WO2022252464A1 - 一种路段的路面性能历史数据匹配方法、介质及系统 - Google Patents

一种路段的路面性能历史数据匹配方法、介质及系统 Download PDF

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WO2022252464A1
WO2022252464A1 PCT/CN2021/123676 CN2021123676W WO2022252464A1 WO 2022252464 A1 WO2022252464 A1 WO 2022252464A1 CN 2021123676 W CN2021123676 W CN 2021123676W WO 2022252464 A1 WO2022252464 A1 WO 2022252464A1
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road
route
chainage
matched
interval
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PCT/CN2021/123676
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French (fr)
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王浩仰
杨屹东
王东林
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中公高科养护科技股份有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/20—Administration of product repair or maintenance
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A30/00—Adapting or protecting infrastructure or their operation
    • Y02A30/60—Planning or developing urban green infrastructure

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  • the present disclosure relates to the technical field of road maintenance, in particular to a method, medium and system for matching historical data of road surface performance of a road section.
  • the highway technical condition assessment should take the 1000m road section length as the basic assessment unit, because the road section division is affected by changes in road surface type, technical grade, traffic volume, road surface width, and maintenance and management units.
  • the standard stipulates that at the non-full kilometer section, the unit length is usually 100-1900m; according to the standard, there may be inconsistent pile numbers in the division of road sections every year, for example, in the first year
  • the starting point of a road section is 1, the ending point is 2, the starting point of the second year is 1.2, and the ending point is 1.9; the existing road surface management system can help us store and access data conveniently, but for historical data road sections
  • inconsistent starting and ending points as time goes by, how to accurately match the historical data of road sections with similar stake numbers has become a major obstacle in the application. With the increase of new data, the demand for historical data matching has gradually emerged. .
  • Embodiments of the present disclosure provide a road section historical data matching method, medium and system to solve the problem of inaccurate dynamic acquisition of historical data of road sections with the same or similar stake numbers in the prior art with the increase of new data for road performance detection indicators The problem.
  • a method for matching historical pavement performance data of a road section including: obtaining the starting point number of each road section arranged in the direction of the route, the end point number and the historical data of road surface performance of each road section; obtaining the route The minimum starting point and the maximum end point of the route direction, wherein, the minimum starting point and the maximum end point are rounded integers; the minimum starting point is the lower limit of the interval , the maximum terminal stake is the upper limit of the interval, and the stake interval of the route direction of the route is obtained; the stake interval of the route direction of the route is divided every other stake, and multiple stake intervals to be matched are obtained , wherein, the upper limit and the lower limit of each stake interval to be matched are integer stakes; calculate the distance between a road section in this route direction of the route and the midpoint of each stake interval to be matched; if a road section and If the distance between the midpoint of the chainage interval to be matched is the smallest, and the minimum distance is smaller than a preset threshold
  • a computer-readable storage medium is provided, and computer program instructions are stored on the computer-readable storage medium; when the computer program instructions are executed by a processor, the road section as described in the embodiment of the first aspect above is implemented. Pavement performance historical data matching method.
  • a road surface performance historical data matching system for road sections including: the computer-readable storage medium as described in the embodiment of the second aspect above.
  • the embodiments of the present disclosure by introducing the historical data matching method, can quickly and accurately obtain dynamic index data such as historical data of pavement performance of road sections with the same or similar stake numbers as time goes by and the expansion of samples, so that the existing data can be improved.
  • the function of the pavement management system does not require manual intervention, and has the characteristics of scalability, self-adaptation and automation.
  • FIG. 1 is a flow chart of a method for matching historical road performance data of road sections according to an embodiment of the present disclosure
  • Figure 2 schematically illustrates a block diagram of a computing processing device for performing a method according to the present disclosure
  • Fig. 3 schematically shows a storage unit for holding or carrying program codes implementing the method according to the present disclosure.
  • the embodiment of the present disclosure discloses a method for matching historical data of road surface performance of a road section.
  • the pavement performance historical data matching method includes the following steps:
  • Step S1 Obtain the starting point number and end point number of each road section of a route arranged according to the route direction, and the historical data of road surface performance of each road section.
  • the route direction includes an uplink direction and a downlink direction.
  • a route can include multiple segments.
