Traffic engineering design data collaboration system and method

Abstract

The invention discloses a traffic engineering design data collaboration system and method, and relates to the technical field of data collaboration, a data receiving and collecting module is utilized to receive and collect traffic engineering design data of the same elements in two design platforms and collaboration synchronization conditions, and a data processing module is utilized to process the traffic engineering design data. Sequentially calculating and outputting a design data synchronization error value W, collaborative design efficiency L and an adjustment factor K, outputting a collaborative result and an adjustment decision based on the adjustment factor K and conformity between same elements in the two design platforms by using an adjustment decision module, and outputting a collaborative design result and an adjustment decision based on the collaborative result and the adjustment decision. According to the invention, through accurately evaluating the data synchronization error, quantitatively evaluating the collaborative design efficiency and providing an intelligent adjustment guidance mechanism, the comprehensive evaluation and optimization of the design data collaborative process are realized, so that the design efficiency and accuracy are improved; and powerful support is provided for traffic engineering design.

Description

Technical Field

[0001] The present invention relates to the technical field of data collaboration, and in particular to a traffic engineering design data collaboration system and method. Background Art

[0002] Traffic engineering design is a comprehensive work involving multiple disciplines and fields, including road design, bridge design, tunnel design, and traffic planning. These design data are interrelated, and in traffic engineering design, data collaborative processing is a crucial link. Since the design process involves multiple software and platforms, including two-dimensional design platform, reinforcement calculation platform, structural calculation platform and BIM platform, it is necessary to achieve synchronous update and import and export of data between these software and platforms.

[0003] However, existing systems can only simply determine whether the data is consistent, but it is difficult to accurately evaluate the error size of data synchronization, which makes it difficult for designers and engineers to understand the accuracy of data synchronization, making it difficult to make effective adjustments and optimizations. In addition, existing systems lack an evaluation mechanism for collaborative design efficiency and are unable to quantify the extent to which the system improves design efficiency. This makes it difficult for designers and engineers to accurately evaluate the performance of the system and make reasonable decisions. For data that needs to be adjusted, existing systems can only provide simple prompts and warnings, but lack intelligent adjustment guidance, which makes the adjustment process complicated and difficult to control, increasing design costs and time. Summary of the invention

[0004] The purpose of the present invention is to provide a traffic engineering design data collaboration system to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides a traffic engineering design data collaboration method, and the specific implementation steps are as follows: Step 1: Use the data receiving and collecting module to receive and collect the traffic engineering design data of the same elements in the two design platforms and the status of collaborative synchronization. The traffic engineering design data includes road width, road length, and road design standards; Step 2: Using the data processing module, calculate the output design data synchronization error value W, collaborative design efficiency L, and adjustment factor K in sequence; The data processing module includes a unit for intuitively reflecting the accuracy of data synchronization between the two design platforms, a unit for evaluating the degree of improvement of the collaborative system on design efficiency, and a unit for guiding collaborative adjustment of design data; Step 3: Based on the adjustment factor K and the conformity between the same elements in the two design platforms, and using an adjustment decision module, output a collaborative result and an adjustment decision; Step 4: Based on the collaborative results and adjustment decisions, the data receiving and collecting module receives, inputs and stores.

[0006] Optionally, the equipment used by the data receiving and collecting module includes a server, a workstation, and a network communication device; The equipment used by the data processing module includes a data processing computing system; The equipment used by the adjustment decision module includes data analysis software.

[0007] Optionally, the calculation formula for the unit that directly reflects the accuracy of data synchronization between the two design platforms is as follows: W = SQRT[(S1-S2) 2 +(S3-S4) 2 ]-((S1-S2) / 2)×|S3 / S4-1|; in: W is the design data synchronization error value; S1 is the road width of the first platform, S2 is the road width of the second platform, S1 and S2 represent the data values ​​of the same design element in the two design platforms, that is, the data values ​​of the road width in different platforms; S3 is the road length of the first platform, S4 is the road length of the second platform, and S3 and S4 respectively represent the data values ​​of another related design element in the two design platforms, that is, the data values ​​of the road length on different platforms.

