Road transportation informatization safety supervision method and system

Abstract

The invention discloses a road transportation informatization safety supervision method and system, and relates to the technical field of route planning. Acquiring a road network of the target vehicle in the transportation area to obtain a route distribution map; for each section of route in the route distribution map, determining a transportation score, a time score and a danger score corresponding to the section of route according to historical data; determining a total transportation score of each route according to the transportation score, the time score and the danger score; determining an optimal path of the target vehicle from the starting point to the terminal point according to the total transportation score of each section of route; and for each section of route in the optimal path, determining the vehicle detection frequency of the route according to the danger score. The optimal path is determined by comprehensively considering the transportation score, the time score and the danger score, then the vehicle detection frequency of the route with the high danger score is determined, the monitoring strength can be dynamically adjusted, for the route with the high danger score, the vehicle detection frequency is increased, accidents or other safety events are effectively prevented, and the safety of dangerous goods transportation is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of route planning, and in particular relates to a road transport information safety supervision method and system. Background Art

[0002] With the increase in the amount of dangerous goods transportation, traffic accidents, especially explosion accidents, have brought huge safety hazards to society and the environment. The existing dangerous goods transportation safety supervision methods mostly rely on manual inspection and traditional empirical prediction, lacking real-time, systematic and accurate performance. Especially when selecting transportation routes, the safety differences between different routes are not fully considered, resulting in some high-risk routes still being used, thereby increasing the probability of accidents.

[0003] Patent CN117313967A discloses a method for planning the transport path of hazardous goods based on an improved ant colony algorithm. According to the connectivity information of road sections and nodes in the traffic network, a 0-1 matrix is ​​constructed to represent the connectivity relationship. With the goal of minimizing transportation risk and cost, a hazardous goods transport path optimization model is established by considering the path acyclic constraint. The model is solved by an improved ant colony algorithm, a backtracking mechanism is introduced, random and pseudo-random selection rules are combined, and a negative feedback mechanism is used to calculate the node selection probability. A mutation operator and a single-point crossover operator are set in the algorithm to update the pheromone concentration and adaptively adjust the parameters, thereby solving the problem of optimizing the transport path of hazardous goods.

[0004] However, most of the existing optimization of dangerous goods transportation routes only considers the minimization of transportation risks and costs, but lacks detailed consideration of the safety assessment of different routes, especially for vehicles transporting dangerous goods. When accidents or other emergencies occur, the potential threats and harm to the surrounding environment are huge, making the safety of dangerous goods transportation low. Summary of the invention

[0005] The purpose of the present invention is to solve the above-mentioned problems and to propose a road transportation information safety supervision method and system.

[0006] In a first aspect of the present invention, a road transport information safety supervision method is first proposed, the method comprising:

[0007] Obtain the road network of the target vehicle in the transportation area to obtain a route distribution map;

[0008] For each section of the route in the route distribution map, determining the transportation score, time score and danger score corresponding to the section of the route according to historical data;

[0009] Determine the total transport score for each route based on the transport score, time score and danger score;

[0010] Determine the best path for the target vehicle from the starting point to the end point according to the total transportation score of each route;

[0011] For each section of the optimal path, the vehicle detection frequency of the route is determined according to the risk score.

[0012] 2. A road transport information safety supervision method according to claim 1, characterized in that determining the transport score, time score and danger score corresponding to the route section according to historical data comprises:

[0013] Obtain the historical data corresponding to each route of the target vehicle under the first preset condition to obtain a time data set, a transportation loss set and a number of failures; the first preset condition includes the transportation time and the transportation items;

[0014] Calculate the average value of all time data in the time data set to get the average time; calculate the average value of all transportation losses in the transportation loss set to get the average loss; calculate the proportion of the number of failures in the total statistical number to get the average risk;

[0015] For each section of the route in the route distribution map, all average times, average losses and average dangers are sorted according to the second preset condition to obtain a time sorting set, a loss sorting set and a danger sorting set;

[0016] For each sorting set, the data in the sorting set is assigned according to the preset score to obtain the transportation score, time score and danger score corresponding to each route section.

