CN115017252A - Intelligent playback system for vehicle track of mobile phone digital vehicle key - Google Patents
Intelligent playback system for vehicle track of mobile phone digital vehicle key Download PDFInfo
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Abstract
The invention relates to the technical field of data transmission, in particular to a driving track intelligent playback system of a mobile phone digital vehicle key, which comprises: the device comprises a data acquisition module, a track division module, a first parameter acquisition module, a second parameter acquisition module, a compression storage module and a playback module. The intelligent playback system for the vehicle track of the mobile phone digital vehicle key, provided by the invention, utilizes a positioning technology and a data acquisition technology to obtain position information and driving state information in the driving process, and compresses and stores the collected information based on priority through a data compression technology to realize the playback of the vehicle track with small storage data and high retrieval efficiency.
Description
Technical Field
The invention relates to the technical field of data transmission, in particular to an intelligent driving track playback system of a mobile phone digital vehicle key.
Background
A mobile phone digital car key is an innovative technology under the intelligent revolution of cars. The intelligent automobile unlocking system is concerned by more and more automobile enterprises, and can enable an automobile owner to unlock the automobile through a smart phone and perform related operations on the automobile, for example, a driving track is played back through a digital automobile key of the smart phone. The recording and playback of vehicle tracks are one of the extremely important functions in the driving process of automobiles, and the existing driving track system is used for recording and storing data based on a navigation map and then drawing and playing back the map. However, the car track playback generally needs to be reserved for half a year or more, the storage method needs a large amount of storage space, relatively speaking, resources are wasted, the storage sequence is stored according to a time sequence, and great calculation power is needed to search and locate data on the premise of huge data volume.
At present, a mobile phone digital car key is mobile phone software which is installed on a mobile phone and used for unlocking a car and recording car running information, and the mobile phone software integrates a car unlocking function and a car navigation record playback function. The mobile phone and the vehicle are usually connected through communication such as NFC and Bluetooth, the vehicle can be unlocked through the mobile phone digital vehicle key, and the vehicle running information can be recorded under the condition that GPS signals are normal.
In the process of vehicle driving, position information and driving state information need to be recorded, recorded data are compressed and stored, the stored compressed data are decompressed at the later stage according to needs, and the decompressed recorded data are played back on a map of a mobile phone end to obtain a driving track of a vehicle; the vehicle can record the running track of the vehicle and the position information and the vehicle state information of each moment on the track in the mobile phone digital vehicle key at a place where the GPS signal is normal, and can accurately play back the running track of the vehicle; however, the vehicle cannot be accurately positioned at a place with poor GPS signals, and the position information and the vehicle state information of the vehicle cannot be recorded in the mobile phone digital vehicle key, which is considered as an abnormal driving road section, and it is difficult to obtain an accurate driving track in real time. Therefore, in order to ensure the integrity of the running data compression of the abnormal running road section and ensure that the deviation of the subsequent abnormal running track playback is small, the invention provides the intelligent running track playback system of the mobile phone digital car key.