[0008] Optionally, the calculation formula for evaluating the collaborative system for improving the design efficiency is as follows: L=((W prev -W) / W prev )×100+[(S sync / T)×SQRT(S total / S sync )]; in: L is the collaborative design efficiency; W prev Design data synchronization error value for the previous round; S sync The amount of data to be successfully synchronized; T is the synchronization time, and T reflects the amount of data successfully synchronized S sync the time required; S total is the total design data volume.

[0009] Optionally, the calculation formula of the guiding design data collaborative adjustment unit is as follows: K = ((L / 100) × SQRT (S adjust ))+[(W / Wprev )×|S key -S target |]; in: K is the adjustment factor; S adjust Adjust the amount of data as needed; S key It is the data value of the key design element, and the key design element is specifically the road design standard; S target It is the target design element data value, and the target design element is specifically the desired road design standard.

[0010] Optionally, the adjustment analysis based on the adjustment factor K is as follows: If the adjustment factor K increases compared to the previous round of adjustment factor K, it means that in the current design and collaboration process, there is a large amount of data that needs to be adjusted and corrected; If the adjustment factor K is lower than the adjustment factor K of the previous round, and the key design element data value S key Not equal to the target design element data value S target , and the previous difference is still maintained, it means that in the current design and collaboration process, there are still differences between the current design data and the target value that need to be adjusted; In both cases, the key design element data value S key and the target design element data value S target The differences between them are analyzed and adjusted in detail; If the adjustment factor K is lower than the adjustment factor K of the previous round, and the key design element data value S key and the target design element data value S target If the difference between them decreases, it means that the adjustment in the current design and collaboration process is effective and the design data is close to the target value.

[0011] Optionally, the key design element data value S key and the target design element data value S target The detailed adjustments of the differences are as follows: Identify discrepant data points: By comparing and analyzing the key design element data values ​​S of road length and width key and the target design element data value S target , determine which data points do not match; Assess the need for adjustment: Evaluate each different data point to determine whether it needs to be adjusted and the impact of the adjustment on the overall design; Determine the adjustment plan: Formulate an adjustment plan based on the assessment results, including the direction, magnitude and specific measures of the adjustment; Estimated adjustment data volume: According to the adjustment plan, it is estimated that the amount of data S needs to be adjusted adjust , which includes the number of adjustments for individual data points; Implementation adjustments: According to the adjustment plan, adjust the design data to ensure that the adjusted key design element data value S key Equal to the target design element data value S target ; Verification and feedback: Verify the adjusted data.

[0012] The present invention also provides a traffic engineering design data collaboration system, including a method for collaborating traffic engineering design data of two design platforms, judging the accuracy of collaboration, evaluating the efficiency of collaboration, and guiding the collaboration of design data; It includes data receiving and collecting module, data processing module and adjustment decision module; Data receiving and collecting module: responsible for receiving and storing the data values ​​of the same design element and related design elements in the two design platforms, as well as the data values ​​of key design elements and target design elements; Data processing module: responsible for calculating the output design data synchronization error value W, collaborative design efficiency L, and adjustment factor K in sequence; Adjustment decision module: responsible for adjusting the result value of the adjustment factor K and the key design element data value S key and the target design element data value S target to determine whether adjustments are needed and determine the direction and magnitude of the adjustments; Data receiving and collecting module: outputs the data items that need to be adjusted and the adjusted data values.

[0013] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention enables the system to accurately calculate the design data synchronization error value W by intuitively reflecting the data synchronization accuracy unit between the two design platforms, thereby reflecting the accuracy of data synchronization between the two design platforms. This helps to understand the error size of data synchronization and provides strong support for subsequent adjustment and optimization.

[0014] 2. The present invention enables the system to quantitatively evaluate the collaborative design efficiency L by evaluating the unit of improvement of the design efficiency of the collaborative system, thereby reflecting the degree of improvement of the design efficiency of the system, which helps to accurately evaluate the performance of the system and provide a scientific basis for optimizing the system design.

