Road digital operation value-benefit quantitative calculation model construction method

Abstract

The invention discloses a method for constructing a highway digital operation value-benefit quantitative calculation model. The method comprises the following steps: dividing the digitization of a highway operation period into highway network perception digitization and highway network monitoring and scheduling digitization; in road network perception digitalization, data acquisition efficiency, data processing analysis capability, road network perception human cost and perception data cooperation capability are selected as digitalization indexes, and a quantitative model of each digitalization index is established; in road network monitoring and scheduling digitization, the road network service level, the information transmission efficiency, the safety level, the road network monitoring human cost and the asset management efficiency are selected as digitization indexes, and a quantitative model of each digitization index is established. Based on this, it can be ensured that digital related elements in the highway operation period can be quantified and calculated, and support is provided for safe and efficient operation.

Description

Technical Field

[0001] The present invention relates to the technical field of digitalization of highway infrastructure, and in particular to a method for constructing a quantitative calculation model for the value and benefit of digital operation of highways. Background Art

[0002] In order to accelerate the digital construction of highways, build a digital economy with data as the key element, and promote the integrated development of the real economy and the digital economy. Digitalization has become the direction of national transformation. At present, clear arrangements have been made to promote the digital transformation of highway infrastructure. The goal is to significantly increase the carrying capacity of transportation infrastructure with fewer resources and effectively strengthen the high-quality supply of transportation infrastructure with less capital investment.

[0003] my country has a long mileage of expressways. Faced with such a huge road network, the safe and efficient operation of highways has become a top priority. How to use the new generation of information technology and adopt digital methods to conduct quantitative evaluations of road network perception digitization, road network monitoring and scheduling, and then provide support for refined management services, is an urgent problem to be solved in the development of the industry. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a method for constructing a quantitative calculation model for the value and benefits of digital highway operations.

[0005] The present invention discloses a method for constructing a quantitative calculation model for the value and benefit of digital highway operation, comprising:

[0006] The digitization of highway operation period is divided into highway network perception digitization and highway network monitoring and dispatching digitization;

[0007] In the digitalization of highway network perception, data collection efficiency, data processing and analysis capabilities, road network perception labor costs, and perception data coordination capabilities are selected as digitalization indicators, and a quantitative model for each digitalization indicator is established to achieve the calculation and evaluation of the digitalization of each indicator;

[0008] In the digitalization of highway network monitoring and dispatching, road network service level, information transmission efficiency, safety level, road network monitoring labor cost and asset management efficiency are selected as digital indicators, and a quantitative model for each digital indicator is established to realize the digital calculation and evaluation of each indicator.

[0009] As a further improvement of the present invention,

[0010] The quantitative model of data collection efficiency DCE (unit: data / day) is:

[0011] DCE=NMCR×TFMA×DCS (1)

[0012] Where: NMCR is the road network monitoring coverage (unit: %), TFMA is the traffic flow monitoring accuracy (unit: %), DCS is the data collection speed (unit: data / day);

[0013] The quantitative model of data processing and analysis capacity DPAC (unit: hour) is:

[0014]

[0015] Where: IDPT is the initial data processing time (unit: hours), AA is the accuracy of the analysis results (unit: %), and CRIDM is the contribution rate to intelligent decision-making (unit: %);

[0016] The quantitative model of road network perception human cost NPHC (unit: person-day) is:

[0017] NPHC=NPP×POT (3)

[0018] Where: NPP is the number of perception workers (unit: person); POT is the perception operation time (unit: day);

[0019] The quantitative model of perception data coordination capability PDCC (unit: hour) is:

[0020]

[0021] Where: DTT is the data transmission time (unit: hours), DSL is the data sharing degree (unit: %).