Disclosure of Invention
In order to solve the above technical problem, an object of the present invention is to provide an intelligent playback system for a vehicle track of a mobile phone digital vehicle key, comprising:
the data acquisition module is used for acquiring the driving data of abnormal driving of the vehicle; acquiring initial coordinates of the starting time and ending coordinates of the abnormal running of the vehicle through a mobile phone digital vehicle key; the driving data comprises position data and vehicle state information which are acquired when the vehicle runs abnormally;
the track division module is used for acquiring the abnormal driving track of the vehicle according to the driving data and fitting to acquire a driving track function; obtaining a plurality of predicted turning position points when the vehicle runs abnormally by performing high-order derivation on the running track function;
acquiring the overall united difference of abnormal vehicle running according to the coordinates of the plurality of predicted position points; screening out a plurality of accurate position points from the plurality of predicted position points according to the coordinates of the plurality of predicted position points and the overall combined difference of abnormal vehicle running;
dividing the abnormal driving track into a plurality of abnormal intervals according to a plurality of accurate position points;
the first parameter acquisition module is used for acquiring the distribution weight of each abnormal interval according to the coordinates of the initial accurate position point and the final accurate position point of each abnormal interval and the number of the predicted position points in each abnormal interval;
acquiring the weight value of each abnormal interval according to the distribution weight value of each abnormal interval and the maximum value and the minimum value in the distribution weight values of all the abnormal intervals;
the second parameter acquisition module is used for acquiring a simulation termination coordinate of the abnormal running termination moment of the vehicle according to the running data; acquiring the integral error degree of the abnormal driving track according to the initial coordinate, the termination coordinate and the simulated termination coordinate of the abnormal driving of the vehicle; acquiring an error value of each abnormal interval according to the weight value of each abnormal interval and the integral error degree of the abnormal driving track;
the compression storage module is used for carrying out Huffman coding on the running data in each abnormal interval and carrying out lossless compression to obtain first compression data according to the probability product of the error value of each abnormal interval and the running data in the corresponding abnormal interval as a weight; the mobile phone digital car key is used for acquiring running data of a vehicle when the vehicle normally runs in each running process of the vehicle, performing lossy compression on the running data of the vehicle when the vehicle normally runs to acquire second compressed data, and storing the first compressed data and the second compressed data in the mobile phone digital car key;
and the playback module is used for decompressing the stored second compressed data and then directly playing back the second compressed data, and the first compressed data is corrected and then the vehicle driving track is reconstructed for playing back the first compressed data.
In one embodiment, in the trajectory division module, the driving trajectory function is fitted according to position data acquired by a vehicle in an abnormal driving process; the position data comprises longitude and latitude coordinates of the vehicle at each moment in the abnormal driving process; the independent variable of the driving track function is longitude, and the dependent variable is latitude.
In one embodiment, the predicted location points of the plurality of turns are obtained by:
obtaining a second derivative function by carrying out second order derivation on the traveling track function; meanwhile, carrying out third-order derivation on the traveling track function to obtain a third-order derivative function;
and taking a plurality of coordinate points corresponding to the driving track function, which enable the second derivative function to be equal to zero and enable the third derivative function not to be equal to zero, as predicted position points of a plurality of turns.
In an embodiment, in the trajectory dividing module, the plurality of accurate position points are obtained according to the following steps:
according to the coordinate of the first predicted position point in the plurality of predicted position points and the second predicted position pointCalculating the coordinates of the predicted position points to obtain the first predicted position point to the second predicted position pointInterval difference of the predicted position points; when the interval difference is equal to the overall combined difference of abnormal vehicle running, judging whether the interval difference is equal to the overall combined difference of abnormal vehicle runningThe predicted position points are accurate position points;
then by the firstThe coordinates of the predicted position points and the coordinates of the subsequent predicted position points are calculated in sequence, and a plurality of accurate position points are obtained by analogy in sequence.
In one embodiment, the calculation formula of the overall combined difference of the abnormal driving of the vehicle is as follows:
in the formula,representing the overall united difference of the abnormal running of the vehicle;is shown asCoordinates of the predicted location points;,representing the total number of predicted location points.
In an embodiment, in the first parameter obtaining module, a calculation formula of the allocation weight of each abnormal interval is as follows:
in the formula,is shown asThe distribution weight of each abnormal interval;is shown asCoordinates of initial accurate position points of the abnormal intervals;is shown asCoordinates of the ending accurate position point of each abnormal interval;is as followsThe number of predicted location points within an interval;is a firstEach interval including prediction bitsNumber of placement points and exact placement points.
In an embodiment, the data acquisition module further comprises driving data for acquiring abnormal driving of the vehicle in a plurality of different time periods during each driving process of the vehicle; dividing the abnormal running track corresponding to each time period into a plurality of abnormal intervals according to a track dividing module;
acquiring a weight value of each abnormal interval corresponding to each time period through a first parameter acquisition module;
acquiring the integral error degree of the abnormal running track corresponding to each time period and the error value of each corresponding abnormal interval through a second parameter acquisition module;
performing Huffman coding on the running data in each abnormal interval corresponding to each time period by using a compression storage module to perform lossless compression to obtain first compressed data, wherein the product of the error value of each abnormal interval corresponding to each time period and the probability of the running data in the corresponding abnormal interval is used as a weight; and storing the first compressed data in the mobile phone digital car key.
