelligent transportation technology.

发明内容 SUMMARY

[0005] 本发明的实施例提供一种浮动车系统配置方法及装置,能够使得浮动车运营商在服务质量和运营成本之间进行权衡,便于浮动车运营商对浮动车系统进行管理,有利于智能交通技术的发展。 [0005] Embodiments of the present invention to provide a floating car system configuration method and apparatus capable of floating cars such operators to trade-off between quality of service and operating costs, to facilitate the floating of the vehicle operator to manage floating car system, facilitate the development of intelligent transportation technology.

[0006] 为达到上述目的,本发明的实施例采用如下技术方案: [0006] To achieve the above object, embodiments of the present invention adopts the following technical solutions:

[0007] 一方面,本发明实施例提供了一种浮动车系统配置方法,包括: [0007] In one aspect, the present invention provides a floating car system configuration method, comprising:

[0008] 建立浮动车系统配置模型; [0008] The model build floating car system configuration;

[0009] 获取所述浮动车系统配置模型的限定参数; [0009] Gets the floating car system configuration parameters defining a model;

[0010] 根据所述限定参数对所述浮动车系统配置模型进行处理,得到浮动车系统的配置结果。 [0010] processed according to the parameters defining the floating car system configuration model, to obtain the configuration floating car system.

[0011] 另一方面,本发明实施例还提供了一种浮动车系统配置装置,包括: [0011] On the other hand, embodiments of the present invention further provides a floating car system configuration apparatus, comprising:

[0012] 建立单元,用于建立浮动车系统配置模型; [0012] establishing means for establishing a floating car system configuration model;

[0013] 获取单元,用于获取所述浮动车系统配置模型的限定参数; [0013] acquiring unit, configured to obtain the floating car system configuration parameters defining a model;

[0014] 处理单元,用于根据所述限定参数对所述浮动车系统配置模型进行处理,得到浮动车系统的配置结果。 [0014] processing means for performing processing according to the parameters defining the floating car system configuration model, to obtain the configuration floating car system.

[0015] 本发明实施例提供的浮动车系统配置方法及装置,通过建立浮动车系统配置模型,能够根据用户设定的服务质量指标对浮动车系统进行配置,得到配置结果以供浮动车运营商进行参考,使得浮动车运营商在运营成本和服务质量之间进行权衡,便于运营商对浮动车系统进行管理,有利于智能交通技术的发展。 [0015] floating car system configuration method and apparatus provided by the embodiment of the present invention is configured by establishing a model of floating car system can be configured for floating car system according to a service quality indicators set by the user, to obtain the configuration for floating car carriers reference is that the floating car operators tradeoffs between operating costs and service quality, ease of operators to manage the floating car system is conducive to the development of intelligent transportation technology.

附图说明 BRIEF DESCRIPTION

[0016] 为了更清楚地说明本发明实施例或现有技术中的技术方案,下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍,显而易见地,下面描述中的附图仅仅是本发明的一些实施例,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其他的附图。 [0016] In order to more clearly illustrate the technical solutions in the embodiments or the prior art embodiment of the present invention, briefly introduced hereinafter, embodiments are described below in the accompanying drawings or described in the prior art needed to be used in describing the embodiments the drawings are only some embodiments of the present invention, those of ordinary skill in the art is concerned, without creative efforts, can derive from these drawings other drawings.

[0017] 图1为本发明实施例1提供的方法流程示意图; [0017] FIG. 1 is a schematic flowchart of a method provided in Example 1 of the embodiment of the present invention;

[0018] 图2为本发明实施例2提供的方法流程示意图; [0018] FIG. 2 is a schematic flowchart of a method provided in Example 2 of the embodiment of the present invention;

[0019] 图3-图6为本发明实施例3提供的装置的结构示意图。 [0019] Figures 3-6 provide a schematic structure of the apparatus in Example 3 of the present invention.

具体实施方式 Detailed ways

[0020] 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。 [0020] below in conjunction with the present invention in the accompanying drawings, technical solutions of embodiments of the present invention are clearly and completely described, obviously, the described embodiments are merely part of embodiments of the present invention, but not all embodiments example. 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。 Based on the embodiments of the present invention, those of ordinary skill in the art to make all other embodiments without creative work obtained by, it falls within the scope of the present invention.

[0021] 实施例1 [0021] Example 1

[0022] 本发明实施例提供了一种浮动车系统配置方法,如图1所示,所述方法包括: [0022] Example embodiments provide a floating car system configuration method according to the present invention, as shown in Figure 1, the method comprising:

[0023] 101、建立浮动车系统配置模型。 [0023] 101, the establishment of floating car system configuration model.

[0024] 102、获取所述浮动车系统配置模型的限定参数。 [0024] 102 to obtain the model parameters defining a floating car system.

[0025] 具体的,所述浮动车系统配置模型的限定参数可以由浮动车运营商进行设定。 [0025] Specifically, the floating car system configuration model defining the parameters can be set by the operator of floating cars.

[0026] 103、根据所述限定参数对所述浮动车系统配置模型进行处理,得到浮动车系统的配置结果。 [0026] 103, the processing according to the parameters defining the floating car system configuration model, to obtain the configuration floating car system.

[0027] 具体的,所述配置结果包括浮动车系统配置的浮动车数量和浮动车数据采集周期,但不仅限于此。 [0027] Specifically, the configuration comprises a number of floating cars floating car system configuration and floating car data acquisition cycle, but is not limited thereto.

[0028] 本发明实施例提供的浮动车系统配置方法,能够根据浮动车运营商设定的限定参数对浮动车系统进行配置,得到配置结果以供浮动车运营商进行参考,使得浮动车运营商在运营成本和服务质量之间进行权衡,便于运营商对浮动车系统进行管理,有利于智能交通技术的发展。 [0028] floating car system configuration method provided in the embodiment of the present invention, can be defined in accordance with the parameters set by the operator of floating cars to the floating car system configuration, to obtain the configuration for reference is floating car carriers, such that carriers of floating cars tradeoffs between operating costs and the quality of services, for operators to manage the floating car system is conducive to the development of intelligent transportation technology.