[0015] 3. The present invention guides the design data collaborative adjustment unit to enable the system to calculate the adjustment factor K of the design data collaboration, and according to the value of the adjustment factor K and the key design element data value S key and the target design element data value S target The software can provide intelligent adjustment guidance based on the differences in design, which helps to quickly locate the data items that need to be adjusted and determine the direction and magnitude of the adjustment, thereby simplifying the adjustment process and reducing design costs and time.

[0016] In addition, the system and method also achieve continuous optimization and improvement of the design data collaboration process through a loop feedback mechanism. key Not equal to the target design element data value S target When the system performs a detailed comparison, it will find the amount of data that does not match and needs to be adjusted. adjust ,Then, according to the value of the adjustment factor K and the comparison results, the system will guide the corresponding adjustment. ,Through continuous feedback and adjustment, the system can gradually optimize the design data and improve ,the design efficiency and accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flow chart of the method for designing a data collaboration system for this transportation project; Figure 2 It is a schematic diagram of the collaborative operation of the data receiving and collecting modules in the present invention; Figure 3 It is a structural schematic diagram of the data processing module of the present invention; Figure 4 Method flow chart of the data collaboration method designed for this transportation project. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0019] Regarding the present traffic engineering design data collaborative system and method, it is different from the existing traffic engineering design data collaborative system. The existing traffic engineering design data collaborative system can often only realize simple data synchronization, but cannot accurately evaluate the error and efficiency of data synchronization. At the same time, for the data that needs to be adjusted, the system lacks intelligent guidance, which makes the adjustment process complicated and difficult to control. The present algorithm unit realizes a comprehensive evaluation and optimization of the design data collaborative process by accurately evaluating data synchronization errors, quantitatively evaluating collaborative design efficiency and providing an intelligent adjustment guidance mechanism. The system and method not only solve the problems and shortcomings of the existing technology, but also improve the design efficiency and accuracy, providing strong support for traffic engineering design.

[0020] For example, see Figures 1 to 4 ,This implementation provides a traffic engineering design data collaboration method as follows: Using the data receiving and collecting module, the traffic engineering design data of the same elements in the two design platforms and the situation of coordinated synchronization are received and collected. The traffic engineering design data includes road width, road length, and road design standards; Using the data processing module, the output design data synchronization error value W, collaborative design efficiency L, and adjustment factor K are calculated in sequence; The data processing module includes a unit that directly reflects the accuracy of data synchronization between the two design platforms, a unit that evaluates the degree to which the collaborative system improves design efficiency, and a unit that guides collaborative adjustment of design data. Based on the adjustment factor K and the conformity between the same elements in the two design platforms, and using the adjustment decision module, the coordination results and adjustment decisions are output; Based on the collaborative results and adjustment decisions, the data receiving and collecting module receives, inputs and stores data; The equipment used in the data receiving and collecting module includes servers, workstations, and network communication equipment; The equipment used by the data processing module includes a data processing computing system; The equipment used in the adjustment decision module includes data analysis software.

[0021] This implementation also provides a traffic engineering design data collaboration system, including methods for collaborating traffic engineering design data of two design platforms, judging the accuracy of collaboration, evaluating the efficiency of collaboration, and guiding the collaboration of design data; It includes data receiving and collecting module, data processing module and adjustment decision module; Data receiving and collecting module: responsible for receiving and storing the data values ​​of the same design element and related design elements in the two design platforms, as well as the data values ​​of key design elements and target design elements; Data processing module: responsible for calculating the output design data synchronization error value W, collaborative design efficiency L, and adjustment factor K in sequence; Adjustment decision module: responsible for adjusting the result value of the adjustment factor K and the key design element data value S key and the target design element data value S target to determine whether adjustments are needed and determine the direction and magnitude of the adjustments; Data receiving and collecting module: outputs the data items that need to be adjusted and the adjusted data values.

