A road waterlogging identification method and device, electronic equipment and storage medium

Abstract

The application discloses a road waterlogging identification method and device, electronic equipment and a storage medium, and relates to the field of urban road waterlogging monitoring. The method comprises the following steps: monitoring the rainfall of a plurality of candidate areas in real time, and regarding the candidate area with rainfall exceeding a preset rainfall threshold as a target area, and selecting a to-be-monitored road section from a plurality of initial road sections included in the target area; determining a current average vehicle speed and a current road section flow according to real-time vehicle driving track data of the to-be-monitored road section in a plurality of current time windows in a current period, and determining a candidate road section with waterlogging hidden dangers from the to-be-monitored road section; determining a waterlogging road section from the candidate road section according to an upstream average vehicle speed and an upstream road section flow of an upstream road section corresponding to the candidate road section in the current time window, and a historical average vehicle speed and a historical road section flow of the candidate road section in a historical same-period time window, and generating waterlogging alarm information for the waterlogging road section. The above technical solution improves the accuracy of waterlogging road section identification.

Description

Technical Field

[0001] This application relates to the field of computer technology, and more particularly to the field of urban road waterlogging monitoring, specifically to a road waterlogging identification method, device, electronic device, and storage medium. Background Technology

[0002] In recent years, the combined effects of global climate change and accelerated urbanization have led to frequent extreme weather events such as torrential rains. Urban overpasses, culverts, tunnels, and low-lying road sections are prone to flooding, seriously threatening traffic safety and the safety of people's lives and property. Against the backdrop of building smart and resilient cities, urban management is shifting from passive emergency response to proactive perception and precise early warning.

[0003] Existing technologies for monitoring road flooding mainly fall into three categories: physical monitoring technology based on IoT sensors, which involves installing electronic water level gauges, ultrasonic level gauges, or hydrostatic water level sensors at known flood-prone areas (such as underpasses and drainage outlets). This technology can acquire high-precision data on flood depth in real time and automatically trigger an alarm when the water level exceeds a threshold; computer vision technology based on video surveillance, which uses urban security monitoring or traffic checkpoint cameras and artificial intelligence image recognition algorithms (detecting water surface ripples, water level gauge markings, or vehicle wading posture) to determine whether the road surface is flooded; and indirect inference technology based on traffic big data, which infers the likelihood of flooding in road sections based on the causes or effects of flooding, using vehicle speed and traffic flow data, combined with Bayesian probability models or historical congestion patterns to infer the probability of flooding.

[0004] However, existing technologies still suffer from insufficient accuracy in identifying road flooding, making it difficult to accurately determine the extent of road flooding. Summary of the Invention

[0005] This application provides a method, apparatus, electronic device, and storage medium for identifying road flooding, which improves the accuracy of identifying flooded road sections.

[0006] According to one aspect of this application, a method for identifying road flooding is provided, comprising: The system monitors rainfall in multiple candidate areas in real time, and selects candidate areas with rainfall exceeding a preset precipitation threshold as target areas. It also selects road segments to be monitored from multiple initial road segments included in the target areas. Based on the real-time vehicle trajectory data of the monitored road segment in multiple current time windows within the current period, the current average vehicle speed and current road segment traffic flow in the current time window are determined, and based on the current average vehicle speed and current road segment traffic flow, candidate road segments with potential water accumulation hazards are identified from the monitored road segments. Based on the upstream average vehicle speed and upstream traffic flow of the candidate road segment in the current time window, as well as the historical average vehicle speed and historical traffic flow of the candidate road segment in the same historical time window, waterlogged road segments are identified from the candidate road segments, and waterlogging alarm information is generated for the waterlogged road segments.

[0007] According to another aspect of this application, a road waterlogging identification device is provided, comprising: The monitoring section determination module is used to monitor the rainfall of multiple candidate areas in real time, and to select the candidate areas whose rainfall exceeds the preset precipitation threshold as target areas, and to select the monitoring section from multiple initial road sections included in the target area. The module for determining candidate road sections with potential water accumulation hazards is used to determine the current average vehicle speed and current road section traffic flow in the current time window based on the real-time vehicle driving trajectory data of the road section to be monitored in multiple current time windows within the current period, and to determine candidate road sections with potential water accumulation hazards from the road sections to be monitored based on the current average vehicle speed and current road section traffic flow. The waterlogged road section determination module is used to determine the waterlogged road section from the candidate road sections based on the upstream average vehicle speed and upstream traffic flow of the corresponding upstream road section in the current time window, as well as the historical average vehicle speed and historical traffic flow of the candidate road section in the same historical time window, and generate waterlogging alarm information for the waterlogged road section.

[0008] According to another aspect of this application, an electronic device is provided, the electronic device comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the road flooding identification method according to any embodiment of this application.

[0009] According to another aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the road flooding identification method according to any embodiment of this application.

[0010] According to another aspect of this application, a computer program product is provided, which includes a computer program that, when executed by a processor, implements any of the road flooding identification methods provided in the embodiments of this application.

