Safety blind guiding system with road condition real-time analysis function

Abstract

The invention discloses a safe blind guiding system with a road condition real-time analysis function, and relates to the technical field of commuting, and the system comprises a position data obtaining unit which obtains original position data between a user and a target object, carries out the preliminary correction of different environmental factor interferences, obtains a position data set after the preliminary correction, and carries out the real-time analysis of a road condition. The signal optimization unit is used for generating a position data set subjected to smoothing processing for subsequent spatial relation judgment according to the position data set subjected to preliminary correction, and the distance measurement unit is used for determining a real-time distance value between a user and a target object according to the position data set subjected to smoothing processing in combination with a preset distance calculation model. An accurate distance measurement result is output; according to the safety blind guiding system with the road condition real-time analysis function, the navigation precision and safety are effectively improved, more intelligent and more reliable traffic guidance is provided for a user, the traffic flow is optimized, the accident risk is reduced, and the overall traffic efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of commuting technology, and more specifically to a safety guidance system for the blind with real-time road condition analysis capabilities. Background Art

[0002] In the field of modern transportation and navigation, accurate spatial positioning and real-time traffic analysis technologies are crucial, directly impacting user travel safety and efficiency, and serving as an indispensable core support for intelligent transportation systems. With the acceleration of urbanization and the increasing complexity of transportation networks, providing users with safe and efficient travel guidance has become a critical issue that urgently needs to be addressed.

[0003] However, current related technologies still have significant shortcomings in dealing with complex environments. Many methods often struggle to adapt to changing environmental factors, such as information acquisition deviations under different weather and lighting conditions, or positioning drift caused by signal interference in areas with high population density and vehicles. These limitations prevent existing solutions from continuously providing stable and reliable services in dynamic scenarios, especially in emergency situations requiring rapid response. Focusing on specific challenges, the key issues in this field are how to accurately measure the distance between the user and target objects, and how to dynamically adjust guidance strategies based on real-time traffic conditions. The accuracy of distance measurement directly determines the system's ability to judge spatial relationships; without accurate distance data, it is difficult to make timely predictions of potential risks. When the distance measurement problem is not properly resolved, it will further affect the rationality of travel speed recommendations, because speed adjustment relies on a comprehensive analysis of distance and road conditions. Speed ​​recommendations lacking accurate data support may leave users confused in complex environments and even increase safety hazards. Summary of the Invention

[0004] The purpose of this invention is to provide a safety guidance system for the blind with real-time road condition analysis capabilities. This system can accurately measure the distance between the user and target objects under dynamic road conditions, dynamically adjust speed recommendations based on real-time analysis results, and provide timely warnings when approaching dangerous areas.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a safety guidance system for the blind with real-time road condition analysis function, the system comprising:

[0006] The location data acquisition unit acquires the raw location data between the user and the target object, performs preliminary corrections for interference from different environmental factors, and obtains a preliminarily corrected location dataset.

[0007] The signal optimization unit generates a smoothed set of position data for the initially corrected position dataset, which is then used for subsequent spatial relationship determination.

[0008] The distance measurement unit determines the real-time distance between the user and the target object based on the smoothed position data set and a preset distance calculation model, and outputs accurate distance measurement results.

[0009] The traffic analysis unit obtains current traffic information from the complex environment of the traffic network through real-time distance measurement results and generates comprehensive traffic assessment data;

[0010] The speed suggestion generation unit adjusts the speed suggestion parameters based on comprehensive road condition assessment data and outputs a speed guidance value for the current distance and road conditions;

[0011] The risk assessment and early warning unit, based on the speed guidance value and real-time distance measurement results, will trigger a warning mechanism and generate a corresponding danger zone warning signal if it determines that the user is approaching a dangerous area.

[0012] The route adjustment unit, through the danger zone warning signal, links with the route planning module in the navigation system to obtain alternative route data and determine a new travel guidance plan;

[0013] The information update and output unit updates the content displayed on the user terminal according to the new travel guidance scheme, and synchronously transmits the adjusted speed guidance value and warning information to complete the real-time dynamic adjustment.

[0014] Preferably, the location data acquisition unit acquires the original location data between the user and the target object, performs preliminary correction for interference from different environmental factors, and obtains a preliminarily corrected location dataset. This dataset includes sensor data acquired from multiple device sources. For the original dataset collected by the devices, a pre-established standardization rule is used for format unification processing to obtain a standardized location information set. Based on the standardized location information set, a filtering tool is used to preliminarily clean the data to address environmental interference factors. If the noise value detected in the data exceeds a preset threshold, a portion of the data is smoothed to obtain a cleaned location information set. Using the cleaned location information set and a data fusion method, the relative location information between the user's location and the target object from different device sources is integrated. If the deviation of the integrated data exceeds a preset threshold, the deviation portion is weighted and adjusted to determine the fused location dataset. The fused location dataset is then acquired, and a correction processing tool is used to perform a secondary verification of the data to meet environmental adaptation requirements. By comparing the correction result with the original dataset, it is determined whether the final corrected location dataset meets the accuracy requirements, thus obtaining the final location information result.

[0015] Preferably, the signal optimization unit generates a smoothed location data set for the initially corrected location dataset, which is used for subsequent spatial relationship judgment. This includes processing the signal drift in the dataset using a mean filter tool based on the initially corrected location dataset, performing point-by-point smoothing on the abnormal fluctuations in the dataset to obtain a drift-optimized location data set; using the drift-optimized location data set, a weighted average tool is used to perform a secondary adjustment on the data set to address location deviations caused by environmental interference. If the deviation value exceeds a preset threshold, some data is corrected to determine the deviation-adjusted location data set; the deviation-adjusted location data set is obtained, and a time synchronization tool is used to align the timestamps of the data set to meet data stability requirements. If a timestamp offset is detected to exceed a preset threshold, the offset portion is interpolated to obtain a time-aligned location data set; from the time-aligned location data set, a coordinate mapping tool is used to transform the data set to a unified coordinate system to determine the final smoothed location data set.

