Evaluation method, device, equipment and storage medium for clearing urban traffic congestion

Abstract

The present application provides an evaluation method, device, equipment and storage medium for clearing urban traffic congestion, which relates to the field of urban traffic management technology. The method includes: when an abnormal event occurs on a target road, obtaining the first vehicle flow data of the target road after the abnormal event occurs; calculating the congestion index of the target road according to the first vehicle flow data; obtaining the clearing rate of vehicles on the target road, and the second vehicle flow data of the associated road of the target road; adjusting the congestion index of the target road according to the clearing rate of vehicles on the target road and the second vehicle flow data of the associated road to obtain a target congestion index; generating a traffic adjustment plan for the target road according to the target congestion index. The technical effect of the present application is: effectively solving the complex traffic conditions caused by abnormal events.

Description

Technical Field

[0001] The present application relates to the field of urban traffic management technology, and in particular to an evaluation method, device, equipment and storage medium for clearing urban traffic congestion. Background Art

[0002] With the acceleration of urbanization and the rapid growth of motor vehicle ownership, urban traffic congestion is becoming increasingly serious, especially when abnormal events such as traffic accidents and road construction occur, the traffic situation often deteriorates sharply. How to accurately assess the impact of abnormal events on road traffic and take effective traffic regulation measures in a timely manner has become an important challenge facing urban traffic management departments.

[0003] At present, many cities have established traffic monitoring systems to assess road congestion by collecting real-time traffic flow data and formulate traffic regulation plans accordingly. This method can reflect the traffic conditions of roads to a certain extent and provide a reference for traffic management decisions. However, this method usually only focuses on the real-time data of the target road and lacks comprehensive consideration of the entire traffic network, resulting in the generated regulation plan being unable to effectively solve the complex traffic conditions caused by abnormal events. Summary of the invention

[0004] The present application provides an evaluation method, device, equipment and storage medium for clearing urban traffic congestion, which are used to effectively solve complex traffic conditions caused by abnormal events.

[0005] In a first aspect, the present application provides an evaluation method for clearing urban traffic congestion, the method comprising: when an abnormal event occurs on a target road, obtaining first vehicle flow data of the target road after the abnormal event occurs; calculating the congestion index of the target road based on the first vehicle flow data; obtaining the clearing rate of vehicles on the target road, and second vehicle flow data of an associated road of the target road; adjusting the congestion index of the target road based on the clearing rate of vehicles on the target road and the second vehicle flow data of the associated road to obtain a target congestion index; generating a traffic adjustment plan for the target road based on the target congestion index.

[0006] By adopting the above technical solution, by obtaining the first traffic flow data of the target road and calculating the congestion index, the direct impact of abnormal events on the target road can be quickly reflected. By introducing the vehicle clearance rate on the target road, the method can evaluate the road's own ability to alleviate congestion. At the same time, by obtaining the second traffic flow data of the associated road, the chain reaction of abnormal events on the surrounding road network is captured. By combining these factors to adjust the congestion index, the target congestion index obtained more accurately reflects the actual situation of the overall traffic network. Finally, based on this comprehensive and accurate target congestion index, a traffic adjustment plan is generated, so that the plan can more effectively cope with complex traffic conditions.

[0007] Optionally, the first vehicle flow data includes: the number of each type of vehicles and the average speed of each type of vehicles, and the calculating the congestion index of the target road according to the first vehicle flow data includes: substituting the number of each type of vehicles and the average speed of each type of vehicles into a preset formula to calculate the congestion index of the target road; wherein the preset formula is: Where CI is the congestion index of the target road, F i is the number of vehicles of the i-th category, ω i is the weight index of the i-th type of vehicle, v i is the average speed of the i-th type of vehicles, L is the actual number of available lanes on the target road, and C is the total vehicle carrying capacity of the target road.

[0008] By adopting the above technical solution, the solution can accurately measure the impact of different types of vehicles on traffic flow by multiplying the number of each type of vehicle by its corresponding weight index and dividing it by the average speed. At the same time, the sum of these influencing factors is divided by the actual number of available lanes and the total number of vehicles on the road, further considering the capacity characteristics of the road itself. This calculation method can not only reflect the changes in the number and speed of vehicles on the road, but also reflect the differentiated impact of different types of vehicles on traffic congestion, as well as the road's own traffic capacity. Therefore, the resulting congestion index can more accurately characterize the actual congestion level of the target road, providing a reliable data basis for the formulation of subsequent traffic regulation plans.

[0009] Optionally, the congestion index of the target road is adjusted according to the clearing rate of vehicles on the target road and the second traffic flow data of the associated road to obtain a target congestion index, including: determining an adjustment factor according to the clearing rate of vehicles on the target road and the second traffic flow data of the associated road; and adjusting the congestion index of the target road by the adjustment factor to obtain a target congestion index.

[0010] By adopting the above technical solution, the solution takes into account the vehicle clearance rate on the target road, which reflects the road's own ability to alleviate congestion; at the same time, it also incorporates the second vehicle flow data of the associated road, which reflects the impact of the surrounding road network on the traffic conditions of the target road. By combining these two key factors to determine the adjustment factor, the solution can capture the overall dynamic changes of the traffic network. Secondly, this adjustment factor is used to adjust the original congestion index, and the resulting target congestion index more comprehensively reflects the actual traffic conditions. This adjustment mechanism allows the evaluation results to not only consider the congestion level of the target road itself, but also cover the road's self-recovery ability and the impact of the surrounding road network, thereby providing a more accurate and dynamic assessment of traffic conditions.