  • the section length of each road section is a preset length. In a preferred embodiment of the present disclosure, the preset length is generally 1 km.
  • the road surface performance historical data includes: road surface performance index and road section length.
  • the road surface performance index PPI includes at least one of the following: road surface damage condition index PCI, road surface ride quality index RQI, road surface rutting depth index RDI, road surface technical condition index PQI. It should be understood that the road surface performance history data is not limited to this, and may also include other parameters. Pavement performance index PPI and road section length are generally collected once a year.
  • the chainage range is [1409.761, 1417.005], and the five-year continuous detection data is shown in Table 1.
  • Step S2 Obtain the minimum starting point and maximum end point of the route in the direction of the route.
  • the minimum start point chainage and the maximum end point chainage are both rounded integer chainages.
  • the minimum starting point number is 1410, which is the rounded integer number of 1409.761
  • the maximum end point number is 1417, which is the rounded integer number of 1417.005.
  • Step S3 Take the smallest starting point number as the lower limit of the interval, and the largest ending point number as the upper limit of the interval, and obtain the point interval of the route in the direction of the route.
  • the stake interval is [1410,1417].
  • Step S4 Divide the chainage intervals of the route in the direction of the route every other chainage to obtain multiple chainage intervals to be matched.
  • the upper limit and the lower limit of each chainage interval to be matched are integer chainages.
  • Step S5 Calculate the distance between a section of the route in the direction of the route and the midpoint of each chainage interval to be matched.
  • S represents the distance between the road section and the midpoint of the chainage interval to be matched
  • S1 represents the starting chainage of the road section
  • S2 represents the terminal chainage of the road section
  • Sm represents the midpoint chainage of the chainage interval to be matched .
  • Step S6 If the distance between a road segment and the midpoint of a chainage interval to be matched is the smallest, and the minimum distance is smaller than a preset threshold, then match the road surface performance history data of the road segment with the chainage interval to be matched.
  • the preset threshold may be determined according to the current section division, for example, in a preferred embodiment of the present disclosure, the preset threshold is 2. Since the distance between this road section and the midpoint of the stake interval [1413,1414] to be matched is the smallest, and the minimum distance 0.26 is also smaller than the preset threshold 2, the 2010 The year's PQI value 91.8 is filled to the position corresponding to the PQI value of 2010 in the stake interval [1413,1414] to be matched, as shown in Table 3. It should be understood that during the matching process, if the historical pavement performance data is related to the year, the corresponding year should also be matched accordingly.
  • step S5 the method of the embodiment of the present disclosure also includes:
  • Step S7 If the distance between the road segment and the midpoint of a chainage section to be matched is the smallest, and the minimum distance is not less than a preset threshold, then the chainage section to be matched does not match any historical data of road surface performance.
  • the embodiment of the present disclosure also discloses a computer-readable storage medium, where computer program instructions are stored on the computer-readable storage medium; when the computer program instructions are executed by a processor, the road surface of the road section as described in the above-mentioned embodiments is realized Performance history data matching method.
  • the embodiment of the present disclosure also discloses a road surface performance historical data matching system for road sections, including: the computer-readable storage medium as described in the above embodiments.
  • the embodiments of the present disclosure by introducing the historical data matching method, can quickly and accurately obtain dynamic index data such as historical data of road surface performance of road sections with the same or similar stake numbers as time goes by and the expansion of samples, so as to improve both It has the functions of the road surface management system without manual intervention, and has the characteristics of scalability, self-adaptation and automation.
  • the device embodiments described above are only illustrative, and the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in One place, or it can be distributed to multiple network elements. Part or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. It can be understood and implemented by those skilled in the art without any creative efforts.
  • the various component embodiments of the present disclosure may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof.
  • a microprocessor or a digital signal processor (DSP) may be used in practice to implement some or all functions of some or all components in the computing processing device according to the embodiments of the present disclosure.
  • DSP digital signal processor
  • the present disclosure can also be implemented as an apparatus or apparatus program (eg, computer program and computer program product) for performing a part or all of the methods described herein.
  • Such a program realizing the present disclosure may be stored on a computer-readable medium, or may have the form of one or more signals.
  • Such a signal may be downloaded from an Internet site, or provided on a carrier signal, or provided in any other form.