[0011] The technical solution of this application embodiment monitors rainfall in real time in various candidate areas, filters target areas based on rainfall, and determines road segments to be monitored. It calculates the current average vehicle speed and current traffic flow using real-time vehicle trajectory data from multiple current time windows within the current period for each monitored road segment, initially screening out candidate road segments potentially prone to flooding. By combining the upstream average vehicle speed and traffic flow of the candidate road segments within the current time window, as well as the historical average vehicle speed and historical traffic flow of the candidate road segments in the same historical time window, a comprehensive analysis of the candidate road segments is performed, ultimately identifying flooded road segments and generating flooding alarm information. This method solves the problems of traditional methods, such as the inability to timely and accurately identify road flooding risks and the susceptibility to misjudgments. It utilizes continuous real-time traffic data, historical traffic data, and upstream traffic data to jointly evaluate the operational status of candidate road segments, thereby accurately identifying flooded road segments and generating early warning information in real time. This provides a reliable decision-making basis for urban road management and assists in traffic control.

[0012] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0013] Figure 1 This is a flowchart of a road water accumulation identification method according to Embodiment 1 of this application; Figure 2 This is a flowchart of another road water accumulation identification method provided according to Embodiment 2 of this application; Figure 3 This is a schematic diagram of a road water accumulation identification device according to Embodiment 3 of this application; Figure 4 This is a schematic diagram of the structure of an electronic device that implements the road water accumulation identification method of the present application. Detailed Implementation

[0014] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0015] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0016] Example 1 Figure 1 This is a flowchart of a road flooding identification method according to Embodiment 1 of this application. This embodiment is applicable to scenarios where urban road flooding is monitored and accurately identified in real time under extreme weather conditions such as heavy rain. The method can be executed by a road flooding identification device, which can be implemented in hardware and / or software and can be configured in a computer device. Figure 1 As shown, the method includes: S101. Monitor the rainfall in multiple candidate areas in real time, and select the candidate areas whose rainfall exceeds the preset precipitation threshold as target areas, and select the road segment to be monitored from the multiple initial road segments included in the target area.

[0017] In this embodiment, candidate areas are determined by dividing the urban road network into square spatial grids of a preset size, with each grid serving as a candidate area. Simultaneously, radar echo rainfall data acquired from weather stations is mapped to each candidate area, matching a corresponding real-time rainfall amount to each area. The target area refers to the region identified as having a risk of road flooding after filtering based on rainfall conditions from all candidate areas, thus narrowing the scope of subsequent analysis. The initial road segments refer to all road segments located within the target area. The road segments to be monitored refer to those further identified based on the initial road segments and preset filtering rules, aiming to improve the targeting and efficiency of road flooding monitoring.

[0018] Specifically, in urban road flooding monitoring scenarios, real-time rainfall is monitored in multiple pre-defined candidate areas. When rainfall exceeds a preset threshold, the corresponding candidate area is designated as the target area. Then, road segments to be monitored are selected from multiple initial road segments covered by the target area, achieving a step-by-step focusing and selection from area to road segment. This method dynamically determines the target area to be monitored based on real-time meteorological data and selects the road segments to be monitored accordingly. This approach effectively avoids indiscriminate monitoring of all road segments, reduces data processing and resource consumption, and increases attention to high-risk road segments, thereby improving the targeting and response efficiency of road flooding monitoring.

[0019] S102. Based on the real-time vehicle trajectory data of the road segment to be monitored in multiple current time windows within the current period, determine the current average vehicle speed and current road segment traffic flow in the current time window, and based on the current average vehicle speed and current road segment traffic flow, determine candidate road segments with potential water accumulation hazards from the road segments to be monitored.

[0020] In this embodiment, the current period can be understood as a complete monitoring and analysis time period, which is the overall time range used to determine the risk of road flooding. Within the current period, real-time vehicle trajectory data is continuously collected to provide continuous reference data for subsequent assessment of flooding hazards. The current period can be a few minutes, tens of minutes, or several hours, depending on the monitoring frequency and road conditions. The current time window is a further subdivision of the current period into smaller time segments. Data within each current time window is used to calculate more refined indicator data, such as average vehicle speed and traffic flow. By dividing the current period into multiple current time windows, changes in road operating conditions can be quantified, and short-term traffic anomalies in certain road segments can be detected in a timely manner.

[0021] Real-time vehicle trajectory data refers to real-time data collected from taxi, ride-hailing, or navigation software user terminals, including vehicle trajectories, speeds, timestamps, and location information. Current average speed refers to the average speed calculated statistically from the speeds of all vehicles on the monitored road segment within the current time window. Current road segment traffic flow refers to the number of vehicles passing through the monitored road segment within the current time window, used to characterize the traffic situation of that segment. Candidate road segments are those determined based on the analysis of current average speed and current road segment traffic flow. When vehicles are stopped or nearly stationary and traffic flow is significantly reduced or nonexistent, it indicates that the road segment may be obstructed due to water accumulation, and thus is identified as a candidate road segment with potential water accumulation risks.