[0029] 实施例2 [0029] Example 2

[0030] 本发明实施例提供了一种浮动车系统配置方法,如图2所示,所述方法包括: [0030] Example embodiments provide a floating car system configuration method according to the present invention, as shown in FIG, 2, the method comprising:

[0031] 201、对路网信息进行分析,确定影响路网覆盖率和路网可靠度的因素,所述因素包括但不限于浮动车数量、路网中的道路密度以及各等级道路在所述路网中所占的比例系数。 [0031] 201, the road network information is analyzed to determine the factors affecting the road network and road network coverage reliability, the factors including but not limited to the number of floating cars, road density road network and level of the road in each of the the proportion coefficient road network.

[0032] 值得说明的是,路网覆盖率和路网可靠度是评价浮动车系统服务质量的重要指标;由于路网中的道路信息较为固定,所以浮动车运营商通过设定浮动车数量是改善路网覆盖率和路网可靠度的首选方法。 [0032] It should be noted that the coverage of the road network and road network reliability is an important indicator of the quality evaluation system floating car services; road information because the road network is relatively fixed, floating car operators by setting the number of floating car is the preferred method for improving the road network and road network coverage reliability.

[0033] 202、根据所述影响路网覆盖率和路网可靠度的因素分别建立路网覆盖率模型和路网可靠度模型,得到路网覆盖率函数和路网可靠度函数的表达式,所述表达式用于表征浮动车数量的不同取值对应的路网覆盖率函数和路网可靠度。 [0033] 202, respectively, to establish the reliability of road network coverage model and the model of road network based on factors such road network and road network coverage affect the reliability, an expression for the road network and road network coverage function reliability function, the expression is used to characterize the number of floating cars corresponding to different values ​​of the road network and road network coverage function reliability.

[0034] 203、根据所述路网覆盖率模型和路网可靠度模型,以及交通信息服务质量和运营成本,建立所述浮动车数量配置模型。 [0034] 203, a model of the road network based on the reliability model and road network coverage, quality of service and traffic information and operating costs, the number of floating cars establishing the configuration model.

[0035] 为了便于理解,本发明实施例提供了一种浮动车数量配置模型以供参考, [0035] For ease of understanding, embodiments of the present invention provides a number of floating cars by reference configuration model,

[0036] 具体如下: [0036] as follows:

[0037] [0037]

Figure CN102496279BD00071

[0038] 其中,Yl代表路网覆盖率函数,Υ2代表路网可靠度函数;MinC0Verage为路网覆盖率的最小期望值,MinReliability为路网可靠度的最小期望值,MinImprove为路网覆盖率改善度的最小值,Nmax为路网中能够运行的浮动车数量的最大值;其中,路网覆盖率改善度以百分点为单位,用于表征在浮动车数量为N的基础上,增加η辆浮动车时路网覆盖率的改善值,所述η由浮动车运营商设定。 [0038] wherein, Yl function representative of road network coverage, Υ2 representative of road network reliability function; MinC0Verage minimum desired value of road network coverage, MinReliability minimum desired value for the road network reliability, MinImprove road network coverage is improved degree minimum value, the maximum number Nmax of the road network is capable of operating in floating car; wherein the improvement of road network coverage in units of percentage points, the basis for characterizing the number of floating cars is N, the floating car vehicle increases η improve the road network coverage value, set by the floating η vehicle operator. 例如:如果浮动车运营商将η设定为100,将MinImprove设定为20 则表征浮动车运营商期望在当前浮动车系统中,增加100辆浮动车,路网覆盖率至少要提高20% ;若增加100辆浮动车,路网覆盖率的改善值低于20%,则浮动车运营商可以判定为不需要增加浮动车辆。 For example: if the probe vehicle operators will η is set to 100, the set 20 MinImprove floating vehicle operator desires to characterize the current floating car system, increasing the floating cars 100, road network coverage for at least 20%; If the increase in floating car 100, the value of the road network to improve the coverage is less than 20%, the float can be determined that the vehicle operator does not need to increase the floating vehicle.

[0039] 显而易见的,在浮动车系统中,路网中存在的浮动车数量η越大,则每增加N量浮动车带来的路网覆盖率改善度越小。 [0039] apparent in the floating car system, the number of road network in the presence of floating car larger η, the smaller each additional amount of N floating car brings improvement of road network coverage.

[0040] 204、获取所述浮动车数量配置模型的限定参数,以作为步骤203中浮动车数量配置模型的约束条件。 [0040] 204 to obtain the number of floating cars configuration model defining parameters as constraints in step 203 the number of floating cars configuration model.

[0041] 具体的,所述限定参数由浮动车运营商进行设定,所述限定参数包括:路网中能够运行的浮动车数量的最大值、路网覆盖率的最小期望值、路网可靠度的最小期望值以及路网覆盖率改善度的最小值,其中,所述路网覆盖率改善度用于表征在路网中每增加N辆浮动车时路网覆盖率的改善值,所述N由浮动车运营商设定。 [0041] Specifically, the parameters are set by defining a floating vehicle operator, said defining parameters include: the minimum expected value of the number of road network capable of running maximum floating car, road network coverage, reliability road network the minimum expected value and a minimum value of the road network to improve the coverage, wherein, to improve the coverage of the road network in the network for characterizing each of the floating units to increase the value of N to improve the car road network coverage, the N a floating cars set by the operator.

[0042] 205、根据所述浮动车数量配置模型的限定参数,对所述浮动车数量配置模型进行计算,得到浮动车数量的配置结果,以供浮动车运营商进行参考。 [0042] 205, according to the number of floating cars configuration model defining the parameters, the number of floating cars configuration model calculation, the number of floating cars configuration, for reference is floating car carriers. 其中,所述配置结果包括:路网覆盖率的上限值MaxCoverage、路网可靠度的上限值MaxReliability、路网覆盖率的改善度范围,以及最优的浮动车数量。 Wherein, said configuration comprising: an upper limit value of road network coverage MaxCoverage, the upper limit of the road network reliability MaxReliability, to improve the coverage range of the road network, and the optimal number of floating cars.

