A road marking full life cycle performance detection system

Abstract

The present application belongs to the technical field of road marking performance detection, and specifically discloses a road marking full life cycle performance detection system, which collects the initial retroreflective luminance coefficient and geographical position of the whole road in the marking construction acceptance stage, generates a road marking optical performance benchmark digital atlas, and collects the real-time initial retroreflective luminance coefficient and position of the marking in the daily service of the road, thereby taking the benchmark atlas as a reference to compare and evaluate the optical performance of the marking in the service state point by point, realizing the dynamic characterization of the real performance state of the marking in the whole life cycle, and at the same time, identifying the optical mutation event in the service state comparison based on the benchmark digital atlas, and connecting external event data for correlation, so that the maintenance decision is changed from the passive response and appearance repair mode to the active intelligent intervention paradigm with traceable causes and directional measures, and the precision and timeliness of road marking maintenance are significantly improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of road marking performance detection, and specifically discloses a road marking full-life-cycle performance detection system. BACKGROUND

[0002] As a key passive safety facility for ensuring driving safety and traffic order, the optical performance of road marking, especially the retroreflective luminance coefficient, directly determines the visibility distance and recognition ability of the driver to the marking under night and low-illumination conditions. With the increase of the service life of the road, the performance of the marking will decay, and more importantly, under the influence of external disturbance events, the optical performance may suddenly decrease, which seriously weakens the driving guidance function and endangers the safety of road operation. Therefore, the monitoring and evaluation of the performance of the marking from the construction to the retirement are the key prerequisites for implementing scientific maintenance and ensuring traffic safety.

[0003] The existing optical performance detection technology of road marking has developed from the traditional manual inspection to the automation and intelligentization. For example, the Chinese patent with the publication number CN120870057A proposes a road traffic marking retroreflective coefficient detection and intelligent line repairing device and method. The scheme uses a detection vehicle equipped with a multi-spectral camera, a GPS and an environment sensor to collect the optical image and the spatial data of the marking, uses a neural network model to extract the marking position and the retroreflective coefficient matrix, and combines the environment parameters to perform dynamic threshold determination, so as to identify the marking defects and trigger the line repairing operation.

[0004] The above scheme still has the following limitations when facing the full-life-cycle performance management.

[0005] The above scheme is essentially a snapshot inspection and response system facing defect identification, and the output is the absolute retroreflective value at an isolated time point. The initial optical performance benchmark covering the whole line is not constructed synchronously at the construction acceptance stage of the marking. The missing of this benchmark data will lead to the inability to accurately quantify the real performance state of the marking in the service process, and further makes it difficult to depict the evolution of the health state, so that it is impossible to provide reliable data support for predictive maintenance.

[0006] The existing method mainly focuses on the static state discrimination of the optical performance of the marking, that is, when the performance decreases, only the alarm or the repair suggestion based on the characterization result can be triggered, and the correlation analysis between this phenomenon and the external events in the space-time range is lacked. The limitation of only knowing the phenomenon but not the cause makes the maintenance decision only be able to passively repair the characterization problem, and it is difficult to realize the diagnosis of the deterioration source and the targeted prevention. SUMMARY

[0007] In view of this, the application aims to propose a road marking full-life-cycle performance detection system, which effectively solves the problems mentioned in the background technology.

[0008] The object of the present application can be achieved by the following technical solution: a road marking full life cycle performance detection system, comprising:

[0009] A reference atlas construction module: in the marking construction acceptance stage, drive the retroreflective measurement unit mounted on the detection vehicle, continuously collect the initial retroreflective luminance coefficient and geographical position of each unit marking of the whole road, and generate a road marking optical performance reference digital atlas;

[0010] A service dynamic monitoring module: in the daily service of the road, the real-time retroreflective luminance coefficient and position and time information of the marking are collected by the retroreflective rapid acquisition unit and are returned in real time;

[0011] A performance comparison and analysis module: according to the returned position information, the initial reference value is matched in the reference digital atlas, the real-time performance retention rate is calculated, and the average performance retention rate of the road section is calculated according to the performance retention rate of the continuous position points;

[0012] A mutation recognition and correlation module: access external event data sources, identify optical mutation events by monitoring the decline of the performance retention rate, and correlate the optical mutation events with external events within the same space-time range;

[0013] A hierarchical early warning module: according to the results of the correlation and binding of the optical mutation events and external events during the service of the road marking, hierarchical early warning information is generated.