[0022] Specifically, by processing real-time vehicle trajectory data collected from multiple consecutive time windows within the current period for the monitored road segment, the current average vehicle speed and current traffic flow for each current time window are calculated. Based on the current average vehicle speed and current traffic flow, the monitored road segment is evaluated to identify candidate road segments that may have potential flooding risks. This method can dynamically reflect the road segment's operational status based on continuous real-time traffic data, initially screening out candidate road segments that may experience flooding interruptions, providing a basis for subsequent detailed analysis and the identification of flooded road segments.

[0023] S103. Based on the upstream average vehicle speed and upstream traffic flow of the candidate road segment in the current time window, and the historical average vehicle speed and historical traffic flow of the candidate road segment in the same historical time window, determine the waterlogged road segment from the candidate road segment, and generate waterlogging alarm information for the waterlogged road segment.

[0024] In this embodiment, the upstream road segment refers to the road segment that a vehicle passes through before reaching the candidate road segment and is directly adjacent to the candidate road segment. The operational status of the upstream road segment can help determine the potential flooding risk of the candidate road segment. The upstream average vehicle speed and upstream road segment flow rate refer to the average driving speed and number of vehicles passing through the upstream road segment corresponding to the candidate road segment within the current time window, used to reflect the upstream traffic operation status. The historical same-period time window refers to the historical observation period corresponding to the current time window, such as records within the same time period of the previous day or week, used to compare the historical traffic operation status of the candidate road segment, thereby determining whether the current traffic anomaly may be caused by flooding. The historical average vehicle speed and historical road segment flow rate are calculated from the data within the historical same-period time window corresponding to the current time window. The flooded road segment refers to the road segment that, after analyzing the traffic data of the candidate road segment in the current time window and the historical same-period time window, and combining it with the traffic data of the upstream segment, is ultimately determined to have potential flooding and affect traffic. This road segment will be used as a warning target to generate alarm information.

[0025] Specifically, by acquiring the average vehicle speed and traffic flow of the upstream road segment corresponding to the candidate road segment in the current time window, and combining this with the historical average vehicle speed and historical traffic flow of the candidate road segment in the same historical time window, the operational status of the candidate road segment is comprehensively analyzed to identify road segments experiencing water accumulation and generate water accumulation alarm information for these road segments. This method, by comprehensively analyzing the traffic operation status of the candidate road segment in the current time window, the traffic operation status of its upstream road segment, and the operational data of the candidate road segment in the same historical time window, can eliminate misjudgments caused by upstream traffic interruptions or historical traffic interruptions, such as chronic congestion due to poor visibility in rainy weather or traffic interruptions due to road construction. This allows for accurate identification of road segment interruptions caused by water accumulation, enabling timely and accurate judgment and early warning of waterlogged road segments. It provides reliable decision-making basis for urban road management and helps guide the implementation of traffic control and safety protection measures.

[0026] The technical solution of this application embodiment monitors rainfall in real time in various candidate areas, filters target areas based on rainfall, and determines road segments to be monitored. It calculates the current average vehicle speed and current traffic flow using real-time vehicle trajectory data from multiple current time windows within the current period for each monitored road segment, initially screening out candidate road segments potentially prone to flooding. By combining the upstream average vehicle speed and traffic flow of the candidate road segments within the current time window, as well as the historical average vehicle speed and historical traffic flow of the candidate road segments in the same historical time window, a comprehensive analysis of the candidate road segments is performed, ultimately identifying flooded road segments and generating flooding alarm information. This method solves the problems of traditional methods, such as the inability to accurately and timely identify road flooding risks and the susceptibility to misjudgments. It utilizes continuous real-time traffic data, historical traffic data, and upstream traffic data to jointly evaluate the operational status of candidate road segments, thereby accurately identifying flooded road segments and generating early warning information. This provides a reliable decision-making basis for urban road management and assists in traffic control.

[0027] Example 2 Figure 2 This is a flowchart of another road waterlogging identification method provided in Embodiment 2 of this application. The technical solution of this embodiment further refines the method for determining waterlogged road sections based on the technical solution of the above embodiments. Figure 2 As shown, the method includes: S201. Monitor the rainfall in multiple candidate areas in real time, and select the candidate areas whose rainfall exceeds the preset precipitation threshold as target areas, and select the road segment to be monitored from multiple initial road segments included in the target area.

[0028] S202. Based on the real-time vehicle trajectory data of the road segment to be monitored in multiple current time windows within the current period, determine the current average vehicle speed and current road segment traffic flow in the current time window, and based on the current average vehicle speed and current road segment traffic flow, determine candidate road segments with potential water accumulation hazards from the road segments to be monitored.

[0029] S203. If the average speed of the upstream road segment corresponding to the candidate road segment is greater than a preset speed threshold for a consecutive preset number of current time windows, and the traffic flow of the upstream road segment is greater than a preset traffic flow threshold, then the candidate road segment is determined to meet the traffic conditions of the upstream road segment.