[0022] In this embodiment, the system cooperates with the three algorithm units and combines the three operation results of W, L and K, which together constitute the core components of the traffic engineering design data collaborative system and method, thereby providing a basis for quantitative evaluation, intelligent adjustment and continuous improvement. Specifically, W is the design data synchronization error value, which not only considers the absolute value of the data difference, but also considers the relative degree of data change, so as to more comprehensively evaluate the accuracy of data synchronization. L is the collaborative design efficiency, which not only considers the improvement of data synchronization accuracy, but also considers the influence of synchronization speed and total data volume, so as to more comprehensively evaluate the accuracy of data synchronization. The effect of the collaborative system is evaluated, and K is the adjustment factor. This value not only reflects the necessity and urgency of the adjustment, but also reflects the direction and magnitude of the adjustment. Therefore, according to the value of the adjustment factor K, a more reasonable and effective data adjustment plan can be formulated to improve the design efficiency and accuracy. The calculation results of W and L can also affect the calculation of K, which makes the three algorithms of this system play an important role in the collaborative system and method of traffic engineering design data. The mutual influence and correlation between the three algorithms provide a quantitative evaluation standard and guide the direction of data adjustment and system optimization, which is conducive to the accurate synchronization of data and efficient collaborative design.

[0023] See also Figures 1 to 4 , the calculation formula that directly reflects the accuracy of data synchronization between two design platforms is as follows: W = SQRT[(S1-S2) 2 +(S3-S4) 2 ]-((S1-S2) / 2)×|S3 / S4-1|; in: W is the design data synchronization error value; S1 is the road width of the first platform, S2 is the road width of the second platform, S1 and S2 represent the data values ​​of the same design element in the two design platforms, that is, the data values ​​of the road width in different platforms; S3 is the road length of the first platform, S4 is the road length of the second platform, and S3 and S4 respectively represent the data values ​​of another related design element in the two design platforms, that is, the data values ​​of the road length on different platforms.

[0024] In this embodiment: First, in this algorithm unit, "SQRT[(S1-S2) 2 +(S3-S4) 2 ]” The calculation part calculates the square root of the sum of the squares of the differences between the two data pairs, that is, the square root of the Euclidean distance. This calculation part reflects the absolute value of the data difference between the corresponding design elements of the two design platforms. By calculating this distance, the accuracy of the data synchronization between the two platforms can be intuitively understood, that is, the size of the data difference. This calculation part is the core of the unit that intuitively reflects the accuracy of data synchronization between the two design platforms. It is used to measure the size of the design data synchronization error value W, which directly determines the design data synchronization error value W, thereby reflecting the accuracy of data synchronization; The calculation part of "((S1-S2) / 2)×|S3 / S4-1|" calculates the product of the average value of two data "((S1-S2) / 2)" and another data "|S3 / S4|", and then subtracts 1. This calculation reflects the relative change of the data, that is, the change trend of the data in the collaborative process. By calculating this value, we can understand the relative stability or variability of the data in the collaborative process. This calculation part is a supplement to the unit that directly reflects the accuracy of data synchronization between the two design platforms. Together with the previous distance calculation, it constitutes a complete measure of the design data synchronization error value W. It provides information about the relative change of the data, which helps to more comprehensively evaluate the accuracy of data synchronization. This algorithm unit can intuitively see the error size of data synchronization between two design platforms by calculating the design data synchronization error value W, which helps to quickly identify data synchronization problems and take targeted measures to correct them. The smaller the design data synchronization error value W, the higher the accuracy of data synchronization, and vice versa. This quantitative evaluation standard helps to achieve accurate data synchronization and ensure the consistency and accuracy of the design. By analyzing the composition of the design data synchronization error value W, it is possible to identify which design elements have large data differences. These differences are often the main cause of the data synchronization error. By comparing the data differences of different design elements, it is possible to prioritize the data with large differences, thereby more effectively reducing the data synchronization error. Continuously iterating and calculating the design data synchronization error value W and adjusting the design data according to the changes in the design data synchronization error value W can gradually optimize the performance of the traffic engineering design data collaborative system. By analyzing the changing trend of the design data synchronization error value W, problems and deficiencies in the system design can be discovered, thereby making targeted optimizations and improvements.