[0014] Compared with the prior art, the present application has the following beneficial effects: 1. The present application collects the initial retroreflective luminance coefficient and geographical position of the whole road in the marking construction acceptance stage, generates a road marking optical performance reference digital atlas, and collects the real-time initial retroreflective luminance coefficient and position of the marking in the daily service of the road, thereby taking the reference atlas as a reference for space-time alignment, comparing and quantitatively evaluating the optical performance of the marking in the service state point by point, realizing the dynamic description of the real performance state of the marking in the whole life cycle, and providing a reliable data basis for predictive maintenance.

[0015] In the process of service state comparison based on the road marking optical performance reference digital atlas, the present application introduces an optical performance mutation event recognition mechanism, which can accurately capture the abnormal degradation of the marking performance, and on this basis, after detecting the mutation event, actively accesses multi-source external event data for correlation, so that the maintenance decision is changed from the traditional passive response and superficial repair mode to the active intelligent intervention paradigm of cause traceability, risk judgment and measure orientation, which significantly improves the accuracy, timeliness and resource utilization efficiency of road marking maintenance. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort based on these drawings.

[0017] Figure 1 It is a schematic diagram of system module connection in the present application.

[0018] Figure 2 It is a flow chart of identification of point optical mutation event in the present application.

[0019] Figure 3 It is a schematic diagram of content of hierarchical early warning in the present application. DETAILED DESCRIPTION

[0020] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort belong to the scope of protection of the present application.

[0021] The present application provides a road marking full life cycle performance detection system, comprising a reference atlas construction module, a service dynamic monitoring module, a performance comparison and analysis module, a mutation identification and correlation module and a hierarchical early warning module.

[0022] Referring to Figure 1 As shown in the figure, the reference atlas construction module and the service dynamic monitoring module are connected with the performance comparison and analysis module, the performance comparison and analysis module is connected with the mutation identification and correlation module, and the mutation identification and correlation module is connected with the hierarchical early warning module.

[0023] The reference atlas construction module is used to drive the retroreflective measurement unit carried on the detection vehicle in the marking construction acceptance stage, continuously collect the initial retroreflective luminance coefficient and geographical position of each unit marking of the whole road, and generate a digital atlas of road marking optical performance.

[0024] In the preferred embodiment of the present application, the above module content is as follows:

[0025] In the marking construction acceptance stage, the special detection vehicle is controlled to drive along the center track of the lane marking.

[0026] During driving, the retroreflective measurement unit is triggered synchronously to continuously emit measurement light beams to the road marking in unit length according to the standard measurement geometric conditions such as observation angle, incidence angle, etc., and real-time collect the reflected light signals, and continuously output the original reading of the initial retroreflective luminance coefficient corresponding to each sampling point;

[0027] By detecting the navigation position of the vehicle, latitude and longitude coordinates and road post information are marked for each sampling point.

[0028] The initial retroreflective luminance coefficient raw readings marked with position information are filtered and smoothed to generate an initial retroreflective luminance coefficient value sequence continuously distributed along the road direction.

[0029] The initial retroreflective luminance coefficient value sequence is associated and encapsulated according to the geographical position sequence to form a road marking optical performance reference digital map.

[0030] The description applied to the above operation indicates that the road marking construction is completed at the marking construction acceptance stage, at which time the marking is in an initial perfect state, and its retroreflective performance represents the optimal level of material and construction quality, and the data obtained can be used as the only reliable reference benchmark for subsequent full life cycle performance degradation evaluation.

[0031] Since the road marking is usually continuously linearly distributed and covers a long mileage, the manual point measurement method cannot meet the requirements of spatial continuity and efficiency. Therefore, a special detection vehicle is required to travel at a uniform speed along the target lane marking center line to realize efficient and automatic scanning of the marking on the whole line.