In one embodiment, in the storage process, the running data is stored hierarchically according to the overall error of the abnormal running track corresponding to each time segment in each running process of the vehicle and the weight value of each abnormal interval corresponding to each time segment.
In one embodiment, the hierarchical storage is performed according to the following steps:
establishing a first priority storage layer, establishing a second priority storage layer in each first priority storage layer, and establishing a third priority storage layer in each second priority storage layer;
sequentially storing the running data of the abnormal running tracks of different time periods of each running in a first priority storage layer according to the sum of the overall error degrees of the abnormal running tracks of the different time periods in the running process of the vehicle;
sequentially storing the running data of the abnormal running track of each time period in a second priority storage layer in the first priority storage layer according to the sum of the error values of each abnormal interval in the abnormal running track of each time period;
and sequentially storing the running data of each abnormal section in a third priority storage layer in the second priority storage layer according to the error value of each abnormal section in the abnormal running track.
In one embodiment, in the playback module, when the driving track of the vehicle is played back in the mobile phone digital vehicle key, the first compressed data and the second compressed data in the driving process are retrieved from the compressed storage module, the first compressed data and the second compressed data are sequenced based on the time sequence, the driving data in normal driving is directly decompressed and played back, and after the driving data in abnormal driving is corrected, the driving track of the vehicle is reconstructed and played back.
The invention has at least the following beneficial effects:
the invention provides a traffic track intelligent playback system of a mobile phone digital car key, which acquires running data of abnormal running of a car through a data acquisition module, analyzes the running data of the abnormal running of the car through the integral error analysis of the abnormal running of the car to reflect the integral error of each abnormal traffic track to the maximum extent, divides each abnormal traffic track into abnormal intervals through inflection points, analyzes the abnormal intervals, distributes errors according to the analysis result, judges the running path length and the accumulated condition of the errors of each abnormal interval so as to acquire the abnormal degree of each abnormal interval, and further performs lossless compression on the running data of each abnormal interval in the abnormal traffic tracks according to the abnormal degree of the abnormal intervals by using a Hoffman coding algorithm, wherein the larger the abnormal degree is, the shorter the coding is, the higher the safety is, the integrity of the driving data in the whole abnormal driving track can be ensured, and the phenomenon that the data is more abnormal due to the fact that the driving data is originally abnormal in the compression process is avoided; the data with small memory space is realized, and the occupation of the memory space is reduced; in addition, the invention also carries out priority level layer storage on the driving data according to the abnormal degree, improves the subsequent retrieval efficiency, and can quickly retrieve the driving data of the abnormal driving track, thereby realizing the playback of the driving track with small storage data and high retrieval efficiency.
The invention mainly utilizes a gyroscope positioning technology and a data acquisition technology to obtain the position information of a vehicle in the driving process and the state information of the vehicle in the driving process, carries out priority compression on the collected driving data through a data compression technology, stores the driving data of an abnormal driving track in a mobile phone digital vehicle key under the condition that a vehicle GPS signal is normal, and records the driving track of the vehicle and the position information and the vehicle state information of each moment on the track in the mobile phone digital vehicle key through lossy compression when the vehicle is in a place where the GPS signal is normal, thereby realizing small-storage-quantity data.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a block diagram of a driving track intelligent playback system of a mobile phone digital car key according to an embodiment of the present invention.
Detailed Description
To further illustrate the technical means and effects of the present invention for achieving the predetermined purpose, the following describes the following detailed description of the track intelligent playback system of the mobile phone digital car key according to the present invention with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" refers to not necessarily the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The mobile phone digital car key is mobile phone software which is installed on a mobile phone and used for unlocking a car and recording the running information of the car, and the mobile phone software integrates the car unlocking function and the car navigation record playback function. The mobile phone is usually connected with the vehicle through communication such as NFC and Bluetooth, the vehicle can be unlocked through the mobile phone digital vehicle key, and the vehicle driving information can be recorded under the condition that GPS signals are normal.