[0030] S204. If the historical average vehicle speed of the candidate road segment in the same historical time window is greater than the preset vehicle speed threshold, and the historical traffic flow of the road segment is greater than the preset traffic flow threshold, then the candidate road segment is determined to meet the historical window passage conditions.

[0031] S205. The candidate road segment that simultaneously meets the upstream road segment traffic conditions and the historical window traffic conditions shall be designated as the waterlogged road segment.

[0032] In this embodiment, by setting a continuous preset value as the observation period, the stability and continuity of the data are ensured, eliminating misjudgments caused by sudden temporary congestion, thereby improving the accuracy of water accumulation identification. For example, three consecutive current time windows. The vehicle speed threshold is used to determine the activity level of vehicles in the road segment. If the average vehicle speed is lower than the preset vehicle speed threshold, it is considered as traffic stagnation, and vehicles in the road segment are almost stationary or not moving. The flow rate threshold is used to determine the vehicle traffic status of the road segment. If the flow rate of the road segment is lower than the preset flow rate threshold, it indicates that no vehicles are actually passing through the road segment. The preset vehicle speed threshold and the preset flow rate threshold are usually set to zero.

[0033] Upstream traffic conditions are used to eliminate the impact of traffic flow interruptions on candidate road segments. If the upstream road segment of a candidate road segment maintains its speed and flow rates above zero for multiple consecutive current time windows, it indicates that the upstream road segment is operating normally and traffic flow can be stably delivered to the candidate road segment. In this case, the chain reaction caused by upstream congestion or road closures can be effectively eliminated, and the road segment where the road interruption has occurred can be identified.

[0034] Historical window traffic conditions are used to compare the historical average vehicle speed and historical traffic flow of the same time window in the same period of the previous week (such as the same day last week) to confirm that the candidate road segment has normal traffic capacity under the same historical conditions. This method can eliminate interference from non-flooding factors such as long-term construction, permanent road changes, or seasonal traffic restrictions, ensuring that the identified flooding events are genuine.

[0035] Specifically, by analyzing the average vehicle speed and traffic flow of the upstream road segment within a consecutive preset number of current time windows for the candidate road segment, when the average vehicle speed and traffic flow of the upstream road segment remain consistently greater than the preset speed threshold and the preset traffic flow threshold, it indicates that the upstream traffic is smooth and can stably transport vehicles to the candidate road segment, thus eliminating the possibility of current road segment interruption caused by upstream traffic interruption or road closure. At the same time, by comparing the candidate road segment with the historical average vehicle speed and historical traffic flow of the same time window in the same period of history, when the historical average vehicle speed and historical traffic flow of the candidate road segment remain consistently greater than the preset speed threshold and the preset traffic flow threshold in the same period of history, it indicates that the candidate road segment has normal traffic capacity in the same period of history, thus eliminating the interference of non-water accumulation factors such as long-term construction, permanent road changes or seasonal traffic restrictions. The candidate road segment that simultaneously meets the upstream road segment traffic conditions and the historical window traffic conditions is finally determined as the water accumulation road segment. This method effectively improves the accuracy and reliability of identifying waterlogged road sections through dual spatial and temporal verification, enabling timely early warning of waterlogged road sections, providing accurate decision-making basis for urban road management, and supporting the implementation of traffic control and safety protection measures.

[0036] S206. Generate water accumulation alarm information for the waterlogged road section.

[0037] The technical solution of this embodiment further refines the method for determining waterlogged road sections. By comprehensively analyzing the upstream average vehicle speed and traffic flow of the upstream road section corresponding to the candidate road section, and combining the historical average vehicle speed and historical traffic flow of the candidate road section corresponding to the same historical time window, the candidate road section is subjected to a comprehensive spatial and temporal dual verification, and road sections with real waterlogging risk are screened out. This solves the problem of misjudgment caused by upstream road interruption and historical traffic anomalies in traditional methods, and can accurately identify waterlogged road sections, realize timely early warning, and provide a reliable decision-making basis for urban road management and traffic control.

[0038] In one optional implementation, determining candidate road segments with potential water accumulation hazards from the monitored road segments based on the current average vehicle speed and current road segment traffic flow includes: if the current average vehicle speed of the monitored road segment is less than or equal to a preset vehicle speed threshold within a consecutive preset number of current time windows, and the current road segment traffic flow is less than or equal to a preset traffic flow threshold, then the monitored road segment is determined to meet the current road segment traffic interruption condition; the monitored road segments that meet the current road segment traffic interruption condition are designated as candidate road segments with potential water accumulation hazards.

[0039] In this embodiment, the current road segment interruption condition is used to initially determine whether the monitored road segment is experiencing a traffic interruption within the current period. Specifically, if the current average vehicle speed and current traffic flow of the monitored road segment are consistently less than or equal to preset vehicle speed thresholds and preset traffic flow thresholds within a consecutive preset number of time windows, then the monitored road segment is determined to meet the current road segment interruption condition and is identified as a candidate road segment with potential water accumulation risks. This method, by introducing the constraint of continuous time windows to filter short-term data fluctuations, can reliably identify road segments with continuous abnormal traffic interruptions, providing a reliable basis for further distinguishing the impact of water accumulation from other interference factors and improving the effectiveness of candidate road segment selection.