  • FIG. 2 illustrates a computing processing device that may implement methods according to the present disclosure.
  • the computing processing device conventionally includes a processor 1010 and a computer program product or computer readable medium in the form of memory 1020 .
  • Memory 1020 may be electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read Only Memory), EPROM, hard disk, or ROM.
  • the memory 1020 has a storage space 1030 for program code 1031 for performing any method steps in the methods described above.
  • the storage space 1030 for program codes may include respective program codes 1031 for respectively implementing various steps in the above methods. These program codes can be read from or written into one or more computer program products.
  • These computer program products comprise program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks.
  • Such a computer program product is typically a portable or fixed storage unit as described with reference to FIG. 3 .
  • the storage unit may have storage segments, storage spaces, etc. arranged similarly to the memory 1020 in the computing processing device of FIG. 2 .
  • the program code can eg be compressed in a suitable form.
  • the storage unit includes computer readable code 1031', i.e. code readable by, for example, a processor such as 1010, which code, when executed by a computing processing device, causes the computing processing device to perform the above-described methods. each step.
  • references herein to "one embodiment,” “an embodiment,” or “one or more embodiments” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Additionally, please note that examples of the word “in one embodiment” herein do not necessarily all refer to the same embodiment.
  • any reference signs placed between parentheses shall not be construed as limiting the claim.
  • the word “comprising” does not exclude the presence of elements or steps not listed in a claim.
  • the word “a” or “an” preceding an element does not exclude the presence of a plurality of such elements.
  • the disclosure can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means can be embodied by one and the same item of hardware.