[0032] During the detection process, the vehicle-mounted retroreflective measurement unit continuously emits measurement light beams at a preset spatial interval, such as every 0.5 meters, to the marking surface within a unit length according to the standard geometric conditions including fixed observation angle, incident angle and light source-detector configuration specified by international or industry standards, and simultaneously receives the reflected signals to generate an initial retroreflective luminance coefficient raw sampling sequence. At the same time, accurate geographical coordinates and corresponding road post information are assigned to each sampling point during the detection to ensure that the optical performance data and the spatial position are strictly aligned.

[0033] The finally formed road marking optical performance reference digital map not only covers the whole line but also has spatial indexing capability, which can provide a reference benchmark for subsequent performance comparison during the service period.

[0034] The service dynamic monitoring module is used to collect real-time retroreflective luminance coefficients, position and time information of the marking by using the retroreflective rapid acquisition unit during the daily service of the road and to return them in real time.

[0035] In an optional embodiment of the present application, the implementation content of the service dynamic monitoring module is as follows:

[0036] The inverse reflection rapid acquisition unit is a calibrated light inverse reflection coefficient sensor, which is integrated in the front or side of the inspection vehicle in a fixed installation posture and in a standard measurement geometry, so that the measurement light path can cover the marking area of the lane traveled by the vehicle.

[0037] The inverse reflection brightness coefficient is collected according to the preset spatial interval during the vehicle travel, thereby generating a unit length continuous spatial sampling point sequence distributed along the road longitudinally.

[0038] The positioning device is configured on the special inspection vehicle, and the current position and timestamp are recorded at the same time when the real-time inverse reflection brightness coefficient reading is collected, and the data packet is uploaded to the performance comparison analysis module in real time through the wireless communication network.

[0039] It can be understood that, in the optical performance detection of the road marking in the daily service stage, in order to ensure that the real-time acquisition data and the road marking optical performance benchmark digital atlas established in the construction acceptance stage have strict spatial alignment and physical comparability, the system triggers the inverse reflection measurement at the same geographical coordinate position as the benchmark atlas, i.e. the homologous sampling point, according to the positioning information during the inspection vehicle travel.

[0040] Through this repeated sampling strategy in space-time consistency, the inverse reflection performance of the same marking unit at different service time points can be accurately compared longitudinally, so as to effectively eliminate the evaluation deviation introduced by the sampling position offset, lane switching or inconsistent spatial resolution.

[0041] The performance comparison analysis module is used to match the initial benchmark value in the benchmark digital atlas according to the returned position information, calculate the real-time performance retention rate, and calculate the average performance retention rate of the road section according to the performance retention rate of the continuous position points.

[0042] Due to the natural differences in the material type, paint batch, drawing process and environmental conditions adopted by the road marking in the construction stage, the absolute values of the initial inverse reflection brightness coefficient of different road sections or even adjacent sections may have significant discreteness. If the data measured in the service period is directly compared with the unified threshold, it is easy to lead to misjudgment, for example, the initial performance of the marking is high, and its absolute value may be higher than the threshold even if it has been obviously degraded; and the initial performance of the marking is low, and it may be misjudged as unqualified even if it remains stable.

[0043] Therefore, when comparing the optical performance data collected in the daily service state with the benchmark atlas, the performance retention rate is used as the core comparison index, which eliminates the interference of the initial performance difference and truly reflects the relative degradation degree of the marking in its own service process.

[0044] In a specific implementation, the real-time performance retention rate is calculated as follows:

[0045] A fixed road section length is set as a statistical unit;

[0046] For a statistical unit, the retroreflective luminance coefficient values and positions of all sampling points falling within the geographical range of the statistical unit are extracted from the real-time data stream returned by the service dynamic monitoring module.

[0047] According to the positions of the sampling points, the matched initial retroreflective luminance coefficient values are extracted one by one from the road marking optical performance benchmark digital map.

[0048] The real-time performance retention rate is calculated by taking the ratio of the real-time retroreflective luminance coefficient value of each sampling point to the initial retroreflective luminance coefficient benchmark value.

