Intelligent positioning method and system for vehicle rescue state

Abstract

The application provides a kind of intelligent positioning method and system of vehicle rescue state, it is related to vehicle rescue positioning technical field.The method includes receiving to vehicle-mounted end historical position information, if the curve corresponding to its analysis is sawtooth curve with amplitude, vibration frequency exceeding threshold value in set time length, determine to enter GPS signal invalid region.After receiving rescue request signal, obtain last effective positioning point before invalidation, vehicle speed data and historical trajectory information, determine predicted driving distance in combination with vehicle speed and effective time, then determine candidate path in combination with historical trajectory, positioning point and topographic path map, determine candidate position set matched with predicted distance on candidate path, determine the final position to be rescued in combination with ground base station position information.The positioning method of this multi-dimensional information fusion can not only realize intelligent prediction positioning of vehicle position in the case of GPS signal failure, but also provide reliable position basis for timely rescue work.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicle rescue positioning, and particularly relates to an intelligent positioning method and system for vehicle rescue state. BACKGROUND

[0002] With the rapid growth of the number of cars, the demand for vehicle rescue is increasing. Traditional vehicle rescue often requires the vehicle owner to report the vehicle location information through a telephone or other means. This method has the problems of inaccurate information transmission and long response time, which seriously affects the rescue efficiency, easily causes rescue delay, and brings inconvenience to the vehicle owner.

[0003] In view of the above problems, the intelligent positioning system for vehicle rescue based on GPS positioning has been developed. The system installs a GPS positioning module on the vehicle. When the vehicle breaks down and needs rescue, the system automatically obtains the latitude and longitude information of the vehicle and sends it to the rescue platform. The rescue personnel can quickly reach the rescue site according to the positioning information, which improves the rescue efficiency.

[0004] However, there is a problem in the prior art that when the vehicle to be rescued is located in a special terrain area such as a mountainous area or a valley, the satellite signal of the GPS is easily blocked or reflected, causing the GPS to fail, resulting in large deviation of the positioning information. In this case, the rescue vehicle is difficult to accurately find the specific position of the vehicle to be rescued, which not only delays the rescue time, but also increases the rescue cost and affects the rescue effect. SUMMARY

[0005] The present application provides an intelligent positioning method and system for vehicle rescue state, which is used for accurate positioning of the vehicle to be rescued in the GPS signal failure area (such as complex terrain such as valley, suburb, etc.).

[0006] In a first aspect, the application provides an intelligent positioning method for a vehicle rescue state, which comprises: after receiving historical position information sent by a vehicle-mounted terminal in a communication connection, if a curve corresponding to the historical position information is a sawtooth curve with an amplitude exceeding a set amplitude and a vibration frequency exceeding a set frequency within a set time length, it is determined that the vehicle-mounted terminal has entered a GPS signal invalid area; after receiving a vehicle rescue request signal sent by the vehicle-mounted terminal at a first time after entering the GPS signal invalid area, obtaining a last valid positioning point of a vehicle to be rescued at a second time before entering the GPS signal invalid area, vehicle speed data and historical trajectory information within a preset time length; determining a predicted distance traveled by the vehicle after entering the GPS signal invalid area in combination with the vehicle speed data and the effective time between the second time and the first time; determining a candidate predicted path of travel in combination with the historical trajectory information, the last valid positioning point and a topographic path map within a preset range of the last valid positioning point; determining a candidate position information set matching the predicted distance traveled on the candidate predicted path of travel; determining base station position information of a ground base station sending the vehicle rescue request signal; determining final position information closest to the base station position information from the candidate position information set, and determining the final position information as a final position to be rescued.

[0007] By adopting the above technical solution, the GPS signal invalid area is first identified by analyzing the curve characteristics of the historical position information, so that positioning abnormalities can be discovered in a timely manner. In combination with the last valid positioning point, vehicle speed data and historical trajectory of the vehicle before entering the signal invalid area, the predicted distance traveled by the vehicle can be calculated. The possible travel path is further determined through the topographic path map, and the final position is determined in combination with the base station position information. This multi-dimensional information fusion positioning method can not only realize intelligent prediction positioning of the vehicle position in the case of GPS signal invalidity, but also significantly improve the positioning accuracy, providing a reliable position basis for timely rescue work.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the last valid positioning point of the vehicle to be rescued at the second time before entering the GPS signal invalid area is obtained, specifically comprising: taking a time before the set time length of the sawtooth curve as the second time, and determining historical position information corresponding to the time before the set time length of the sawtooth curve as the last valid positioning point.

[0009] By adopting the above technical solution, the accuracy of the last valid positioning point is ensured by taking the time before the sawtooth curve appears as the last valid time point. This time point selection method based on curve characteristics avoids using unstable positioning data, ensuring the reliability of the basic data for subsequent position prediction from the source, making the entire positioning prediction process more accurate and reliable, and thus improving the accuracy of the final rescue position determination.

[0010] In some embodiments of the first aspect, in some embodiments, the step of determining the second time point before the set time length and the historical position information corresponding to the second time point as the last valid positioning point comprises: obtaining P continuous historical position points before the sawtooth curve appears; pairing the P continuous historical position points in time sequence two by two, and calculating the position offset distance between the adjacent two position points; dividing each position offset distance by the corresponding time interval to obtain the position offset rate per unit time; comparing each position offset rate with the actual vehicle speed reported by the vehicle-mounted terminal in the corresponding time period, and calculating a plurality of position drift degrees; when the plurality of position drift degrees are less than a preset offset degree threshold, the time point at which the last position drift degree less than the preset threshold is taken as the second time point, and the corresponding position point is determined as the last valid positioning point.