  • the use of the words first, second, and third, etc. does not indicate any order. These words can be interpreted as names.

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Abstract

一种路段的路面性能历史数据匹配方法、介质及系统。该方法包括：获取一路线按路线方向排列的每一路段的起点桩号、终点桩号和路面性能历史数据；获取该路线的该路线方向的最小起点桩号和最大终点桩号；以最小起点桩号为区间下限，最大终点桩号为区间上限，得到该路线的该路线方向的桩号区间；将该路线的该路线方向的桩号区间每隔一个桩号进行划分，得到待匹配桩号区间；计算该路线的该路线方向的一路段与每一待匹配桩号区间的中点的距离；若一路段与一待匹配桩号区间的中点的距离最小，且该最小的距离小于预设阈值，则将该路段的路面性能历史数据与该待匹配桩号区间匹配。本公开可快速、准确获取桩号相同或相近路段的路面性能历史数据。

Description

一种路段的路面性能历史数据匹配方法、介质及系统
相关申请的交叉引用
本申请优先权日为2021年6月4日、优先权号为202110627473.4、名称为“一种路段的路面性能历史数据匹配方法、介质及系统”的中国专利申请的优先权，其全部内容通过引用结合在本公开中。
技术领域
本公开涉及于公路养护技术领域，尤其涉及一种路段的路面性能历史数据匹配方法、介质及系统。
背景技术
中国大部分省份省级公路管理部门为向财政申请年度路面养护资金，每年都委托专业的检测单位开展路网级的路面自动化检测工作。按照公路技术状况评定标准(JTG 5210-2018)的规定，公路技术状况评定应以1000m路段长度为基本评定单元，由于路段划分受路面类型、技术等级、交通量、路面宽度和养管单位等变化的影响，可能存在非整千米路段，标准进一步规定在非整千米路段处，单元长度通常为100～1900m；按照标准规定，每年路段划分可能会有桩号不一致的情况，例如第一年某路段起点桩号为1，终点桩号为2，第二年起点桩号为1.2，终点桩号为1.9；现有的路面管理系统能够帮助我们方便地存储和访问数据，然而针对历史数据路段起终点划分不一致的情况，随着时间的推移，如何将桩号相近路段的历史数据准确匹配成为应用中的一大阻碍，随着新增数据的增多，对历史数据匹配的需求也逐渐涌现出来。
概述
本公开实施例提供一种路段的路面性能历史数据匹配方法、介质及系统，以解决现有技术随着路面性能检测指标新增数据的增多，桩号相同或相近路段的历史数据动态获取不准确的问题。
第一方面，提供一种路段的路面性能历史数据匹配方法，包括：获取一路线按路线方向排列的每一路段的起点桩号、终点桩号和每一路段的路面性 能历史数据；获取该路线的该路线方向的最小起点桩号和最大终点桩号，其中，所述最小起点桩号和所述最大终点桩号均为四舍五入处理后的整数桩号；以所述最小起点桩号为区间下限，所述最大终点桩号为区间上限，得到该路线的该路线方向的桩号区间；将该路线的该路线方向的桩号区间每隔一个桩号进行划分，得到多个待匹配桩号区间，其中，每一所述待匹配桩号区间的上限和下限均为整数桩号；计算该路线的该路线方向的一路段与每一待匹配桩号区间的中点的距离；若一路段与一待匹配桩号区间的中点的距离最小，且该最小的距离小于预设阈值，则将该路段的路面性能历史数据与该待匹配桩号区间匹配。
第二方面，提供一种计算机可读存储介质，所述计算机可读存储介质上存储有计算机程序指令；所述计算机程序指令被处理器执行时实现如上述第一方面实施例所述的路段的路面性能历史数据匹配方法。
第三方面，提供一种路段的路面性能历史数据匹配系统，包括：如上述第二方面实施例所述的计算机可读存储介质。
这样，本公开实施例，通过引入历史数据匹配方法，随着时间的推移和样本的扩大可快速、准确的获取桩号相同或相近路段的路面性能历史数据等动态指标数据，从而可以完善既有路面管理系统的功能，无需人工干预，具有可扩展、自适应和自动化特点。
上述说明仅是本公开技术方案的概述，为了能够更清楚了解本公开的技术手段，而可依照说明书的内容予以实施，并且为了让本公开的上述和其它目的、特征和优点能够更明显易懂，以下特举本公开的具体实施方式。
附图简述
为了更清楚地说明本公开实施例的技术方案，下面将对本公开实施例的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公开的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1是本公开实施例的路段的路面性能历史数据匹配方法的流程图；
图2示意性地示出了用于执行根据本公开的方法的计算处理设备的框图；并且
图3示意性地示出了用于保持或者携带实现根据本公开的方法的程序代码的存储单元。
详细描述
下面将结合本公开实施例中的附图，对本公开实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本公开一部分实施例，而不是全部的实施例。基于本公开中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获取的所有其他实施例，都属于本公开保护的范围。
本公开实施例公开了一种路段的路面性能历史数据匹配方法。如图1所示，该路面性能历史数据匹配方法包括如下的步骤：