[0043] 具体的,可以采用二分法对所述浮动车数量配置模型进行计算以确定最优的浮动车数量,但不仅限于此。 [0043] Specifically, the configuration may be employed dichotomy model calculations to determine the optimal number of floating cars to the number of floating cars, but is not limited thereto. 例如,可以采用但不限于如下步骤: For example, it can be employed but is not limited to the following steps:

[0044] ①根据路网覆盖率的改善度范围确定浮动车数量的区间,记作[N1,N2],N1 < N2 ; [0044] ① determination section according to the number of floating cars to improve the coverage range of the road network, referred to as [N1, N2], N1 <N2;

[0045]②令 Nmid= (N1+N2)/2,计算Nmid 处的改善度,记作MidImprove ; [0045] ② order Nmid = (N1 + N2) / 2, to improve the calculation nmid, denoted MidImprove;

[0046] ③将MidImprove与浮动车运营商设定的路网覆盖率改善度的最小值MinImprove进行比较,如果MidImprove = MinImprove,那么Nmid即为所求解,即最优的浮动车数量;如果MidImprove > MInImprove,则令NI = Nmid, N2 = N2,返回步骤②;如果MidImprove [0046] ③ The MidImprove floating car MinImprove minimum set by the operator of the road network to improve coverage compared, if MidImprove = MinImprove, then the obtained solution is the Nmid, i.e., the optimal number of floating cars; if MidImprove> MInImprove, then let NI = nmid, N2 = N2, returns to step ②; if MidImprove

< MinImprove,则令NI = NI, N2 = Nmid,返回步骤②;[0047] ④当满足预设精度,或达到预设的循环次数时,将得到的结果作为所求解,求解结束。 <MinImprove, then let NI = NI, N2 = Nmid, returns to step ②; when [0047] ④ When satisfies a predetermined accuracy, or reaches a preset number of cycles, obtained as a result of the solver, solving the end.

[0048] 优选的,浮动车运营商可以设定根据路网覆盖率的改善度范围确定浮动车数量的配置方法。 [0048] Preferably, the floating car operator can determine the number of floating cars setting configuration method to improve the coverage range of the road network. 例如,路网覆盖率的改善度范围为[a, b],其中a < b,则设定方法可参考如下: For example, to improve the coverage range of the road network is [a, b], where a <b, the setting method may refer to the following:

[0049] ①当运营商认为MinCoverage已经满足需求,无需再提高覆盖率时,覆盖率改善度的取值应该在[b-ε,b]内取值,其中ε是相对a、b较小的一个值,如[a, b] = [0.05, [0049] ① when an operator to meet the needs that have MinCoverage, no longer need to increase coverage, improve the value of the coverage should be the value in the [b-ε, b] inside, where [epsilon] is the relative a, b smaller a value, such as [a, b] = [0.05,

0.15],则ε 可取0.02 或0.01 ; 0.15], ε is preferably 0.02 or 0.01;

[0050] ②当浮动车运行商认为在MinCoverage已经满足基本需求的前提下仍然需要提高覆盖率时,可以从经济和路网覆盖率改善两个对立方面进行权衡,最终确定合适的改善度。 [0050] ② When the floating car run business considers the premise MinCoverage already meet the basic needs still need to improve coverage, can improve the trade-off from two opposing aspects of the economy and road network coverage, and ultimately determine the appropriate degree of improvement. 当改善度太小时,路网覆盖率虽然仍会增加,但是改善不大,此时会造成经济上的浪费。 When the degree of improvement is too small, although the road network coverage will increase, but little improvement, this time will result in economic waste. 如[a,b] = [0.0005,0.05],当浮动车运营商选择增加浮动车数量时,对应的改善度会小于 Such as [a, b] = [0.0005,0.05], when the float vehicle operators choose to increase the number of floating cars, the degree of improvement will be less than the corresponding

0.005,例如0.0004,则代表增加η (例如:100)辆浮动车只能提高0.04个百分点,改善效果不大。 0.005, 0.0004, for example, represents an increase η (example: 100) units of floating cars can only increase 0.04 percentage points, improving little effect.

[0051] 206、对路网信息进行分析,确定影响地图匹配准确度的因素,所述因素主要包括浮动车数据采集周期。 [0051] 206, the road network information is analyzed to determine the accuracy of the map matching factors, the factors include the floating car data acquisition cycle.

[0052] 值得说明的是,地图匹配准确度是评价浮动车系统服务质量的重要指标,而浮动车数据采集周期是决定地图匹配准确度的主要因素。 [0052] It is worth noting, map matching accuracy is an important indicator of the quality evaluation system floating car service, and floating car data collection period is the major factor in determining the accuracy of map matching.

[0053] 207、根据所述影响地图匹配准确度的因素、以及交通信息服务质量和运营成本,建立所述浮动车数据采集周期配置模型,得到地图匹配准确度的函数表达式。 [0053] 207, based on the factors affecting map matching accuracy, as well as traffic information service quality and operating costs, the establishment of the floating car data acquisition cycle allocation model to obtain the map matching accuracy function expression.

[0054] 为了便于理解,本发明实施例提供了一种浮动车数据采集周期配置模型以供参考,具体如下: [0054] For ease of understanding, embodiments of the present invention provides a floating car data collection period arranged model for reference, as follows:

[0055] [0055]

Figure CN102496279BD00081

[0056] 其中,Y3代表地图匹配准确度函数;MinACCuraCy为地图匹配精度的最小期望值,MinImprove2为地图匹配准确度改善度的最小值,Tmin为浮动车数据采集周期的最小值;其中,地图匹配准确度改善度以百分点为单位,用于表征在浮动车数据采集周期为T的基础上降低t时地图匹配准确度的改善值,所述t由浮动车运营商设定。 [0056] wherein, Y3 representative of the accuracy of map-matching function; MinACCuraCy minimum desired value map matching accuracy, MinImprove2 minimum value for the map matching accuracy improvement degrees, the minimum value of Tmin floating car data acquisition period; wherein the map matching accuracy degree of improvement in percentage units for characterizing at reduced floating car data acquisition cycle T t based on the improved map matching accuracy value t is set by the operator of floating cars. 例如:如果浮动车运营商将t设定为5秒,将MinImpix)Ve2设定为20%,则表征浮动车运营商期望在当前浮动车系统中,将浮动车数据采集周期降低5秒,地图匹配准确度至少要提高20% ;若将浮动车数据采集周期降低5秒,地图匹配准确度的改善值低于20%,则浮动车运营商认为不需要降低浮动车数据采集周期。 For example: if the probe vehicle operators t is set to 5 seconds, the MinImpix) Ve2 is set to 20%, characterized by floating car desired by the operator in the current floating car system, a floating car data acquisition cycle by 5 seconds Map to increase the matching accuracy of at least 20%; floating car data acquisition cycle if 5 seconds decreased to improve the accuracy of map matching value is less than 20%, the floating car that does not require the operator to reduce floating car data acquisition cycle.