[0022] As a further improvement of the present invention,

[0023] The quantitative model of road network service level NSL (unit: hour) is:

[0024]

[0025] Where: SCR is the service coverage rate (unit: %), SRR is the service reach rate (unit: %), AIRT is the average accident handling time (unit: hours);

[0026] The quantitative model of information transmission efficiency ITE (unit: information / hour) is:

[0027] ITE=ITS×IAR (6) Where: ITS is the information transmission speed (unit: information / hour), IAR is the information accuracy rate (unit: %);

[0028] The quantitative model of safety level SL (unit: %) is:

[0029] SL = (1-NIR) × (1-NFR) 2×(1-OSIR) (7)

[0030] Where: NIR is the road network accident rate (unit: %), NFR is the road network mortality rate (unit: %), OSIR is the operation safety accident rate (unit: %);

[0031] The quantitative model of road network monitoring manpower cost NMHC (unit: person-day) is:

[0032] NMHC=NMDP×MDWT (8)

[0033] Where: NMDP is the number of monitoring and scheduling personnel (unit: person), MDWT is the monitoring and scheduling operation time (unit: day);

[0034] The quantitative model of asset management efficiency AME (unit: / yuan) is:

[0035]

[0036] In the formula: ALUAR is the automation rate of asset ledger update (unit: %), AMC is the asset maintenance cost (unit: yuan), and AUR is the asset utilization rate (unit: %).

[0037] As a further improvement of the present invention, it also includes:

[0038] The quantitative models of various indicators in the digitalization of highway network perception and the digitalization of highway network monitoring and scheduling are stored on computing devices or storage devices respectively; the quantitative models corresponding to different stages are selected and retrieved at different stages of highway operation, and the corresponding indicator calculation results are obtained after the corresponding data are input, and the calculated indicator data are stored and output.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The present invention divides the highway operation period into two stages, namely, highway network perception and highway network monitoring and scheduling, according to the actual highway operation content. In each stage, multiple indicators for quantifying the value and benefits of highway digital operation are selected, and a calculation method for each indicator is established, and finally a digital quantitative evaluation model for the highway operation period is constructed; it can ensure that the digital-related elements of the highway operation period are quantifiable and calculable, providing support for safe and efficient operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 The present invention discloses a flow chart of a method for constructing a quantitative calculation model for the value and benefit of digital highway operations. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0043] The present invention is further described in detail below in conjunction with the accompanying drawings:

[0044] like Figure 1 As shown, the present invention provides a method for constructing a quantitative calculation model for the value and benefit of highway digital operation, comprising:

[0045] Step 1: Divide the digitization of the highway operation period into the digitization of highway network perception and the digitization of highway network monitoring and scheduling;

[0046] Step 2: In the digitalization of highway network perception, select data collection efficiency, data processing and analysis capabilities, road network perception labor costs, and perception data coordination capabilities as digitalization indicators, and establish a quantitative model for each digitalization indicator to achieve digital calculation and evaluation of each indicator;

[0047] Specific:

[0048] Four first-level indicators and 10 second-level indicators were constructed, as shown in Table 1 below.

[0049] Table 1

[0050]

[0051] Establish a quantitative model for each indicator to achieve digital calculation and evaluation;

[0052] The quantitative model of data collection efficiency DCE (unit: data / day) is:

[0053] DCE=NMCR×TFMA×DCS (1)

[0054] Where: NMCR is the road network monitoring coverage (unit: %), TFMA is the traffic flow monitoring accuracy (unit: %), DCS is the data collection speed (unit: data / day);

[0055] The quantitative model of data processing and analysis capacity DPAC (unit: hour) is:

[0056]

[0057] Where: IDPT is the initial data processing time (unit: hours), AA is the accuracy of the analysis results (unit: %), and CRIDM is the contribution rate to intelligent decision-making (unit: %);

[0058] The quantitative model of road network perception human cost NPHC (unit: person-day) is:

[0059] NPHC=NPP×POT (3)

[0060] Where: NPP is the number of perception operators (unit: person); POT is the perception operation time (unit: day).