[0040] In one optional implementation, selecting the road segment to be monitored from the plurality of initial road segments included in the target area includes: matching the plurality of initial road segments included in the target area with the water accumulation hazard road segments in a preset water accumulation hazard road segment database, and taking the successfully matched initial road segments as the road segments to be monitored; wherein, the water accumulation hazard road segment database is predetermined based on road geographic information data.

[0041] In this embodiment, the flood-prone road segment database is pre-determined based on road geographic information data and includes multiple road segments with flood-prone risks. This database is used to screen initial road segments within the target area during monitoring. For example, each road segment in the database includes roads with potential flood-prone characteristics such as low-lying terrain, weak drainage capacity, or a history of flooding. These roads can be classified according to the degree of flood risk, and corresponding flood risk coefficients can be assigned to different risk levels, thus providing a basis for subsequent flood risk classification and early warning. Specifically, multiple initial road segments within the target area are matched one by one with the pre-constructed flood-prone road segment database, and the flood-prone road segments corresponding to those in the database are selected as the road segments to be monitored. This method enables rapid screening of road segments with flood risk after rainfall exceeds a preset threshold, avoiding monitoring irrelevant road segments, achieving pre-screening and precise limitation of monitoring targets, thereby improving the targeting of subsequent flood identification.

[0042] In one optional embodiment, the method further includes determining the road sections with potential water accumulation hazards by: acquiring road geographic information data; wherein the road geographic information data includes ground elevation information, road section name, and road section type; calculating the relative elevation of each road section based on the ground elevation information; identifying water accumulation hazards in each road section according to the corresponding road section name, road section type, and the relative elevation, and obtaining identification results; the identification results include road sections with high water accumulation hazards and road sections with regular water accumulation hazards.

[0043] In this embodiment, road geographic information data includes, but is not limited to, ground elevation information, road segment names, and road segment types. Ground elevation information refers to the numerical value of the road's location relative to a reference surface, reflecting the road's elevation distribution in geographic space and serving as a basis for determining whether a road is located in a low-lying area. The reference surface can be mean sea level or an elevation reference surface. Road segment names and types characterize the road's topographical features and engineering structural attributes, supplementing information on the road's low-lying status and drainage capacity. For example, road segment names containing terms like "under a bridge," "tunnel," or "underpass" typically correspond to road segments with lower elevations than the surrounding area. Road segment types such as underground passages, underpasses, or auxiliary roads under interchanges typically correspond to road segments with water catchment characteristics and greater drainage difficulties, making them more prone to water accumulation. Relative elevation information indicates the elevation difference of each road segment relative to its surrounding area or other road segments within a reference range, characterizing the relative elevation relationship of roads and thus identifying low-lying road segments that may be at risk of water accumulation. The identification results, based on information such as road segment name, road segment type, and relative elevation, are obtained by analyzing each road segment to determine the degree of water accumulation hazard. This is used to distinguish the degree of water accumulation hazard in different road segments, including high-risk and moderate-risk segments. High-risk segments are those with lower relative elevations, determined to be more prone to water accumulation and having a higher risk of water accumulation after considering segment attribute analysis. Moderate-risk segments are those with a relatively lower risk of water accumulation compared to high-risk segments, but still possess a certain possibility of water accumulation.

[0044] Specifically, by acquiring road geographic information data including ground elevation, road segment name, and road segment type, the ground elevation information of each road segment is processed to calculate the relative elevation. Combined with the road segment name and type, a comprehensive analysis is performed on each road segment to identify road segments with different levels of water accumulation risk and generate identification results. This method, through comprehensive analysis of road elevation distribution and road attribute characteristics, enables the early identification of potentially waterlogged road segments, effectively distinguishing between high-risk and conventional water accumulation road segments, and providing a basis for subsequently determining road segments to be monitored.

[0045] In one optional implementation, the flooded road section includes road sections with high flood risk and road sections with regular flood risk; generating flood alarm information for the flooded road section includes: determining the warning level of the flooded road section based on the correlation between a preset warning level and a flood risk coefficient range, and the flood risk coefficient of the flooded road section; wherein the flood risk coefficient of the road section with high flood risk is greater than the flood risk coefficient of the road section with regular flood risk; and generating alarm information for the flooded road section based on the warning level.

[0046] In this embodiment, the warning level is a grading index used to characterize the warning methods corresponding to different severity levels of road flooding risk. It classifies the handling methods for road sections with different flooding risk coefficients into several levels to guide corresponding handling measures. For example, when a flooded road section is a high-risk flooding section with a high flooding risk coefficient, a red warning may be issued, indicating the need for emergency drainage or traffic control measures. When a flooded road section is a normal-risk flooding section with a low flooding risk coefficient, a yellow warning may be issued, indicating close monitoring and necessary protective measures. The high-risk flooding coefficient is greater than the low-risk flooding coefficient. The flooding risk coefficient is a comprehensive indicator used to quantify the degree of road flooding risk. It is determined based on factors such as ground elevation information, road section name, and road section type in road geographic information data, and reflects the probability and severity of flooding in different road sections. The flooding risk coefficient for high-risk flooding sections is greater than that for normal-risk flooding sections.