[0017] 3. A road transport information safety supervision method according to claim 1, characterized in that, according to the total transport score of each route, determining the best path from the starting point to the end point of the target vehicle comprises:

[0018] Obtaining a target starting point and a target end point in the route distribution map, and generating a route set from the target starting point to the target end point by using an ant algorithm;

[0019] Obtaining a total transportation score corresponding to each route in the route distribution map, and calculating a total route score for each route in the route set;

[0020] Screening the route set according to the preset route total score to obtain a valid route set;

[0021] The optimal path is obtained by performing line generation on the effective line set through a preset algorithm.

[0022] 4. A road transport information safety supervision method according to claim 3, characterized in that generating the best path from the valid route set by a preset algorithm comprises:

[0023] Calculating a target value for each valid route in the valid route set; the target value includes a transportation value and a time value;

[0024] Determine the dominance relationship between every two valid routes according to the target value, and classify the routes according to the dominance relationship, wherein the first-level routes are routes that are not dominated by other routes;

[0025] Get all first-level routes and sort them from low to high according to their total scores, and get the route with the lowest total score to get the best path.

[0026] 5. A road transport information safety supervision method according to claim 1, characterized in that determining the vehicle detection frequency of the route according to the risk score comprises:

[0027] Obtaining a risk score corresponding to each section of the optimal path, and determining a ratio of detection times corresponding to each section of the route according to the risk score corresponding to each section of the route;

[0028] Acquire the driving environment of the target vehicle on the current road section, and determine the number of detections of the current road section according to the driving environment;

[0029] The detection frequency of the next road section is determined according to the detection times of the current road section and the detection times ratio.

[0030] In a second aspect of the present invention, a road transport information safety supervision system is provided, comprising:

[0031] A route distribution map determination module is used to obtain a road network of a target vehicle in a transportation area to obtain a route distribution map;

[0032] A route scoring module, for determining, for each route segment in the route distribution map, a transportation score, a time score and a danger score corresponding to the route segment according to historical data;

[0033] A total transport score determination module is used to determine the total transport score of each route according to the transport score, time score and danger score;

[0034] The optimal path determination module is used to determine the optimal path of the target vehicle from the starting point to the end point according to the total transportation score of each route;

[0035] The detection frequency determination module is used to determine the vehicle detection frequency of each route section in the optimal path according to the risk score.

[0036] 7. A road transport information safety supervision system according to claim 6, characterized in that the route scoring module comprises:

[0037] A data acquisition module, used to acquire the historical data corresponding to each route of the target vehicle under a first preset condition to obtain a time data set, a transportation loss set and a number of failures; the first preset condition includes the transportation time and the transportation items;

[0038] The average value calculation module is used to calculate the average value of all time data in the time data set to obtain the average time; calculate the average value of all transportation losses in the transportation loss set to obtain the average loss; calculate the proportion of the number of failures in the total statistical number to obtain the average risk;

[0039] A route sorting module, for sorting all average times, average losses and average dangers for each route in the route distribution map according to a second preset condition to obtain a time sorting set, a loss sorting set and a danger sorting set;

[0040] The route assignment module is used to assign values ​​to the data in each sorted set according to preset scores to obtain the transportation score, time score and danger score corresponding to each route segment.

[0041] 8. A road transport information safety supervision system according to claim 6, characterized in that the optimal path determination module comprises:

[0042] A route set determination module, used to obtain a target starting point and a target end point in the route distribution map, and generate a route set from the target starting point to the target end point by using an ant algorithm;

[0043] A route total score determination module is used to obtain the total transportation score corresponding to each route in the route distribution map, and calculate the route total score of each route in the route set;

[0044] A line screening module, used for screening the line set according to the preset line total score to obtain a valid line set;

[0045] The line generation module is used to generate lines for the effective line set by using a preset algorithm to obtain an optimal path.

[0046] 9. A road transport information safety supervision system according to claim 8, characterized in that the route generation module comprises:

[0047] A target value calculation module, used to calculate the target value of each valid route in the valid route set; the target value includes a transportation value and a time value;

[0048] A line classification module, used to determine the dominance relationship between every two valid lines according to the target value, and classify the lines according to the dominance relationship, wherein the lines of the first level are lines that are not dominated by other lines;

[0049] The best path generation module is used to obtain all first-level routes and sort them from low to high according to the total score of the routes, and obtain the route with the lowest total score to obtain the best path.