[0016] Preferably, the distance measurement unit determines the real-time distance value between the user and the target object based on the smoothed location data set and a preset distance calculation model, and outputs an accurate distance measurement result. This includes processing the smoothed location data set using a coordinate mapping tool to convert the location information into a unified coordinate framework, resulting in a converted location data set; synchronizing the timestamps of the data set using a time alignment tool to meet real-time measurement requirements, and interpolating the offset portion if the timestamp offset exceeds a preset threshold, to determine the time-synchronized location data set; analyzing the user's position and the target object's position point-by-point using a geometric calculation tool to calculate the straight-line distance between each set of position points, resulting in a preliminary distance data set; and adjusting the distance data using a weighted average tool to address deviations caused by environmental interference, and smoothing the fluctuation portion if the fluctuation exceeds a preset threshold, to determine the final real-time distance measurement result.

[0017] Preferably, the traffic condition analysis unit obtains current traffic condition information from the complex environment of the traffic network through real-time distance measurement results, and generates comprehensive traffic condition assessment data. This includes: based on the real-time distance measurement results, and considering the complex environmental characteristics of the traffic network, using data acquisition tools to obtain distance measurement data and corresponding traffic condition information from multiple road segments; if the timestamp offset between the distance measurement data and the traffic condition information exceeds a preset threshold, time alignment processing is performed to obtain a synchronized data combination; using the synchronized data combination, and considering the needs of dynamic analysis, using data integration tools to match the distance measurement data and traffic condition information to obtain real-time data of each road segment in the traffic network and determine the classified traffic condition data set; obtaining the classified traffic condition data set, and considering the goal of comprehensive assessment, using data fusion tools to weight the multi-source information in the traffic condition data set; if the traffic condition fluctuation of a road segment exceeds a preset threshold, smoothing adjustment is performed to determine the adjusted traffic condition feature data; based on the adjusted traffic condition feature data, and considering the business requirements of traffic condition updates, using information mapping tools to associate the feature data with the actual road segments of the traffic network to obtain the final traffic condition assessment result.

[0018] Preferably, the speed suggestion generation unit adjusts speed suggestion parameters based on comprehensive road condition assessment data and outputs a speed guidance value for the current distance and road conditions. This includes acquiring road condition data and obstacle distance information from real-time monitoring equipment, classifying the data using pre-established road condition assessment rules, and obtaining the current congestion level and distance judgment results based on the characteristics of traffic congestion and obstacle distance. Based on the congestion level and distance judgment results, a preset threshold is used for comparison. If the congestion level is higher than the threshold or the obstacle distance is lower than the safe range, the speed suggestion parameters are dynamically adjusted to determine a preliminary speed guidance range. Using the preliminary speed guidance range and combining it with specific information about the current distance, a secondary calibration is performed for the congestion level under different road conditions to obtain an adjusted speed guidance value. Based on the adjusted speed guidance value and the real-time monitoring of road condition data updates, if changes in traffic congestion or obstacle proximity are detected, the parameters are adjusted again to output the final speed guidance value.

[0019] Preferably, the risk judgment and early warning unit, based on the speed guidance value and real-time distance measurement results, if it determines that the user is approaching a dangerous area, triggers a warning mechanism to generate a corresponding dangerous area warning signal. This includes acquiring the target user's real-time distance data and current location information from the dynamic monitoring device, comparing the data with pre-established area division rules, and determining a preliminary judgment result that the user is approaching a dangerous area if the current location falls within the dangerous area range. Based on the preliminary judgment result, it acquires specific data of the speed guidance value and the real-time distance, compares them using a preset threshold, and generates a trigger condition if the real-time distance is below the safe range, obtaining a confirmation signal of approaching a dangerous area. Using the confirmation signal and the preset rules of the warning mechanism, it generates a corresponding warning signal using an audio prompt tool based on the specific location and distance judgment result of the dangerous area, determining the final signal output format. Based on the signal output format and in conjunction with an instant feedback tool, it transmits the generated warning signal to the target user's receiving device to obtain a guidance update value adapted to the current distance.

[0020] Preferably, the route adjustment unit, through a danger zone warning signal, links with the route planning module in the navigation system to obtain alternative route data and determine a new travel guidance scheme. This includes obtaining the target user's real-time location data and the range information of the danger zone from the warning signal; comparing the data with pre-established area division rules; if the real-time location exceeds the safe range, generating a route adjustment trigger condition and determining the start judgment of route planning; based on the route adjustment trigger condition, obtaining at least one alternative route data through the route planning module; comparing the distance between the alternative route and the danger zone using a preset distance judgment rule to obtain a route option that meets the safe range; using the route option that meets the safe range, combined with a navigation update tool, generating a new travel guidance scheme based on the specific direction of the alternative route and the target user's real-time location, and determining the guidance content adapted to the current scenario; and based on the new travel guidance scheme, using a signal transmission tool to transmit the guidance content to the target user's receiving device, and using a feedback mechanism to confirm the transmission status and determine whether the transmission is complete.

[0021] Preferably, the information update and output unit updates the user terminal display content according to the new travel guidance scheme, synchronously transmits the adjusted speed guidance value and warning information, and completes real-time dynamic adjustment by: obtaining the corresponding display content data from a pre-established guidance database according to the new travel guidance scheme; adapting the display content to the user terminal's interface layout rules; generating an adapted interface display scheme; and determining the final display content update scheme. Using the adapted interface display scheme, the unit transmits the adjusted speed guidance value and warning information to the user terminal using an information synchronization tool, verifies the transmission process using a preset transmission protocol, and obtains a confirmation result of the transmission status.