[0011] By adopting the above technical solution, the calculation and judgment mechanism of the position drift degree is introduced, and by comparing the position offset rate with the actual vehicle speed, the reliability of the positioning data can be more accurately judged. When the position drift degrees of the continuous multiple points are within a reasonable range, the last valid positioning point is determined. This multi-point verification method greatly improves the reliability of the last valid positioning point, and provides a more accurate starting reference point for subsequent position prediction.

[0012] In some embodiments of the first aspect, in some embodiments, the step of determining the candidate predicted-to-go path based on the historical trajectory information, the last valid positioning point, and the topographic path map within the preset range of the last valid positioning point comprises: obtaining road information within a preset range of the last valid positioning point from the topographic path map, the road information including feasible road paths and road direction information; determining N last trajectory points before the last valid positioning point according to the historical trajectory information, and determining a trajectory direction according to the trajectory points; calculating the angle between the trajectory direction and the road direction information, and eliminating the feasible road paths with an angle greater than a preset angle threshold, and determining the remaining feasible road paths as the candidate predicted-to-go path.

[0013] By adopting the above technical solution, the historical trajectory direction is compared with the road direction information, and the roads with large deviation from the actual driving direction are eliminated, which significantly reduces the possible path options. This path screening method based on historical trajectory not only greatly improves the accuracy of the candidate path, but also reduces the calculation complexity of subsequent position prediction, so that the finally determined position to be rescued is more consistent with the actual driving trajectory characteristics of the vehicle.

[0014] In some embodiments of the first aspect, before the step of determining the predicted distance traveled by the vehicle after the GPS signal failure based on the vehicle speed data and the effective time between the second time and the first time, the method further comprises: obtaining driving record information sent by the vehicle terminal; determining whether the vehicle to be rescued stayed between the second time and the first time based on the driving record information, and determining the duration of the stay; and obtaining the effective time by subtracting the duration of the stay from the total time between the second time and the first time.

[0015] By analyzing the driving record information to identify the vehicle stay state and calculate the duration of the stay, the actual driving time of the vehicle can be accurately obtained. This time calculation method considering the vehicle stay factor avoids the distance prediction deviation caused by counting the parking time as driving time, significantly improves the accuracy of the predicted distance traveled, and provides a more accurate distance reference for subsequent position determination.

[0016] In some embodiments of the first aspect, after the step of obtaining the effective time by subtracting the duration of the stay from the total time between the second time and the first time, the method further comprises: determining the real-time vehicle speed data within the effective time based on the driving record information after determining that the vehicle to be rescued stayed between the second time and the first time; and determining the predicted distance traveled based on the real-time vehicle speed data and the effective time.

[0017] By using the above technical solution, the effective driving time is corrected based on the stay time, and the predicted distance traveled is calculated based on the real-time vehicle speed data. This dynamic speed-time integration calculation method takes into account the actual situation of vehicle speed changes, avoids the calculation deviation that may be caused by using average speed, and makes the calculation result of the predicted distance more accurate, providing a reliable distance basis for determining the rescue position.

[0018] In some embodiments of the first aspect, after the step of determining the final position information closest to the base station position information from the candidate position information set and determining the final position information as the final rescue position, the method further comprises: sending a signal strength query request to a plurality of target base stations within a set range of the final rescue position; receiving signal strength data for the vehicle terminal and target base station position information returned by each target base station; and calibrating the final rescue position based on the signal strength data returned by at least three target base stations and the target base station position information using a weighted triangular positioning algorithm to obtain a calibrated final rescue position.

[0019] By adopting the technical scheme, the multi-base station signal strength data and the weighted triangular positioning algorithm are introduced to calibrate the preliminarily determined rescue position. The multi-base station cooperative positioning method based on actual signal strength can effectively eliminate the error of single-base station positioning, significantly improve the positioning accuracy through multi-dimensional position calibration, and finally obtain more accurate and reliable rescue position coordinates.

[0020] In a second aspect, the present application provides an intelligent positioning system, comprising: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is configured to store computer program code, the computer program code comprising computer instructions, the one or more processors invoking the computer instructions to enable the intelligent positioning system to perform the method described in the first aspect and any possible implementation manner of the first aspect.

[0021] In a third aspect, the present application provides a computer readable storage medium comprising instructions that, when executed on an intelligent positioning system, cause the intelligent positioning system to perform the method described in the first aspect and any possible implementation manner of the first aspect.

[0022] In a fourth aspect, the present application provides a computer program product that, when executed on an intelligent positioning system, causes the intelligent positioning system to perform the method described in the first aspect and any possible implementation manner of the first aspect.

[0023] The one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0024] 1. By adopting the above technical scheme, since the technical means of identifying GPS signal failure based on historical position information curve characteristics, combining distance prediction with last valid positioning point and vehicle speed data, and multi-dimensional fusion positioning with terrain path map and base station position information are adopted, the technical problem that the position of the rescue vehicle cannot be accurately positioned in the GPS signal failure area in the prior art is effectively solved, and the technical effect of intelligently predicting and positioning the position of the vehicle in the GPS signal failure case is achieved, and the positioning accuracy is significantly improved.

[0025] 2. By adopting the above technical scheme, since the technical means of comparing and verifying the actual vehicle speed based on continuous multi-point position drift degree calculation, and dynamically determining the last valid positioning point by setting a preset threshold are adopted, the technical problem that the starting reference position is inaccurate because the GPS signal failure time point cannot be accurately determined in the prior art is effectively solved, and the technical effect of accurately identifying the last valid positioning point and providing a reliable reference point for subsequent position prediction is achieved.