[0011] Optionally, the calculation factor is determined based on the vehicle clearance rate on the target road and the second vehicle flow data of the associated road, including: determining the outflow of vehicles on the target road based on the vehicle clearance rate on the target road; determining the inflow of vehicles on the target road based on the second vehicle flow data of the associated road; calculating the net vehicle flow of the target road based on the outflow and the inflow; comparing the net vehicle flow with a set threshold, if the net vehicle flow is greater than the set threshold, setting the adjustment factor to a first preset value less than 1; if the net vehicle flow is less than the set threshold, setting the adjustment factor to a second preset value greater than 1.

[0012] By adopting the above technical solution, the outflow is determined by the dredging rate of the vehicles on the target road, and the inflow is calculated by using the second vehicle flow data of the associated road, so as to obtain the net vehicle flow of the target road. This calculation method comprehensively considers the input and output of the road and accurately reflects the actual traffic flow of the target road. Secondly, the scheme introduces a set threshold as a judgment criterion, and dynamically adjusts the adjustment factor by comparing the net vehicle flow with the threshold. When the net vehicle flow is greater than the set threshold, it means that the dredging capacity of the road is strong and the traffic conditions have improved. Therefore, the adjustment factor is set to a first preset value less than 1 to appropriately reduce the congestion index. On the contrary, when the net vehicle flow is less than the set threshold, it indicates that the road congestion may intensify. At this time, the adjustment factor is set to a second preset value greater than 1 to increase the congestion index. This threshold-based dynamic adjustment mechanism enables the evaluation results to reflect the changing trend of road traffic conditions in a timely manner, and improves the sensitivity and accuracy of the evaluation. At the same time, this method also provides a more refined and reliable decision-making basis for traffic management departments, which helps to formulate more targeted and effective traffic regulation measures.

[0013] Optionally, adjusting the congestion index of the target road by the adjustment factor to obtain a target congestion index includes: acquiring environmental factor data of the target road; correcting the adjustment factor according to the environmental factor data to obtain a target adjustment factor; arithmetically multiplying the target adjustment factor by the congestion index of the target road to obtain a target congestion index.

[0014] By adopting the above technical solution, the solution obtains the environmental factor data of the target road, which may include weather conditions, road conditions information, special events and other external factors that affect traffic flow. By considering these environmental factors, the various variables that affect road traffic conditions can be evaluated more comprehensively. Secondly, the original adjustment factor is corrected based on the environmental factor data to obtain the target adjustment factor. This step makes the adjustment process more refined and can better reflect the complexity of the actual traffic environment. Finally, the target adjustment factor is arithmetically multiplied by the congestion index of the target road to obtain the final target congestion index. This calculation method not only takes into account the traffic flow of the road itself and the influence of the surrounding road network, but also incorporates the role of environmental factors, thereby obtaining a more comprehensive and accurate congestion assessment result. This multi-dimensional assessment method significantly improves the accuracy and adaptability of traffic condition assessment, and can better cope with the complex and changing urban traffic environment.

[0015] Optionally, generating a traffic adjustment plan for the target road based on the target congestion index includes: determining a congestion level of the target road based on the target congestion index; selecting a corresponding adjustment strategy from an adjustment strategy library based on the congestion level; generating a traffic adjustment plan for the target road based on the adjustment strategy; wherein the traffic adjustment plan includes at least one or more of adjusting traffic signal timing plans, implementing vehicle restriction measures, suggesting vehicle detour routes, and increasing public transportation capacity.

[0016] By adopting the above technical solution, the solution determines the congestion level of the target road according to the calculated target congestion index. This step converts the continuous congestion index value into a discrete level, which is convenient for subsequent decision-making. Secondly, based on the determined congestion level, the corresponding adjustment strategy is selected from the pre-established adjustment strategy library. This method ensures the matching of the adjustment measures with the actual congestion level and improves the pertinence and effectiveness of traffic management. Finally, according to the selected adjustment strategy, a specific traffic adjustment plan is generated. By combining accurate traffic condition assessment with flexible and diverse adjustment measures, the scientificity, accuracy and effectiveness of urban traffic management are significantly improved, providing strong support for the realization of intelligent and efficient urban traffic management.

[0017] Optionally, after generating the traffic adjustment plan for the target road, it also includes: acquiring real-time traffic condition data of the target road; determining the execution effect of the traffic adjustment plan based on the real-time traffic condition data; if the execution effect does not meet the preset standard, adjusting the traffic adjustment plan to obtain an optimized traffic adjustment plan; sending the optimized traffic adjustment plan to the traffic management system for guiding the traffic management department to implement traffic control measures.

[0018] By adopting the above technical solutions, after the implementation of the traffic regulation plan, the real-time traffic condition data of the target road is continuously obtained, which ensures that the management system can keep abreast of the latest traffic dynamics. Secondly, by analyzing these real-time data, the solution can accurately evaluate the implementation effect of the traffic regulation plan, thereby quickly identifying the effectiveness of the current measures. When the implementation effect does not meet the preset standard, the solution will automatically trigger the adjustment mechanism and generate an optimized traffic regulation plan. This dynamic adjustment capability enables the traffic management system to flexibly respond to complex and changing traffic environments and continuously improve management efficiency. Finally, the optimized traffic regulation plan is sent to the traffic management system, providing the traffic management department with the latest and best control suggestions, which helps to implement more accurate and effective traffic control measures. This intelligent management model also reduces the workload of traffic management personnel and improves decision-making efficiency.