[0022] Preferably, the information update and output unit updates the content displayed on the user terminal according to the new travel guidance scheme, synchronously transmits the adjusted speed guidance value and warning information, and completes real-time dynamic adjustment. This also includes, if the transmission status confirmation result shows success, integrating the displayed content, speed guidance value, and warning information through a terminal update tool, refreshing the display logic of the user terminal, and determining whether the refresh is complete; based on the refresh result, using a real-time dynamic monitoring tool to track the presentation status of the displayed content and speed guidance value on the user terminal, comparing it with dynamic adjustment rules, and determining whether it meets the preset dynamic adjustment standards.

[0023] As can be seen from the above technical solution, the present invention has the following beneficial effects:

[0024] This safety guidance system for the visually impaired, equipped with real-time road condition analysis, achieves accurate real-time distance measurement by acquiring and correcting / filtering the raw position data between the user and target objects. Combined with dynamic road condition analysis, the system can adjust speed recommendations based on current traffic conditions and trigger warning mechanisms when approaching dangerous areas. Furthermore, this invention can be linked with navigation systems to automatically plan alternative routes and update the user terminal display when traffic congestion or obstacles are detected. Through this real-time dynamic adjustment mechanism, this invention effectively improves navigation accuracy and safety, providing users with smarter and more reliable traffic guidance, helping to optimize traffic flow, reduce accident risks, and improve overall traffic efficiency. Attached Figure Description

[0025] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0027] like Figure 1 As shown, the present invention provides a technical solution: a safety guidance system for the blind with real-time road condition analysis function, the system comprising:

[0028] The location data acquisition unit acquires the raw location data between the user and the target object, performs preliminary corrections for interference from different environmental factors, and obtains a preliminarily corrected location dataset.

[0029] The signal optimization unit generates a smoothed set of position data for the initially corrected position dataset, which is then used for subsequent spatial relationship determination.

[0030] The distance measurement unit determines the real-time distance between the user and the target object based on the smoothed position data set and a preset distance calculation model, and outputs accurate distance measurement results.

[0031] The traffic analysis unit obtains current traffic information from the complex environment of the traffic network through real-time distance measurement results and generates comprehensive traffic assessment data;

[0032] The speed suggestion generation unit adjusts the speed suggestion parameters based on comprehensive road condition assessment data and outputs a speed guidance value for the current distance and road conditions;

[0033] The risk assessment and early warning unit, based on the speed guidance value and real-time distance measurement results, will trigger a warning mechanism and generate a corresponding danger zone warning signal if it determines that the user is approaching a dangerous area.

[0034] The route adjustment unit, through the danger zone warning signal, links with the route planning module in the navigation system to obtain alternative route data and determine a new travel guidance plan;

[0035] The information update and output unit updates the content displayed on the user terminal according to the new travel guidance scheme, and synchronously transmits the adjusted speed guidance value and warning information to complete the real-time dynamic adjustment.

[0036] This safety guidance system for the visually impaired first uses a location data acquisition unit to collect raw location data between the user and target objects in real time, based on a built-in GPS receiver module or UWB positioning module. An environmental interference detection module identifies light intensity, electromagnetic interference, and multipath effects, and a weighted filtering algorithm performs preliminary correction to eliminate abnormal coordinate points, forming a preliminarily corrected location dataset. Subsequently, a signal optimization unit uses cubic spline interpolation and a weighted moving average algorithm to smooth the location dataset, outputting a location data set with strong continuity and low error fluctuation. Based on this smoothed location data set, the distance measurement unit calls the system's built-in distance calculation model based on Euclidean distance or the Haversine formula to calculate the actual distance between the user and target objects point by point in time sequence, outputting the corrected real-time distance value as the basic input for subsequent modules. The traffic analysis unit obtains traffic information within the user's current geographic area by calling accessed traffic network interfaces (such as the Gaode Map API or urban traffic big data platform), including traffic speed, traffic density, and road conditions. It then combines this information with real-time distance values ​​to construct a location-indexed traffic model, outputting the current route's traffic safety index and congestion level. The speed suggestion generation unit dynamically adjusts the suggested speed range based on comprehensive traffic assessment data and distance change rate using a gradient adjustment model, outputting a clear numerical speed guidance value. The risk assessment and early warning unit sets a warning trigger threshold and compares the speed guidance value with the distance value in real time. When it determines that the user is less than the set safety threshold (e.g., 2 meters) from a danger zone and the speed exceeds the suggested upper limit (e.g., 1.5 m / s), it triggers a voice warning and vibration signal, generating a danger zone warning signal and transmitting it to the route adjustment unit. Upon receiving the warning signal, the route adjustment unit calls the route planning module in the navigation system (e.g., A* or Dijkstra algorithm), using the current user location as the starting point, comprehensively analyzes the traversability and safety of alternative routes, generates at least one new route that does not pass through the danger zone, and sets it as the current navigation route. After receiving the new path, the information update and output unit synchronizes it to the user terminal, updates the voice command content through the voice broadcast module, updates the new navigation path on the visual interface, and transmits the adjusted speed guidance value and warning information to the user display module and vibration feedback module in real time, thus completing the dynamic update of the navigation path and guidance information and ensuring that the system has a complete closed-loop real-time response capability in practical applications.

[0037] The location data acquisition unit acquires raw location data between the user and the target object, performs preliminary corrections for interference from various environmental factors, and obtains a preliminarily corrected location dataset. This dataset includes sensor data from multiple device sources. The raw datasets collected by the devices are formatted using pre-established standardization rules to obtain a standardized set of location information. Based on the standardized location information set, a filtering tool is used to preliminarily clean the data to address environmental interference factors. If noise values ​​in the data exceed a preset threshold, some data is smoothed to obtain a cleaned location information set. Using the cleaned location information set and a data fusion method, the relative location information between the user and the target object from different device sources is integrated. If the deviation of the integrated data exceeds a preset threshold, the deviation is weighted and adjusted to determine the fused location dataset. The fused location dataset is then acquired, and a correction processing tool is used to perform a secondary verification based on environmental adaptation requirements. By comparing the correction result with the original dataset, it is determined whether the final corrected location dataset meets the accuracy requirements, thus obtaining the final location information result.