[0061] The quantitative model of perception data coordination capability PDCC (unit: hour) is:

[0062]

[0063] Where: DTT is the data transmission time (unit: hours), DSL is the data sharing degree (unit: %).

[0064] Step 3: In the digitalization of highway network monitoring and dispatching, select the road network service level, information transmission efficiency, safety level, road network monitoring labor cost and asset management efficiency as digital indicators, and establish a quantitative model for each digital indicator to realize the calculation and evaluation of the digitalization of each indicator;

[0065] Specific:

[0066] Five first-level indicators and 13 second-level indicators were constructed, as shown in Table 2 below.

[0067] Table 2

[0068]

[0069]

[0070] Establish a quantitative model for each indicator to achieve digital calculation and evaluation;

[0071] The quantitative model of road network service level NSL (unit: hour) is:

[0072]

[0073] Where: SCR is the service coverage rate (unit: %), SRR is the service reach rate (unit: %), AIRT is the average accident handling time (unit: hours);

[0074] The quantitative model of information transmission efficiency ITE (unit: information / hour) is:

[0075] ITE=ITS×IAR (6) Where: ITS is the information transmission speed (unit: information / hour), IAR is the information accuracy rate (unit: %);

[0076] The quantitative model of safety level SL (unit: %) is:

[0077] SL = (1-NIR) × (1-NFR) 2 ×(1-OSIR) (7)

[0078] Where: NIR is the road network accident rate (unit: %), NFR is the road network mortality rate (unit: %), OSIR is the operation safety accident rate (unit: %);

[0079] The quantitative model of road network monitoring manpower cost NMHC (unit: person-day) is:

[0080] NMHC=NMDP×MDWT (8)

[0081] Where: NMDP is the number of monitoring and scheduling personnel (unit: person), MDWT is the monitoring and scheduling operation time (unit: day);

[0082] The quantitative model of asset management efficiency AME (unit: / yuan) is:

[0083]

[0084] In the formula: ALUAR is the automation rate of asset ledger update (unit: %), AMC is the asset maintenance cost (unit: yuan), and AUR is the asset utilization rate (unit: %).

[0085] Based on the quantitative models of various indicators constructed, it also includes:

[0086] The quantitative models of various indicators in the digitalization of highway network perception and the digitalization of highway network monitoring and scheduling are stored separately on a computing device or a storage device (such as a computer), and the storage method can be classified storage; for example, after entering the application, two modules of the digitalization of highway network perception and the digitalization of highway network monitoring and scheduling are displayed. After clicking to enter the digitalization of highway network perception, the data collection efficiency, data processing and analysis capabilities, road network perception human cost and perception data coordination capability indicator calculation modules are displayed. After clicking to enter the data collection efficiency, the input boxes of the road network monitoring coverage, traffic flow monitoring accuracy and data collection speed are displayed; the form of the calculation modules of various indicators in the digitalization of highway network perception is the same as the data collection efficiency indicator calculation module, and the quantitative models of various indicators in the digitalization of highway network monitoring and scheduling are consistent with the digitalization of highway network perception; at different stages of highway operation, the quantitative models corresponding to different stages are selected to be retrieved, and the corresponding indicator calculation results are obtained after inputting (manual input, drop-down box selection input or automatic input through relevant collection equipment) the corresponding data, and the calculated indicator data are stored and output.

[0087] Based on this, the calculation status of different indicators can be viewed through the computer, and the unfinished indicators can be quantified.

[0088] like:

[0089] Select road network perception digitization on the corresponding application on the computer, and then the indicator calculation module of data collection efficiency, data processing and analysis capabilities, road network perception labor cost and perception data coordination capability will be displayed. Enter the data collection efficiency calculation module, and the user can obtain the calculation result of the indicator - data collection efficiency by inputting the road network monitoring coverage, traffic flow monitoring accuracy and data collection speed, and store, display and output it.