[0026] 3. By adopting the above technical solutions, since the vehicle staying state is identified based on the driving record information, and the actual effective driving time is corrected by the staying time, the technical problem of the deviation of the driving distance prediction caused by the vehicle staying factor in the prior art is effectively solved, and more accurate vehicle driving distance prediction is achieved, and the technical effect of providing accurate distance reference is provided. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 is a flowchart of the intelligent positioning method of the vehicle rescue state in the embodiments of the present application;

[0028] Figure 2 is a flowchart of the intelligent positioning method of the vehicle rescue state in the embodiments of the present application;

[0029] Figure 3 is another application scenario diagram of the intelligent positioning method of the vehicle rescue state in the embodiments of the present application;

[0030] Figure 4 is an entity device structure diagram of the intelligent positioning system in the embodiments of the present application. DETAILED DESCRIPTION

[0031] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments and are not intended to be limiting to the present application. As used in the specification and the appended claims of the present application, the singular forms "a," "an" and "the" are intended to include both singular and plural forms, unless the context clearly indicates otherwise. It will be further understood that the terms "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0032] Hereinafter, the terms "first" and "second" are only used for description purposes, and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first" and "second" can explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, the meaning of "a plurality of" is two or more, unless otherwise specified.

[0033] For ease of understanding, the method provided by the present embodiment is described in the flow. Please refer to Figure 1 is a flowchart of the intelligent positioning method of the vehicle rescue state in the embodiments of the present application;

[0034] S101, after receiving the historical position information sent by the vehicle-mounted end of the communication connection, if the curve corresponding to the historical position information is a sawtooth curve with an amplitude exceeding a set amplitude and a vibration frequency exceeding a set frequency within a set time length, it is determined that the vehicle-mounted end has entered a GPS signal failure area;

[0035] The historical position information represents a sequence of GPS positioning coordinates collected by the vehicle-mounted end at a preset time interval. The vehicle-mounted end refers to a smart terminal device installed on a vehicle with GPS positioning and communication functions. The sawtooth curve refers to a curve that presents irregular fluctuations in a coordinate system with time as the horizontal axis and position coordinates as the vertical axis, similar to a sawtooth shape, reflecting unstable changes in position information. The set amplitude is used to represent the maximum allowed range of position fluctuations, for example, set to 50 meters, if the position changes exceed this distance, it is considered abnormal fluctuations. The set frequency refers to the threshold number of position changes per unit time, for example, more than 8 times per minute, which may be abnormal. The GPS signal failure area refers to an area where the quality of GPS signal reception is significantly reduced due to factors such as terrain and buildings. In mountainous and canyon areas, satellite signals are difficult to transmit stably due to mountain blockage.

[0036] The user can bind the vehicle-mounted end with the platform of the intelligent positioning system in advance, which can be a smart positioning function of the trailer company platform. Specifically, when the user binds the vehicle-mounted end with the platform of the intelligent positioning system in advance, and drives into non-flat areas such as mountainous and canyon areas, the vehicle-mounted end combines vehicle positioning information and map data to determine that it has entered a non-flat area, and sends historical position information to the intelligent positioning system. The intelligent positioning system receives the information and processes the historical position information in a sliding window manner, and the window length is the set time length. In each window, the system calculates the distance between adjacent position points to determine the position fluctuation amplitude, and counts the number of position changes to obtain the vibration frequency. If the amplitude continuously exceeds the set amplitude and the vibration frequency is higher than the set frequency in a plurality of consecutive sliding windows, the position-time curve drawn at this time presents a sawtooth shape, and the system can determine that the vehicle-mounted end has entered a GPS signal failure area. In addition, the system will also make auxiliary judgments combined with surrounding terrain data. If the area where the vehicle is located has terrain features such as high mountains, dense forests, and other signal-shielding features, it will further enhance the judgment basis for signal failure and reduce false positives caused by normal driving bumps or temporary signal interference.

[0037] S102, after receiving the vehicle rescue request signal sent by the vehicle-mounted end at the first time after entering the GPS signal failure area, obtaining the last valid positioning point, vehicle speed data and historical trajectory information within a preset time length of the vehicle to be rescued before entering the GPS signal failure area;

[0038] The vehicle rescue request signal refers to an emergency help instruction sent by the vehicle owner to the intelligent positioning system through the vehicle terminal when the vehicle encounters an accident, a breakdown or other difficulties and is in a GPS signal failure area. The signal contains the vehicle identity, the time when the rescue request is sent, and other key information. The first time refers to the specific time when the vehicle owner triggers the rescue request signal. The second time refers to the last time when the vehicle position information is still stable and reliable before the GPS signal fails. The last effective positioning point is the latitude and longitude coordinates corresponding to the second time, which is used as the starting reference point for subsequent positioning calculation. The vehicle speed data refers to the driving speed of the vehicle within a certain period of time before and after the second time point, which can be obtained from the vehicle speed sensor or calculated from the position information. The historical trajectory information within the preset time length refers to the continuous position change record of the vehicle within a fixed time length (such as 5 minutes) before the second time, which is used to analyze the driving trend and behavior habit of the vehicle.