[0038] In this implementation, the location data acquisition unit first collects sensor data in real time from various devices, including a GPS module, an inertial measurement unit (IMU), a Bluetooth positioning system, and a camera, forming a raw dataset. The system then processes the collected data using pre-defined format standardization rules (e.g., unified to the WGS-84 coordinate system, unified timestamp format, and data granularity) to obtain a standardized location information set. For this set, the system performs preliminary cleaning using a filtering tool combining median filtering and threshold detection. For high-frequency noise values ​​or isolated points in the data, if they exceed a set threshold (e.g., deviation from the average value exceeding 10 meters), the corresponding data segments are smoothed using a three-point weighted average or spline interpolation method, outputting the cleaned location information set. Subsequently, the system initiates a fusion module to perform spatiotemporal registration of user location information from different sensors with target object location information, and executes a Kalman filter fusion algorithm to generate consistent relative location information. Based on this, if the deviation between the fusion results of each device exceeds a preset tolerance (e.g., 2 meters), the system performs weighted adjustment processing on the error portion to improve the reliability of the fused data. Finally, the system inputs the fused location data into the correction processing tool. This tool performs secondary verification based on multiple rounds of comparison (such as comparison with historical trajectories) and determines whether it meets the accuracy requirements (such as an error not exceeding 1.5 meters) based on the error difference. If it does, the final location information result is output for use by downstream modules; otherwise, a correction failure signal is issued and the current data is marked as invalid.

[0039] The signal optimization unit generates a smoothed location data set for the initially corrected location dataset, used for subsequent spatial relationship determination. This includes processing signal drift in the dataset using a mean filter, and performing point-by-point smoothing on abnormal fluctuations to obtain a drift-optimized location data set. Using this drift-optimized data set, a weighted average tool is used to further adjust the data set to address location deviations caused by environmental interference. If the deviation exceeds a preset threshold, some data is corrected to determine the deviation-adjusted location data set. The deviation-adjusted location data set is then acquired, and its timestamps are aligned using a time synchronization tool to meet data stability requirements. If a timestamp offset exceeds a preset threshold, the offset is interpolated to obtain a time-aligned location data set. Finally, from the time-aligned location data set, a coordinate mapping tool is used to transform the data set to a unified coordinate system to determine the final smoothed location data set.

[0040] The signal optimization unit first receives the location dataset after preliminary correction and uses a moving average filter with a set window width (e.g., 5 sampling points) to process continuous drift in the data, eliminating slow offset errors and forming a preliminary drift-free data set. The system then performs anomaly detection on this set, identifying data abrupt changes (e.g., single-point jumps exceeding 3σ), and corrects abnormal fluctuation segments through point-by-point smoothing operations (e.g., weighted median or neighborhood average), outputting a drift-optimized location data set. Based on this, the signal optimization unit calls a weighted averaging tool to perform a secondary adjustment of the data set according to device weights (e.g., GPS weight 0.6, IMU weight 0.4). If the deviation of any data point relative to the weighted result exceeds a preset threshold of 2 meters, linear compensation correction is performed, generating a deviation-adjusted location data set. Next, the system analyzes the timestamps of each data point within the dataset using a time synchronization tool. If a time drift greater than 100 milliseconds is found between adjacent data points, linear or cubic interpolation is used to smoothly fill the time interval, outputting a time-aligned location data set. Finally, based on a unified spatial reference coordinate system (such as WGS-84), the system uses a coordinate mapping tool to map all time-aligned data points onto a unified coordinate plane, eliminates non-physically reasonable coordinate points, and generates a final smoothed position data set for subsequent spatial relationship determination.

[0041] The distance measurement unit, based on the smoothed location data set and a preset distance calculation model, determines the real-time distance between the user and the target object, and outputs accurate distance measurement results. This includes processing the smoothed location data set using a coordinate mapping tool, considering the spatial relationship between the user's position and the target object, to transform the location information into a unified coordinate framework, resulting in a transformed location data set; using this transformed location data set, and for real-time measurement needs, using a time alignment tool to synchronize the timestamps of the data set; if the timestamp offset exceeds a preset threshold, interpolation is performed on the offset portion to determine the time-synchronized location data set; acquiring the time-synchronized location data set, and for distance calculation needs, using a geometric calculation tool to analyze the user's position and the target object's position point-by-point in the data set, calculating the straight-line distance between each set of position points, resulting in a preliminary distance data set; from this preliminary distance data set, using a weighted average tool to adjust the distance data to account for deviations caused by environmental interference; if the fluctuation amplitude exceeds a preset threshold, the fluctuation portion is smoothed, and the final real-time distance measurement result is determined.

[0042] The distance measurement unit first receives smoothed location data sets from the signal optimization unit. The system then uses a coordinate mapping tool to transform the user and target object coordinates into a unified geographic coordinate framework (such as WGS-84 or a local equidistant rectangular coordinate system), forming a unified coordinate data set. Subsequently, the system uses a time alignment tool to compare and verify the timestamps of each coordinate point in the data set. If the time offset between any time pair exceeds a set upper limit (e.g., 100 milliseconds), linear interpolation is used to fill in the missing time period, ensuring that the user's location and the target object's location have corresponding values ​​at the same time point, resulting in a time-synchronized location data set. Based on this, the system calls the built-in geometric calculation module to calculate the real-time distance between each user point and the target point pair according to the straight-line distance formula or the Haversine spherical distance formula, generating a preliminary distance data set. For this preliminary data set, the system further performs weighted averaging, calculating a moving average using the most recent N distance values ​​(e.g., 20 points within the past 10 seconds) to eliminate sudden errors. If a distance data fluctuation value exceeding a preset threshold is detected (e.g., the rate of change is greater than 1 meter / second), the abnormal segment is processed using a multi-stage smoothing algorithm (e.g., three-stage moving average) to finally generate a stable and reliable real-time distance measurement result, which is then provided to subsequent modules for risk assessment and path adjustment.