[0057] 208、获取所述浮动车数据采集周期配置模型的限定参数,以作为步骤207中浮动车数据采集周期配置模型的约束条件。 [0057] 208, obtaining parameters defining the floating car data collection period arranged model, as in step 207 constraints floating car data collection period arranged model.

[0058] 具体的,所述浮动车数据采集周期配置模型的限定参数由浮动车运营商进行设定,包括:浮动车数据采集周期的最小值、地图匹配准确度的最小期望值以及地图匹配准确度改善度的最小值,其中,所述地图匹配准确度改善度用于表征将所述浮动车数据采集周期每降低t时地图匹配准确度的改善值,所述t值由浮动车运营商设定。 [0058] Specifically, the floating car data acquisition cycle configuration model defining the parameters set by the operator floating vehicle, comprising: a floating car data acquisition cycle minimum, the map matching accuracy the minimum expected value and the accuracy of map matching the minimum degree of improvement, wherein said map matching accuracy for characterizing the degree of improvement floating car data acquisition cycle value t to improve the accuracy of map matching for each lowered, the t value set by the operator by a floating car .

[0059] 209、根据所述浮动车数据采集周期配置模型的限定参数对所述浮动车数据采集周期配置模型进行计算,得到浮动车数据采集周期的配置结果,以供浮动车运营商进行参考。 [0059] 209, the configuration of the floating car data acquisition cycle configuration model parameters of the model defining the floating car data acquisition period has been calculated, the configuration of the floating car data acquisition cycle, for which reference floating car carriers. 其中,所述配置结果包括:地图匹配准确度的上限值MaxAccuracy、地图匹配准确度的改善度范围,以及最优的浮动车数据采集周期等。 Wherein, said configuration comprising: map matching accuracy upper limit MaxAccuracy, improve the range of the map matching accuracy, and most of the other floating car data acquisition cycle.

[0060] 具体的,可以采用二分法对所述浮动车数据采集周期配置模型进行计算,具体实现方法可以参考步骤205中采用二分法对浮动车数量配置模型进行计算的方法,此处不再赘述。 [0060] Specifically, the model may be configured using the dichotomy floating car data acquisition cycle is calculated, refer to the specific method steps of the method of bisection floating car model calculated the number of configurations 205 employed, not repeated here .

[0061] 210、将得到的浮动车数量的配置结果以及浮动车数据采集周期的配置结果进行显示,以供浮动车运营商进行参考。 [0061] 210, the configuration of the number of floating cars obtained configuration and a floating car data acquisition cycle for display to the vehicle operator for the floating reference is made.

[0062] 本发明实施例提供的浮动车系统配置方法,能够对浮动车数量和浮动车数据采集周期进行配置,以供浮动车运营商进行参考。 [0062] floating car system configuration method provided in the embodiment of the present invention, it is possible to configure the number of floating cars and floating car data acquisition cycle, for which reference floating car carriers. 与现有技术相比,本发明实施例提供的方法能够使得浮动车运营商在运营成本和服务质量之间进行权衡,便于浮动车运营商对浮动车系统进行管理,有利于智能交通技术的发展。 Compared with the prior art, the method provided in the embodiment of the present invention enables operators floating car trade-off between quality of service and operating costs, to facilitate the floating of the vehicle operator to manage floating car system is conducive to the development of intelligent transportation technology .

[0063] 本发明实施例还提供了一种浮动车系统配置装置,如图3所示,所述装置包括: [0063] Embodiments of the present invention further provides a floating car system configuration device, shown in Figure 3, the apparatus comprising:

[0064] 建立单元31,用于建立浮动车系统配置模型; [0064] establishing unit 31, for establishing a floating car system configuration model;

[0065] 获取单元32,用于获取所述浮动车系统配置模型的限定参数; [0065] acquiring unit 32, configured to obtain the floating car system configuration parameters defining a model;

[0066] 处理单元33,用于根据所述限定参数对所述浮动车系统配置模型进行处理,得到浮动车系统的配置结果。 [0066] The processing unit 33, for performing processing according to the parameters defining the floating car system configuration model, to obtain the configuration floating car system.

[0067] 进一步的,如图4所示,所述建立单元31包括: [0067] Further, as shown in FIG. 4, the establishing unit 31 comprises:

[0068] 第一建立子单元311,用于建立浮动车数量配置模型,所述浮动车数量配置模型用于对浮动车系统的浮动车数量进行配置; [0068] establishing a first sub-unit 311, arranged for establishing a model number of floating cars, the number of floating cars model configured for the number of floating cars floating car system configuration;

[0069] 第二建立子单元312,用于建立浮动车数据采集周期配置模型,所述浮动车数据采集周期配置模型用于对浮动车系统的浮动车数据采集周期进行配置。 [0069] The second sub-unit 312 to establish, configure model for floating car data acquisition cycle, the floating car data acquisition cycle model configured for floating car system floating car data acquisition cycle is configured.

[0070] 进一步的,如图5所示,所述第一建立子单元311包括: [0070] Further, as shown in FIG. 5, the establishment of the first sub-unit 311 comprises:

[0071] 第一分析模块3111,用于对路网信息进行分析,确定影响路网覆盖率和路网可靠度的因素,所述因素包括浮动车数量、路网中的道路密度以及各等级道路在所述路网中所占的比例系数; [0071] a first analyzing module 3111, a road network information for analysis, the factors determining road network and road network coverage reliability impact, the factors including the number of floating cars, road density and road network in different level road proportion of the coefficient of the road network;

[0072] 第二分析模块3112,用于对所述影响路网覆盖率和路网可靠度的因素进行分析,确定所述影响路网覆盖率的因素与路网覆盖率的对应关系,以及确定所述影响路网可靠度的因素与路网可靠度的对应关系; [0072] The second analyzing module 3112, the factors for the road network and road network coverage effect on the reliability of the analysis to determine the correspondence relationship between the influence factors and road network coverage road network coverage, and determining Effect of the corresponding relationship between the road network and the road network reliability reliability factors;

[0073] 第一建立模块3113,用于根据所述影响路网覆盖率的因素与路网覆盖率的对应关系,以及所述影响路网可靠度的因素与路网可靠度的对应关系,以及交通信息服务质量和运营成本,建立所述浮动车数量配置模型,所述浮动车数量配置模型用于表征不同的浮动车数量对应的路网覆盖率和路网可靠度。 [0073] a first establishing module 3113, according to the corresponding relationship between the influence factors and road network coverage road network coverage, reliability and the influence of the road network and the road network reliability factor corresponding relationship, and traffic information service quality and operating costs, the number of floating cars establishing the configuration model, the number of floating cars model configured for different number of floating cars corresponding to characterize the road network and road network coverage reliability.