[0039] Specifically, after receiving the rescue request signal sent by the vehicle terminal and confirming that it is in a GPS signal failure area, the intelligent positioning system needs to determine the reliable positioning starting point before the signal failure. The system first draws a time-position curve based on historical position information, identifies the starting time of the sawtooth curve through waveform analysis, and sets a time period of a certain length (such as 10 minutes) before this time as the candidate data interval. In this interval, the system extracts P consecutive historical position points and arranges them in chronological order as an ordered sequence, where P is a positive integer set by the platform in advance. For each pair of adjacent position points, the system converts the geographic coordinates (latitude and longitude) into plane coordinates (such as Mercator projection), calculates the Euclidean distance between the two points as the position offset distance, and obtains the time stamps of the adjacent points to calculate the time interval. Divide the offset distance by the time interval to get the position offset rate per unit time. Then, the system retrieves the actual vehicle speed data for the corresponding period from the vehicle terminal historical data. If the actual vehicle speed is 0 (such as the vehicle is stationary) in a certain period, skip the drift degree calculation for that period to avoid invalid comparison. For periods with non-zero actual vehicle speed, the system calculates the absolute difference between the offset rate and the actual vehicle speed, and then divides it by the actual vehicle speed to get the drift percentage. When multiple drifts (such as 3) are less than the preset threshold, the system determines that the position data in that period is reliable, and determines the time of the last position point that meets the condition as the second time, and the coordinates of which are the last effective positioning point. In this process, the system needs to handle data anomalies, such as missing time stamps for certain position points, which are filled in by interpolation of the previous and next time points. If the actual vehicle speed data is interrupted, the mean value of the adjacent periods is used instead.

[0040] S103, determining a predicted distance traveled by the vehicle after the GPS signal failure based on the vehicle speed data and the effective time between the second time and the first time;

[0041] The vehicle speed data represents the vehicle speed collected by the vehicle-mounted speed sensor in real time or calculated by the position offset. The effective time between the second time and the first time refers to the actual driving time after deducting the vehicle stay duration between the last reliable time before the GPS signal failure (the second time) and the time when the vehicle owner triggers the rescue request (the first time), and the unit is seconds or minutes. The traveled predicted distance refers to the estimated value of the distance traveled by the vehicle from the last valid positioning point after the GPS signal failure based on the vehicle speed data and the effective time.

[0042] The timing of this step is after the intelligent positioning system receives the rescue request signal sent by the vehicle-mounted terminal and has obtained relevant data such as vehicle speed data, the second time, the first time, and driving record information. The scenario is when the vehicle is in a GPS signal failure area and needs to predict its driving distance through other data to determine the rescue location. Specifically, the intelligent positioning system first needs to obtain the driving record information sent by the vehicle-mounted terminal, and determine whether the vehicle to be rescued has a stay between the second time and the first time by analyzing the information. If there is a stay, the system needs to further determine the duration of the stay, which can be achieved by identifying the period in which the vehicle speed is zero and lasts for a period of time in the driving record. Then, the system subtracts the stay duration from the total duration between the second time and the first time to obtain the effective time. After obtaining the effective time, the system needs to determine the driving speed of the vehicle within the effective time according to the vehicle speed data. The vehicle speed data here can be a constant value or a real-time change. If the vehicle speed data is a real-time change, the system needs to integrate the vehicle speed within the effective time to obtain the accurate driving distance. For example, if the vehicle speed is 60 km / h for 3 minutes and then 40 km / h for 4 minutes within the effective time, the system needs to calculate the distance of the two segments respectively and then add them up. If the vehicle speed data is constant, the driving distance can be obtained by multiplying the vehicle speed by the effective time. Through such processing, the system can more accurately determine the traveled predicted distance of the vehicle after the GPS signal failure, providing a reliable basis for subsequent location determination.

[0043] In some embodiments, the predicted distance can be determined by combining the vehicle speed data and the effective time in various ways: alternatively, the intelligent positioning system first obtains the driving record information from the vehicle terminal, extracts the vehicle speed data from the second time to the first time, analyzes the vehicle's stay in this time period, calculates the stay duration, subtracts the stay duration from the total duration to obtain the effective time, and then determines whether the vehicle speed data is a constant value. If it is a constant value, the predicted distance is obtained by multiplying the vehicle speed by the effective time; if the vehicle speed data is variable, the effective time is divided into multiple time periods, the average speed in each time period is assumed to be the average speed in that time period, the driving distance in each time period is calculated, and the distances in all time periods are added to obtain the predicted distance. Alternatively, the system first determines the effective time according to the driving record information, then obtains the real-time vehicle speed data of the vehicle terminal within the effective time, converts the effective time to hours, and then integrates the real-time vehicle speed data, i.e., by mathematical integration, the vehicle speed at each time point is multiplied by the corresponding time element, and then the total driving distance is obtained by accumulation.

[0044] S104, determine a candidate predicted going path in combination with the historical trajectory information, the last effective positioning point, and the topographic path map within the preset range of the last effective positioning point;

[0045] The historical trajectory information represents the continuous position change record of the vehicle within a preset time period before the second time, reflecting the driving trend and behavior habit of the vehicle before entering the GPS signal invalid area. The last effective positioning point refers to the latitude and longitude coordinates corresponding to the last time when the vehicle position information is still in a stable and reliable state before the GPS signal is invalid, serving as the starting reference point for subsequent path determination. The topographic path map is used to represent the topographic features and road distribution within the preset range of the last effective positioning point, including feasible road paths and road direction information, etc. For example, the preset range can be a region within 5 kilometers around the last effective positioning point, and the topographic path map will display all roads and the direction of the roads within this region.