步骤S1：获取一路线按路线方向排列的每一路段的起点桩号、终点桩号和每一路段的路面性能历史数据。
路线方向包括上行方向和下行方向。一路线可以包括多个路段。每一路段的路段长度为预设长度。本公开一优选实施例中，该预设长度一般为1km。
本公开一优选实施例中，路面性能历史数据包括：路面性能指标和路段长度。路面性能指标PPI包括如下的至少一种：路面损坏状况指数PCI、路面行驶质量指数RQI、路面车辙深度指数RDI、路面技术状况指数PQI。应当理解的是，路面性能历史数据并不以此为限，还可以包括其它的参数。路面性能指标PPI和路段长度一般一年采集一次。
以路线编码G104上行为例，其桩号范围为[1409.761,1417.005]，连续检测五年数据，如表1所示。
表1某路段多年检测数据
年份 路线 方向 PQI .... 路段起点桩号 路段终点桩号 路段长度
2010 G104 A 84.3   1409.761 1411 1239
2010 G104 A 81.7   1411 1412 1000
2010 G104 A 91.1   1412 1413.34 1340
2010 G104 A 91.8   1413.34 1414.6 1060
2010 G104 A 74.3   1414.4 1414.66 260
2010 G104 A 82.7   1414.66 1416 1340
2010 G104 A 76.4   1416 1417.005 1005
2011 G104 A 90.5   1409.761 1411 1239
2011 G104 A 91.1   1411 1412 1000
2011 G104 A 93.4   1412 1413 1000
2011 G104 A 92.5   1413 1414 1000
2011 G104 A 93   1414 1414.546 546
2011 G104 A 78   1414.546 1416 1454
2011 G104 A 74.4   1416 1417 1000
2012 G104 A 83.6   1409.761 1411 1239
2012 G104 A 81.7   1411 1412 1000
2012 G104 A 85.6   1412 1413 1000
2012 G104 A 89.2   1413 1414 1000
2012 G104 A 90.9   1414 1414.546 546
2012 G104 A 75.9   1414.546 1416 1454
2012 G104 A 70   1416 1416.966 966
2013 G104 A 80.3   1409.761 1411 1239
2013 G104 A 77.3   1411 1412 1000
2013 G104 A 83.8   1412 1413 1000
2013 G104 A 86.4   1413 1414 1000
2013 G104 A 88.4   1414 1414.546 546
2013 G104 A 72.3   1414.546 1416 1454
2013 G104 A 69.8   1416 1416.922 922
2014 G104 A 80.4   1409.761 1411 1239
2014 G104 A 82.2   1411 1412 1000
2014 G104 A 83.2   1412 1413 1000
2014 G104 A 86.4   1413 1414 1000
2014 G104 A 92.7   1414 1414.546 546
2014 G104 A 81.5   1414.546 1416 1454
2014 G104 A 77.3   1416 1416.998 998
步骤S2：获取该路线的该路线方向的最小起点桩号和最大终点桩号。
其中，最小起点桩号和最大终点桩号均为四舍五入处理后的整数桩号。
以路线编码G104上行为例，最小起点桩号为1410，即1409.761四舍五入处理后的整数桩号，最大终点桩号为1417，即1417.005四舍五入处理后的整数桩号。
步骤S3：以最小起点桩号为区间下限，最大终点桩号为区间上限，得到该路线的该路线方向的桩号区间。
以路线编码G104上行为例，桩号区间为[1410,1417]。
步骤S4：将该路线的该路线方向的桩号区间每隔一个桩号进行划分，得到多个待匹配桩号区间。
其中，每一待匹配桩号区间的上限和下限均为整数桩号。
以路线编码G104上行为例，待匹配桩号区间如表2所示。
表2待匹配桩号区间
路线 上下行 路段起点桩号 路段终点桩号
G104 A 1410 1411
G104 A 1411 1412
G104 A 1412 1413
G104 A 1413 1414
G104 A 1414 1415
G104 A 1415 1416
G104 A 1416 1417
步骤S5：计算该路线的该路线方向的一路段与每一待匹配桩号区间的中点的距离。
具体的，计算式为：
S＝|S m-S 1|+|S 2-S m|。
其中，S表示该路段与该待匹配桩号区间的中点的距离，S1表示该路段的起点桩号，S2表示该路段的终点桩号，Sm表示该待匹配桩号区间的中点桩号。