[0043] The traffic condition analysis unit acquires current traffic condition information from the complex environment of the traffic network through real-time distance measurement results, generating comprehensive traffic condition assessment data. This includes: based on the real-time distance measurement results, and considering the complex environmental characteristics of the traffic network, using data acquisition tools to obtain distance measurement data and corresponding traffic condition information from multiple road segments; if the timestamp offset between the distance measurement data and the traffic condition information exceeds a preset threshold, time alignment processing is performed to obtain a synchronized data combination; using the synchronized data combination, and for the needs of dynamic analysis, using data integration tools to match the distance measurement data and traffic condition information, obtaining real-time data for each road segment in the traffic network, and determining the classified traffic condition data set; obtaining the classified traffic condition data set, and for the goal of comprehensive assessment, using data fusion tools to weight the multi-source information in the traffic condition data set; if the traffic condition fluctuation of a road segment exceeds a preset threshold, smoothing adjustment is performed to determine the adjusted traffic condition characteristic data; based on the adjusted traffic condition characteristic data, and for the business requirements of traffic condition updates, using information mapping tools to associate the characteristic data with the actual road segments of the traffic network, obtaining the final traffic condition assessment result.

[0044] The system's traffic analysis unit first identifies multiple traffic segments involved in the user's current and potential travel paths based on real-time distance measurement results from the distance measurement unit. The system then invokes data acquisition tools to obtain real-time traffic information such as traffic speed, congestion index, and traffic status for the corresponding road segments from a traffic big data platform (such as an urban traffic monitoring system or a third-party API interface), and simultaneously records the corresponding timestamps. Simultaneously, each distance measurement result extracted from the navigation path also carries time information. The system performs alignment verification on the timestamps of both types of data. If the offset exceeds 100ms, time interpolation or a weighted nearest neighbor algorithm is used to achieve synchronization, generating a time-consistent data combination. Next, the system performs matching processing on this data combination, associating the distance data with the corresponding road segment traffic conditions through spatial mapping, forming a real-time data view of each road segment in the traffic network. Subsequently, the traffic analysis unit uses data fusion tools to weight and integrate traffic information from multiple sources (such as vehicle terminals, roadside cameras, and third-party platforms). If the traffic parameters of a certain road segment fluctuate beyond a set threshold (e.g., the congestion index changes by more than 30% within 5 minutes), a cubic spline or exponential smoothing model is used to process the data, outputting adjusted traffic feature data. Finally, the system uses an information mapping tool to bind these feature data with the actual road segment numbers in the map system, forming a final structured traffic assessment result. This result includes the current traffic level, safety risk indicators, and recommended travel methods for each target road segment, which are then used by the downstream route planning and speed suggestion modules.

[0045] The speed suggestion generation unit adjusts speed suggestion parameters based on comprehensive road condition assessment data and outputs a speed guidance value for the current distance and road conditions. This includes acquiring road condition data and obstacle distance information from real-time monitoring equipment, classifying the data according to pre-established road condition assessment rules, and obtaining the current congestion level and distance judgment results based on the characteristics of traffic congestion and obstacle distance. Based on the congestion level and distance judgment results, a preset threshold is used for comparison. If the congestion level is higher than the threshold or the obstacle distance is lower than the safe range, the speed suggestion parameters are dynamically adjusted to determine a preliminary speed guidance range. Using the preliminary speed guidance range and combining it with specific information about the current distance, a secondary calibration is performed for the congestion level under different road conditions to obtain an adjusted speed guidance value. Based on the adjusted speed guidance value and the real-time monitoring of road condition data updates, if changes in traffic congestion or obstacle proximity are detected, the parameters are adjusted again to output the final speed guidance value.

[0046] The speed suggestion generation unit first collects traffic flow, traffic status, and obstacle distance information along the user's current path from connected real-time monitoring devices (including cameras, LiDAR, UWB positioning modules, etc.). The system then calls upon its built-in road condition assessment rule base to categorize the collected data, classifying it according to rules such as traffic speed below 5 km / h as congestion and obstacle distance less than 1.5 meters as danger, to obtain the current congestion level (e.g., mild, moderate, severe) and obstacle proximity level (e.g., safe, warning, dangerous). Next, the system compares the congestion level and obstacle distance values ​​with preset thresholds. For example, if the congestion index exceeds "moderate," or the obstacle distance is less than the safe threshold (1 meter), a dynamic adjustment mechanism is activated. This mechanism dynamically adjusts the output range downwards or upwards based on standard speed suggestion parameters (e.g., 1.2 m / s to 0.5 m / s), forming a preliminary speed guidance range. Subsequently, the system combines real-time distance data between the user and the target object provided by the distance measurement unit to perform a secondary calibration of the speed guidance value. Specifically, in cases of severe congestion and when the obstacle distance is less than 0.8 meters, the maximum speed is limited to 0.3 meters per second. The system further integrates real-time data stream monitoring to continuously track changes in road conditions. If the traffic status changes from "smooth" to "congested" or an obstacle suddenly enters the warning distance (e.g., less than 0.6 meters), the system immediately updates the recommended parameters, performs a final adjustment to the speed guidance value, and outputs the final speed value to the route adjustment and user prompt module.

[0047] The risk assessment and early warning unit, based on the speed guidance value and real-time distance measurement results, determines if the user is approaching a dangerous area. It then triggers a warning mechanism to generate a corresponding dangerous area warning signal. This involves acquiring the target user's real-time distance data and current location information from dynamic monitoring equipment, comparing the data with pre-established area division rules, and confirming the user's approach to a dangerous area if the current location falls within that area. Based on this preliminary assessment, it acquires the specific data of the speed guidance value and the real-time distance, comparing them with a preset threshold. If the real-time distance is below a safe range, it generates a trigger condition, obtaining a confirmation signal of approaching a dangerous area. Using this confirmation signal and the preset rules of the warning mechanism, it generates a corresponding warning signal based on the specific location and distance of the dangerous area, using an audio prompt tool to determine the final signal output format. Finally, based on the signal output format and in conjunction with an instant feedback tool, it transmits the generated warning signal to the target user's receiving device to obtain an updated guidance value adapted to the current distance.