[0019] In a second aspect, the present application provides an evaluation device for clearing urban traffic congestion, the device comprising: a first acquisition module, a calculation module, a second acquisition module, an adjustment module and a generation module; wherein the first acquisition module is used to obtain, when an abnormal event occurs on a target road, first vehicle flow data of the target road after the abnormal event occurs; the calculation module is used to calculate the congestion index of the target road based on the first vehicle flow data; the second acquisition module is used to obtain the clearing rate of vehicles on the target road and second vehicle flow data of an associated road of the target road; the adjustment module is used to adjust the congestion index of the target road based on the clearing rate of vehicles on the target road and the second vehicle flow data of the associated road to obtain a target congestion index; the generation module is used to generate a traffic adjustment plan for the target road based on the target congestion index.

[0020] In the third aspect, the present application provides an electronic device, adopting the following technical solution: including a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a computer program such as any of the above-mentioned urban traffic congestion relief evaluation methods.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: a computer program that can be loaded by a processor and execute any of the above-mentioned evaluation methods for relieving urban traffic congestion is stored.

[0022] In summary, the present application includes at least one of the following beneficial technical effects: 1. By obtaining the first traffic flow data of the target road and calculating the congestion index, the direct impact of abnormal events on the target road can be quickly reflected. By introducing the vehicle clearance rate on the target road, the method can evaluate the road's own ability to alleviate congestion. At the same time, by obtaining the second traffic flow data of the associated road, the chain reaction of abnormal events on the surrounding road network is captured. By combining these factors to adjust the congestion index, the target congestion index obtained more accurately reflects the actual situation of the overall traffic network. Finally, based on this comprehensive and accurate target congestion index, a traffic adjustment plan is generated, so that the plan can more effectively cope with complex traffic conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flow chart of an evaluation method for clearing urban traffic congestion provided in an embodiment of the present application; Figure 2 It is a structural schematic diagram of an evaluation device for clearing urban traffic congestion provided by an embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0024] Description of reference numerals: 1000, electronic device; 1001, processor; 1002, communication bus; 1003, user interface; 1004, network interface; 1005, memory. DETAILED DESCRIPTION

[0025] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0026] In the description of the embodiments of the present application, words such as "illustrative", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "illustrative", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "illustrative", "for example" or "for example" is intended to present related concepts in a concrete way.

[0027] Figure 11 is a flow chart of an evaluation method for clearing urban traffic congestion provided by an embodiment of the present application. Figure 1 As shown, the method includes S101-S105: S101, when an abnormal event occurs on a target road, obtaining first vehicle flow data of the target road after the abnormal event occurs.

[0028] In one example, the first vehicle flow data can be obtained by various traffic monitoring devices deployed on the target road. These devices may include but are not limited to vehicle detectors, cameras, radar sensors, etc. These devices can capture vehicle information on the road in real time, including the number and average speed of various types of vehicles. In order to ensure the accuracy and comprehensiveness of the data, multiple monitoring points can be set at key nodes of the road, such as intersections, main roads, etc.

[0029] When an abnormal event (such as a traffic accident, road construction, or a large-scale event) occurs on a target road, the traffic management system will receive a report of the abnormal event. At this point, the system will immediately trigger the data collection program and begin collecting traffic flow data after the abnormal event. These data are usually collected and updated at certain time intervals (such as every 5 minutes or every 10 minutes) to reflect the dynamic changes in road traffic conditions.

[0030] The first vehicle flow data obtained mainly includes two key indicators: the number of vehicles of each type and the average speed of each type of vehicle. Vehicle types may include small private cars, buses, trucks and other types, and each type of vehicle has a different impact on road capacity and traffic flow. By distinguishing different types of vehicles, the actual use of the road can be more accurately assessed.

[0031] S102: Calculate the congestion index of the target road according to the first vehicle flow data.

[0032] In one example, the number of vehicles of each type and the average speed in the first vehicle flow data obtained in step S101 need to be substituted into the formula. Different weight indexes are assigned to different types of vehicles, which reflects the differentiated impact of different vehicle types on road capacity. For example, large trucks may be assigned a higher weight because they occupy more road space and may cause greater traffic obstruction.

[0033] The calculation process also needs to take into account the physical characteristics of the target road, including the actual number of available lanes and the total number of vehicles carried. These parameters are usually predetermined based on road design standards and actual conditions. After substituting all these data into the formula, a quantitative indicator reflecting the current road congestion level can be obtained - the congestion index.

[0034] The advantage of this calculation method is that it takes into account multiple influencing factors, including not only indicators that directly reflect traffic conditions such as traffic volume and speed, but also the capacity of the road itself and the impact of different types of vehicles. This allows the calculated congestion index to more comprehensively and accurately reflect the actual congestion situation of the road.

[0035] Based on the above embodiment, as an optional implementation, in S102, the first vehicle flow data includes: the number of each type of vehicles and the average speed of each type of vehicles. According to the first vehicle flow data, calculating the congestion index of the target road specifically includes: Substitute the number of each type of vehicles and the average speed of each type of vehicles into the preset formula to calculate the congestion index of the target road; the preset formula is: Where CI is the congestion index of the target road, F i is the number of vehicles of the i-th category, ω i is the weight index of the i-th type of vehicle, v i is the average speed of the i-th type of vehicles, L is the actual number of available lanes on the target road, and C is the total vehicle carrying capacity of the target road.