以表1中2010年的一路段，其起点桩号和终点桩号分别为1413.34和1414.6为例，该路段与表2中的一待匹配桩号区间[1413,1414]的中点1413.5的距离为：|1413.5-1413.34|+|1414.6-1413.5|＝0.16+0.1＝0.26。
同样的，该路段与表2中的一待匹配桩号区间[1412,1413]的中点1412.5的距离为：|1412.5-1413.34|+|1414.6-1412.5|＝0.84+2.1＝2.94。
该路段与其它待匹配桩号区间的中点的距离计算重复同样的过程。通过计算结果，可得到该路段与待匹配桩号区间[1413,1414]的中点的距离最小。
步骤S6：若一路段与一待匹配桩号区间的中点的距离最小，且该最小的距离小于预设阈值，则将该路段的路面性能历史数据与该待匹配桩号区间匹配。
预设阈值可根据当前的区间划分确定，例如，本公开一优选实施例中， 预设阈值为2。由于该路段与待匹配桩号区间[1413,1414]的中点的距离最小，且最小的距离0.26也小于预设阈值2，则将该路段(起点桩号1413.34，终点桩号1414.6)的2010年的PQI值91.8填充到待匹配桩号区间[1413,1414]对应2010年的PQI值的位置，如表3所示。应当理解的是，匹配的过程中，如路面性能历史数据是与年份相关的，也应对应匹配相应的年份。
表3匹配填充示例
路线编码 上下行 路段起点 路段终点 2010 2011 2012 2013 2014
G104 A 1410 1411          
G104 A 1411 1412          
G104 A 1412 1413          
G104 A 1413 1414 91.8        
G104 A 1414 1415          
G104 A 1415 1416          
G104 A 1416 1417          
此外，步骤S5之后，本公开实施例的方法还包括：
步骤S7：若一路段与一待匹配桩号区间的中点的距离最小，且该最小的距离不小于预设阈值，则该待匹配桩号区间与任何路面性能历史数据均不匹配。
此时，在表3对应的格子中不填充任何数据。
以路线编码G104上行为例，其桩号范围[1409.761,1417.005]，通过上述的步骤，路面技术状况指数PQI指标连续五年匹配完的结果如表4所示。同样的，检测路段其它属性数据也可以完成匹配，例如历年路段长度信息，如表4所示。
表4本公开实施例的方法的匹配结果
Figure PCTCN2021123676-appb-000001
作为本公开实施例技术效果的对比，采用现有技术的起点一致匹配的方 法进行路面性能历史数据匹配，结果如表5所示。
表5按照起点一致匹配的方法的匹配结果
Figure PCTCN2021123676-appb-000002
表5中出现了孤立数据，即有的桩号区间未能匹配路面性能历史数据，没有最大化利用历史数据。而本公开实施例的方法的桩号区间均匹配了路面性能历史数据，且与表5的非孤立数据具有相同的匹配结果，因此，本公开实施例的方法优于按照起点桩号一致匹配的方法。
本公开实施例还公开了一种计算机可读存储介质，所述计算机可读存储介质上存储有计算机程序指令；所述计算机程序指令被处理器执行时实现如上述实施例所述的路段的路面性能历史数据匹配方法。
本公开实施例还公开了一种路段的路面性能历史数据匹配系统，包括：如上述实施例所述的计算机可读存储介质。
综上，本公开实施例，通过引入历史数据匹配方法，随着时间的推移和样本的扩大可快速、准确的获取桩号相同或相近路段的路面性能历史数据等动态指标数据，从而可以完善既有路面管理系统的功能，无需人工干预，具有可扩展、自适应和自动化特点。
以上所述，仅为本公开的具体实施方式，但本公开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公开揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本公开的保护范围之内。因此，本公开的保护范围应以权利要求的保护范围为准。
以上所描述的装置实施例仅仅是示意性的，其中所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或 者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部模块来实现本实施例方案的目的。本领域普通技术人员在不付出创造性的劳动的情况下，即可以理解并实施。
本公开的各个部件实施例可以以硬件实现，或者以在一个或者多个处理器上运行的软件模块实现，或者以它们的组合实现。本领域的技术人员应当理解，可以在实践中使用微处理器或者数字信号处理器(DSP)来实现根据本公开实施例的计算处理设备中的一些或者全部部件的一些或者全部功能。本公开还可以实现为用于执行这里所描述的方法的一部分或者全部的设备或者装置程序(例如，计算机程序和计算机程序产品)。这样的实现本公开的程序可以存储在计算机可读介质上，或者可以具有一个或者多个信号的形式。这样的信号可以从因特网网站上下载得到，或者在载体信号上提供，或者以任何其他形式提供。