[0049] It can be understood that since the initial retroreflective luminance coefficient of each sampling point is measured during the marking construction acceptance stage, it represents the maximum theoretical retroreflective ability of the marking at this position in its life cycle. The retroreflective performance of the road marking usually shows a decay trend during subsequent service, that is, the measured retroreflective luminance coefficient at any time will be less than the benchmark value, so the real-time performance retention rate is valued between 0 and 1. The greater the data monitored in subsequent service, the greater the real-time performance retention rate, indicating that the current state of the marking is closer to the initial performance and the degradation degree is lower. Conversely, it indicates that the performance degradation is more serious.

[0050] Considering that the real-time retroreflective luminance coefficient of a single sampling point reflects the local and instantaneous state of the marking, which is easily disturbed by accidental factors. Road maintenance and management usually take road sections such as 100 meters, 500 meters or units divided by stake numbers as the basic decision unit. By calculating the mean value of the real-time retroreflective luminance coefficients of all effective sampling points in a road section, a representative index of the overall optical performance of the section can be obtained, which more truly reflects its systematic service level.

[0051] Based on this, the road section average performance retention rate is calculated as follows:

[0052] The real-time performance retention rates of all sampling points in each statistical unit are arithmetically averaged to obtain the average performance retention rate of the statistical unit in this monitoring period.

[0053] The mutation identification and correlation module is used to access external event data sources, identify optical mutation events by monitoring the decline of the performance retention rate, and correlate the optical mutation events with external events within the same spatiotemporal range.

[0054] During the normal service of road marking, its optical performance usually presents a slow, continuous and predictable progressive decay, however, when encountering sudden external disturbance, the retroreflective performance of the marking may have a non-continuous, sharp drop, i.e. optical mutation, such mutation events are high-risk abnormal states in the whole life cycle performance monitoring, which often significantly weaken the visibility function of the marking in a short time, and constitute a potential traffic safety hazard. Therefore, in the process of comparing the measured data in the service period with the initial baseline profile to evaluate the optical performance retention state of the marking, optical mutation event identification needs to be performed.

[0055] Referring to Figure 2 As shown in the above scheme, in the manner that the above scheme can be implemented, the optical mutation event includes the following identification process: for each spatial sampling point, continuously accumulate the performance retention rate data obtained by its previous inspection to form a performance retention rate time sequence.

[0056] The performance retention rate of each time point in the performance retention rate time sequence is calculated relative to the previous time.

[0057] Specifically, the performance retention rate is the difference between the performance retention rate of the previous time and the current time performance retention rate divided by the performance retention rate of the previous time.

[0058] If the performance retention rate of a spatial sampling point at a certain time point is higher than the performance sharp decrease threshold, it is determined that the spatial sampling point has a point-like optical mutation event at the time point.

[0059] The performance sharp decrease threshold in the above embodiment reflects the maximum reasonable short-term decay rate of the marking material under typical service conditions. For example, according to the laboratory accelerated aging curve of the marking material type, the maximum theoretical natural decay rate of the marking material within a typical inspection period, such as 3 months, can be calculated as the performance sharp decrease threshold.

[0060] An event record is generated for each marked point-like optical mutation event, and the record at least contains event identification, event type, event location and event occurrence time window.

[0061] Understandably, under the normal service state of the road marking, the performance retention rate of each spatial sampling point presents a small and smooth change in the time sequence. Therefore, if the performance retention rate of a sampling point between two consecutive monitoring appears a significant drop, it highly suggests that an optical performance mutation event may have occurred at this location.

[0062] To scientifically quantify such abnormal changes, the performance retention rate is introduced as a core criterion in the mutation discrimination. Compared with directly using the absolute drop value of the retroreflective luminance coefficient, the relative drop rate can effectively eliminate the evaluation deviation caused by the initial performance difference of the marking.

[0063] After determining the point-like optical mutation event, the event identification, event type, location where the event occurs, and event time window are recorded, which can be used as a spatiotemporal index for correlating external events.