[0046] The timing of this step is after the intelligent positioning system has determined the last valid positioning point, obtained the historical trajectory information and the terrain path map, and needs to predict the driving path of the vehicle after the GPS signal is invalid to determine the possible candidate path. The scenario is that after the vehicle enters the GPS signal invalid area, it cannot obtain the real-time position through GPS, and needs to rely on historical driving trajectory and terrain map to speculate its possible driving route. Specifically, the intelligent positioning system first obtains the road information within a preset range of the last valid positioning point from the terrain path map. These road information includes all feasible road paths and the direction information of each road. For example, the preset range is 3 kilometers around the last valid positioning point, and the system will extract all roads in this range from the terrain path map, such as trunk roads, secondary trunk roads, branch roads, etc., and obtain the direction of each road, such as east-west direction, north-south direction, etc. Then, the system determines the last N trajectory points before the last valid positioning point according to the historical trajectory information. N can be set according to actual conditions, such as 5 or 10. Through these trajectory points, the system can calculate the driving direction of the vehicle before entering the last valid positioning point, i.e. the trajectory direction. Next, the system compares the trajectory direction with the direction information of each feasible road to calculate the included angle between them. If the included angle is greater than a preset included angle threshold, it means that the direction of the road deviates greatly from the historical driving direction of the vehicle, and the possibility of the vehicle continuing to drive along this road is small, so this road is excluded. The remaining feasible road paths are the candidate predicted-to-go paths. Through such processing, the system can exclude some unreasonable roads, narrow the range of candidate paths, and improve the accuracy of subsequent position determination.

[0047] In some embodiments, the determination of the candidate predicted-to-go path in combination with the historical trajectory information, the last valid positioning point and the terrain path map can be realized in various ways: optionally, the intelligent positioning system first extracts all road information within a preset range of the last valid positioning point from the terrain path map, including feasible road paths and road direction information, and then obtains the last N trajectory points before the last valid positioning point from the historical trajectory information. Connect these trajectory points in chronological order, determine the trajectory direction by calculating the slope of this line, then calculate the included angle between the trajectory direction and the direction of each road, and exclude roads with an included angle greater than a preset threshold, and the remaining roads are used as candidate paths. Optionally, the system first performs smoothing processing on the historical trajectory information to eliminate the influence of some noise points, then determines the last N trajectory points before the last valid positioning point, fits a curve through these trajectory points to obtain the trajectory direction, and then compares it with the road direction in the terrain path map to exclude roads with too large included angles and obtain the candidate path.

[0048] S105、In the candidate predicted-to-go path, determine a set of candidate position information matching the traveled predicted distance;

[0049] The candidate predicted-to-go path represents a road path that the vehicle can travel on after the GPS signal is lost, determined by combining the historical trajectory information, the last valid positioning point, and the terrain path map; the traveled predicted distance is the distance traveled by the vehicle after the GPS signal is lost, calculated by combining the vehicle speed data and the valid time; and the candidate position information set is used to represent a set of all possible vehicle position points on the candidate predicted-to-go path that match the traveled predicted distance. For example, the candidate predicted-to-go path is a 10-kilometer road, and the traveled predicted distance is 5 kilometers, so the candidate position information set is all possible position points on the road that are 5 kilometers away from the last valid positioning point in the direction of the road.

[0050] The timing of this step is after the intelligent positioning system has determined the candidate predicted-to-go path and the traveled predicted distance. It is necessary to find possible positions on these paths that match the predicted distance in order to determine the final rescue position in combination with the base station position information later. The scenario is when the vehicle is driving in a GPS signal loss area and cannot determine the specific position. By determining the possible position points on the candidate path according to the predicted distance, a reference is provided for rescue. Specifically, the intelligent positioning system first needs to process each candidate predicted-to-go path. For each path, the system needs to determine its starting point, which is the projection point or the nearest point of the last valid positioning point on the path. Then, the system calculates the distance from the starting point in the direction of the path to find the position point that matches the traveled predicted distance. Since the road may have bends, branches, and other situations, the actual length and direction of the road need to be considered when calculating the distance. For example, a curved road may have an actual length greater than the straight-line distance, so the travel distance needs to be calculated according to the actual trajectory of the road. In addition, turning, lane changing, and other situations that may occur during driving need to be considered, but since the GPS signal is lost, real-time driving information cannot be obtained, so only the candidate path and the predicted distance can be used to determine the possible position point. When determining the position point, the system needs to ensure that the position point is on the candidate path and the distance from the starting point is equal to the traveled predicted distance. For each candidate path, there may be one or more position points that meet the conditions, and these position points constitute the candidate position information set. Through such processing, the system can find all possible vehicle position points on the candidate path, providing rich candidate information for subsequent position determination.

[0051] In some embodiments, the determination of the candidate location information set matching the predicted distance traveled on the candidate predicted-to-go path can be implemented in various ways: alternatively, the intelligent positioning system first models each candidate predicted-to-go path digitally, representing it as a series of coordinate point sequences, then calculates the nearest point to the last valid positioning point on the path as the starting point, and then from the starting point, calculates the distance from the starting point to each point along the coordinate point sequence of the path, and when the distance equals the predicted distance traveled, records the coordinates of the point as the candidate location point, until the entire path is traversed, and all points meeting the conditions are collected to form the candidate location information set.

[0052] S106, determining the base station location information of the ground base station from which the vehicle rescue request signal is sent;

[0053] Wherein, the ground base station represents a wireless communication base station deployed on the ground for realizing the communication between the vehicle terminal and the intelligent positioning system, and the vehicle terminal within the coverage range of the base station can send a rescue request signal through the base station; the vehicle rescue request signal refers to an emergency help signal containing the vehicle identity, the sending time, etc. triggered by the vehicle terminal in the GPS signal invalid area; the base station location information is used to represent the specific geographic coordinates (such as latitude and longitude) of the ground base station, which is usually pre-stored in the database of the intelligent positioning system or can be obtained by querying the communication network. For example, when the vehicle terminal triggers a rescue request in a mountainous area, the signal will be received by the nearest ground base station and forwarded to the intelligent positioning system, and the location information of the base station is the base station location information required here.