[0048] The risk assessment and early warning unit first calls upon dynamic monitoring equipment (such as positioning modules, radar sensors, or camera systems) to obtain the user's real-time location information and precise distance data between the user and surrounding obstacles. The system loads a pre-set area division rule library, which sets the boundaries of dangerous areas (such as intersections, construction zones, and areas with high traffic density) based on map data and the site environment, and performs spatial matching analysis on the user's current location information. If the current coordinates fall within the boundary range of any dangerous area (e.g., within 10 meters), a preliminary judgment result is output, confirming that the user is approaching a dangerous area. Subsequently, the system extracts the current speed guidance value and real-time distance data, comparing them with set thresholds (e.g., distance less than 1.2 meters or speed greater than 0.8 meters per second). If both low distance and high speed conditions are met simultaneously, a trigger condition is generated, and a "dangerous area approaching" confirmation signal is output. Based on this confirmation signal, the system further calls the warning mechanism parameter table, combining the current location with the orientation and risk level of obstacles, and selects an appropriate prompting method (e.g., a buzzer alarm, a voice announcement "Danger area ahead, please slow down") to determine the final output format. The system ultimately transmits the warning signal to the target user's device in real time via instant feedback tools (such as Bluetooth headsets, smart bracelets, or mobile terminals), and updates the suggested guidance parameters (such as reducing the speed guidance value to 0.3 m / s) based on the user's reaction and the current distance, thereby achieving synchronous updates of dynamic risk warnings and navigation guidance.

[0049] The route adjustment unit, upon receiving a danger zone warning signal, triggers the route planning module in the navigation system to acquire alternative route data and determine a new travel guidance scheme. This includes obtaining the target user's real-time location data and the extent of the danger zone from the warning signal, comparing the data with pre-established area division rules, and generating a route adjustment trigger condition if the real-time location exceeds the safe range, thus initiating the route planning process. Based on the trigger condition, the route planning module acquires data for at least one alternative route, compares the distance between the alternative route and the danger zone using preset distance judgment rules, and obtains route options that meet the safe range. Using these safe route options, and in conjunction with a navigation update tool, a new travel guidance scheme is generated based on the specific direction of the alternative route and the target user's real-time location, determining guidance content suitable for the current scenario. Based on the new travel guidance scheme, the guidance content is transmitted to the target user's receiving device using a signal transmission tool, and a feedback mechanism confirms the transmission status to determine whether the transmission is complete.

[0050] The path adjustment unit receives danger zone warning signals from the risk assessment and early warning unit and extracts the user's real-time location and the boundary coordinates of the danger zone. The system invokes built-in area division rules to perform spatial judgment on the real-time location. If the current location is in or about to enter a danger zone (e.g., less than 2 meters from the boundary), path adjustment trigger conditions are automatically generated, and the path planning module is activated. The path planning module uses the current user location as the starting point and the original target location as the ending point, and calls a map engine (e.g., A*, Dijkstra, or dynamic obstacle avoidance algorithms) to calculate multiple alternative paths. According to preset path safety assessment rules, the system calculates the minimum distance between each segment of the alternative path and the danger zone. If the minimum distance is greater than a set safety threshold (e.g., 5 meters), the path is marked as a safe path, forming a set of selectable paths. Based on this, the system further uses a navigation update tool to filter out the optimal alternative path based on the current user's orientation, location stability, and the turning angle of the path direction, and generates a new travel guidance plan with step-by-step navigation instructions, directional guidance, and landmark prompts. This guidance content is sent in real-time to the user's terminal, such as a voice headset or smart guide device, via signal transmission tools (e.g., Bluetooth, Wi-Fi, or cellular network). To ensure successful information transmission, the system also activates a feedback mechanism to detect the terminal's confirmation signal. If no confirmation is received within a preset time, the system will retry the transmission or prompt the user for confirmation to ensure that the path adjustment result is successfully received and executed.

[0051] The information update and output unit updates the content displayed on the user terminal according to the new travel guidance scheme, synchronously transmits the adjusted speed guidance value and warning information, and completes real-time dynamic adjustment. This includes obtaining the corresponding display content data from a pre-established guidance database according to the new travel guidance scheme, adapting it to the user terminal's interface layout rules, generating an adapted interface display scheme, and determining the final display content update scheme. Through the adapted interface display scheme, the unit uses an information synchronization tool to transmit the adjusted speed guidance value and warning information to the user terminal, verifies the transmission process using a preset transmission protocol, and obtains a confirmation result of the transmission status.

[0052] Upon receiving a new travel guidance plan generated by the route adjustment unit, the information update and output unit immediately retrieves the corresponding graphic elements, text prompts, voice content, and warning icons from the system's pre-set guidance database. The system adapts the display data to the user terminal's interface layout rules (such as screen size, resolution, and color contrast requirements). For example, it automatically adjusts text size and color contrast for users with low vision, or optimizes layer layout and focus position for smart glasses devices. After adaptation, a complete interface display plan is generated and used as the base template for updating display content. The system then calls information synchronization tools (such as Bluetooth communication modules, Wi-Fi Direct, MQTT protocol push modules, etc.) to bind speed guidance values ​​and danger warning information to the aforementioned display template and transmit them synchronously to the user terminal. To ensure the stability and accuracy of the transmission process, the system applies a pre-set transmission protocol (such as TCP / IP or BLE timed verification mechanism) to perform real-time verification of the transmission status, including data packet integrity verification and confirmation response latency monitoring. Once the transmission is confirmed to be complete, the system marks the update task as "complete" and allows the user terminal to automatically refresh the display interface, update voice broadcasts and other interactive prompts, achieving integrated dynamic guidance updates from path changes and speed adjustments to warning reminders.