[0064] It is worth noting that the initial identification of the mutation event is based on a single monitoring moment in the performance retention time sequence. However, the impact of actual external disturbances often has persistence or hysteresis, and it is difficult to accurately define the start and end range of disturbance action only with a single time point as the event timestamp. Therefore, to improve the accuracy of event correlation and causal inference, a reasonable event time window should be constructed by moderately expanding the time axis forward and backward, such as backtracking 1-3 inspection periods forward and extending 1-2 periods backward, centered on the identification moment, thereby improving the matching recall rate with the external event database.

[0065] Based on the performance retention rate of a single spatial sampling point, point-like optical mutation events are identified, and further consideration of systematic degradation behavior on the road segment scale is needed. Due to the influence of regional external disturbances such as continuous construction and large-scale pollution, the optical performance degradation of road markings is often not limited to isolated points, but may exhibit coordinated attenuation within continuous segments.

[0066] Therefore, the identification mechanism of optical mutation events should not only focus on local point-like abnormalities, but also simultaneously build the ability to perceive the performance evolution trend at the segment level.

[0067] Based on the above description, in the further implementable manner of the above scheme, the optical mutation event further includes the following identification process: for each statistical unit, continuously gather the average performance retention rate calculated in each inspection period to form an average performance retention rate time sequence evolution curve.

[0068] In the average performance retention rate time sequence evolution curve of each statistical unit, a sliding time window is used to perform linear regression fitting on the average performance retention rate data sequence in each window to obtain the fitting straight line slope of the performance degradation trend in the corresponding window.

[0069] If the slope of the fitting straight line slope in multiple consecutive windows is not only negative, but also its absolute value exceeds the normal aging rate threshold preset based on the material type and environmental conditions, it is determined that the unit has a segment optical mutation event.

[0070] The normal aging rate threshold in the above represents the maximum acceptable natural decay rate of the performance retention rate of road markings per unit time under specific marking material type and service environmental conditions.

[0071] In one specific embodiment, the normal aging rate threshold is set in the following manner:

[0072] Firstly, collect a large number of inspection data of the same type of marking line section without external disturbance record for many years, and group them according to material type, climate zone, etc.

[0073] Secondly, calculate the average performance retention time series of each group, and fit the typical natural decay slope.

[0074] Finally, take the high quantile of the slope distribution of each group, such as 90% or 95%, as the normal aging rate threshold of this category.

[0075] Generate an event record for each marked section optical mutation event, which at least contains event identification, event type, event location, and event time window.

[0076] Understandably, during the normal service of road marking, the performance retention rate of the section usually presents a slow and gradual decay trend that conforms to the inherent aging law of the material. When performing sliding window linear regression analysis on the average performance retention time series curve of a statistical unit, if the degradation slopes fitted by multiple consecutive time windows are not only negative, but also significantly exceed the normal aging rate threshold based on the characteristics of the marking line material and environmental conditions, it indicates that the performance degradation of the section has exceeded the expected natural decay category, and it is determined as a section optical trend degradation event.

[0077] Further, the process of associating optical performance mutation events with external events is as follows: when an optical mutation event record is generated, use the geographic location and time window in the event record as the association retrieval condition.

[0078] Initiate a query to the external event data source, requesting to obtain all traffic events, maintenance events and special weather events that occur within the time window and within a preset radius range centered on the geographic location.

[0079] The above-mentioned traffic events, maintenance events and special weather events are not randomly selected as external events for association analysis, but are based on their explicit and significant potential impact on the optical performance of the marking line in physical mechanism and actual operation scene, as follows:

[0080] Among them, traffic accidents, vehicle leaks, etc. in traffic events may cause the marking line to be crushed, scraped or covered with oil stains and chemicals; such events have the characteristics of suddenness, strong locality and direct impact, and are common causes of point-like optical mutations.

[0081] Road milling, high-pressure washing, etc. in maintenance events may damage the surface microstructure of the marking line and corrode the marking line material. Maintenance is a controllable but high-frequency external disturbance, and its impact on the performance of the marking line has predictability and traceability, and is an important explanatory variable for section-level degradation.