[0025] See also Figures 1 to 4 , the calculation formula for evaluating the degree of improvement of design efficiency by the collaborative system is as follows: L=((W prev -W) / W prev )×100+[(S sync / T)×SQRT(S total / S sync )]; in: L is the collaborative design efficiency; W prev Design data synchronization error value for the previous round; S sync The amount of data to be successfully synchronized; T is the synchronization time, and T reflects the amount of data successfully synchronized S sync the time required; S total is the total design data volume.

[0026] In this embodiment, first, "((W prev -W) / W prev )” calculation part calculates the synchronization error value W of the previous round of design data prev The difference between the current round of design data synchronization error value W and the previous round of design data synchronization error value W prev , this calculation part reflects the percentage of data synchronization error reduction, that is, the degree of improvement in data synchronization accuracy. By calculating this percentage, we can intuitively understand the effect of the collaborative system on improving data synchronization efficiency. The calculation part is one of the core units for evaluating the degree of improvement of the collaborative system on design efficiency, and is used to measure the degree of improvement of the collaborative design efficiency L. It directly determines a part of the collaborative design efficiency L, thereby reflecting the contribution of the collaborative system to the data synchronization efficiency; “[(S sync / T)×SQRT(S total / S sync The calculation part first calculates the synchronization time T and the amount of successfully synchronized data S sync The ratio of the synchronization speed is then multiplied by the amount of successfully synchronized data S sync The total design data volume S total This calculation reflects the comprehensive index of data synchronization efficiency, that is, the product of synchronization speed and synchronization coverage. By calculating this value, we can understand the overall efficiency of the collaborative system in the data synchronization process. This calculation part is another part of the unit for evaluating the degree of improvement of the collaborative system on design efficiency. Together with the previous error reduction percentage, it constitutes a complete measure of the collaborative design efficiency L. It provides comprehensive information about data synchronization efficiency and helps to more comprehensively evaluate the performance of the collaborative system. This algorithm unit can intuitively reflect the degree of improvement of the design efficiency of the collaborative system through the collaborative design efficiency L. By comparing the collaborative design efficiency L under different collaborative schemes, it can evaluate which scheme is more efficient. The higher the collaborative design efficiency L, the better the effect of collaborative design, which can complete the task faster and reduce errors. By analyzing the composition of collaborative design efficiency L, we can identify factors that affect collaborative efficiency. Specifically, if the percentage of error reduction is very low, we need to optimize the collaborative algorithm and improve the accuracy of data synchronization. By adjusting these influencing factors, we can further improve the efficiency of collaborative design. By comparing the collaborative design efficiency L of different design stages, we can understand the differences in collaborative efficiency of each stage, which helps to allocate resources reasonably and invest more resources in the less efficient stages, thereby improving the overall design efficiency.

[0027] See also Figures 1 to 4 , the calculation formula for guiding the design data collaborative adjustment unit is as follows: K = ((L / 100) × SQRT (S adjust ))+[(W / W prev )×|S key -S target |]; in: K is the adjustment factor; S adjust Adjust the amount of data as needed; S key It is the data value of the key design element, and the key design element is specifically the road design standard; S target It is the target design element data value, and the target design element is specifically the desired road design standard.