[0074] 所述获取单元32包括: [0074] The acquisition unit 32 comprises:

[0075] 第一获取子单元321,用于获取所述浮动车数量配置模型的限定参数; [0075] a first obtaining subunit 321, configured to obtain the number of parameters defining the floating car configuration model;

[0076] 其中,所述浮动车数量配置模型的限定参数包括:路网中能够运行的浮动车数量的最大值、路网覆盖率的最小期望值、路网可靠度的最小期望值以及路网覆盖率改善度的最小值,其中,所述路网覆盖率改善度用于表征在路网中增加N辆浮动车时路网覆盖率的改善值,所述η值由浮动车运营商设定。 [0076] wherein, the number of floating cars configuration model defining parameters include: maximum number of road network in the floating car can run, the minimum expected value of road network coverage, reliability minimum road network and road network coverage expectations the minimum degree of improvement, wherein said road network coverage for characterizing the degree of improvement increasing the value of N to improve the floating car vehicle road network coverage in the network, the η value is set by the operator of floating cars.

[0077] 所述处理单元33包括: [0077] The processing unit 33 comprises:

[0078] 第一处理子单元331,用于根据所述浮动车数量配置模型的限定参数对所述浮动车数量配置模型进行处理,得到所述浮动车数量配置模型的配置结果,所述配置结果包括:路网覆盖率的上限值、路网可靠度的上限值、路网覆盖率的改善度范围,以及最优的浮动车数量。 [0078] The first processing sub-unit 331, the configuration model according to the number of floating cars configuration model defining the parameters of the number of floating cars, to give the configuration of the model number of floating vehicle configuration, the configuration including: the upper limit of the road network coverage, the upper limit of the road network reliability and improve the range of road network coverage, and optimal number of floating cars.

[0079] 具体的,所述第一处理子单元331还用于采用二分法对所述路网覆盖率的改善度范围以及路网覆盖率改善度的最小值进行计算,以获取最优的浮动车数量。 [0079] Specifically, the first sub-processing unit 331 is further configured to use the bisection method to improve the range of road network coverage and a minimum value of the road network to improve the coverage was calculated to obtain the optimal floating the number of cars. 具体的计算方法可以参考上述方法实施例。 Specific calculation method with reference to the foregoing method embodiments may be.

[0080] 进一步的,如图6所示,所述第二建立子单元312包括: [0080] Further, as shown in FIG. 6, the second establishing sub-unit 312 comprises:

[0081] 第三分析模块3121,用于对路网信息进行分析,确定影响地图匹配准确度的因素,所述因素包括浮动车数据采集周期; [0081] The third analyzing module 3121, a road network information is analyzed to determine the factors that influence the accuracy of the map matching, the factors include floating car data collection period;

[0082] 第二建立模块3122,用于根据所述影响地图匹配准确度的因素、以及交通信息服务质量和运营成本,建立所述浮动车数据采集周期配置模型,所述浮动车数据采集周期配置模型用于表征不同的浮动车数据采集周期对应的地图匹配准确度。 [0082] The second establishing module 3122, according to the factors for the map matching accuracy, quality of service and traffic information and operating costs, establishing the floating car data acquisition cycle configuration model, the floating car data acquisition cycle configuration model is used to characterize different floating car data acquisition period corresponding to the map matching accuracy.

[0083] 所述获取单元32包括: [0083] The acquisition unit 32 comprises:

[0084] 第二获取子单元322,用于获取所述浮动车数据采集周期配置模型的限定参数; [0084] The second acquiring subunit 322, configured to obtain the floating car data acquisition cycle defines the parameters of the model;

[0085] 其中,所述浮动车数据采集周期配置模型的限定参数包括:浮动车数据采集周期的最小值、地图匹配准确度的最小期望值以及地图匹配准确度改善度的最小值,其中,所述地图匹配准确度改善度用于表征将所述浮动车数据采集周期降低t时地图匹配准确度的改善值,所述t值由浮动车运营商设定。 [0085] wherein said floating car data acquisition cycle configuration model defining parameters include: the minimum value Min FCD acquisition cycle, the map matching accuracy the minimum expected value and improved accuracy of map matching, wherein said map matching accuracy for characterizing the degree of improvement floating car data acquisition cycle value decreased to improve the accuracy of map matching t, t is set by the operator of floating cars.

[0086] 所述处理单元33包括: [0086] The processing unit 33 comprises:

[0087] 第二处理子单元332,用于根据所述浮动车数据采集周期配置模型的限定参数对所述浮动车数据采集周期配置模型进行处理,得到所述浮动车数据采集周期配置模型的配置结果,所述配置结果包括:地图匹配准确度的上限值、地图匹配准确度改善度范围,以及最优的浮动车数据采集周期值。 [0087] The second sub-processing unit 332, parameters for defining a model according to the configuration of the floating car data acquisition cycle for the floating car data acquisition cycle configuration model, to give the configuration of the floating car data collection period arranged model As a result, the configuration comprising: the upper limit of the map matching accuracy, improving the accuracy of map matching range, and most of the floating car data acquisition cycle value.

[0088] 具体的,所述第二处理子单元332还用于采用二分法对所述地图匹配准确度改善度范围以及地图匹配准确度改善度的最小值进行计算,获取最优的浮动车数据采集周期值。 [0088] Specifically, the second sub-processing unit 332 is further configured to use the bisection method to improve the minimum value of the map matching accuracy of the range and improve the accuracy of map matching is calculated, the optimal floating car data acquisition acquisition cycle value.