[0082] Rainstorm, snowstorm, freeze-thaw cycle and other special weather events can temporarily obscure the markings or cause water film effect, reducing the visibility, and weather events are also the main source of section-level degradation.

[0083] receiving a list of external events returned by the query;

[0084] logically associating the optical mutation event record with the returned list of external events to form an associated pair.

[0085] If there is an external event in the list, the associated external event type is appended in the optical mutation event record; if the list is empty, a note is marked in the record that no explicit external event is associated.

[0086] In the innovative implementation of the present application, it is considered that optical performance mutation is not directly caused by external events, but also may be caused by structural defects or geometric abnormalities of the markings themselves, such as material peeling, edge wear, local missing, etc. Such problems, although not accompanied by obvious external disturbance records, can also cause a sharp drop in retroreflective performance, and if only relying on external event association, it will lead to missed attribution.

[0087] Therefore, the system synchronously collects and stores the high-precision geometric contour information of the markings at each sampling point while constructing the digital atlas of the road marking optical performance benchmark, forming a geometric benchmark contour of the markings as a reference basis for morphological integrity evaluation, and providing an internal consistency verification mechanism for external event association.

[0088] Specifically, the geometric contour of the markings is collected at each sampling point position during the construction of the benchmark atlas as the geometric benchmark contour of the markings.

[0089] In the dynamic monitoring in service, the video image stream of the markings at the sampling point is synchronously collected by using the daily operation vehicles, and the image stream is processed in real time to identify the visual contour of the marking area in the current frame through edge detection and contour extraction.

[0090] The identified visual contour is compared with the geometric benchmark contour of the markings at the corresponding position, and when there is a deviation between the visual contour and the geometric benchmark contour of the markings and the deviation lasts for more than a preset number of frames, a geometric abnormality event record is generated, which includes the abnormal position and the time window of occurrence.

[0091] When associating and binding the point-like optical mutation event with the external event, if a geometric abnormality event record occurring at the same geographical position and in the same time window as the point-like optical mutation event is received, the point-like optical mutation event is preferentially internally associated with the geometric abnormality event, and after the internal association is completed, the merged optical-morphology composite event is taken as the main body to initiate a query to the external event data source for external event association.

[0092] The combination of the optical performance degradation and the geometric shape change is represented as an optical shape composite anomaly, so that the object associated with the external event is upgraded from a single performance index to a multi-dimensional state anomaly body, and the physical rationality and engineering interpretability of the correlation result are significantly improved.

[0093] The hierarchical early warning module is used to generate hierarchical early warning information according to the result of the binding of the optical mutation event and the external event during the service period of the road marking.

[0094] Referring to Figure 3 As shown, specifically, the hierarchical early warning information is as follows:

[0095] If the optical mutation event is a point optical mutation event and is associated with an external event, it indicates that the performance degradation of the marking is directly caused by a confirmable external disturbance, and a first-level immediate disposal early warning is generated to prompt the operation and maintenance unit to immediately carry out targeted emergency disposal.

[0096] If the optical mutation event is a point optical mutation event but is not associated with a clear external event, it is determined to be an abnormal degradation of unknown cause, and a second-level on-site verification early warning is generated to suggest arranging on-site manual verification to exclude the influence of sensor errors, local pollution, hidden construction or other unrecorded events.

[0097] If the optical mutation event is a section optical mutation event and is associated with a persistent external event such as high-frequency heavy traffic, long-term chemical corrosion environment, repeated deicing operation, etc., it indicates that the marking on this section is in an accelerated aging or systematic degradation state, and a third-level early warning is generated to prompt the inclusion in the preventive maintenance plan and the timely implementation of marking recoating or material upgrading.

[0098] If the optical mutation event is a section optical mutation event and is not associated with any external event, it may reflect that the marking material durability is insufficient and the construction quality is defective, and a fourth-level early warning is generated to mark the section as a performance anomaly attention area, strengthen the subsequent inspection frequency and start a special evaluation.

[0099] The above early warning levels are sorted in descending order of response urgency: first level > second level > third level > fourth level.

[0100] The above generates four levels of differentiated early warnings by combining the optical mutation event type and the external event association state, and realizes the organic unification of risk identification-cause diagnosis-response strategy. This mechanism significantly improves the accuracy, interpretability and action orientation of the early warning.