[0050] 10. A road transport information safety supervision system according to claim 6, characterized in that the detection frequency determination module comprises:

[0051] A detection times ratio determination module is used to obtain the risk score corresponding to each section of the optimal path, and determine the detection times ratio corresponding to each section of the route according to the risk score corresponding to each section of the route;

[0052] A current road section detection number determination module is used to obtain the driving environment of the target vehicle on the current road section and determine the detection number of the current road section according to the driving environment;

[0053] The next road section detection frequency determination module is used to determine the detection frequency of the next road section according to the number of detections of the current road section and the ratio of the detection times.

[0054] Beneficial effects of the present invention:

[0055] The present invention proposes a road transport information safety supervision method, which obtains the road network of the target vehicle in the transport area to obtain a route distribution map; for each section of the route in the route distribution map, the transportation score, time score and danger score corresponding to the section of the route are determined according to historical data; the total transportation score of each section of the route is determined according to the transportation score, time score and danger score; according to the total transportation score of each section of the route, the best path from the starting point to the end point of the target vehicle is determined; for each section of the route in the best path, the vehicle detection frequency of the route is determined according to the danger score. By comprehensively considering the transportation score, time score and danger score to determine the best path, the target vehicle can be helped to select the best route. This can not only reduce transportation time and fuel consumption, but also improve transportation efficiency and reduce vehicles traveling in unnecessary risk areas, avoid traffic accidents, and then by determining the vehicle detection frequency of routes with high danger scores, the monitoring intensity can be dynamically adjusted. For routes with higher dangers, the vehicle detection frequency is increased, which effectively prevents accidents or other safety incidents from occurring, and improves the safety of dangerous goods transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The present invention will be further described below in conjunction with the accompanying drawings.

[0057] Figure 1 A flowchart of a road transport information safety supervision method is provided for an embodiment of the present invention;

[0058] Figure 2 A framework diagram of a road transport information safety supervision system is provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0059] 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. The term "and / or" herein is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the present invention, the description of "first", "second", etc. is only used for descriptive purposes, and cannot be understood as indicating or implying its relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" can explicitly or implicitly include at least one of the features. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0060] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of the present invention.

[0061] The embodiment of the present invention provides a road transportation information security supervision method. Figure 1 , Figure 1 A flowchart of a road transport information safety supervision method provided by an embodiment of the present invention. The method comprises the following steps:

[0062] S101, obtaining a road network of a target vehicle in a transportation area to obtain a route distribution map;

[0063] S102, for each route section in the route distribution map, determining the transportation score, time score and danger score corresponding to the route section according to historical data;

[0064] S103, determining a total transportation score for each route segment according to the transportation score, time score, and risk score;

[0065] S104, determining the best path for the target vehicle from the starting point to the end point according to the total transportation score of each route;

[0066] S105: For each section of the optimal path, determine the vehicle detection frequency of the route according to the risk score.

[0067] Based on a road transport information safety supervision method provided by an embodiment of the present invention, the optimal path is determined by comprehensively considering the transport score, time score and danger score, which can help the target vehicle choose the optimal route. This can not only reduce transportation time and fuel consumption, but also improve transportation efficiency and reduce vehicles traveling in unnecessary risk areas, avoid traffic accidents, and then by determining the vehicle detection frequency of routes with high danger scores, the monitoring intensity can be dynamically adjusted. For routes with higher dangers, the vehicle detection frequency is increased, effectively preventing accidents or other safety incidents, and improving the safety of dangerous goods transportation.

[0068] In one implementation, the best path is determined by comprehensively considering the transportation score, time score and danger score, which can help the target vehicle choose the optimal route, which can not only reduce transportation time and fuel consumption, but also improve transportation efficiency and reduce vehicles traveling in unnecessary risk areas, thereby avoiding traffic accidents.

[0069] In one implementation, by setting a hazard score for each route, the system can identify high-risk areas such as accident-prone areas, busy traffic sections, or areas affected by natural disasters based on historical data and actual conditions, thereby avoiding or reducing vehicles from entering these areas and reducing potential safety hazards during transportation.

[0070] In one implementation, the nodes of the route distribution map include the starting node, the end point and the intersection of the target vehicle, and the edge represents the road between two nodes; the target vehicle is a vehicle transporting dangerous goods; the historical data is the driving time, transportation loss and number of accidents of vehicles transporting different dangerous goods on different sections and different time periods.