[0047] Specifically, based on the pre-defined correspondence between warning levels and waterlogging risk coefficient ranges, the system matches the corresponding warning level to the waterlogging risk coefficient of each waterlogged road section. Simultaneously, it generates corresponding alarm information based on the determined warning level to indicate different levels of response measures. This method, by pre-setting graded warnings for waterlogging risks, achieves a shift from single identification to layered warnings, enabling alarm information to reflect differences in waterlogging risk levels. This improves the guidance of warning results and facilitates urban management departments in taking different response measures according to different risk levels.

[0048] In this embodiment, the preset implementation conditions are: 1. Precipitation data is authentic and reliable, with no obvious missing or abnormal conditions; 2. Road traffic operation monitoring is normal and supports historical backtracking; 3. The geographic information data of the entire road network is accurate and reliable. Taking the area of ​​heavy rainfall during a rainstorm in a certain city on August 12, 2025 as the monitoring object, the method proposed in this application will be described.

[0049] Step 1: Monitor the rainfall in each candidate area of ​​the city in real time, with each area as a 5km×5km monitoring unit. If the rainfall in candidate area GX-0524 exceeds the preset rainfall threshold, activate the water accumulation monitoring mode for this candidate area, and then designate this candidate area as the target area.

[0050] Step 2: In the initial road segments within the target area, there are three road segments that successfully match the preset water accumulation hazard road segment database, as shown in Table 1. The successfully matched water accumulation hazard road segments are designated as road segments to be monitored.

[0051] Among them, two road sections with a water accumulation risk coefficient greater than 1 are designated as key monitoring targets, while one road section with a water accumulation risk coefficient equal to 1 is designated as a routine monitoring target. Step 3: Monitor the current average vehicle speed and current traffic flow of each road segment to be monitored in real time, as shown in Table 2. Step 4: For each road segment to be monitored, make a judgment. Taking a certain tunnel segment as an example, if the current average vehicle speed of the certain tunnel segment is less than or equal to the preset vehicle speed threshold in three consecutive current time windows, it indicates that the vehicles in the segment are stopped or almost stationary; and if the current traffic flow of the segment is less than or equal to the preset traffic flow threshold, it indicates that no vehicles are passing through the segment. Then, the certain tunnel segment in the road segment to be monitored meets the current road segment interruption conditions, and the certain tunnel segment is regarded as a candidate road segment with potential water accumulation.

[0052] Step 5: For a tunnel section among the candidate road segments, if the average speed of the upstream road segment corresponding to the tunnel section is greater than a preset speed threshold in three consecutive current time windows, and the flow rate of the upstream road segment is greater than a preset flow rate threshold, then the tunnel section among the candidate road segments is determined to meet the upstream road segment traffic conditions; if the historical average speed of the tunnel section among the candidate road segments is greater than a preset speed threshold in the same historical time window, and the historical flow rate of the road segment is greater than a preset flow rate threshold, then the tunnel section among the candidate road segments is determined to meet the historical window traffic conditions; the tunnel section among the candidate road segments that simultaneously meets the upstream road segment traffic conditions and the historical window traffic conditions is designated as a waterlogged road segment.

[0053] Step 6: For a tunnel section in candidate area GX-0524 that simultaneously meets the current road closure conditions, upstream road passage conditions, and historical window passage conditions, and whose water accumulation risk coefficient of 3 can be obtained from the water accumulation hazard section database, output the corresponding warning level, i.e., a red warning for road water accumulation, to prompt relevant departments to respond urgently. This embodiment achieves full-area automatic detection, eliminating detection blind spots; it does not require the installation of dedicated water level sensors, reducing monitoring and maintenance costs; and by introducing upstream road passage conditions and historical window passage conditions, it can effectively eliminate interference from ordinary congestion and accurately identify severe water accumulation points.

[0054] Example 3 Figure 3 This is a schematic diagram of a road waterlogging identification device according to Embodiment 3 of this application. This embodiment is applicable to scenarios where urban road waterlogging is monitored and accurately identified in real time under extreme weather conditions such as heavy rain. The road waterlogging identification device can be implemented in hardware and / or software and can be configured in a computer device. Figure 3 As shown, the road waterlogging identification device 300 includes: The monitoring section determination module 310 is used to monitor the rainfall of multiple candidate areas in real time, and to select the candidate areas whose rainfall exceeds the preset precipitation threshold as target areas, and to select the monitoring section from multiple initial road sections included in the target area. The flood-prone candidate road segment determination module 320 is used to determine the current average vehicle speed and current road segment traffic flow in the current time window based on the real-time vehicle driving trajectory data of the road segment to be monitored in multiple current time windows within the current period, and to determine the candidate road segments with flood-prone risks from the road segments to be monitored based on the current average vehicle speed and current road segment traffic flow. The waterlogged road section determination module 330 is used to determine the waterlogged road section from the candidate road sections based on the upstream average vehicle speed and upstream traffic flow of the corresponding upstream road section in the current time window, as well as the historical average vehicle speed and historical traffic flow of the candidate road section in the same historical time window, and generate waterlogging alarm information for the waterlogged road section.