[0101] The above embodiments can be realized by software, hardware, firmware or any combination thereof, in whole or in part. When realized by software, the above embodiments can be realized in the form of a computer program product in whole or in part.

[0102] Those skilled in the art can understand that the modules and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to realize the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0103] In addition, each functional module in each embodiment of the present application can be integrated in one processing module, or each module can exist physically alone, or two or more modules can be integrated in one module.

[0104] The above description is merely specific embodiments of the present application, but the protection scope of the present application is not limited thereto. Any modification or replacement within the technical scope disclosed by the present application can be easily thought by those skilled in the art, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0105] Finally, the above description is only the preferred embodiment of the present application, and is not used to limit the present application. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A road marking full life cycle performance detection system, characterized in that, Comprise: Benchmark atlas construction module: in the acceptance stage of marking construction, drive the retroreflective measurement unit mounted on the detection vehicle, continuously collect the initial retroreflective luminance coefficient and geographical position of each unit marking on the whole line of the road, and generate a digital benchmark atlas of the optical performance of road marking; Service dynamic monitoring module: in the daily service of the road, the real-time retroreflective luminance coefficient, position and time information of the marking are collected by the retroreflective rapid acquisition unit, and are returned in real time; Performance comparison and analysis module: according to the position information returned, the initial benchmark value is matched in the digital benchmark atlas, the real-time performance retention rate is calculated, and the average performance retention rate of the section is calculated according to the performance retention rate of the continuous position points; Mutation recognition and correlation module: access external event data source, identify optical mutation events by monitoring the decline of performance retention rate, and correlate optical mutation events with external events within the same space-time range; Graded early warning module: according to the results of the correlation and binding of optical mutation events and external events during the service period of road marking, generate graded early warning information; The optical mutation event includes the following identification process: For each spatial sampling point, continuously accumulate the performance retention rate data obtained by its previous inspection to form a performance retention rate time series; Calculate the performance retention rate of each time point in the performance retention rate time series relative to the previous time; If the performance retention rate of a spatial sampling point at a certain time point is higher than the performance sharp reduction threshold, it is determined that the spatial sampling point has a point-like optical mutation event at the time point; Generate an event record for each marked point-like optical mutation event, which at least contains event identification, event type, event location and event time window; The process of correlating the optical mutation event with the external event within the same space-time range is as follows: After generating an optical mutation event record, use the geographical position and time window in the event record as the correlation retrieval condition; Query the external event data source to request all traffic events, maintenance operation events and special weather events within the time window and within the preset radius range centered on the geographical position; Receive the returned external event list; Logically associate the optical mutation event record with the returned external event list to form a correlation pair; If there is an external event in the list, add the associated external event type to the optical mutation event record; If the list is empty, mark it as not associated with an explicit external event in the record.

2. The road marking full life cycle performance detection system of claim 1, wherein: The implementation content of the benchmark atlas construction module is as follows: In the marking construction acceptance stage, control the special detection vehicle to drive along the center trajectory of the lane marking; During driving, trigger the retroreflective measurement unit to continuously emit measurement light beams according to the standard measurement geometric conditions within the unit length of the road marking, and continuously output the initial retroreflective luminance coefficient original reading corresponding to each sampling point by real-time acquisition of its reflected light signal; Mark each sampling point with latitude and longitude coordinates and road stake information through the navigation positioning of the detection vehicle; Filtering and smoothing the initial retroreflectivity coefficient raw readings with position information to generate a sequence of initial retroreflectivity coefficient values continuously distributed along the road alignment; Associating and encapsulating the sequence of initial retroreflectivity coefficient values according to geographical position to form a digital map of road marking optical performance benchmark.