[0053] The information update and output unit updates the content displayed on the user terminal according to the new travel guidance scheme, synchronously transmits the adjusted speed guidance value and warning information, and completes real-time dynamic adjustment. If the confirmation result of the transmission status shows success, it integrates the displayed content, speed guidance value and warning information through the terminal update tool, refreshes the display logic of the user terminal, and determines whether the refresh is complete. Based on the refresh result, it uses a real-time dynamic monitoring tool to track the presentation status of the displayed content and speed guidance value of the user terminal, compares it with the dynamic adjustment rules, and determines whether it meets the preset dynamic adjustment standards.

[0054] After the aforementioned guidance content, speed guidance values, and warning information are successfully transmitted to the user terminal, this unit immediately invokes the terminal update tool to logically integrate the received information and perform a structural refresh operation based on the terminal display architecture (such as split-screen layout, scrolling display area, and voice broadcast channel). The refresh process includes multiple sub-steps such as updating page elements, adjusting color and font rendering, and triggering sound prompts. After the refresh, the system calls the status detection module to read display status identifiers (such as refresh flags and content consistency check codes) to determine whether the refresh is complete. If the refresh is confirmed to be complete, the system further activates the real-time dynamic monitoring tool, which periodically samples the user terminal interface output status and speed value feedback to generate a presentation status data stream. The data stream will be compared in real time with the dynamic adjustment rules set in the system. For example, the delay in updating the displayed content must not exceed 2 seconds, and the error in the speed value presentation must not exceed ±0.1 m / s. If the detection result meets all the comparison items, it is determined that the dynamic adjustment process meets the standard. If there is a deviation, the compensation update process will be automatically triggered, including secondary data push, re-triggering of voice prompts, and highlighting of prompt windows, to ensure that users receive accurate and complete guidance information during movement.

[0055] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A safety guidance system for the visually impaired with real-time road condition analysis capabilities, characterized in that, The system includes: The location data acquisition unit acquires the raw location data between the user and the target object, performs preliminary corrections for interference from different environmental factors, and obtains a preliminarily corrected location dataset. The signal optimization unit generates a smoothed set of position data for the initially corrected position dataset, which is then used for subsequent spatial relationship determination. The distance measurement unit determines the real-time distance between the user and the target object based on the smoothed position data set and a preset distance calculation model, and outputs accurate distance measurement results. The traffic analysis unit obtains current traffic information from the complex environment of the traffic network through real-time distance measurement results and generates comprehensive traffic assessment data; The speed suggestion generation unit adjusts the speed suggestion parameters based on comprehensive road condition assessment data and outputs a speed guidance value for the current distance and road conditions; The risk assessment and early warning unit, based on the speed guidance value and real-time distance measurement results, will trigger a warning mechanism and generate a corresponding danger zone warning signal if it determines that the user is approaching a dangerous area. The route adjustment unit, through the danger zone warning signal, links with the route planning module in the navigation system to obtain alternative route data and determine a new travel guidance plan; The information update and output unit updates the content displayed on the user terminal according to the new travel guidance scheme, and synchronously transmits the adjusted speed guidance value and warning information to complete the real-time dynamic adjustment.

2. A safety guidance system for the visually impaired with real-time road condition analysis function according to claim 1, characterized in that: The location data acquisition unit acquires the raw location data between the user and the target object, performs preliminary correction for interference from different environmental factors, and obtains a preliminarily corrected location dataset. This dataset includes sensor data from multiple device sources. For the raw dataset collected by the devices, a pre-established standardization rule is used for format unification to obtain a standardized location information set. Based on the standardized location information set, a filtering tool is used to preliminarily clean the data to address environmental interference factors. If the noise value detected in the data exceeds a preset threshold, a portion of the data is smoothed to obtain a cleaned location information set. Using the cleaned location information set and a data fusion method, the relative location information between the user's location and the target object from different device sources is integrated. If the deviation of the integrated data exceeds a preset threshold, the deviation portion is weighted and adjusted to determine the fused location dataset. The fused location dataset is then acquired, and a correction processing tool is used to perform a secondary verification of the data to meet environmental adaptation requirements. By comparing the correction result with the original dataset, it is determined whether the final corrected location dataset meets the accuracy requirements, thus obtaining the final location information result.

3. A safety guidance system for the visually impaired with real-time road condition analysis function according to claim 1, characterized in that: The signal optimization unit generates a smoothed location data set for the initially corrected location dataset, used for subsequent spatial relationship determination. This includes processing signal drift in the dataset using a mean filter, smoothing abnormal fluctuations point-by-point to obtain a drift-optimized location data set; using this drift-optimized set, a weighted average is applied to adjust the data set for location deviations caused by environmental interference. If the deviation exceeds a preset threshold, some data is corrected to determine the deviation-adjusted location data set; the time synchronization tool is used to align the timestamps of the adjusted data set to ensure data stability. If a timestamp offset exceeds a preset threshold, interpolation is applied to the offset portion to obtain a time-aligned location data set; and finally, a coordinate mapping tool is used to transform the data set to a unified coordinate system to determine the final smoothed location data set.

4. A safety guidance system for the visually impaired with real-time road condition analysis function according to claim 1, characterized in that: The distance measurement unit determines the real-time distance between the user and the target object based on the smoothed position data set and a preset distance calculation model, and outputs accurate distance measurement results. This includes processing the smoothed position data set using a coordinate mapping tool to transform the position information into a unified coordinate framework, resulting in a transformed position data set; synchronizing the timestamps of the data set using a time alignment tool to meet real-time measurement requirements; and interpolating the offset if it exceeds a preset threshold to determine a time-synchronized position data set. Finally, based on the distance calculation needs, a geometric calculation tool analyzes the user's and target object's positions point-by-point in the data set to calculate the straight-line distance between each set of positions, resulting in a preliminary distance data set. From the initial distance data set, a weighted average tool is used to adjust the distance data to account for deviations caused by environmental interference. If the fluctuation amplitude exceeds a preset threshold, the fluctuating part is smoothed to determine the final real-time distance measurement result.