[0036] In one example, the design concept of the preset formula is to take into account the number of various types of vehicles on the road, the speed and the characteristics of the road itself, so as to obtain a more comprehensive and accurate congestion index. The numerator of this formula calculates the weighted occupancy of all vehicles on the road, while the denominator represents the overall capacity of the road.

[0037] When implementing this step, we first need to extract the number and average speed of each type of vehicle from the first traffic flow data. This data can be obtained in real time through various sensors and cameras installed on the road. Then, we need to assign a weight index ω to each type of vehicle. i This weight index reflects the impact of different types of vehicles on road congestion. For example, large trucks may be given a higher weight because they take up more road space and travel slower.

[0038] Next, substitute these data into the preset formula for calculation. During the calculation process, the system multiplies the number of each type of vehicle by its weight and then divides it by the average speed of the vehicle in that type, thus obtaining the contribution of each type of vehicle to road congestion. Add up the contributions of all types of vehicles to obtain the total congestion contribution. Finally, divide this total contribution by the overall capacity of the road (i.e. C×L) to obtain the final congestion index CI.

[0039] The formula consists of two parts, the numerator is in, F iis the number of vehicles of the i-th category, considering that the number of vehicles is the most direct factor reflecting the degree of road congestion. Different types of vehicles are calculated separately because they have different effects on traffic flow.

[0040] ω i is the weight index of the i-th type of vehicle. The weight is introduced to reflect the differentiated impact of different types of vehicles on traffic flow. For example, large vehicles occupy more space and have a greater impact on traffic flow, so they may be given a higher weight. This design allows the formula to more accurately reflect the actual traffic conditions.

[0041] v i is the average speed of the i-th type of vehicles. Speed ​​is an important indicator to measure the degree of traffic flow. i ×ω i ) divided by v i , which means that the lower the speed, the greater the contribution to congestion. This is consistent with the actual situation: for the same number of vehicles, the slower the driving speed, the more congested the road. Finally, the impact of all types of vehicles is accumulated to obtain the overall congestion of the road.

[0042] The denominator is C×L; where C is the total number of vehicles on the target road, which represents the theoretical maximum capacity of the road. Including it in the calculation makes the congestion index of roads of different sizes comparable.

[0043] L is the actual number of available lanes on the target road, and multiplying by the number of lanes is to further refine the calculation of road capacity. This takes into account the physical characteristics of the road, so that the index can more accurately reflect the actual usage of the road.

[0044] By combining multiple key factors, a comprehensive, accurate and practical road congestion assessment method is provided. It not only accurately reflects the current traffic conditions, but also provides a powerful decision support tool for traffic management, and is an important part of the intelligent transportation system.

[0045] S103, obtaining the clearing rate of vehicles on the target road and second vehicle flow data of roads associated with the target road.

[0046] In one example, the clearing rate: The clearing rate refers to the speed at which vehicles leave the target road. It reflects the ability of the road system to handle and evacuate traffic. Specifically: it indicates how many vehicles can leave the target road per unit time, which can be expressed in units such as "vehicles / hour" or "vehicles / minute". A high clearing rate means that the road can quickly evacuate vehicles, which helps to alleviate congestion; a low clearing rate means that it is difficult for vehicles to leave the road, which may lead to increased congestion.

[0047] Related roads: Related roads refer to roads that are directly connected to the target road in terms of traffic flow. This includes: branches or trunk roads directly connected to the target road, parallel roads that can divert or merge traffic on the target road, and roads that form important node connections with the target road in the traffic network. The traffic conditions of related roads will directly affect the changes in traffic flow on the target road.

[0048] Secondary vehicle flow data: Secondary vehicle flow data refers to traffic flow information collected from associated roads. These data include: the number of vehicles on the associated roads, the speed of vehicles, and possibly the distribution of vehicle types.

[0049] The purpose of obtaining the clearing rate of vehicles on the target road is to understand the dynamic changes of traffic flow. The clearing rate reflects the speed at which vehicles leave the target road, which is very important for evaluating the self-recovery ability of the road. In specific implementation, this data can be obtained by setting up vehicle counters and speed monitoring devices at the exit of the target road. These devices can record the number and speed of vehicles leaving the target road in real time, thereby calculating the average clearing rate.

[0050] At the same time, the second traffic flow data of the associated roads of the target road is obtained in order to consider the influence of the surrounding road network. Associated roads usually refer to roads that are directly connected to the target road or have a close relationship in traffic flow. The traffic conditions of these associated roads will directly affect the changes in the traffic flow of the target road. In specific implementation, the road network topology relationship in the traffic management system can be used to determine the associated roads related to the target road. Then, the real-time traffic flow data of these associated roads (such as cameras, vehicle detectors, etc.) is obtained through traffic monitoring equipment (such as cameras, vehicle detectors, etc.) on these associated roads, that is, the second traffic flow data.

[0051] S104, adjusting the congestion index of the target road according to the clearing rate of vehicles on the target road and the second vehicle flow data of the associated road to obtain a target congestion index.

[0052] In one example, the evacuation rate data obtained in step S103 and the second vehicle flow data of the associated road need to be substituted into the formula first. The evacuation rate directly reflects the self-recovery ability of the target road. A higher evacuation rate will reduce the adjusted congestion index because it indicates that the road has the ability to quickly evacuate vehicles. The average flow rate of the associated road reflects the potential impact of the surrounding road network on the target road. A higher average flow rate will increase the adjusted congestion index because it indicates that more vehicles may enter the target road.