[0071] In one implementation, the total transport score of each route is determined based on the transport score, time score and danger score. The total transport score can be obtained by summing the transport score, time score and danger score. The total transport score can also be obtained by calculating the average value of the transport score, time score and danger score. The lower the total transport score, the better the route and the greater the probability of selection.

[0072] In one implementation, historical data analysis is used to evaluate the transportation score, time score, and hazard score of each route, so that path selection does not only rely on theoretical models or assumptions, but is based on actual conditions in the real world, ensuring the accuracy and scientificity of decision-making.

[0073] In one implementation, by determining the vehicle inspection frequency for routes with high risk scores, the monitoring intensity can be dynamically adjusted. For routes with higher risk, the vehicle inspection frequency is increased to ensure that the vehicle status, such as equipment failure and cargo safety, is checked in a timely manner, effectively preventing accidents or other safety incidents.

[0074] In one implementation, by optimizing transportation routes, reducing risks and improving detection efficiency, transportation costs can be significantly saved, ineffective or dangerous transportation time can be reduced, and not only fuel consumption can be reduced, but also wear and tear on vehicles and maintenance costs can be reduced.

[0075] In one embodiment, determining the transportation score, time score, and danger score corresponding to the route segment according to the historical data includes:

[0076] Obtain the historical data corresponding to each route of the target vehicle under the first preset condition to obtain a time data set, a transportation loss set, and a number of failures; the first preset condition includes the transportation time and the transportation items;

[0077] Calculate the average value of all time data in the time data set to get the average time; calculate the average value of all transportation losses in the transportation loss set to get the average loss; calculate the proportion of the number of failures in the total statistical number to get the average risk;

[0078] For each section of the route in the route distribution map, all average times, average losses and average dangers are sorted according to the second preset condition to obtain a time sorting set, a loss sorting set and a danger sorting set;

[0079] For each sorting set, the data in the sorting set is assigned according to the preset score to obtain the transportation score, time score and danger score corresponding to each route section.

[0080] In one implementation, by calculating the average time, average loss, and average risk of failures based on historical data, the system can obtain important information from actual transportation experience. Compared with traditional empirical decisions, data-driven decisions can more accurately predict potential problems in the transportation process and optimize routes.

[0081] In one implementation, the second preset condition is the average time, average loss and average danger for each route section, wherein the average time is sorted from small to large to obtain a time sorted set, the average loss is sorted from small to large to obtain a loss sorted set, and the average danger is sorted from small to large to obtain a danger sorted set. The data in the sorted set are assigned according to the preset scores to obtain the transportation score, time score and danger score corresponding to each route section, specifically the highest score is 100 and the lowest score is 30. According to the number in the sorted set, the number of sorts in the sorted set is reduced by one as the target value, and 70 is divided by the target value to determine the score difference between each two adjacent sorts. For example, if there are 8 data in the time sorted set, the score of the first sort is 100, the score of the second sort is 90, the score of the third sort is 80, the score of the fourth sort is 70, the score of the fifth sort is 60, the score of the sixth sort is 50, the score of the seventh sort is 40, and the score of the eighth sort is 30.

[0082] In one implementation, each route is sorted by transportation time, transportation loss, and number of failures, and each sorted set is assigned a corresponding score. This allows for a clearer understanding of the performance and characteristics of each route. The quantitative scoring method helps to clarify which routes perform better and which routes have potential risks, thereby supporting decision makers to make more targeted adjustments.

[0083] In one implementation, time is divided into: calculating the average time of each route to help find out which sections have low transportation efficiency, and then optimizing the transportation arrangements of these sections or choosing other more efficient routes to save time and cost; transportation loss is divided into: by analyzing the loss data during the transportation process, the loss of items on each route is evaluated. For sections with high losses, the transportation strategy can be adjusted in time or the monitoring of these sections can be strengthened to reduce losses; danger is divided into: calculating the proportion of failure times and evaluating the safety of each route. By identifying high-risk routes, the frequency of vehicle inspections can be increased, failures and safety accidents can be reduced, and the safety of the transportation process can be ensured.

[0084] In one embodiment, according to the total transportation score of each route segment, determining the best path for the target vehicle from the starting point to the end point includes:

[0085] Obtain the target starting point and target end point in the route distribution map, and generate a route set from the target starting point to the target end point through the ant algorithm;

[0086] Obtain the total transportation score corresponding to each route in the route distribution map, and calculate the total route score of each route in the route set;

[0087] Screening the route set according to the total score of the preset routes to obtain a valid route set;

[0088] The best path is obtained by generating routes for the valid route set through a preset algorithm.