3. The road marking full life cycle performance detection system of claim 1, wherein: The implementation of the service dynamic monitoring module is as follows: In the daily service of the road, the retroreflective rapid acquisition unit configured on the special inspection vehicle is used to implement continuous dynamic detection of the entire road, wherein the retroreflective rapid acquisition unit is a calibrated light-weight retroreflectivity coefficient sensor integrated in the front or side of the inspection vehicle in a fixed installation posture and in a manner conforming to the standard measurement geometry, so that the measurement light path can cover the marking area of the lane on which the vehicle travels; During the vehicle travel, the sensor is triggered according to the preset spatial interval to collect the retroreflectivity coefficient, thereby generating a sequence of unit length continuous spatial sampling points longitudinally distributed along the road; A positioning device is configured on the special inspection vehicle, and the current position and time stamp are recorded at the same time when each real-time retroreflectivity coefficient reading is collected, and the data packet is uploaded in real time to the performance comparison and analysis module through a wireless communication network.

4. The road marking full life cycle performance detection system of claim 1, wherein: The real-time performance retention rate is calculated as follows: A fixed road section length is set as a statistical unit; For a statistical unit, the retroreflectivity coefficient values and positions of all sampling points falling within the geographical range of the statistical unit are extracted from the real-time data stream returned by the service dynamic monitoring module; According to the positions of the sampling points, the matched initial retroreflectivity coefficient values are extracted one by one from the digital map of road marking optical performance benchmark; The real-time performance retention rate is obtained by ratio calculation of the real-time retroreflectivity coefficient value of each sampling point and the initial retroreflectivity coefficient benchmark value.

5. The road marking full life cycle performance detection system of claim 4, wherein: The average performance retention rate of the road section is calculated as follows: The real-time performance retention rates of all sampling points in each statistical unit are arithmetically averaged to obtain the average performance retention rate of the statistical unit in the current monitoring period.

6. The road marking life cycle performance detection system of claim 1, wherein: The optical mutation event continues to include the following identification process: For each statistical unit, the average performance retention rates calculated in the previous inspection periods are continuously aggregated to form an average performance retention rate time series evolution curve; In the average performance retention rate time series evolution curve of each statistical unit, a sliding time window is used to perform linear regression fitting on the average performance retention rate data sequence in each window to obtain the fitting straight line slope of the performance degradation trend in the corresponding window; If the slopes of the fitting straight line slopes in multiple consecutive windows are not only negative but also exceed the normal aging rate threshold preset based on the material type and environmental conditions, it is determined that a section optical mutation event occurs in the unit; An event record is generated for each marked section optical mutation event, and the record at least contains event identification, event type, event location, and event occurrence time window.

7. The road marking life cycle performance detection system of claim 1, wherein: The mutation identification association module further includes the following content: During the construction of the benchmark map, the marking geometry profile is collected at each sampling point position as a marking geometry benchmark profile; In the service dynamic monitoring, the video image stream of the marking line of the sampling point is synchronously collected by using the daily operation vehicle, and the image stream is processed in real time, the visual profile of the marking line region in the current frame is recognized through edge detection and contour extraction; The recognized visual profile is compared with the marking line geometric reference profile at the corresponding position, and when there is deviation between the visual profile and the marking line geometric reference profile and the deviation lasts for more than a preset number of frames, a geometric morphology abnormal event record is generated, which contains the abnormal position and the time window of occurrence; When the point-like optical mutation event and the external event are associated and bound, if a geometric morphology abnormal event record occurring at the same geographical position and in the same time window as the point-like optical mutation event is received, the point-like optical mutation event is preferentially internally associated with the geometric morphology abnormal event, and after the internal association is completed, the merged optical-morphology composite event is taken as the main body to initiate a query to the external event data source for external event association.

8. The road marking full life cycle performance detection system of claim 1, wherein: The generated hierarchical early warning information includes the following contents: If the optical mutation event is a point-like optical mutation event and is associated with an external event, a first-level immediate disposal early warning is generated; If the optical mutation event is a point-like optical mutation event but is not associated with a clear external event, a second-level on-site verification early warning is generated; If the optical mutation event is a section optical mutation event and is associated with a persistent external event, a third-level early warning is generated, prompting to be included in the preventive maintenance plan; If the optical mutation event is a section optical mutation event and is not associated with any external event, a fourth-level early warning is generated, marking the road section as a performance abnormal attention zone.

Images