[0053] The setting of weight coefficients has an important impact on the adjustment results. These coefficients can be determined based on historical data analysis and expert experience to reflect the relative importance of the clearing rate and the associated road flow to the target road traffic conditions. For example, in some cases, the clearing rate may be given more importance, while in other cases, the impact of the associated roads may be more concerned.

[0054] Based on the above embodiment, as an optional implementation, in S104, adjusting the congestion index of the target road according to the clearing rate of vehicles on the target road and the second vehicle flow data of the associated road, and obtaining the target congestion index specifically includes S41-S42: S41, determining an adjustment factor according to the clearing rate of vehicles on the target road and the second vehicle flow data of the associated road.

[0055] In one example, two key data need to be obtained first: the vehicle clearance rate on the target road and the second vehicle flow data of the associated road. The clearance rate reflects the traffic flow of the target road itself, which can be obtained by calculating the number of vehicles passing through a certain section of the road per unit time. This indicator directly reflects the road's traffic capacity and current congestion.

[0056] The second traffic flow data of the associated road provides information about the status of the surrounding traffic network. These data usually include information such as traffic flow, average speed, and vehicle type composition. The selection of associated roads should be based on their geographical location relationship with the target road and the correlation of traffic flow. For example, a road directly connected to the target road or a parallel road that can divert traffic from the target road can be selected.

[0057] The process of determining the adjustment factor requires comprehensive consideration of these two parts of data. Specifically, a basic adjustment factor can be set and then adjusted according to the target road's clearing rate. If the clearing rate is higher than expected, it means that the road is in good condition and the adjustment factor can be appropriately lowered; conversely, if the clearing rate is lower than expected, the adjustment factor needs to be increased to reflect more severe congestion.

[0058] Next, we need to consider the impact of the second traffic volume data of the associated road on the adjustment factor. If the traffic volume of the associated road is large, it means that the surrounding road network is also in a relatively congested state. At this time, the adjustment factor may need to be further increased to reflect the pressure of the entire traffic network. On the contrary, if the traffic volume of the associated road is small, the adjustment factor can be appropriately reduced, because it means there is room for diversion.

[0059] Based on the above embodiment, as an optional implementation, in S41, according to the clearing rate of vehicles on the target road and the second vehicle flow data of the associated road, determining the calculation factor specifically includes S401-S405: S401, determining the outflow of vehicles on the target road according to the clearing rate of vehicles on the target road.

[0060] In one example, it is first necessary to obtain the traffic flow rate data of vehicles on the target road. The traffic flow rate reflects the average speed of vehicles on the road and is an important indicator for measuring the degree of traffic flow. This data can be obtained through speed sensors installed on the road, camera recognition systems, or floating vehicle data. The purpose of obtaining traffic flow rate data is to understand the actual traffic conditions of the current road, so as to more accurately estimate the vehicle outflow of the road.

[0061] The process of determining the vehicle outflow needs to consider the relationship between the dredging rate and the outflow. Generally, there is a certain correlation between the dredging rate and the outflow. When the dredging rate is high, it means that the road is smooth and the number of vehicles that can flow out per unit time is also large. On the contrary, when the dredging rate is low, it means that the road may be congested and the number of vehicles flowing out per unit time will decrease accordingly.

[0062] In practical applications, it is also necessary to consider the physical characteristics of the road, such as the number of lanes, road width, etc. These factors will affect the relationship between the dredging rate and the outflow. For example, for a wide road with multiple lanes, the same dredging rate may result in a larger outflow.

[0063] In addition, it is also important to note that the relationship between the dredging rate and the outflow may be different under different traffic conditions. For example, when the traffic volume is small, the increase in the rate will directly lead to an increase in the outflow; but when it is close to saturation, the increase in the rate may not lead to a significant increase in the outflow. Therefore, in practical applications, it may be necessary to consider this relationship separately according to different traffic conditions.

[0064] S402: Determine the inflow of vehicles on the target road according to the second vehicle flow data of the associated road.

[0065] In one example, it is first necessary to determine the roads associated with the target road. These associated roads usually include branches directly connected to the target road, other roads at intersections, etc. Then, it is necessary to collect the second traffic flow data on these associated roads. The second traffic flow refers to the number of vehicles traveling on the associated roads but about to enter the target road. These data can be obtained in a variety of ways, such as vehicle detectors installed on the road, image analysis of traffic cameras, GPS navigation data, etc.

[0066] After acquiring the data, it is necessary to process and analyze the data. First, it is necessary to consider the degree of influence of each associated road on the target road. For example, the main road may have a greater impact than a small branch road. Second, it is necessary to consider the probability of a vehicle entering the target road from the associated road. This probability may be affected by many factors, such as road design, traffic control measures, historical traffic patterns, etc.

[0067] Based on these considerations, a weight coefficient can be set for each associated road to reflect its contribution to the inflow of the target road. Then, the second vehicle flow of each associated road is multiplied by the corresponding weight coefficient, and all the results are added together to obtain the estimated inflow of the target road.

[0068] S403, calculating the net vehicle flow of the target road according to the outflow and inflow.

[0069] S404, comparing the net vehicle flow with a set threshold, if the net vehicle flow is greater than the set threshold, setting the adjustment factor to a first preset value less than 1.