[0089] 本发明实施例提供的浮动车系统配置装置,能够对浮动车数量和浮动车数据采集周期进行配置,以供浮动车运营商进行参考。 Floating car system according to an embodiment of the [0089] configuration of the present invention apparatus, it is possible to configure the number of floating cars and floating car data acquisition cycle, for which reference floating car carriers. 与现有技术相比,本发明实施例提供的方法能够使得浮动车运营商在运营成本和服务质量之间进行权衡,便于浮动车运营商对浮动车系统进行管理,有利于智能交通技术的发展。 Compared with the prior art, the method provided in the embodiment of the present invention enables operators floating car trade-off between quality of service and operating costs, to facilitate the floating of the vehicle operator to manage floating car system is conducive to the development of intelligent transportation technology .

[0090] 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。 [0090] By the above described embodiments, those skilled in the art may clearly understand that the present invention may be implemented by software plus necessary universal hardware implemented, also be implemented by hardware, but the former is preferred in many cases embodiments. 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。 Based on such understanding, the technical solutions of the present invention in essence or the part contributing to the prior art may be embodied in a software product out, in the storage medium may be readable, such as a floppy disk of the computer software product is stored and the like, a hard disk or optical disk, and include several instructions that enable a computer device (may be a personal computer, a server, or network device) to execute the methods according to embodiments of the present invention.

[0091] 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。 [0091] The above are only specific embodiments of the present invention, but the scope of the present invention is not limited thereto, any skilled in the art in the art within the technical scope of the present invention is disclosed, variations may readily occur or Alternatively, it shall fall within the protection scope of the present invention. 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。 Accordingly, the scope of the present invention should be defined by the scope of the claims.

Claims (18)