[0055] In one optional implementation, the flooded road section determination module 330 is specifically used for: If the average speed of the upstream road segment corresponding to the candidate road segment is greater than a preset speed threshold for a consecutive preset number of current time windows, and the traffic flow of the upstream road segment is greater than a preset traffic flow threshold, then the candidate road segment is determined to meet the traffic conditions of the upstream road segment. If the historical average vehicle speed of the candidate road segment in the same historical time window is greater than the preset vehicle speed threshold, and the historical traffic flow of the road segment is greater than the preset traffic flow threshold, then the candidate road segment is determined to meet the historical window passage conditions. Candidate road sections that simultaneously meet the upstream road section traffic conditions and the historical window traffic conditions will be designated as the waterlogged road sections.

[0056] In one optional implementation, the candidate road section determination module 320 for identifying potential waterlogging hazards is specifically used for: If the current average vehicle speed of the monitored road segment is less than or equal to a preset vehicle speed threshold within a consecutive preset number of current time windows, and the current traffic flow of the road segment is less than or equal to a preset traffic flow threshold, then the monitored road segment is determined to meet the current road segment interruption conditions. The monitored road sections that meet the current road section interruption conditions will be considered as candidate road sections with potential water accumulation risks.

[0057] In one optional implementation, the road segment determination module 310 is specifically used for: The target area includes multiple initial road segments, which are matched with the water accumulation hazard road segments in the preset water accumulation hazard road segment database. The initial road segments that are successfully matched are used as the road segments to be monitored. The reservoir of road sections with potential water accumulation hazards is pre-determined based on road geographic information data.

[0058] In one optional embodiment, the road flooding identification device 300 further includes a flood-prone road section determination module, which is specifically used for: Acquire road geographic information data; wherein, the road geographic information data includes ground elevation information, road segment name, and road segment type; Based on the ground elevation information, the relative elevation of each road segment is calculated; Based on the road segment name, road segment type, and relative elevation of each road segment, water accumulation hazard identification is performed on each road segment to obtain identification results; the identification results include road segments with high water accumulation hazard and road segments with regular water accumulation hazard.

[0059] In one optional embodiment, the flooded road section determination module 330 further includes a flooded road section alarm module, which is specifically used for: Based on the pre-defined correlation between the warning level and the water accumulation risk coefficient range, and the water accumulation risk coefficient of the water accumulation section, the warning level of the water accumulation section is determined; wherein, the water accumulation risk coefficient of the high water accumulation risk section is greater than that of the ordinary water accumulation risk section. Based on the aforementioned warning level, alarm information is generated for the waterlogged road section.

[0060] The road waterlogging identification device provided in this application embodiment can execute the road waterlogging identification method provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects of the method execution.

[0061] This application also provides an electronic device, a readable storage medium, and a computer program product. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the arbitrary road flooding identification method of this application.

[0062] Example 4 Figure 4 This is a schematic diagram of the structure of an electronic device that implements the road water accumulation identification method of the embodiments of this application. Figure 4A schematic diagram of an electronic device 410 that can be used to implement embodiments of this application is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the application described and / or claimed herein.

[0063] like Figure 4 As shown, the electronic device 410 includes at least one processor 411 and a memory, such as a read-only memory (ROM) 412 or a random access memory (RAM) 413, communicatively connected to the at least one processor 411. The memory stores computer programs executable by the at least one processor. The processor 411 can perform various appropriate actions and processes based on the computer program stored in the ROM 412 or loaded from storage unit 418 into the RAM 413. The RAM 413 may also store various programs and data required for the operation of the electronic device 410. The processor 411, ROM 412, and RAM 413 are interconnected via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0064] Multiple components in electronic device 410 are connected to I / O interface 415, including: input unit 416, such as keyboard, mouse, etc.; output unit 417, such as various types of displays, speakers, etc.; storage unit 418, such as disk, optical disk, etc.; and communication unit 419, such as network card, modem, wireless transceiver, etc. Communication unit 419 allows electronic device 410 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0065] Processor 411 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 411 performs the various methods and processes described above, such as road flooding identification methods.

[0066] In some embodiments, the road flooding identification method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 418. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 410 via ROM 412 and / or communication unit 419. When the computer program is loaded into RAM 413 and executed by processor 411, one or more steps of the road flooding identification method described above may be performed. Alternatively, in other embodiments, processor 411 may be configured to perform the road flooding identification method by any other suitable means (e.g., by means of firmware).