The invention aims at the scene that in the running process of a vehicle, under the condition that a GPS signal of the vehicle is normal, the position information and running state information of the vehicle can be recorded in a mobile phone digital vehicle key in real time, then the subsequent running track playback is carried out on a map of the mobile phone digital vehicle key according to the recorded data, but the vehicle cannot be accurately positioned in a place with a weaker GPS signal, the running data of the vehicle cannot be recorded in the mobile phone digital vehicle key in real time, the coordinate position can be calculated only through a gyroscope and a speed sensor arranged on the vehicle, but larger abnormity or error exists with the running data recorded when the GPS signal is normal, so the abnormity degree in the abnormal running state of the running data is calculated, then data compression is carried out according to the abnormity degree, and the running data is stored in the mobile phone digital vehicle key in a priority level mode according to the abnormity degree, the method ensures the integrity of abnormal driving data and realizes the playback of the driving track with small memory data and high searching efficiency.
The invention provides a system for intelligently replaying a vehicle track of a mobile phone digital vehicle key, which mainly utilizes a gyroscope positioning technology and a data acquisition technology to obtain position information of a vehicle in the driving process and state information of the vehicle in the driving process, carries out priority compression on the collected driving data through the data compression technology, stores the driving data of an abnormal vehicle track in the mobile phone digital vehicle key under the condition that a vehicle GPS signal is normal, and records the vehicle track of the vehicle and the position information and the vehicle state information of each moment on the track in the mobile phone digital vehicle key through lossy compression when the vehicle is in a place where the GPS signal is normal, thereby realizing small-memory-quantity data.
The following describes a specific scheme of the intelligent playback system of the vehicle track of the mobile phone digital vehicle key provided by the invention in detail with reference to the accompanying drawings.
Referring to fig. 1, a block diagram of a structure of a system for intelligently playing back a vehicle track of a mobile phone digital vehicle key according to an embodiment of the present invention is shown, where the system for intelligently playing back a vehicle track of a mobile phone digital vehicle key includes: the device comprises a data acquisition module, a track division module, a first parameter acquisition module, a second parameter acquisition module, a compression storage module and a playback module;
the data acquisition module is used for acquiring the driving data of abnormal driving of the vehicle; acquiring initial coordinates of the starting time and ending coordinates of the abnormal running of the vehicle; the driving data comprises position data and vehicle state information which are acquired when the vehicle runs abnormally;
in this embodiment, the data acquisition module is configured to use longitude and latitude coordinates acquired by a gyroscope when a vehicle runs as position data, and acquire vehicle state information including driving speed and vehicle direction information during driving; the position data of the vehicle in the normal running process is directly collected by using a positioning technology in a mobile phone digital vehicle key, such as a GPS, a Beidou and the like; the driving data of the abnormal driving of the vehicle mainly depends on a gyroscope, a speed sensor and the like mounted on the vehicle. Note that the start time of the abnormal driving state is recorded as,The longitude and latitude coordinates of the moment are initial coordinatesThe abnormal driving state ending time is,Longitude and latitude coordinates of time are termination coordinates. It should be noted that the position information and the vehicle state information of the starting time and the ending time of each section of abnormal driving state can be obtained by a mobile phone digital vehicle key; the starting time of the abnormal state is the last time of losing the GPS signal; the abnormal state termination time is the first time when the GPS signal is re-received.
The track division module is used for acquiring the abnormal driving track of the vehicle according to the driving data and fitting to acquire a driving track function; obtaining a plurality of predicted turning position points when the vehicle runs abnormally by performing high-order derivation on the running track function;
acquiring the overall united difference of abnormal vehicle running according to the coordinates of the plurality of predicted position points; screening out a plurality of accurate position points from the plurality of predicted position points according to the coordinates of the plurality of predicted position points and the overall combined difference of abnormal vehicle running;
dividing the abnormal running track into a plurality of abnormal intervals according to a plurality of accurate position points;
in the track division module, a driving track function is formed by fitting according to position data acquired in the abnormal driving process of the vehicle; the position data comprises longitude and latitude coordinates of the vehicle at each moment in the abnormal driving process; the independent variable of the driving track function is longitude, and the dependent variable is latitude.