1.一种浮动车系统配置方法,其特征在于,包括: 建立浮动车系统配置模型,包括:建立浮动车数量配置模型,所述浮动车数量配置模型用于对浮动车系统的浮动车数量进行配置;建立浮动车数据采集周期配置模型,所述浮动车数据采集周期配置模型用于对浮动车系统的浮动车数据采集周期进行配置; 获取所述浮动车系统配置模型的限定参数; 根据所述限定参数对所述浮动车系统配置模型进行处理,得到浮动车系统的配置结果; 其中,所述建立浮动车数量配置模型包括:对路网信息进行分析,确定影响路网覆盖率和路网可靠度的因素,所述因素包括浮动车数量、路网中的道路密度以及各等级道路在所述路网中所占的比例系数;对所述影响路网覆盖率和路网可靠度的因素进行分析,确定所述影响路网覆盖率的因素与路网覆盖率的对应关系,以及确定所述 A floating car system configuration method, comprising: establishing a floating car system configuration model, comprising: establishing a number of floating cars configuration model, the model number of floating vehicle configured for the number of floating cars for floating car system configuration; floating car data acquisition cycle to establish the configuration model, the floating car data acquisition cycle model configured for floating car system floating car data acquisition cycle is configured; acquiring the parameters defining the configuration of floating cars model system; according to the parameters defining the system configuration for the floating car model, to give the floating car system configuration; wherein, the establishing the number of floating cars model configuration comprising: road network information is analyzed to determine the effect of road network coverage and reliable road network factors degrees, the density of the road factors including the number of floating cars, road network and road grade scale factors of respective share in the road network; factors affect the road network and road network coverage reliability is analysis to determine the corresponding relationship between the influence factors of road network coverage and coverage of the road network, and determining the 影响路网可靠度的因素与路网可靠度的对应关系;根据所述影响路网覆盖率的因素与路网覆盖率的对应关系,以及所述影响路网可靠度的因素与路网可靠度的对应关系,以及交通信息服务质量和运营成本,建立所述浮动车数量配置模型,所述浮动车数量配置模型用于表征不同的浮动车数量对应的路网覆盖率和路网可靠度。 Effects of road network and road network Reliability Reliability factors corresponding relation; Reliability factor corresponding relationship between the road network and road network coverage coverage, and the factors that affect the road network and the road network based on the reliability of impact the correspondence, as well as traffic information service quality and operational costs, the establishment of a number of floating car configuration model, the number of floating vehicle configuration for the number of different models to characterize floating cars corresponding road network coverage and reliability of road network.
2.根据权利要求1所述的方法,其特征在于,所述获取所述浮动车系统配置模型的限定参数包括: 获取所述浮动车数量配置模型的限定参数; 其中,所述浮动车数量配置模型的限定参数包括:路网中能够运行的浮动车数量的最大值、路网覆盖率的最小期望值、路网可靠度的最小期望值以及路网覆盖率改善度的最小值,其中,所述路网覆盖率改善度用于表征在路网中增加η辆浮动车时路网覆盖率的改善值,所述η值由浮动车运营商设定。 2. The method according to claim 1, wherein the acquiring the parameters defining the floating car system model comprises: obtaining the parameter defining the number of floating cars model configuration; wherein said number of floating car configuration defining model parameters include: the minimum value of the maximum number of road network floating car can run, the minimum expected value of road network coverage, the minimum expected value of road network reliability and improved coverage of the road network, wherein said path network coverage for characterizing the degree of improvement in the network and increasing the value of η to improve the floating car vehicle road network coverage, the η value is set by the operator of floating cars.
3.根据权利要求2所述的方法,其特征在于,所述根据所述限定参数对所述浮动车系统配置模型进行处理,得到浮动车系统的配置结果包括: 根据所述浮动车数量配置模型的限定参数对所述浮动车数量配置模型进行处理,得到所述浮动车数量配置模型的配置结果,所述配置结果包括:路网覆盖率的上限值、路网可靠度的上限值、路网覆盖率的改善度范围,以及最优的浮动车数量。 3. The method according to claim 2, wherein the parameter defining the floating car system configuration according to the process model to obtain the configuration floating car system comprising: a configuration model according to the number of floating cars parameters defining the number of floating cars model, to give the configuration of the model number of floating vehicle configuration, said configuration comprising: an upper limit value of road network coverage, reliability upper limit of the road network, improve the range of road network coverage, and optimal number of floating cars.
4.根据权利要求3所述的方法,其特征在于,所述根据所述限定参数对所述浮动车系统配置模型进行处理,得到浮动车系统的配置结果包括: 采用二分法对所述路网覆盖率的改善度范围以及路网覆盖率改善度的最小值进行计算,以获取最优的浮动车数量。 4. The method according to claim 3, wherein said processing the floating car system model according to the configuration parameters defined to give floating car system configuration comprising: a dichotomy of the road network improve coverage range and a minimum value of the road network to improve the coverage was calculated to obtain the optimal number of floating cars.
5.根据权利要求1所述的方法,其特征在于,所述建立浮动车数据采集周期配置模型包括: 对路网信息进行分析,确定影响地图匹配准确度的因素,所述影响地图匹配准确度的因素包括浮动车数据采集周期; 根据所述影响地图匹配准确度的因素、同时结合交通信息服务质量和运营成本,建立所述浮动车数据采集周期配置模型,所述浮动车数据采集周期配置模型用于表征不同的浮动车数据采集周期对应的地图匹配准确度。 5. The method according to claim 1, wherein said establishing floating car data acquisition cycle model configuration comprising: road network information is analyzed to determine factors that influence the accuracy of the map matching, the map matching accuracy influence the factors include floating car data collection period; map matching accuracy factors, combined with traffic information service quality and operational costs, the establishment of the floating car data acquisition cycle configuration model, the floating car data acquisition cycle allocation model based on the influence characterize different for floating car data acquisition period corresponding to the map matching accuracy.
6.根据权利要求5所述的方法,其特征在于,所述获取所述浮动车系统配置模型的限定参数包括: 获取所述浮动车数据采集周期配置模型的限定参数; 其中,所述浮动车数据采集周期配置模型的限定参数包括:浮动车数据采集周期的最小值、地图匹配准确度的最小期望值以及地图匹配准确度改善度的最小值,其中,所述地图匹配准确度改善度用于表征将所述浮动车数据采集周期降低t时地图匹配准确度的改善值,所述t值由浮动车运营商设定。 6. The method as claimed in claim 5, wherein the acquiring the parameters defining the model floating car system comprising: obtaining parameters defining the floating car data acquisition cycle configuration model; wherein said floating car data acquisition cycle configuration model defining parameters include: the minimum value of the floating car data acquisition cycle, the map matching accuracy the minimum expected value and the minimum value to improve the accuracy of map matching degrees, wherein said map matching accuracy for characterizing the degree of improvement the floating car data acquisition cycle reduced to improve accuracy of map matching value t, the value of t is set by the operator of floating cars.
7.根据权利要求6所述的方法,其特征在于,所述根据所述限定参数对所述浮动车系统配置模型进行处理,得到浮动车系统的配置结果包括: 根据所述浮动车数据采集周期配置模型的限定参数对所述浮动车数据采集周期配置模型进行处理,得到所述浮动车数据采集周期配置模型的配置结果,所述浮动车数据采集周期配置模型的配置结果包括:地图匹配准确度的上限值、地图匹配准确度改善度范围,以及最优的浮动车数据采集周期值。 7. The method according to claim 6, wherein the parameter defining the floating car system configuration according to the process model to obtain the configuration floating car system comprising: a floating car based on the data collection period configuration model defining the parameters of the floating car data acquisition cycle model, to give the configuration of the floating car data acquisition cycle configuration model, the floating car data acquisition cycle the configuration model comprising: map matching accuracy upper limit, the map matching accuracy improved range, and most of the floating car data acquisition cycle value.
8.根据权利要求7所述的方法,其特征在于,所述根据所述限定参数对所述浮动车系统配置模型进行处理,得到浮动车系统的配置结果包括: 采用二分法对所述地图匹配准确度改善度范围以及地图匹配准确度改善度的最小值进行计算,获取最优的浮动车数据采集周期值。 8. The method according to claim 7, wherein the configuration according to the model parameters defining the floating car system, to give the floating car system configuration comprising: using the map matching dichotomy improved accuracy and range of the minimum value to improve the accuracy of map matching degree is calculated, obtaining the optimal values ​​floating car data acquisition cycle.