[0089] In one implementation, by obtaining the target starting point and end point and using the route set generated by the ant algorithm, multiple possible paths can be generated in a short time. After scoring and calculation, these paths can be further screened out to find the best performing paths, and finally the best path can be selected, avoiding possible deviations and limitations in manual path planning and ensuring that the selected path is optimal.

[0090] In one implementation, for each route in the route set, the total route score of the route is calculated by summing the total transportation scores of all route segments in the route. The lower the total route score, the better and safer the route. The preset route total score usually obtains one-third of the number of routes in the route set starting from the lowest score to obtain the total route score at this position as the preset route total score. The preset route total score can also be determined by technical personnel; route screening is to obtain routes with a total route score lower than the preset route total score.

[0091] In one implementation, each route has a corresponding total transportation score. Based on this score, the algorithm can accurately evaluate the comprehensive performance of each route, such as transportation time, loss, safety and other factors. By calculating and sorting these scores, those routes with poor performance can be eliminated, thereby avoiding the selection of high-risk or inefficient routes and improving the scientificity and accuracy of decision-making.

[0092] In one implementation, the route set is screened by a preset total route score, which can effectively eliminate unqualified or suboptimal paths, reduce the amount of calculation, and further find the optimal path among the remaining valid routes, which helps to speed up the path optimization and avoid the high computational complexity that may be caused by the traditional exhaustive search method.

[0093] In one implementation, by comprehensively considering the total transportation score of each route, including information on multiple dimensions such as time, loss, and safety, the overall performance of each route can be comprehensively evaluated, so that the final selected path is not only the shortest path, but also the path with the best overall benefits, which can effectively balance various factors.

[0094] In one embodiment, generating a route from a valid route set by a preset algorithm to obtain an optimal path includes:

[0095] Calculate the target value of each valid route in the valid route set; the target value includes a transportation value and a time value;

[0096] Determine the dominance relationship between every two valid routes according to the target value, and classify the routes according to the dominance relationship, wherein the first-level routes are the routes that are not dominated by other routes;

[0097] Get all first-level routes and sort them from low to high according to their total scores, and get the route with the lowest total score to get the best path.

[0098] In one implementation, by calculating the dominance relationship between routes, it is possible to clearly identify which routes are superior to other routes in certain aspects such as time or transportation loss. The dominance relationship ensures that each route is fairly compared with other routes, avoiding the selection of suboptimal routes and ensuring that the selected paths are optimal in different dimensions or at least cannot be dominated by other routes.

[0099] In one implementation, the transport value and the time value are the transport score and the time score. For each pair of routes in the route set, their performance on each objective (time and cost) is compared. If route A is better than route B on all objectives, then route A dominates route B. According to the dominance relationship, the routes are divided into multiple levels. The first level contains those routes that are not dominated by any other routes, and the next levels contain solutions dominated by other routes. Each route is assigned a level so that we can identify which routes belong to the optimal solution set. First, select the routes in the first level, which are the optimal solutions that are not dominated by other routes. Among the routes in the first level, use the total score sorting to further determine the optimal route. If there is no route that meets the requirements, you can select routes in other levels and sort them by the total score in turn until the best route that meets the requirements is selected.

[0100] In one implementation, by sorting the total scores of the first-level routes, it is possible to ensure that the path selection has a clear priority, and the path with the lowest score will be the path with the best overall performance, and no other path will be better than it in multiple key factors. This sorting method ensures that the final selected path is the most cost-effective and meets the maximum requirements of the transportation task.

[0101] In one implementation, the routes are graded according to the dominance relationship and sorted according to the score, which can clearly reveal the basis for route selection, making the decision process more objective and enabling logistics managers and relevant decision makers to have a higher degree of trust in the selected route. The sorting and decision logic of each route is clear and traceable, enhancing the interpretability of the decision.

[0102] In one embodiment, determining the vehicle detection frequency of the route according to the risk score includes:

[0103] Obtain the risk score corresponding to each section of the optimal path, and determine the proportion of detection times corresponding to each section of the route according to the risk score corresponding to each section of the route;

[0104] Obtain the driving environment of the target vehicle on the current road section, and determine the number of detections for the current road section based on the driving environment;

[0105] The detection frequency of the next road section is determined based on the number of detections and the ratio of the number of detections of the current road section.