[0070] S405: If the net vehicle flow is less than the set threshold, the adjustment factor is set to a second preset value greater than 1.

[0071] S42, adjusting the congestion index of the target road by adjusting the factor to obtain a target congestion index.

[0072] In an example, we first need to identify the key adjustment factors that affect the degree of crowding. These factors may include, but are not limited to, weather conditions, special events, time factors, seasonal changes, etc. Each adjustment factor should be assigned a certain weight to reflect the intensity of its impact on the degree of crowding. Next, we need to establish an adjustment mechanism that combines the original crowding index with each adjustment factor. This mechanism should be able to adjust the original crowding index accordingly based on the status and weight of different adjustment factors.

[0073] In practical applications, the specific values ​​and weights of each adjustment factor need to be determined based on historical data and expert experience. This may require a lot of data analysis and model verification. At the same time, these adjustment factors and weights should be dynamically adjustable to adapt to changes in the urban traffic environment.

[0074] Based on the above embodiment, as an optional implementation, in S42, adjusting the congestion index of the target road by adjusting the factor to obtain the target congestion index specifically includes S421-S423: S421, obtaining environmental factor data of the target road.

[0075] S422, modifying the adjustment factor according to the environmental factor data to obtain a target adjustment factor.

[0076] In one example, weather conditions directly affect the driving conditions of vehicles on the target road, thereby indirectly affecting other adjustment factors. For example, rainy and snowy weather will reduce the friction coefficient of the road, causing vehicles to slow down, which in turn affects the road's capacity and congestion. Therefore, by making weather-related corrections to the adjustment factors, a target adjustment factor that is more in line with the actual situation can be obtained, thereby improving the accuracy and reliability of the entire traffic assessment system.

[0077] During the specific implementation process, it is necessary to first collect and analyze real-time weather data in the area where the target road is located. These data mainly include indicators such as precipitation, visibility, and wind speed. Next, it is necessary to establish a correlation between weather factors and adjustment factors. This correlation should be able to reflect the degree of influence of different weather conditions on vehicle driving conditions, and how this influence is converted into a correction to the adjustment factor.

[0078] For example, when encountering heavy rain, vehicles usually reduce their driving speed and increase the distance between vehicles, which will lead to a decrease in road capacity. In this case, the adjustment factor of the congestion index needs to be increased accordingly. Similarly, in foggy weather, due to reduced visibility, vehicles drive more cautiously, which will also lead to a decrease in road capacity, so the adjustment factor also needs to be adjusted appropriately.

[0079] In practical applications, historical data can be analyzed to determine the patterns of how different weather conditions affect vehicle driving conditions. Traffic management departments can develop a series of adjustment rules based on these patterns to automatically adjust the adjustment factors based on real-time weather data. These rules should be reviewed and updated regularly to ensure that they accurately reflect current traffic conditions and weather impacts.

[0080] S423, arithmetically multiplying the target adjustment factor by the congestion index of the target road to obtain a target congestion index.

[0081] S105: Generate a traffic adjustment plan for the target road according to the target congestion index.

[0082] In one example, it is first necessary to establish a preset congestion index threshold system to correspond different ranges of congestion index to different levels of traffic conditions. For example, the congestion index can be divided into levels such as light congestion (0.5-0.7), moderate congestion (0.7-0.9) and severe congestion (above 0.9). Then, a series of possible traffic regulation measures are preset for each level. These measures may include adjusting the timing of traffic lights, opening emergency lanes, implementing vehicle restrictions, and suggesting vehicle diversions.

[0083] In actual operation, the system will compare the target congestion index obtained in step S104 with the preset threshold to determine the current congestion level. Based on this level, the system will select an appropriate traffic adjustment plan from the preset measure library. For example, when the target congestion index is at a moderate congestion level, the system may recommend adjusting the traffic light timing to increase the travel time of the target road, and at the same time issue traffic warning information to the driver and recommend choosing an alternative route.

[0084] However, generating a traffic regulation plan is not just a simple match of the preset plan, but also requires consideration of other factors. These factors include but are not limited to: Time factors: Different time periods (such as morning and evening peaks, off-peak periods) may require different regulation strategies. Spatial factors: Consider the location and importance of the target road in the entire traffic network. Historical data: Refer to the measures taken in the past under similar circumstances and their effects. Special events: Special situations such as large-scale events, bad weather, etc. that may affect traffic.

[0085] A traffic adjustment plan for a target road is generated according to a target congestion index, including: determining a congestion level of the target road according to the target congestion index; selecting a corresponding adjustment strategy from an adjustment strategy library according to the congestion level; generating a traffic adjustment plan for the target road according to the adjustment strategy; wherein the traffic adjustment plan includes at least one or more of adjusting a traffic signal timing plan, implementing vehicle restriction measures, suggesting a detour route for vehicles, and increasing public transportation capacity.

[0086] In one example, the congestion level of the target road is determined based on the target congestion index. The purpose of this step is to convert the continuous congestion index value into discrete congestion levels to facilitate subsequent decision making. Congestion levels can be divided into multiple levels, such as mild congestion, moderate congestion, and severe congestion. The criteria for determining congestion levels should be based on the actual situation of the city and the traffic management goals, and need to be reviewed and adjusted regularly to adapt to changes in the urban traffic environment.