[0054] The timing of this step is to determine the location of the ground base station that sent the signal after the intelligent positioning system receives the vehicle rescue request signal sent by the vehicle terminal, so as to determine the rescue location in combination with the candidate location information. The scene is that when the vehicle sends a rescue request in a GPS signal failure area, the intelligent positioning system needs to trace the base station through the communication link to obtain the location coordinates of the base station. Specifically, after receiving the rescue request signal, the intelligent positioning system first parses the communication protocol field in the signal to extract the identification information of the ground base station through which the signal is transmitted. Then, the system queries the geographic coordinates corresponding to the base station identifier according to the pre-stored mapping relationship database of base station identifier and location information. If the database does not directly store the base station location information, the system will send a query request to the operator's base station positioning server through the communication network, submit the base station identifier information, receive and parse the base station location coordinate data returned by the server. In addition, the system also verifies the validity of the obtained base station location information, such as checking whether the coordinate value is within a reasonable range and whether it matches the signal strength and other parameters reported by the vehicle terminal, to ensure the accuracy of the base station location information. Through this series of processing, the intelligent positioning system can quickly and accurately determine the location information of the ground base station that sent the rescue request signal, providing key reference coordinates for subsequent location matching.

[0055] S107, determining the final location information closest to the base station location information from the candidate location information set, and determining the final location information as the final rescue location.

[0056] Among them, the final location information closest to the distance is used to represent the position point in the candidate location set with the smallest Euclidean distance or geographic distance from the base station location coordinate, which is identified as the most possible rescue location of the vehicle.

[0057] The timing of this step is to determine the location of the ground base station that sent the signal after the intelligent positioning system receives the vehicle rescue request signal sent by the vehicle terminal, so as to determine the rescue location in combination with the candidate location information. The scene is that when the vehicle sends a rescue request in a GPS signal failure area, the intelligent positioning system needs to trace the base station through the communication link to obtain the location coordinates of the base station. Specifically, after receiving the rescue request signal, the intelligent positioning system first parses the communication protocol field in the signal to extract the identification information of the ground base station through which the signal is transmitted. Then, the system queries the geographic coordinates corresponding to the base station identifier according to the pre-stored mapping relationship database of base station identifier and location information. If the database does not directly store the base station location information, the system will send a query request to the operator's base station positioning server through the communication network, submit the base station identifier information, receive and parse the base station location coordinate data returned by the server. In addition, the system also verifies the validity of the obtained base station location information, such as checking whether the coordinate value is within a reasonable range and whether it matches the signal strength and other parameters reported by the vehicle terminal, to ensure the accuracy of the base station location information. Through this series of processing, the intelligent positioning system can quickly and accurately determine the location information of the ground base station that sent the rescue request signal, providing key reference coordinates for subsequent location matching.

[0058] In the above embodiments, since the technical means of identifying the GPS signal invalid area based on the historical position information curve feature, combining the last valid positioning point and the vehicle speed data for distance prediction, and using the terrain path map and the base station position information for multi-dimensional fusion positioning are adopted, the vehicle driving track and position can be accurately predicted in the GPS signal invalid condition, the problem of large positioning deviation and low rescue efficiency caused by the GPS signal being blocked by the terrain in the prior art is effectively solved, and intelligent prediction positioning of the vehicle position is realized, which provides reliable position basis for timely rescue work and significantly improves the positioning accuracy and rescue response efficiency.

[0059] In some embodiments, after the final rescue position is determined in step S107, the position can be further calibrated to eliminate single base station positioning error or terrain interference. Specifically, the intelligent positioning system first determines a set range (for example, 2-5 kilometers according to the base station coverage radius) centered on the preliminarily determined final rescue position, and screens all target base stations within the range. Then, a signal strength query request is sent to each target base station, which carries the unique identifier of the vehicle terminal so that the base station can identify and feed back the corresponding signal data. After receiving the request, each target base station queries the current received signal strength of the vehicle terminal and returns the signal strength data and its own position coordinates (latitude and longitude). After receiving data from at least three base stations, the system starts a weighted triangular positioning algorithm: first, according to the empirical formula of signal strength and distance (for example, the signal strength decreases by 3dBm, and the distance increases by about 1 times), the virtual distance from the vehicle terminal to each base station is estimated; then, the absolute value or normalized value of the signal strength is used as the weight (for example, the base station with RSSI of-60dBm has higher weight than the base station with RSSI of-75dBm), the position coordinates of each base station are weighted and averaged, or the position deviation is corrected through geometric triangular calculation combined with the weight, and finally the calibrated final rescue position is obtained. This process effectively reduces the random error of single base station positioning through multi-dimensional signal data fusion, and can significantly improve the positioning reliability, especially in complex terrain.

[0060] An application scenario of the embodiment of the present application is introduced below. Please refer to Figure 2 , Figure 2 is an application scenario diagram of the intelligent positioning method of the vehicle rescue state in the embodiment of the present application.

[0061] Figure 2The intelligent positioning system is presented in the scene of mountainous area. When the vehicle is running normally, the GPS module continuously acquires position information. When the vehicle reaches the "last effective positioning point", the GPS signal is blocked by the mountainous terrain such as mountain and valley, and the vehicle cannot receive effective satellite signal, so the GPS positioning fails. If the vehicle owner finds that the engine is abnormal, the tire is faulty or other faults during driving, the vehicle owner can actively operate the vehicle terminal to send a vehicle rescue request signal to the system. The signal is transmitted wirelessly and captured by the first base station closest to the current position of the vehicle. The first base station forwards the rescue request signal to the intelligent positioning platform according to the communication protocol and link.