[0106] In one implementation, by combining the hazard score of each route with the ratio of the number of inspections, the system can increase the inspection frequency in sections with higher risks, promptly identify potential safety issues, and make dynamic adjustments based on risks, which helps reduce accidents, equipment failures and other transportation safety hazards, ensuring safer and more reliable vehicle operations.

[0107] In one implementation, the ratio of the number of detections corresponding to each section of the route is determined based on the risk score corresponding to each section of the route. Specifically, the ratio of the number of detections corresponding to each section of the route is determined using the risk score corresponding to each section of the route as a ratio.

[0108] In one implementation, the driving environment of the target vehicle on the current road section is obtained through the on-board sensor data, where the on-board sensor data can be, GPS positioning information: obtaining the longitude and latitude of the target vehicle, which helps to determine the current road section of the vehicle; speed sensor: obtaining the vehicle's driving speed, which is important for judging the current risk, especially in traffic congestion or high-speed driving; gyroscope and acceleration sensor: these sensors can monitor the lateral and longitudinal acceleration changes of the vehicle, and judge whether there are sudden braking, sharp turns, etc., reflecting potential safety risks; tire pressure sensor: monitoring tire pressure, it can determine whether there are tire abnormalities to prevent the vehicle from having problems such as tire blowouts; environmental sensors: such as temperature, humidity, rainfall sensors, etc., help determine whether the road surface is waterlogged, ice and snow, wet and slippery, etc., and the corresponding number of detections in the historical data will be searched based on the detected data.

[0109] In one implementation, after knowing the number of detection times of the route, the detection frequency of the next stage can be determined according to the ratio of the detection times. After determining the detection frequency of the next section of the route, when driving the next section of the route for driving environment detection, if the detection data is in the corresponding number of detections in the historical data, if the number of detections for three consecutive times exceeds 20% of the original number of detections, the current number of detections will be modified to the current number of detections.

[0110] In one implementation, the target vehicle's driving environment is acquired and the detection frequency is adjusted based on environmental changes, so that the detection mechanism not only relies on the pre-set danger value, but can also respond flexibly according to actual conditions. If a section of road encounters severe weather or sudden traffic conditions, the system will automatically increase the detection frequency to ensure the safety of the vehicle in complex environments.

[0111] In one implementation, by closely linking the detection frequency with the hazard score of each road section and the ratio of the number of detections, the system can avoid over-inspection of low-risk sections and reduce unnecessary inspections, thereby reducing costs and waste of resources, improving resource utilization efficiency, and saving unnecessary time and expenses.

[0112] In one implementation, based on the driving environment and real-time data feedback, the system can provide more frequent inspections in high-risk sections, monitor the vehicle status in a timely manner, ensure that the vehicle can be more fully inspected when passing through dangerous sections, improve the accuracy of inspections, ensure that potential problems are quickly discovered and handled, and reduce the probability of accidents; by optimizing the inspection frequency and reducing unnecessary inspection and inspection processes, vehicle inspection time can be saved and unnecessary delays in the transportation process can be avoided. The system will only increase the inspection frequency when necessary, thereby improving transportation efficiency while ensuring safety.

[0113] Based on the same inventive concept, the embodiment of the present invention also provides a road transportation information safety supervision system. Figure 2 , Figure 2 A framework diagram of a road transport information safety supervision system provided by an embodiment of the present invention includes:

[0114] A route distribution map determination module is used to obtain a road network of a target vehicle in a transportation area to obtain a route distribution map;

[0115] The route scoring module is used to determine the transportation score, time score and danger score corresponding to each route section in the route distribution map according to historical data;

[0116] A total transport score determination module is used to determine the total transport score of each route according to the transport score, time score and danger score;

[0117] The best path determination module is used to determine the best path for the target vehicle from the starting point to the end point according to the total transportation score of each route;

[0118] The detection frequency determination module is used to determine the vehicle detection frequency of each route in the optimal path according to the risk score.