It should be noted that, in order to ensure the integrity of the driving data in the abnormal driving track in the compression process, the abnormal driving track is subjected to mark point partition, then the section characteristics are analyzed, error distribution is performed according to the analysis result, and the driving data is compressed according to the priority of the error distribution.
In the embodiment, the longitude and latitude information in the driving data is used for simulating the abnormal driving track, the abnormal driving track is obtained by using the coordinates of a starting point and an ending point of the vehicle in the abnormal driving process as fixed points and then performing triangular reconstruction by using the simulated coordinates calculated by using the gyroscope and the speed sensor data in the driving process as variable points.
The predicted position points of the plurality of turns are obtained according to the following steps:
obtaining a second derivative function by carrying out second order derivation on the traveling track function; meanwhile, carrying out third-order derivation on the traveling track function to obtain a third-order derivative function; and taking a plurality of coordinate points corresponding to the driving track function, which enable the second derivative function to be equal to zero and enable the third derivative function not to be equal to zero, as predicted position points of a plurality of turns.
In the embodiment, the function of longitude and latitude is simulated and generated by using the position data of the driving data of the vehicle in the abnormal driving process, namely the driving track functionTo utilizeObtaining the predicted position points of a plurality of turns, wherein the specific process is as follows:
first, the function of the driving trackThe high-order derivation is carried out, and the purpose of the high-order derivation is to carry out the function of the traveling trackAnd judging the inflection point, wherein the inflection point in the driving track function can preliminarily consider the position of the vehicle with the large probability turning in the driving track. Second, a second derivative function is obtainedAnd third derivative functionThen all the second derivative functions are selectedAnd is provided withCorresponding toThe point is used as a predicted position point(ii) a Wherein,is shown asCoordinates of the predicted location points; the concrete practical meaning of the predicted position point is the position point of the vehicle with high probability of turning in the driving track.
The calculation formula of the overall united difference of the abnormal running of the vehicle is as follows:
in the formula,representing the overall united difference of the abnormal running of the vehicle;is shown asCoordinates of the predicted location points;,representing the total number of predicted location points.Representing the overall united difference of the abnormal running of the vehicle; specifically, the overall united difference of abnormal vehicle running is represented by the difference value between a single predicted position point and all the overall predicted position points through variance calculation.
In the track division module, a plurality of accurate position points are obtained according to the following steps:
according to the coordinate of the first predicted position point in the plurality of predicted position points and the second predicted position pointCalculating the coordinates of the predicted position points to obtain the first predicted position point to the second predicted position pointInterval difference of the predicted position points; when the interval difference is equal to the overall combined difference of abnormal vehicle running, judging whether the interval difference is equal to the overall combined difference of abnormal vehicle runningThe predicted position points are accurate position points;
then by the firstThe coordinates of the predicted position points and the coordinates of the subsequent predicted position points are calculated in sequence, and a plurality of accurate position points are obtained by analogy in sequence.
In this embodiment, a plurality of abnormal sections of the abnormal driving trajectory are obtained, and section end point values are used as accurate position points, so that the abnormal sections are combined with the integral united differencesThe termination conditions are specifically as follows:
first, the first and second predicted position points are used as the basis to perform the firstThe individual and second predicted position points are used as interval calculation interval differences in the same calculation mode as the overall combined difference calculation formula, and then whether the interval differences are equal to the overall combined differences is judged, if not, the next predicted position point is added continuously for recalculation until the first predicted position point is reachedA predicted position pointWhen the interval difference is equal to the overall combined difference, the first one is selectedThe predicted position points are used as accurate position points; then by the firstA candidate mark pointThe calculation is restarted, all the accurate position points can be screened, and the accurate position points are obtained according to the methodThe marking points divide the abnormal driving track into a plurality of abnormal intervals according to a plurality of accurate position points; the overall data between every two adjacent accurate position points is an abnormal interval of the driving track, and the total data isAnd (5) an abnormal driving track interval. For understanding, similar to iterative computation in obtaining accurate location points, e.g. the computation will be performedFrom 1 to 1Become to calculate=1 to=2The same is terminated, the different continues to calculate=1 to=3Same termination, different continuation of calculation=1 to=4Sequentially calculate toA predicted position pointWhen the interval difference is equal to the overall combined difference, the first one is selectedThe predicted position points are used as accurate position points.