[0028] In this embodiment, the algorithm unit first "((L / 100)×SQRT(S adjust The calculation part of )) calculates the collaborative design efficiency L divided by 100, and the amount of data that needs to be adjusted under the square root S adjust The product of , this calculation reflects the necessity and urgency of the adjustment, that is, the priority of the adjustment is comprehensively evaluated according to the collaborative design efficiency and the amount of data that needs to be adjusted. By calculating this value, we can understand which data needs to be adjusted first. This calculation part is one of the cores of the collaborative adjustment unit for guiding the design data. It is used to guide the adjustment priority of the design data. It directly determines a part of the adjustment factor K, thereby reflecting the necessity and urgency of the adjustment; “[(W / W prev )×|S key -S target|]” The calculation part calculates the synchronization error value W of the previous round of design data prev The ratio of the synchronization error value W of the current round of design data, multiplied by the key design element data value S key and the target design element data value S target This calculation reflects the combined impact of the error change and the difference between the key design elements and the target value, that is, the direction and magnitude of the adjustment are comprehensively evaluated according to the degree of error change and the difference between the key design elements and the target value. By calculating this value, we can understand in which direction the adjustment should be made and the magnitude of the adjustment. This calculation part, as another part of the guiding design data collaborative adjustment unit, together with the previous adjustment priority, constitutes a complete measure of the design data collaborative adjustment factor K, which provides information about the adjustment direction and magnitude and helps to guide the adjustment of design data more accurately. In this algorithm unit, the necessity and urgency of adjustment can be reflected by adjusting the factor K. When the adjustment factor K is high, it means that a large adjustment is needed to improve the data synergy effect. By analyzing the composition of the adjustment factor K, the direction and magnitude of the adjustment can be determined. If the key design element data value S key and the target design element data value S target If the difference is large, then it is necessary to focus on adjusting the data of these elements; Continuously iterating and calculating the adjustment factor K and adjusting the design data according to the changes in the adjustment factor K can gradually optimize the data adjustment process, which helps to reduce unnecessary adjustment work and improve the efficiency and accuracy of data adjustment; Adjustment factor K is used as the basis for collaborative adjustment of design data, which helps to promote the collaboration and consistency of data between different design platforms. By adjusting data items with higher adjustment factor K, data synchronization and collaboration between different platforms can be better achieved; In summary, the unit that intuitively reflects the accuracy of data synchronization between the two design platforms, the unit that evaluates the degree of improvement of the collaborative system on design efficiency, and the unit that guides the collaborative adjustment of design data and their parameters play an important role in the collaborative system and method for transportation engineering design data. They not only provide quantitative evaluation criteria, but also guide the direction of data adjustment and system optimization, which helps to achieve accurate data synchronization and efficient collaborative design.

[0029] For example 2, please refer to Figures 1 to 4 , the adjustment analysis based on the adjustment factor K is as follows: If the adjustment factor K increases compared to the previous round of adjustment factor K, it means that in the current design and collaboration process, there is a large amount of data that needs to be adjusted and corrected; If the adjustment factor K is lower than the adjustment factor K of the previous round, and the key design element data value S keyNot equal to the target design element data value S target , and the previous difference is still maintained, it means that in the current design and collaboration process, there are still differences between the current design data and the target value that need to be adjusted; In both cases, the key design element data value S key and the target design element data value S target The differences between them are analyzed and adjusted in detail; If the adjustment factor K is lower than the adjustment factor K of the previous round, and the key design element data value S key and the target design element data value S target If the difference between them decreases, it means that the adjustment in the current design and collaboration process is effective and the design data is close to the target value. Key design element data value S key and the target design element data value S target The detailed adjustments of the differences are as follows: Identify discrepant data points: By comparing and analyzing the key design element data values ​​S of road length and width key and the target design element data value S target , determine which data points do not match; Assess the need for adjustment: Evaluate each different data point to determine whether it needs to be adjusted and the impact of the adjustment on the overall design; Determine the adjustment plan: Formulate an adjustment plan based on the assessment results, including the direction, magnitude and specific measures of the adjustment; Estimated adjustment data volume: According to the adjustment plan, it is estimated that the amount of data S needs to be adjusted adjust , which includes the number of adjustments for individual data points; Implementation adjustments: According to the adjustment plan, adjust the design data to ensure that the adjusted key design element data value S key Equal to the target design element data value S target ; Verification and feedback: Verify the adjusted data.