[0119] Based on a road transport information safety supervision system provided by an embodiment of the present invention, the best path is determined by comprehensively considering the transport score, time score and danger score, which can help the target vehicle choose the best route. This can not only reduce the transportation time and fuel consumption, but also improve the transportation efficiency and reduce the number of vehicles traveling in unnecessary risk areas, avoiding traffic accidents. By determining the vehicle detection frequency of routes with high danger scores, the monitoring intensity can be dynamically adjusted. For routes with higher danger scores, the vehicle detection frequency can be increased, effectively preventing accidents or other safety incidents, and improving the safety of dangerous goods transportation.

[0120] In one embodiment, the route scoring module includes:

[0121] A data acquisition module is used to acquire historical data corresponding to each route of the target vehicle under a first preset condition to obtain a time data set, a transportation loss set, and a number of failures; the first preset condition includes the transportation time and the transportation items;

[0122] The average value calculation module is used to calculate the average value of all time data in the time data set to obtain the average time; calculate the average value of all transportation losses in the transportation loss set to obtain the average loss; calculate the proportion of the number of failures in the total statistical number to obtain the average risk;

[0123] A route sorting module, for sorting all average times, average losses and average dangers for each route in the route distribution map according to a second preset condition to obtain a time sorting set, a loss sorting set and a danger sorting set;

[0124] The route assignment module is used to assign values ​​to the data in each sorted set according to preset scores to obtain the transportation score, time score and danger score corresponding to each route segment.

[0125] In one embodiment, the optimal path determination module includes:

[0126] A route set determination module is used to obtain a target starting point and a target end point in a route distribution map, and generate a route set from the target starting point to the target end point through an ant algorithm;

[0127] A route total score determination module is used to obtain the total transport score corresponding to each route in the route distribution map, and calculate the route total score of each route in the route set;

[0128] A route screening module, used to screen the route set according to the preset route total score to obtain a valid route set;

[0129] The line generation module is used to generate lines for the valid line set through a preset algorithm to obtain the best path.

[0130] In one embodiment, the line generation module includes:

[0131] A target value calculation module is used to calculate the target value of each valid route in the valid route set; the target value includes a transportation value and a time value;

[0132] A line classification module is used to determine the dominance relationship between every two valid lines according to the target value, and classify the lines according to the dominance relationship, wherein the first-level line is a line that is not dominated by other lines;

[0133] The best path generation module is used to obtain all first-level routes and sort them from low to high according to the total score of the routes, and obtain the route with the lowest total score to obtain the best path.

[0134] In one embodiment, the detection frequency determination module includes:

[0135] A detection times ratio determination module is used to obtain the risk score corresponding to each section of the optimal path, and determine the detection times ratio corresponding to each section of the route according to the risk score corresponding to each section of the route;

[0136] The current road section detection number determination module is used to obtain the driving environment of the target vehicle on the current road section and determine the detection number of the current road section according to the driving environment;

[0137] The next road section detection frequency determination module is used to determine the detection frequency of the next road section according to the detection times and the detection times ratio of the current road section.

[0138] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A road transport information safety supervision method, characterized in that: The method comprises: Obtain the road network of the target vehicle in the transportation area to obtain a route distribution map; For each route section in the route distribution map, determining the transportation score, time score and danger score corresponding to the route section according to historical data; Determine the total transport score for each route based on the transport score, time score and danger score; Determine the best path for the target vehicle from the starting point to the end point according to the total transportation score of each route; For each section of the optimal path, the vehicle detection frequency of the route is determined according to the risk score.

2. A road transport information safety supervision method according to claim 1, characterized in that: The transportation score, time score and danger score corresponding to this route segment determined based on historical data include: Obtain the historical data corresponding to each route of the target vehicle under the first preset condition to obtain a time data set, a transportation loss set and a number of failures; the first preset condition includes the transportation time and the transportation items; Calculate the average value of all time data in the time data set to get the average time; calculate the average value of all transportation losses in the transportation loss set to get the average loss; calculate the proportion of the number of failures in the total statistical number to get the average risk; For each section of the route in the route distribution map, all average times, average losses and average dangers are sorted according to the second preset condition to obtain a time sorting set, a loss sorting set and a danger sorting set; For each sorting set, the data in the sorting set is assigned according to the preset score to obtain the transportation score, time score and danger score corresponding to each route section.