In the present embodiment, in order to clarify the error of each abnormal section in the abnormal travel locus, the correction is performed for each abnormal sectionBody error distribution in order toAn individual interval as an exampleThe method comprises the following steps:
the first parameter acquisition module is used for acquiring the distribution weight of each abnormal interval according to the coordinates of the initial accurate position point and the coordinates of the final accurate position point of each abnormal interval and the number of the predicted position points in each abnormal interval;
acquiring the weight value of each abnormal interval according to the distribution weight value of each abnormal interval and the maximum value and the minimum value in the distribution weight values of all the abnormal intervals;
in the first parameter obtaining module, a calculation formula of the distribution weight of each abnormal interval is as follows:
in the formula,is shown asThe distribution weight of each abnormal interval;denotes the firstCoordinates of the initial accurate position points of the abnormal intervals;is shown asCoordinates of the ending accurate position point of each abnormal interval;is as followsThe number of predicted position points within each anomaly interval;is as followsThe total number of predicted location points and accurate location points are included within each anomaly interval.
If calculatedThe larger the position change frequency, the larger the trend of the overall position change frequency in the interval, and the error accumulation is easier to occur under the condition of the larger position change frequency; then, the number of the predicted position points is used for calculating the ratio of the number of the whole track points in the abnormal intervalThe predicted position point is the inflection point position of a driving track function in the driving process, the inflection point position is a vehicle direction change point in a simulation track in the driving process, and errors are easy to occur in the direction change in the driving process in the basic theory; finally, the number of the integral track points of the whole interval is used for amplificationThe more the number of the whole driving track points in the whole interval is, the longer the actual driving distance in the interval is, and the longer the distance is, the more errors are easily accumulated. The whole track point comprises a predicted position point and an accurate position point in the abnormal interval.
In this embodiment, the above calculation is performed for each abnormal interval, and the distribution weight value sequence of each interval can be obtained:
Then, the weight value sequence is distributed to calculate the weight value of each abnormal interval, so as toFor example, the weight value of the abnormal intervalThe calculation is as follows:
in the formula,distributing the minimum weight in the weight sequence;distributing the weight value to the maximum distributing weight value in the distributing weight value sequence;denotes the firstThe distribution weight of each abnormal interval;is shown asThe weight value of each abnormal interval.
And calculating all the distribution weight values in the mode to obtain the weight value of each abnormal interval.
In this embodiment, in order to assign an error value to each abnormal interval, the overall error degree of the entire abnormal trajectory is obtained first, and the error value is assigned by a weight value of each abnormal interval, which is specifically as follows:
the second parameter acquisition module is used for acquiring a simulation termination coordinate of the abnormal running termination moment of the vehicle according to the running data; acquiring the integral error degree of the abnormal driving track according to the initial coordinate, the termination coordinate and the simulated termination coordinate of the abnormal driving of the vehicle; acquiring an error value of each abnormal interval according to the weight value of each abnormal interval and the integral error degree of the abnormal driving track;
in the embodiment, in order to obtain the overall error when the vehicle runs abnormally, the overall error degree of the abnormal driving track is obtained according to the following steps:
acquiring initial coordinates and ending coordinates of abnormal running of the vehicle; in the present embodiment, the starting time of recording the abnormal driving state is,The longitude and latitude coordinates of the time are initial coordinatesThe abnormal running state ending time is,Longitude and latitude coordinates of time are termination coordinates. The starting time of the abnormal state is the last time of losing the GPS signal; the abnormal state termination moment is the first moment when the GPS signal is received again;
then the abnormal running state is processed by the prior artThe gyroscope data and the speed data collected by the data collection module in the state are subjected to simulation calculation of the traffic track data to obtain a simulated abnormal traffic track, and the last longitude and latitude coordinate in the calculated abnormal traffic track is recorded as a simulation termination coordinate;
Acquiring the integral error degree of the abnormal driving track according to the initial coordinate, the termination coordinate and the simulated termination coordinate of the abnormal driving of the vehicle; the specific calculation formula is as follows:
in the formula,representing the integral error degree of the abnormal driving track;a simulation end coordinate indicating an end time of abnormal travel of the vehicle;initial coordinates indicating abnormal travel of the vehicle;the end coordinates of abnormal travel of the vehicle. In this embodiment, the difference between the simulation ending coordinate and the initial coordinate of the abnormal driving track of the simulated vehicle in the abnormal state is compared with the difference between the ending coordinate and the initial coordinate, and the error analysis is performed on the whole abnormal driving starting and ending coordinate, wherein the initial coordinate and the ending coordinate are actual values, and the simulation ending coordinate is a simulation calculation value, and the whole error of the simulated abnormal driving track can be reflected to the maximum extent by performing the error calculation on the whole abnormal driving interval by using the simulation calculation value and the actual value. It should be noted that in the present embodiment, the operation is performed mainly according to the actual situation of the vehicle runningThe overall error of the abnormal driving track is obtained, and the starting point and the end point of each abnormal driving track are not the same coordinate point.