[0062] After the intelligent positioning platform receives the signal, the positioning and rescue process is started immediately. First, the historical trajectory data of the vehicle driving to the "last effective positioning point" is called. These data record the complete driving path of the vehicle before, which can present the driving habit and direction. At the same time, combined with the path map of the mountainous terrain, the road distribution around the "last effective positioning point" is analyzed, and two feasible paths that the vehicle may go after the fault (such as continuing to drive along the main road, turning into the branch road to avoid danger, etc.) are screened out. Then, the vehicle speed data is obtained, which can be collected by the vehicle speed sensor in real time, or the stable vehicle speed can be calculated by using the previous data if the effective data before GPS failure. The driving time from the "last effective positioning point" to the sending of the rescue request by the vehicle owner is extracted synchronously, and the distance of the vehicle driving in the GPS failure stage is calculated by associating the vehicle speed and time. Then, based on the driving trend of the historical trajectory, the reference position of the "last effective positioning point", the driving distance in the failure stage, and the two feasible paths screened out, the platform simulates the driving process of the vehicle after GPS failure, and predicts the positions matching the driving distance on the two paths, i.e. the first candidate position and the second candidate position, to form a candidate position set. Then, the platform calls the pre-stored base station position database to obtain the position information such as the latitude and longitude of the first base station receiving the signal, and calculates the distance between the first candidate position and the second candidate position and the first base station by using the spatial distance algorithm (such as the spherical distance calculation of latitude and longitude), and determines the candidate position closest to the distance as the final rescue position, which provides the coordinate basis for the rescue force to accurately rush to the scene, so as to solve the problem of vehicle positioning caused by GPS signal failure in mountainous area and ensure the efficient development of rescue.

[0063] In some embodiments, the vehicle owner who has a vehicle fault in the mountainous area or the suburb can actively fill in the rescue information through the mobile phone terminal bound with the intelligent positioning system in advance. Please refer to Figure 3 , Figure 3 which is another application scene diagram of the intelligent positioning method of vehicle rescue state in the embodiment of the present application.

[0064] In Figure 3In clause (a), if a car owner is involved in a sudden accident in the suburbs and understands the nature of the accident and the type of assistance required, then... Figure 3 As shown in (a), fill in the rescue information. In mountainous areas and other places, the location may be inaccurate. If the user clicks... Figure 3 The location marker corresponding to the incident location in (a) can then display, as shown below. Figure 3 The content shown in (b) is as follows.

[0065] The intelligent positioning system accurately locates the vehicle owner's current location information according to the methods described in steps S101 to S107, and accurately displays "Your Location" in the corresponding location. If the user needs to enter a destination, they can click as shown below. Figure 3 The input box corresponding to "Please enter destination" displayed at the top of (b) will then display the following: Figure 3 The content shown in (c) displays the user's final destination. If the user feels that the current location is inaccurate, they can move the "Your Location" icon to reposition. In this way, car owners can actively fill in rescue information even in mountainous areas or suburbs where positioning is inaccurate, and can also flexibly correct their location through interaction (clicking the location marker or input box), improving operational autonomy and convenience.

[0066] The intelligent positioning system in the embodiments of this invention is described below from the perspective of hardware processing. Please refer to [link / reference]. Figure 4 This is a schematic diagram of the physical device structure of an intelligent positioning system in an embodiment of this application.

[0067] It should be noted that, Figure 4 The structure of the intelligent positioning system shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0068] like Figure 4 As shown, the intelligent positioning system includes a Central Processing Unit (CPU) 401, which can perform various appropriate actions and processes based on programs stored in Read-Only Memory (ROM) 402 or programs loaded from storage section 408 into Random Access Memory (RAM) 403, such as performing the methods described in the above embodiments. The RAM 403 also stores various programs and data required for system operation. The CPU 401, ROM 402, and RAM 403 are interconnected via a bus 404. An Input / Output (I / O) interface 405 is also connected to the bus 404.

[0069] The following components are connected to the I / O interface 405: an input section 406 including an audio input device, a push button switch, and the like; an output section 407 including a Liquid Crystal Display (LCD), and an audio output device, a lamp, and the like; a storage section 408 including a hard disk and the like; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, and the like. The communication section 409 performs a communication process via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as necessary. A removable recording medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like, is attached to the drive 410 as necessary so that a computer program read therefrom can be installed into the storage section 408 as necessary.

[0070] In particular, the processes described above with reference to the flow charts can be implemented as a computer software program in accordance with embodiments of the present application. For example, an embodiment of the present application includes a computer program product comprising a computer program carried on a computer readable medium, the computer program containing computer programs for executing the methods shown in the flow charts. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 409, and / or installed from the removable recording medium 411. When the computer program is executed by the central processing unit (CPU) 401, various functions defined in the present application are performed.

[0071] Note that specific examples of the computer readable storage medium can include but are not limited to an electric connection having one or more conductive wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read only memory (ROM), an erasable programmable read only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read only memory (CD-ROM), an optical storage device, a magnetic storage device, or any appropriate combination of the foregoing. In the present application, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0072] The computer program product of the present application can be a computer program embodied on a tangible medium or transmitted from a remote computer.

[0073] In particular, the intelligent positioning system of the embodiment includes a processor and a memory, and the memory stores a computer program. When the computer program is executed by the processor, the intelligent positioning method for vehicle rescue state provided in the above embodiment is implemented.

[0074] As another aspect, the present application also provides a computer readable storage medium. The storage medium can be included in the intelligent positioning system described in the above embodiments, or can exist independently without being assembled into the intelligent positioning system. The storage medium carries one or more computer programs. When the one or more computer programs are executed by a processor of the intelligent positioning system, the intelligent positioning system implements the intelligent positioning method for vehicle rescue state provided in the above embodiments.