9.一种浮动车系统配置装置,其特征在于,包括: 建立单元,用于建立浮动车系统配置模型; 获取单元,用于获取所述浮动车系统配置模型的限定参数; 处理单元,用于根据所述限定参数对所述浮动车系统配置模型进行处理,得到浮动车系统的配置结果。 A floating car system configuration device, characterized by comprising: establishing means for establishing a floating car system configuration model; acquiring unit for acquiring the parameters defining the model of the system configuration of floating cars; a processing unit for the parameters defining the configuration of the floating car system model, to give the floating car system configuration.
10.根据权利要求9所述的装置,其特征在于,所述建立单元包括: 第一建立子单元,用于建立浮动车数量配置模型,所述浮动车数量配置模型用于对浮动车系统的浮动车数量进行配置; 第二建立子单元,用于建立浮动车数据采集周期配置模型,所述浮动车数据采集周期配置模型用于对浮动车系统的浮动车数据采集周期进行配置。 10. The apparatus according to claim 9, wherein said establishing means comprises: establishing a first sub-unit, configured to establish a number of floating cars model, the number of floating cars model configured for floating car system the number of floating cars configuration; establishment of a second sub-unit, for establishing a floating car data acquisition cycle configuration model, the floating car data acquisition cycle for the floating car model configured for floating car data acquisition cycle for the system configuration.
11.根据权利要求10所述的装置,其特征在于,所述第一建立子单元包括: 第一分析模块,用于对路网信息进行分析,确定影响路网覆盖率和路网可靠度的因素,所述因素包括浮动车数量、路网中的道路密度以及各等级道路在所述路网中所占的比例系数; 第二分析模块,用于对所述影响路网覆盖率和路网可靠度的因素进行分析,确定所述影响路网覆盖率的因素与路网覆盖率的对应关系,以及确定所述影响路网可靠度的因素与路网可罪度的对应关系; 第一建立模块,用于根据所述影响路网覆盖率的因素与路网覆盖率的对应关系,以及所述影响路网可靠度的因素与路网可靠度的对应关系,以及交通信息服务质量和运营成本,建立所述浮动车数量配置模型,所述浮动车数量配置模型用于表征不同的浮动车数量对应的路网覆盖率和路网可靠度。 11. The apparatus according to claim 10, wherein the first subunit establishing comprises: a first analysis module for analyzing the road network information, determine the impact of the road network and road network coverage Reliability factors, including the number of floating cars scaling factor, the density of roads in the road network and the road occupied by each class in the road network; second analysis module for road network coverage and the impact on the road network factors for reliability analysis to determine the correspondence relationship between the influence factors and road network coverage road network coverage, and determining that the correspondence relationship may affect the road network of factors sin road network reliability; establishing a first module, for the corresponding relationship between the road network coverage factors and road network coverage, and the correspondence between the influence factors and the reliability of the road network road network reliability, quality of service and traffic information based on the impact and operating costs establishing the number of floating cars configuration model, the number of floating cars model configured for different number of floating cars corresponding to characterize the road network and road network coverage reliability.
12.根据权利要求11所述的装置,其特征在于,所述获取单元包括: 第一获取子单元,用于获取所述浮动车数量配置模型的限定参数;其中,所述浮动车数量配置模型的限定参数包括:路网中能够运行的浮动车数量的最大值、路网覆盖率的最小期望值、路网可靠度的最小期望值以及路网覆盖率改善度的最小值,其中,所述路网覆盖率改善度用于表征在路网中增加η辆浮动车时路网覆盖率的改善值,所述η值由浮动车运营商设定。 12. The apparatus according to claim 11, wherein said obtaining unit comprises: a first obtaining subunit, configured to obtain the number of parameters defining the configuration of the floating car model; wherein said number of floating car configuration model defining parameters include: the minimum expected value of road network coverage, improved coverage and a minimum value of the minimum expected value of the road network reliability road network the maximum number of road network in the floating car can run, wherein the road network improve coverage for characterizing the degree of improvement increasing the value of η floating car vehicle road network coverage in the network, the η value is set by the operator of floating cars.
13.根据权利要求10所述的装置,其特征在于,所述处理单元包括: 第一处理子单元,用于根据所述浮动车数量配置模型的限定参数对所述浮动车数量配置模型进行处理,得到所述浮动车数量配置模型的配置结果,所述浮动车数量配置模型的配置结果包括:路网覆盖率的上限值、路网可靠度的上限值、路网覆盖率的改善度范围,以及最优的浮动车数量。 13. The apparatus according to claim 10, wherein the processing unit comprises: a first sub-processing unit for performing processing according to the number of parameters that define the configuration of the model number of the floating floating car vehicle model configuration , arranged to obtain the number of floating cars model configuration, the configuration of the floating amount of the vehicle model configuration comprising: road network coverage upper limit value, the upper limit of the road network reliability, improvement of road network coverage range, and the optimal number of floating cars.
14.根据权利要求13所述的装置,其特征在于,所述第一处理子单元具体用于采用二分法对所述路网覆盖率的改善度范围以及路网覆盖率改善度的最小值进行计算,以获取最优的浮动车数量。 14. The apparatus according to claim 13, wherein the first processing sub-unit is configured to dichotomy minimum range of the road network to improve coverage and improved coverage of the road network calculated to obtain the optimal number of floating cars.
15.根据权利要求10所述的装置,其特征在于,所述第二建立子单元包括: 第三分析模块,用于对路网信息进行分析,确定影响地图匹配准确度的因素,所述因素包括浮动车数据采集周期; 第二建立模块,用于根据所述影响地图匹配准确度的因素、以及交通信息服务质量和运营成本,建立所述浮动车数据采集周期配置模型,所述浮动车数据采集周期配置模型用于表征不同的浮动车数据采集周期对应的地图匹配准确度。 15. The apparatus according to claim 10, wherein the second establishing sub-unit comprises: a third analysis module for analyzing the road network information, the map matching accuracy factors determining the influence of the factors comprising a floating car data acquisition cycle; a second establishing module, configured to model the floating factors according to the map matching accuracy, quality of service and traffic information and operating costs, establishing the floating car data acquisition cycle vehicle data acquisition cycle configuration model to characterize different floating car data acquisition period corresponding to the map matching accuracy.
16.根据权利要求15所述的装置,其特征在于,所述获取单元包括: 第二获取子单元,用于获取所述浮动车数据采集周期配置模型的限定参数; 其中,所述浮动车数据采集周期配`置模型的限定参数包括:浮动车数据采集周期的最小值、地图匹配准确度的最小期望值以及地图匹配准确度改善度的最小值,其中,所述地图匹配准确度改善度用于表征将所述浮动车数据采集周期降低t时地图匹配准确度的改善值,所述t值由浮动车运营商设定。 16. Apparatus according to claim 15, wherein said obtaining unit comprises: a second obtaining subunit, configured to obtain the floating car data acquisition cycle configuration model defining parameters; wherein said FCD `opposite acquisition cycle with parameters defining the model include: minimum floating car data acquisition cycle, the minimum value of the minimum expected value of the map matching and to improve the accuracy of map matching accuracy, wherein said map matching for improved accuracy of Characterization of the floating car data acquisition cycle reduced to improve accuracy of map matching value t, the value of t is set by the operator of floating cars.
17.根据权利要求16所述的装置,其特征在于,所述处理单元包括: 第二处理子单元,用于根据所述浮动车数据采集周期配置模型的限定参数对所述浮动车数据采集周期配置模型进行处理,得到所述浮动车数据采集周期配置模型的配置结果,所述浮动车数据采集周期配置模型的配置结果包括:地图匹配准确度的上限值、地图匹配准确度改善度范围,以及最优的浮动车数据采集周期值。 17. The apparatus according to claim 16, wherein the processing unit comprises: a second cycle of processing sub-unit, according to the configuration model for floating car data acquisition cycle parameters defining the floating car data collection configuration model, to give the configuration of the floating car data acquisition cycle configuration model, the floating car data acquisition cycle the configuration models comprises: upper limit value of the map matching accuracy, improving the accuracy of map matching range, and most of the floating car data acquisition cycle value.
18.根据权利要求17所述的装置,其特征在于,所述第二处理子单元具体用于采用二分法对所述地图匹配准确度改善度范围以及地图匹配准确度改善度的最小值进行计算,获取最优的浮动车数据采集周期值。 18. The apparatus according to claim 17, wherein the second processing sub-unit is configured to use the bisection method to improve the accuracy of map matching, and map matching range of the minimum value to improve the accuracy of calculation obtaining an optimal value of the floating car data acquisition cycle.
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