3. A road transport information safety supervision method according to claim 1, characterized in that: According to the total transport score of each route, the optimal path from the starting point to the end point of the target vehicle is determined including: Obtaining a target starting point and a target end point in the route distribution map, and generating a route set from the target starting point to the target end point by using an ant algorithm; Obtaining a total transportation score corresponding to each route in the route distribution map, and calculating a total route score for each route in the route set; Screening the route set according to the preset route total score to obtain a valid route set; The optimal path is obtained by performing line generation on the effective line set through a preset algorithm.

4. A road transport information safety supervision method according to claim 3, characterized in that: Generating a route from the valid route set by a preset algorithm to obtain an optimal path includes: Calculating a target value for each valid route in the valid route set; the target value includes a transportation value and a time value; Determine the dominance relationship between every two valid routes according to the target value, and classify the routes according to the dominance relationship, wherein the first-level routes are routes that are not dominated by other routes; Get all first-level routes and sort them from low to high according to their total scores, and get the route with the lowest total score to get the best path.

5. A road transport information safety supervision method according to claim 1, characterized in that: The vehicle inspection frequency for this route is determined based on the risk score, including: Obtaining a risk score corresponding to each section of the optimal path, and determining a ratio of detection times corresponding to each section of the route according to the risk score corresponding to each section of the route; Acquire the driving environment of the target vehicle on the current road section, and determine the number of detections of the current road section according to the driving environment; The detection frequency of the next road section is determined according to the detection times of the current road section and the detection times ratio.

6. A road transport information safety supervision system, characterized in that: The device comprises: A route distribution map determination module is used to obtain a road network of a target vehicle in a transportation area to obtain a route distribution map; A route scoring module, for determining, for each route segment in the route distribution map, a transportation score, a time score and a danger score corresponding to the route segment according to historical data; A total transport score determination module is used to determine the total transport score of each route according to the transport score, time score and danger score; The optimal path determination module is used to determine the optimal path of the target vehicle from the starting point to the end point according to the total transportation score of each route; The detection frequency determination module is used to determine the vehicle detection frequency of each route section in the optimal path according to the risk score.

7. A road transport information safety supervision system according to claim 6, characterized in that: The route scoring module includes: A data acquisition module, used to acquire the historical data corresponding to each route of the target vehicle under a first preset condition to obtain a time data set, a transportation loss set and a number of failures; the first preset condition includes the transportation time and the transportation items; The average value calculation module is used to calculate the average value of all time data in the time data set to obtain the average time; calculate the average value of all transportation losses in the transportation loss set to obtain the average loss; calculate the proportion of the number of failures in the total statistical number to obtain the average risk; A route sorting module, for sorting all average times, average losses and average dangers for each route in the route distribution map according to a second preset condition to obtain a time sorting set, a loss sorting set and a danger sorting set; The route assignment module is used to assign values ​​to the data in each sorted set according to preset scores to obtain the transportation score, time score and danger score corresponding to each route segment.

8. A road transport information safety supervision system according to claim 6, characterized in that: The optimal path determination module comprises: A route set determination module, used to obtain a target starting point and a target end point in the route distribution map, and generate a route set from the target starting point to the target end point by using an ant algorithm; A route total score determination module is used to obtain the total transportation score corresponding to each route in the route distribution map, and calculate the route total score of each route in the route set; A line screening module, used for screening the line set according to the preset line total score to obtain a valid line set; The line generation module is used to generate lines for the effective line set by using a preset algorithm to obtain an optimal path.

9. A road transport information safety supervision system according to claim 8, characterized in that: The line generation module comprises: A target value calculation module, used to calculate the target value of each valid route in the valid route set; the target value includes a transportation value and a time value; A line classification module, used to determine the dominance relationship between every two valid lines according to the target value, and classify the lines according to the dominance relationship, wherein the lines of the first level are lines that are not dominated by other lines; The best path generation module is used to obtain all first-level routes and sort them from low to high according to the total score of the routes, and obtain the route with the lowest total score to obtain the best path.

10. A road transport information safety supervision system according to claim 6, characterized in that: The detection frequency determination module includes: A detection times ratio determination module is used to obtain the risk score corresponding to each section of the optimal path, and determine the detection times ratio corresponding to each section of the route according to the risk score corresponding to each section of the route; A current road section detection number determination module is used to obtain the driving environment of the target vehicle on the current road section and determine the detection number of the current road section according to the driving environment; The next road section detection frequency determination module is used to determine the detection frequency of the next road section according to the number of detections of the current road section and the ratio of the detection times.

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