[0090] The advantages of the present invention are:

[0091] The present invention divides the highway operation period into two stages, namely, highway network perception and highway network monitoring and scheduling, according to the actual highway operation content. In each stage, multiple indicators for quantifying the value and benefits of highway digital operation are selected, and a calculation method for each indicator is established, and finally a digital quantitative evaluation model for the highway operation period is constructed; it can ensure that the digital-related elements of the highway operation period are quantifiable and calculable, providing support for safe and efficient operation.

[0092] The above are only preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for constructing a quantitative calculation model for the value and benefit of highway digital operation, characterized in that: include: The digitization of highway operation period is divided into highway network perception digitization and highway network monitoring and dispatching digitization; In the digitalization of highway network perception, data collection efficiency, data processing and analysis capabilities, road network perception labor costs, and perception data coordination capabilities are selected as digitalization indicators, and a quantitative model for each digitalization indicator is established; In the digitalization of highway network monitoring and dispatching, road network service level, information transmission efficiency, safety level, road network monitoring labor cost and asset management effectiveness are selected as digital indicators, and a quantitative model for each digital indicator is established.

2. The method for constructing a quantitative calculation model for the value and benefit of highway digital operation according to claim 1, characterized in that: The quantitative model of data collection efficiency DCE (unit: data / day) is: DCE=NMCR×TFMA×DCS (1) Where: NMCR is the road network monitoring coverage (unit: %), TFMA is the traffic flow monitoring accuracy (unit: %), DCS is the data collection speed (unit: data / day); The quantitative model of data processing and analysis capacity DPAC (unit: hour) is: Where: IDPT is the initial data processing time (unit: hours), AA is the accuracy of the analysis results (unit: %), and CRIDM is the contribution rate to intelligent decision-making (unit: %); The quantitative model of road network perception human cost NPHC (unit: person-day) is: NPHC=NPP×POT (3) Where: NPP is the number of perception workers (unit: person); POT is the perception operation time (unit: day); The quantitative model of perception data coordination capability PDCC (unit: hour) is: Where: DTT is the data transmission time (unit: hours), DSL is the data sharing degree (unit: %).

3. The method for constructing a quantitative calculation model for the value and benefit of highway digital operation according to claim 1, characterized in that: The quantitative model of road network service level NSL (unit: hour) is: Where: SCR is service coverage rate (unit: %), SRR is service reach rate (unit: %), AIRT is the average accident handling time (unit: hours); The quantitative model of information transmission efficiency ITE (unit: information / hour) is: ITE=ITS×IAR (6) Where: ITS is the information transmission speed (unit: information / hour), IAR is the information accuracy rate (unit: %); The quantitative model of safety level SL (unit: %) is: SL=(1-NIR)×(1-NFR)2×(1-OSIR) (7) Where: NIR is the road network accident rate (unit: %), NFR is the road network mortality rate (unit: %), OSIR is the operation safety accident rate (unit: %); The quantitative model of road network monitoring manpower cost NMHC (unit: person-day) is: NMHC=NMDP×MDWT (8) Where: NMDP is the number of monitoring and scheduling personnel (unit: person), MDWT is the monitoring and scheduling operation time (unit: day); The quantitative model of asset management efficiency AME (unit: / yuan) is: In the formula: ALUAR is the automation rate of asset ledger update (unit: %), AMC is the asset maintenance cost (unit: yuan), and AUR is the asset utilization rate (unit: %).

4. The method for constructing a quantitative calculation model for the value and benefit of highway digital operation according to claim 1, characterized in that: Also includes: The quantitative models of various indicators in the digitalization of highway network perception and the digitalization of highway network monitoring and scheduling are stored on computing devices or storage devices respectively; the quantitative models corresponding to different stages are selected and retrieved at different stages of highway operation, and the corresponding indicator calculation results are obtained after the corresponding data are input, and the calculated indicator data are stored and output.

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