[0030] In this embodiment, by calculating the adjustment factor K and adjusting the design data according to the adjustment factor K, the design data synchronization error value W can be gradually reduced. This dynamic adjustment process helps to continuously improve the accuracy of data synchronization. Specifically, with the continuous iterative calculation and adjustment of the adjustment factor K, the design data collaboration process will gradually tend to be optimized, which helps to reduce data inconsistencies and conflicts, improve design efficiency and accuracy, and by continuously monitoring and analyzing the changes in the adjustment factor K and the design data synchronization error value W, it is possible to promptly discover problems and deficiencies in the system and make continuous improvements and optimizations, which helps to improve the overall performance and reliability of the traffic engineering design data collaboration system. By continuously paying attention to the changes in the design data collaboration adjustment factor K, it is possible to more accurately identify which data needs to be adjusted. When the collaboration adjustment factor K increases, it means that more data needs to be paid attention to and needs to be adjusted. This improvement in accuracy helps to avoid unnecessary adjustment work, thereby saving time and resources; At the same time, by comparing the key design element data value S key and the target design element data value S target The difference between the design data and the target value can be directly found. This difference is the direct basis for adjustment. This comparison method makes the adjustment work more targeted and avoids blind adjustment. Based on the above, specifically, after determining the data that needs to be adjusted, the adjustment factor K and the key design element data value S key and the target design element data value S target By comprehensively considering these factors, a more reasonable and feasible adjustment plan can be formulated. These plans can not only meet the requirements of the design standards, but also better meet the needs of customers and achieve the sustainability of the design based on environmental factors; After one or more rounds of adjustments, the value of the design data collaborative adjustment factor K usually decreases, which indicates that the adjustment is effective and the design data has approached the target value. This adjustment feedback mechanism can timely understand the effect of the adjustment and make further adjustments as needed. Through this continuous adjustment and optimization, the design data can gradually approach and reach the target value, thereby improving the quality and efficiency of the design. At the same time, this adjustment feedback mechanism also helps to accumulate experience and knowledge, and provide reference and reference for future design work. In the process of collaborative adjustment of design data, designers and engineers need to work closely together and communicate, and need to jointly analyze the adjustment factor K and the key design element data value S key and the target design element data value S targetCompare the results between the two, formulate adjustment plans, and conduct continuous monitoring and evaluation during the implementation process. This process of collaboration and communication helps to build trust and tacit understanding between the platforms of each department, improve the cohesion and execution of the team. At the same time, by sharing information and experience, we can learn from each other and jointly improve our design capabilities and levels. In summary, the unit that directly reflects the accuracy of data synchronization between the two design platforms, the unit that evaluates the degree of improvement of the collaborative system on design efficiency, and the unit that guides the collaborative adjustment of design data each have significant beneficial effects in the collaborative system and method for traffic engineering design data, and the unit that guides the collaborative adjustment of design data has a beneficial effect of circular influence on the unit that directly reflects the accuracy of data synchronization between the two design platforms. These formulas together constitute the core components of the collaborative system and method for traffic engineering design data, and thus provide a basis for quantitative evaluation, intelligent adjustment and continuous improvement. In addition, the collaborative adjustment factor K of design data and the data value S of key design elements are used. key and the target design element data value S target The comparison between them serves as the basis for evaluation and adjustment, which can bring many beneficial effects in the process of collaborative adjustment of design data. These effects not only help to improve the accuracy of adjustment and optimize the adjustment plan, but also improve design quality and efficiency, and promote team collaboration and communication.

[0031] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A traffic engineering design data collaboration method, characterized in that: The specific implementation steps are as follows: Step 1: Use the data receiving and collecting module to receive and collect the traffic engineering design data of the same elements in the two design platforms and the status of collaborative synchronization. The traffic engineering design data includes road width, road length, and road design standards; Step 2: Using the data processing module, calculate the output design data synchronization error value W, collaborative design efficiency L, and adjustment factor K in sequence; The data processing module includes a unit for intuitively reflecting the accuracy of data synchronization between the two design platforms, a unit for evaluating the degree of improvement of the collaborative system on design efficiency, and a unit for guiding collaborative adjustment of design data; Step 3: Based on the adjustment factor K and the conformity between the same elements in the two design platforms, and using an adjustment decision module, output a collaborative result and an adjustment decision; Step 4: Based on the collaborative results and adjustment decisions, the data receiving and collecting module receives, inputs and stores.

2. A traffic engineering design data collaboration method according to claim 1, characterized in that: The equipment used by the data receiving and collecting module includes servers, workstations, and network communication equipment; The equipment used by the data processing module includes a data processing computing system; The equipment used by the adjustment decision module includes data analysis software.