5. A safety guidance system for the visually impaired with real-time road condition analysis function according to claim 1, characterized in that: The traffic condition analysis unit acquires current traffic condition information from the complex environment of the traffic network through real-time distance measurement results, generating comprehensive traffic condition assessment data. This includes acquiring distance measurement data and corresponding traffic condition information from multiple road segments using data acquisition tools based on the real-time distance measurement results and considering the complex environmental characteristics of the traffic network. If the timestamp offset between the distance measurement data and the traffic condition information exceeds a preset threshold, time alignment processing is performed to obtain a synchronized data combination. Using the synchronized data combination, and considering the needs of dynamic analysis, a data integration tool is used to match the distance measurement data and traffic condition information to acquire real-time data for each road segment in the traffic network, determining a categorized traffic condition data set. After acquiring the categorized traffic condition data set, and considering the goal of comprehensive assessment, a data fusion tool is used to weight the multi-source information in the traffic condition data set. If the traffic condition fluctuation of a road segment exceeds a preset threshold, a smoothing adjustment is performed to determine the adjusted traffic condition characteristic data. Based on the adjusted traffic condition characteristic data, and considering the business requirements of traffic condition updates, an information mapping tool is used to associate the characteristic data with the actual road segments of the traffic network to obtain the final traffic condition assessment result.

6. A safety guidance system for the visually impaired with real-time road condition analysis function according to claim 1, characterized in that: The speed suggestion generation unit adjusts speed suggestion parameters based on comprehensive road condition assessment data and outputs a speed guidance value for the current distance and road conditions. This includes acquiring road condition data and obstacle distance information from real-time monitoring equipment, classifying the data using pre-established road condition assessment rules, and determining the current congestion level and distance judgment results based on the characteristics of traffic congestion and obstacle distance. A preset threshold is used for comparison based on the congestion level and distance judgment results. If the congestion level is higher than the threshold or the obstacle distance is lower than the safe range, the speed suggestion parameters are dynamically adjusted to determine a preliminary speed guidance range. Using the preliminary speed guidance range and combining it with specific information about the current distance, a secondary calibration is performed for the congestion level under different road conditions to obtain an adjusted speed guidance value. Based on the adjusted speed guidance value and the real-time monitoring of road condition data updates, if changes in traffic congestion or obstacle proximity are detected, the parameters are adjusted again to output the final speed guidance value.

7. A safety guidance system for the visually impaired with real-time road condition analysis function according to claim 1, characterized in that: The risk assessment and early warning unit, based on the speed guidance value and real-time distance measurement results, triggers a warning mechanism if it determines that the user is approaching a dangerous area. This mechanism generates a corresponding dangerous area warning signal. The process includes acquiring the target user's real-time distance data and current location information from dynamic monitoring equipment, comparing the data with pre-established area division rules, and determining a preliminary assessment result if the current location falls within the dangerous area range. Based on this preliminary assessment, the unit acquires specific data on the speed guidance value and the real-time distance, comparing it with a preset threshold. If the real-time distance is below a safe range, a trigger condition is generated, resulting in a confirmation signal of approaching a dangerous area. Using this confirmation signal and the preset rules of the warning mechanism, a corresponding warning signal is generated based on the specific location and distance of the dangerous area, employing an audio prompt tool to determine the final signal output format. Finally, based on the signal output format and in conjunction with an instant feedback tool, the generated warning signal is transmitted to the target user's receiving device to obtain an updated guidance value adapted to the current distance.

8. A safety guidance system for the visually impaired with real-time road condition analysis function according to claim 1, characterized in that: The route adjustment unit, through a danger zone warning signal, links with the route planning module in the navigation system to obtain alternative route data and determine a new travel guidance scheme. This includes obtaining the target user's real-time location data and the range information of the danger zone from the warning signal, comparing the data with pre-established area division rules, and generating a route adjustment trigger condition if the real-time location exceeds the safe range, thus determining the start judgment of route planning. Based on the route adjustment trigger condition, the route planning module obtains data for at least one alternative route, compares the distance between the alternative route and the danger zone using a preset distance judgment rule, and obtains a route option that meets the safe range. Using the route option that meets the safe range, combined with the navigation update tool, a new travel guidance scheme is generated based on the specific direction of the alternative route and the target user's real-time location, determining the guidance content adapted to the current scenario. Based on the new travel guidance scheme, the guidance content is transmitted to the target user's receiving device using a signal transmission tool, and the transmission status is confirmed using a feedback mechanism to determine whether the transmission is complete.

9. A safety guidance system for the visually impaired with real-time road condition analysis function according to claim 1, characterized in that: The information update and output unit updates the content displayed on the user terminal according to the new travel guidance scheme, synchronously transmits the adjusted speed guidance value and warning information, and completes real-time dynamic adjustment, including obtaining the corresponding display content data from the pre-established guidance database according to the new travel guidance scheme, adapting it to the interface layout rules of the user terminal, generating the adapted interface display scheme, and determining the final display content update scheme. Using the adapted interface display scheme, the adjusted speed guidance value and warning information are transmitted to the user terminal through an information synchronization tool. The transmission process is verified in conjunction with the preset transmission protocol to obtain a confirmation result of the transmission status.

10. A safety guidance system for the visually impaired with real-time road condition analysis function according to claim 9, characterized in that: The information update and output unit updates the content displayed on the user terminal according to the new travel guidance scheme, synchronously transmits the adjusted speed guidance value and warning information, and completes real-time dynamic adjustment. It also includes, if the confirmation result of the transmission status shows success, integrating the displayed content, speed guidance value and warning information through the terminal update tool, refreshing the display logic of the user terminal, and determining whether the refresh is complete; based on the refresh result, using a real-time dynamic monitoring tool to track the presentation status of the displayed content and speed guidance value of the user terminal, comparing it with the dynamic adjustment rules, and determining whether it meets the preset dynamic adjustment standards.

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