[0087] After determining the congestion level, select the corresponding regulation strategy from the regulation strategy library. The regulation strategy library is a pre-established strategy set that contains various traffic management measures for different congestion levels. This strategy library should be based on a large amount of historical data analysis and expert experience summary, which provides a scientific basis and standardized process for traffic management decision-making. When selecting an adjustment strategy, it is necessary to consider the characteristics of the target road, the surrounding road network conditions, time factors, etc., to ensure that the selected strategy can alleviate traffic congestion to the greatest extent.

[0088] According to the selected regulation strategy, a specific traffic regulation plan can be generated. This plan includes at least one or more of adjusting the traffic light timing plan, implementing vehicle restrictions, suggesting vehicle detour routes, and increasing public transportation capacity. For example, for mild congestion, the main approach may be to adjust the traffic light timing plan to improve road traffic efficiency by optimizing the signal cycle and phase difference. For moderate congestion, in addition to adjusting the signal light timing, it may also be necessary to suggest that some vehicles detour to disperse traffic flow. For severe congestion, more powerful measures may be needed, such as implementing vehicle restrictions or significantly increasing public transportation capacity.

[0089] When implementing the traffic light timing plan, the intelligent transportation system can be used to adjust the cycle and phase of the traffic lights in real time to adapt to the current traffic flow conditions. Vehicle restriction measures can be implemented to restrict certain vehicles from entering the target road during a specific period of time based on the last digit of the license plate or the type of vehicle. Suggested detour routes can provide drivers with real-time road condition information and detour suggestions through traffic broadcasts, navigation APP push, etc. Increasing public transportation capacity can be achieved by increasing bus trips, opening temporary special lines, etc.

[0090] After generating the traffic adjustment plan for the target road, it also includes: obtaining the real-time traffic condition data of the target road; determining the execution effect of the traffic adjustment plan based on the real-time traffic condition data; if the execution effect does not meet the preset standard, adjusting the traffic adjustment plan to obtain an optimized traffic adjustment plan; sending the optimized traffic adjustment plan to the traffic management system to guide the traffic management department to implement traffic control measures.

[0091] In one example, it is necessary to obtain real-time traffic status data of the target road. The importance of this step is that it provides the necessary basic data for evaluating the implementation effect of the traffic regulation plan. Real-time traffic status data can be obtained through a variety of channels, including road sensors, traffic cameras, vehicle GPS data, and floating vehicle data generated by mobile devices. These data should include key indicators such as traffic flow, speed, occupancy, etc., to fully reflect the actual operating conditions of the road. Data collection should be continuous and real-time to capture changes in traffic conditions in a timely manner.

[0092] After obtaining the data, determine the implementation effect of the traffic regulation plan based on the real-time traffic status data. The purpose of this step is to evaluate whether the implemented traffic regulation plan has achieved the expected effect. The evaluation methods can include comparing the changes in the congestion index before and after implementation, the degree of improvement in road capacity, and the change in average vehicle speed. In addition, qualitative indicators such as public feedback and satisfaction surveys can also be considered. The evaluation criteria should be clear and quantitative. For example, specific indicators such as the reduction in the congestion index and the percentage of improvement in traffic capacity can be set.

[0093] If the implementation effect does not meet the preset standards, the traffic regulation plan needs to be adjusted to obtain an optimized traffic regulation plan. The adjustment method can include strengthening certain existing measures, such as extending the restricted time or expanding the restricted area; or introducing new regulation measures, such as increasing public transportation capacity or opening up new detour routes. The adjustment process should be based on the analysis of the reasons for non-compliance, which may involve the judgment of traffic engineering experts and the assistance of decision support systems. The optimized plan should be more targeted to solve the specific problems currently faced.

[0094] Finally, the optimized traffic regulation plan is sent to the traffic management system to guide the traffic management department to implement traffic control measures. The traffic management system should be able to quickly receive and process new regulation plans and convert them into specific execution instructions. This may include updating traffic signal control parameters, issuing new traffic control information, dispatching additional public transportation resources, etc. The traffic management department should establish a rapid response mechanism to ensure that new regulation plans can be implemented quickly.

[0095] Based on the above method, the present application also discloses an evaluation device for clearing urban traffic congestion, such as Figure 2 As shown, Figure 2 It is a structural schematic diagram of an evaluation device for clearing urban traffic congestion provided in an embodiment of the present application, and the device includes: a first acquisition module, a calculation module, a second acquisition module, an adjustment module and a generation module; wherein the first acquisition module is used to obtain the first vehicle flow data of the target road after the abnormal event occurs on the target road; the calculation module is used to calculate the congestion index of the target road according to the first vehicle flow data; the second acquisition module is used to obtain the clearing rate of vehicles on the target road and the second vehicle flow data of the associated roads of the target road; the adjustment module is used to adjust the congestion index of the target road according to the clearing rate of vehicles on the target road and the second vehicle flow data of the associated roads to obtain the target congestion index; the generation module is used to generate a traffic adjustment plan for the target road according to the target congestion index.

[0096] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0097] See also Figure 3 , is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 3As shown, the electronic device 1000 may include: at least one processor 1001 , at least one network interface 1004 , a user interface 1003 , a memory 1005 , and at least one communication bus 1002 .

[0098] The communication bus 1002 is used to realize the connection and communication between these components.

[0099] The user interface 1003 may include a display screen (Display) and a camera (Camera), and the optional user interface 1003 may also include a standard wired interface and a wireless interface.