3. A traffic engineering design data collaboration method according to claim 2, characterized in that: The calculation formula for the unit that directly reflects the accuracy of data synchronization between the two design platforms is as follows: <h2 style=";text-align:left;direction:ltr">W=SQRT[(S1-S2)<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> +(S3-S4)<h2 style=";text-align:left;direction:ltr"> 2 <h2 style=";text-align:left;direction:ltr"> ]-((S1-S2) / 2)×|S3 / S4-1|; in: W is the design data synchronization error value; S1 is the road width of the first platform, S2 is the road width of the second platform, S1 and S2 represent the data values ​​of the same design element in the two design platforms, that is, the data values ​​of the road width in different platforms; S3 is the road length of the first platform, S4 is the road length of the second platform, and S3 and S4 respectively represent the data values ​​of another related design element in the two design platforms, that is, the data values ​​of the road length on different platforms.

4. A traffic engineering design data collaboration method according to claim 3, characterized in that: The calculation formula for evaluating the degree of improvement of the design efficiency by the collaborative system is as follows: L=((W prev -W) / W prev )×100+[(S sync / T)×SQRT(S total / S sync )]; in: L is the collaborative design efficiency; W prev Design data synchronization error value for the previous round; S sync The amount of data to be successfully synchronized; T is the synchronization time, and T reflects the amount of data successfully synchronized S sync the time required; S total is the total design data volume.

5. A traffic engineering design data collaboration method according to claim 4, characterized in that: The calculation formula of the guiding design data collaborative adjustment unit is as follows: K=((L / 100)×SQRT(S adjust ))+[(W / W prev )×|S key -S target |]; in: K is the adjustment factor; S adjust Adjust the amount of data as needed; S key It is the data value of the key design element, and the key design element is specifically the road design standard; S target It is the target design element data value, and the target design element is specifically the desired road design standard.

6. A traffic engineering design data collaboration method according to claim 5, characterized in that: The adjustment analysis based on the adjustment factor K is as follows: If the adjustment factor K increases compared to the previous round of adjustment factor K, it means that in the current design and collaboration process, there is a large amount of data that needs to be adjusted and corrected; If the adjustment factor K is lower than the adjustment factor K of the previous round, and the key design element data value S key Not equal to the target design element data value S target , and the previous difference is still maintained, it means that in the current design and collaboration process, there are still differences between the current design data and the target value that need to be adjusted; In both cases, the key design element data value S key and the target design element data value S target The differences between them are analyzed and adjusted in detail; If the adjustment factor K is lower than the adjustment factor K of the previous round, and the key design element data value S key and the target design element data value S target If the difference between them decreases, it means that the adjustment in the current design and collaboration process is effective and the design data is close to the target value.

7. A traffic engineering design data collaboration method according to claim 6, characterized in that: The key design element data value S key and the target design element data value S target The detailed adjustments of the differences are as follows: Identify discrepant data points: By comparing and analyzing the key design element data values ​​S of road length and width key and the target design element data value S target , determine which data points do not match; Assess the need for adjustment: Evaluate each different data point to determine whether it needs to be adjusted and the impact of the adjustment on the overall design; Determine the adjustment plan: Formulate an adjustment plan based on the assessment results, including the direction, magnitude and specific measures of the adjustment; Estimated adjustment data volume: According to the adjustment plan, it is estimated that the amount of data S needs to be adjusted adjust , which includes the number of adjustments for individual data points; Implementation adjustments: According to the adjustment plan, adjust the design data to ensure that the adjusted key design element data value S key Equal to the target design element data value S target ; Verification and feedback: Verify the adjusted data.

8. The collaborative system used in the traffic engineering design data collaborative method according to claim 1 is characterized by: Data receiving and collecting module: responsible for receiving and storing the data values ​​of the same design element and related design elements in the two design platforms, as well as the data values ​​of key design elements and target design elements; Data processing module: responsible for calculating the output design data synchronization error value W, collaborative design efficiency L, and adjustment factor K in sequence; Adjustment decision module: responsible for adjusting the result value of the adjustment factor K and the key design element data value S key and the target design element data value S target to determine whether adjustments are needed and determine the direction and magnitude of the adjustments; Data receiving and collecting module: outputs the data items that need to be adjusted and the adjusted data values.

Images