例如，图2示出了可以实现根据本公开的方法的计算处理设备。该计算处理设备传统上包括处理器1010和以存储器1020形式的计算机程序产品或者计算机可读介质。存储器1020可以是诸如闪存、EEPROM(电可擦除可编程只读存储器)、EPROM、硬盘或者ROM之类的电子存储器。存储器1020具有用于执行上述方法中的任何方法步骤的程序代码1031的存储空间1030。例如，用于程序代码的存储空间1030可以包括分别用于实现上面的方法中的各种步骤的各个程序代码1031。这些程序代码可以从一个或者多个计算机程序产品中读出或者写入到这一个或者多个计算机程序产品中。这些计算机程序产品包括诸如硬盘，紧致盘(CD)、存储卡或者软盘之类的程序代码载体。这样的计算机程序产品通常为如参考图3所述的便携式或者固定存储单元。该存储单元可以具有与图2的计算处理设备中的存储器1020类似布置的存储段、存储空间等。程序代码可以例如以适当形式进行压缩。通常，存储单元包括计算机可读代码1031’，即可以由例如诸如1010之类的处理器读取的代码，这些代码当由计算处理设备运行时，导致该计算处理设备执行上面所描述的方法中的各个步骤。
本文中所称的“一个实施例”、“实施例”或者“一个或者多个实施例”意味着，结合实施例描述的特定特征、结构或者特性包括在本公开的至少一 个实施例中。此外，请注意，这里“在一个实施例中”的词语例子不一定全指同一个实施例。
在此处所提供的说明书中，说明了大量具体细节。然而，能够理解，本公开的实施例可以在没有这些具体细节的情况下被实践。在一些实例中，并未详细示出公知的方法、结构和技术，以便不模糊对本说明书的理解。
在权利要求中，不应将位于括号之间的任何参考符号构造成对权利要求的限制。单词“包含”不排除存在未列在权利要求中的元件或步骤。位于元件之前的单词“一”或“一个”不排除存在多个这样的元件。本公开可以借助于包括有若干不同元件的硬件以及借助于适当编程的计算机来实现。在列举了若干装置的单元权利要求中，这些装置中的若干个可以是通过同一个硬件项来具体体现。单词第一、第二、以及第三等的使用不表示任何顺序。可将这些单词解释为名称。
最后应说明的是：以上实施例仅用以说明本公开的技术方案，而非对其限制；尽管参照前述实施例对本公开进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本公开各实施例技术方案的精神和范围。

Claims (9)

  1. 一种路段的路面性能历史数据匹配方法，其中，包括：
    获取一路线按路线方向排列的每一路段的起点桩号、终点桩号和每一路段的路面性能历史数据；
    获取该路线的该路线方向的最小起点桩号和最大终点桩号，其中，所述最小起点桩号和所述最大终点桩号均为四舍五入处理后的整数桩号；
    以所述最小起点桩号为区间下限，所述最大终点桩号为区间上限，得到该路线的该路线方向的桩号区间；
    将该路线的该路线方向的桩号区间每隔一个桩号进行划分，得到多个待匹配桩号区间，其中，每一所述待匹配桩号区间的上限和下限均为整数桩号；
    计算该路线的该路线方向的一路段与每一待匹配桩号区间的中点的距离；
    若一路段与一待匹配桩号区间的中点的距离最小，且该最小的距离小于预设阈值，则将该路段的路面性能历史数据与该待匹配桩号区间匹配。
  2. 根据权利要求1所述的路段的路面性能历史数据匹配方法，其中，所述计算该路线的该路线方向的一路段与每一待匹配桩号区间的中点的距离的计算式为：
    S＝|S m-S 1|+|S 2-S m|，其中，S表示该路段与该待匹配桩号区间的中点的距离，S1表示该路段的起点桩号，S2表示该路段的终点桩号，Sm表示该待匹配桩号区间的中点桩号。
  3. 根据权利要求1所述的路段的路面性能历史数据匹配方法，其中，所述计算该路线的该路线方向的一路段与每一待匹配桩号区间的中点的距离的步骤之后，所述方法还包括：
    若一路段与一待匹配桩号区间的中点的距离最小，且该最小的距离不小于预设阈值，则该待匹配桩号区间与任何路面性能历史数据均不匹配。
  4. 根据权利要求1所述的路段的路面性能历史数据匹配方法，其中，所述路面性能历史数据包括：路面性能指标和路段长度，所述路面性能指标包括如下的至少一种：路面损坏状况指数PCI、路面行驶质量指数RQI、路面车辙深度指数RDI、路面技术状况指数PQI。
  5. 根据权利要求1所述的路段的路面性能历史数据匹配方法，其中：每一路段的路段长度为预设长度。
  6. 一种计算机可读存储介质，其中：所述计算机可读存储介质上存储有计算机程序指令；所述计算机程序指令被处理器执行时实现如权利要求1～5中任一项所述的路段的路面性能历史数据匹配方法。
  7. 一种路段的路面性能历史数据匹配系统，其中，包括：如权利要求6所述的计算机可读存储介质。
  8. 一种计算处理设备，其中，包括：
    存储器，其中存储有计算机可读代码；以及
    一个或多个处理器，当所述计算机可读代码被所述一个或多个处理器执行时，所述计算处理设备执行如权利要求1-5中任一项所述的数据匹配方法。
  9. 一种计算机程序产品，包括计算机可读代码，当所述计算机可读代码在计算处理设备上运行时，导致所述计算处理设备执行根据权利要求1-5中任一项所述的数据匹配方法。
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