[0100] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0101] Among them, the processor 1001 may include one or more processing cores. The processor 1001 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 1005, and calling data stored in the memory 1005. Optionally, the processor 1001 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 1001 can integrate one or more combinations of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 1001, and it can be implemented separately through a chip.

[0102] Among them, the memory 1005 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 1005 includes a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 1005 may optionally be at least one storage device located away from the aforementioned processor 1001. As Figure 3 As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program of an evaluation method for clearing urban traffic congestion.

[0103] exist Figure 3 In the electronic device 1000 shown, the user interface 1003 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 1001 can be used to call an application program stored in the memory 1005 for an evaluation method for clearing urban traffic congestion. When executed by one or more processors, the electronic device executes one or more of the methods described in the above embodiments.

[0104] An electronic device readable storage medium stores instructions, which, when executed by one or more processors, enable the electronic device to execute one or more of the methods described in the above embodiments.

[0105] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0106] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0107] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0108] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0109] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0110] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0111] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure here, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure. The description and examples are only regarded as exemplary, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A method for evaluating urban traffic congestion relief, the method comprising: When an abnormal event occurs on a target road, obtaining first traffic flow data of the target road after the abnormal event occurs; Calculating a congestion index of the target road according to the first traffic flow data; Acquire the clearing rate of vehicles on the target road and second vehicle flow data of a road associated with the target road; According to the clearing rate of vehicles on the target road and the second vehicle flow data of the associated road, adjusting the congestion index of the target road to obtain a target congestion index; A traffic regulation plan for the target road is generated according to the target congestion index.

2. The method for evaluating the easing of urban traffic congestion according to claim 1, characterized in that: The first traffic flow data includes: the number of each type of vehicles and the average speed of each type of vehicles. The calculation of the congestion index of the target road according to the first traffic flow data includes: Substituting the number of each type of vehicles and the average speed of each type of vehicles into a preset formula, the congestion index of the target road is calculated; wherein, The preset formula is: Where CI is the congestion index of the target road, F i is the number of vehicles of the i-th category, ω i is the weight index of the i-th type of vehicle, v i is the average speed of the i-th type of vehicles, L is the actual number of available lanes on the target road, and C is the total vehicle carrying capacity of the target road.

3. The method for evaluating the easing of urban traffic congestion according to claim 1, characterized in that: The step of adjusting the congestion index of the target road according to the clearing rate of vehicles on the target road and the second vehicle flow data of the associated road to obtain a target congestion index includes: Determining an adjustment factor according to a clearing rate of vehicles on the target road and second vehicle flow data of the associated road; The congestion index of the target road is adjusted by the adjustment factor to obtain a target congestion index.

4. The method for evaluating the easing of urban traffic congestion according to claim 3, characterized in that: The determining of the calculation factor according to the clearing rate of vehicles on the target road and the second vehicle flow data of the associated road includes: Determining the outflow of vehicles on the target road according to the clearing rate of vehicles on the target road; Determining the inflow of vehicles on the target road according to the second vehicle flow data of the associated road; Calculating the net vehicle flow of the target road according to the outflow and the inflow; comparing the net vehicle flow with a set threshold, and if the net vehicle flow is greater than the set threshold, setting the adjustment factor to a first preset value less than 1; If the net vehicle flow is less than the set threshold, the adjustment factor is set to a second preset value greater than 1.

5. The method for evaluating the easing of urban traffic congestion according to claim 3, characterized in that: The step of adjusting the congestion index of the target road by using the adjustment factor to obtain a target congestion index includes: Acquiring environmental factor data of the target road; According to the environmental factor data, the adjustment factor is modified to obtain a target adjustment factor; The target adjustment factor is arithmetically multiplied by the congestion index of the target road to obtain a target congestion index.

6. The method for evaluating the easing of urban traffic congestion according to claim 1, characterized in that: The step of generating a traffic adjustment plan for the target road according to the target congestion index includes: Determining the congestion level of the target road according to the target congestion index; According to the congestion level, selecting a corresponding adjustment strategy from an adjustment strategy library; A traffic adjustment plan for the target road is generated according to the adjustment strategy; wherein the traffic adjustment plan includes at least one or more of adjusting the traffic light timing plan, implementing vehicle restriction measures, suggesting vehicle detour routes, and increasing public transportation capacity.

7. The method for evaluating the easing of urban traffic congestion according to claim 1, characterized in that: After generating the traffic regulation scheme for the target road, the method further includes: Acquiring real-time traffic condition data of the target road; Determining the execution effect of the traffic regulation scheme according to the real-time traffic condition data; If the execution effect does not meet the preset standard, the traffic regulation plan is adjusted to obtain an optimized traffic regulation plan; the optimized traffic regulation plan is sent to the traffic management system to guide the traffic management department to implement traffic control measures.

8. An evaluation device for clearing urban traffic congestion, characterized in that: The device comprises: a first acquisition module, a calculation module, a second acquisition module, an adjustment module and a generation module; wherein, The first acquisition module is used to acquire first vehicle flow data of the target road after an abnormal event occurs on the target road; The calculation module is used to calculate the congestion index of the target road according to the first vehicle flow data; The second acquisition module is used to acquire the clearing rate of vehicles on the target road and second vehicle flow data of roads associated with the target road; The adjustment module is used to adjust the congestion index of the target road according to the clearing rate of vehicles on the target road and the second vehicle flow data of the associated road to obtain a target congestion index; The generating module is used to generate a traffic regulation plan for the target road according to the target congestion index.

9. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 7.

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