[0067] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0068] Computer programs used to implement the methods of this application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0069] In the context of this application, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium can be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0070] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0071] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0072] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0073] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this application can be achieved, and this is not limited herein.

[0074] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for identifying road flooding, characterized in that, include: The system monitors rainfall in multiple candidate areas in real time, and selects candidate areas with rainfall exceeding a preset precipitation threshold as target areas. It also selects road segments to be monitored from multiple initial road segments included in the target areas. Based on the real-time vehicle trajectory data of the monitored road segment in multiple current time windows within the current period, the current average vehicle speed and current road segment traffic flow in the current time window are determined, and based on the current average vehicle speed and current road segment traffic flow, candidate road segments with potential water accumulation hazards are identified from the monitored road segments. Based on the upstream average vehicle speed and upstream traffic flow of the candidate road segment in the current time window, as well as the historical average vehicle speed and historical traffic flow of the candidate road segment in the same historical time window, waterlogged road segments are identified from the candidate road segments, and waterlogging alarm information is generated for the waterlogged road segments.

2. The method according to claim 1, characterized in that, The step of determining waterlogged road sections from the candidate road sections based on the upstream average vehicle speed and upstream traffic flow of the corresponding upstream road sections in the current time window, and the historical average vehicle speed and historical traffic flow of the candidate road sections in the same historical time window, includes: If the average speed of the upstream road segment corresponding to the candidate road segment is greater than a preset speed threshold for a consecutive preset number of current time windows, and the traffic flow of the upstream road segment is greater than a preset traffic flow threshold, then the candidate road segment is determined to meet the traffic conditions of the upstream road segment. If the historical average vehicle speed of the candidate road segment in the same historical time window is greater than the preset vehicle speed threshold, and the historical traffic flow of the road segment is greater than the preset traffic flow threshold, then the candidate road segment is determined to meet the historical window passage conditions. Candidate road sections that simultaneously meet the upstream road section traffic conditions and the historical window traffic conditions will be designated as the waterlogged road sections.

3. The method according to claim 1, characterized in that, The step of identifying candidate road sections with potential water accumulation risks from the monitored road sections based on the current average vehicle speed and current road traffic flow includes: If the current average vehicle speed of the monitored road segment is less than or equal to a preset vehicle speed threshold within a consecutive preset number of current time windows, and the current traffic flow of the road segment is less than or equal to a preset traffic flow threshold, then the monitored road segment is determined to meet the current road segment interruption conditions. The monitored road sections that meet the current road section interruption conditions will be considered as candidate road sections with potential water accumulation risks.

4. The method according to claim 1, characterized in that, The step of selecting the road segment to be monitored from multiple initial road segments included in the target area includes: The target area includes multiple initial road segments, which are matched with the water accumulation hazard road segments in the preset water accumulation hazard road segment database. The initial road segments that are successfully matched are used as the road segments to be monitored. The sections of road with potential water accumulation hazards are pre-determined based on road geographic information data.

5. The method according to claim 4, characterized in that, The method also includes identifying the road sections with potential water accumulation hazards as follows: Acquire road geographic information data; wherein, the road geographic information data includes ground elevation information, road segment name, and road segment type; Based on the ground elevation information, the relative elevation of each road segment is calculated; Based on the road segment name, road segment type, and relative elevation of each road segment, water accumulation hazard identification is performed on each road segment to obtain identification results; the identification results include road segments with high water accumulation hazard and road segments with regular water accumulation hazard.

6. The method according to claim 1, characterized in that, The waterlogged sections include sections with high risk of waterlogging and sections with regular risk of waterlogging; The generation of flood alarm information for the flooded road section includes: Based on the pre-defined correlation between the warning level and the water accumulation risk coefficient range, and the water accumulation risk coefficient of the water accumulation section, the warning level of the water accumulation section is determined; wherein, the water accumulation risk coefficient of the high water accumulation risk section is greater than that of the ordinary water accumulation risk section. Based on the aforementioned warning level, alarm information is generated for the waterlogged road section.

7. A road waterlogging identification device, characterized in that, include: The monitoring section determination module is used to monitor the rainfall of multiple candidate areas in real time, and to select the candidate areas whose rainfall exceeds the preset precipitation threshold as target areas, and to select the monitoring section from multiple initial road sections included in the target area. The module for determining candidate road sections with potential water accumulation hazards is used to determine the current average vehicle speed and current road section traffic flow in the current time window based on the real-time vehicle driving trajectory data of the road section to be monitored in multiple current time windows within the current period, and to determine candidate road sections with potential water accumulation hazards from the road sections to be monitored based on the current average vehicle speed and current road section traffic flow. The waterlogged road section determination module is used to determine the waterlogged road section from the candidate road sections based on the upstream average vehicle speed and upstream traffic flow of the corresponding upstream road section in the current time window, as well as the historical average vehicle speed and historical traffic flow of the candidate road section in the same historical time window, and generate waterlogging alarm information for the waterlogged road section.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the road flooding identification method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the road flooding identification method according to any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the road waterlogging identification method according to any one of claims 1-6.

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