[0075] The above embodiments are only used to illustrate the technical solutions of the present application, but not limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements to some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application.

[0076] In the above embodiments, according to the context, the term "when" can be interpreted as meaning "if" or "after" or "in response to determining" or "in response to detecting". Similarly, according to the context, the phrase "upon determining" or "if detecting (the stated condition or event)" can be interpreted as meaning "if determining" or "in response to determining" or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)".

[0077] Those skilled in the art can understand that all or part of the processes in the above-mentioned method embodiments can be implemented by a computer program instructing relevant hardware to complete, the program can be stored in a computer readable storage medium, and the program can include the processes of the above-mentioned method embodiments when executed. The aforementioned storage medium includes ROM or random storage memory RAM, magnetic disc or optical disc and various storage code medium.

Claims

1. A method for intelligent positioning of a vehicle rescue state, characterized in that, The method comprises: After receiving the historical position information sent by the vehicle-mounted end of the communication connection, if the curve corresponding to the historical position information is a sawtooth curve with an amplitude exceeding a set amplitude and a vibration frequency exceeding a set frequency within a set time length, it is determined that the vehicle-mounted end has entered a GPS signal invalid area; After receiving the vehicle rescue request signal sent by the vehicle-mounted end at a first time after entering the GPS signal invalid area, the last effective positioning point, the vehicle speed data and the historical trajectory information within a preset time length of the vehicle to be rescued at a second time before entering the GPS signal invalid area are obtained; The traveled predicted distance of the vehicle after entering the GPS signal invalid area is determined in combination with the vehicle speed data and the effective time between the second time and the first time; The candidate predicted going path is determined in combination with the historical trajectory information, the last effective positioning point and the topographic path map within a preset range of the last effective positioning point; The candidate position information set matching the traveled predicted distance on the candidate predicted going path is determined; The base station position information of the ground base station sending the vehicle rescue request signal is determined; The final position information closest to the base station position information is determined from the candidate position information set, and the final position information is determined as the final position to be rescued.

2. The method of claim 1, wherein, The last effective positioning point of the vehicle to be rescued at the second time before entering the GPS signal invalid area is obtained, specifically comprising: The time before the set time length of the sawtooth curve is taken as the second time, and the historical position information corresponding to the time before the set time length of the sawtooth curve is determined as the last effective positioning point.

3. The method of claim 2, wherein, The time before the set time length of the sawtooth curve is taken as the second time, and the historical position information corresponding to the time before the set time length of the sawtooth curve is determined as the last effective positioning point. The step specifically comprises: Obtaining the continuous P historical position points before the sawtooth curve appears; Pairing the continuous P historical position points two by two in time sequence, and calculating the position offset distance between the adjacent two position points; Divide each position offset distance by the corresponding time interval to obtain the position offset rate per unit time; Compare each position offset rate with the actual vehicle speed reported by the vehicle-mounted end in the corresponding period to calculate the multiple position drift degrees: When the multiple position drift degrees are less than a preset offset degree threshold, the time when the last position drift degree is less than the preset threshold is taken as the second time, and the corresponding position point is determined as the last effective positioning point.

4. The method of claim 1, wherein, The step of determining the candidate predicted going path in combination with the historical trajectory information, the last effective positioning point and the topographic path map within a preset range of the last effective positioning point specifically comprises: Obtaining the road information of the last effective positioning point within a preset range according to the topographic path map, wherein the road information comprises feasible road path and road direction information; Determining the last N trajectory points before the last effective positioning point according to the historical trajectory information, and determining the trajectory direction according to the trajectory points; An angle between the trajectory direction and the road direction information is calculated, and a feasible road path with an angle greater than a preset angle threshold is removed, and the remaining feasible road path is determined as a candidate predicted-to-go path.

5. The method of claim 1, wherein, Before the step of determining the traveled predicted distance of the vehicle after the GPS signal failure based on the vehicle speed data and the effective time between the second time and the first time, the method further comprises: obtaining driving record information sent by the vehicle terminal; determining whether the vehicle to be rescued stays between the second time and the first time based on the driving record information, and determining a stay duration; subtracting the stay duration from a total duration between the second time and the first time to obtain an effective time.

6. The method of claim 5, wherein, After the step of subtracting the stay duration from the total duration between the second time and the first time to obtain the effective time, the method further comprises: after determining that the vehicle to be rescued stays between the second time and the first time, determining real-time vehicle speed data in the effective time based on the driving record information; determining the traveled predicted distance based on the real-time vehicle speed data and the effective time.

7. The method of claim 1, wherein, After the step of determining the final location information closest to the base station location information from the candidate location information set, and determining the final location information as the final location to be rescued, the method further comprises: sending a signal strength query request to a plurality of target base stations within a set range of the final location to be rescued; receiving signal strength data of the vehicle terminal and target base station location information returned by each target base station; calibrating the final location to be rescued based on the signal strength data returned by at least three target base stations and the target base station location information by using a weighted triangular positioning algorithm to obtain a calibrated final location to be rescued.

8. An intelligent positioning system, characterized by The intelligent positioning system comprises one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, the computer program code comprises computer instructions, and the one or more processors invoke the computer instructions to enable the intelligent positioning system to perform the method according to any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that, When the instructions are run on the intelligent positioning system, the intelligent positioning system performs the method according to any one of claims 1-7.

10. A computer program product, characterised in that, When the computer program product is run on the intelligent positioning system, the intelligent positioning system performs the method according to any one of claims 1-7.

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