In order to reflect the error of the running data of each abnormal section in the abnormal running track most truly, the overall error of the abnormal running track is distributed to each abnormal section in the abnormal running track, which is specifically as follows:
finally, error distribution is carried out according to the weight value of each abnormal interval toFor example, the error value after distribution isThe calculation method is as follows:
in the formula,is shown asError values of the individual abnormal intervals;is shown asA weight value of each abnormal interval;integral error degree representing abnormal driving track
So far, the distributed error value of each abnormal section in all the abnormal driving tracks is obtainedError ofDifference valueThat is, the degree of abnormality of the travel data in the abnormal section.
The compression storage module is used for carrying out Huffman coding on the running data in each abnormal interval and carrying out lossless compression to obtain first compression data according to the probability product of the error value of each abnormal interval and the running data in the corresponding abnormal interval as a weight; and stores the first compressed data.
In this embodiment, the above is to calculate the abnormal degree of the driving data in different abnormal intervals in a section of abnormal driving state of the vehicle in a driving process, and then perform lossless compression on the driving data of the abnormal trajectory by using the huffman coding algorithm according to the abnormal degree, and the specific method is as follows:
to a first orderTaking an abnormal interval as an example, the conventional Huffman coding method is based on the secondThe probability of each data in each abnormal interval appearing in all abnormal intervals is used as a weight value to code, and the data appearance probability cannot reflect the abnormal degree of the abnormal data in the embodiment, according to the second stepError value of each abnormal interval and corresponding firstTaking the probability product of the occurrence of the driving data in the abnormal interval as a weight, and comparing the weight with the weightCarrying out Huffman coding on the driving data in the abnormal intervals and carrying out lossless compression to obtain first compressed data; and stores the first compressed data.
In this embodiment, the data acquisition module further includes driving data for acquiring abnormal driving of the vehicle in a plurality of different time periods during each driving process of the vehicle;
dividing the abnormal running track corresponding to each time period into a plurality of abnormal intervals according to a track dividing module;
acquiring a weight value of each abnormal interval corresponding to each time period through a first parameter acquisition module;
acquiring the integral error degree of the abnormal running track corresponding to each time period and the error value of each corresponding abnormal interval through a second parameter acquisition module;
the error value of each abnormal interval corresponding to each time period and the probability product of the running data in the corresponding abnormal interval are used as weight values through a compression storage module, and the running data in each abnormal interval corresponding to each time period are subjected to Huffman coding and lossless compression to obtain first compression data; and stores the first compressed data.
The compression storage module is used for acquiring running data of the vehicle when the vehicle normally runs in each running process of the vehicle, performing lossy compression on the running data of the vehicle when the vehicle normally runs to acquire second compressed data, and storing the second compressed data. The lossy compression is compression by predictive coding or transform coding.
In the storage process, the driving data is stored in a layered mode according to the integral combined difference of the abnormal driving tracks corresponding to each time period in each driving process of the vehicle and the weight value of each abnormal interval corresponding to each time period.
In the embodiment, when the compressed data is stored, for the driving data when the vehicle normally drives, real-time lossy compression is performed to obtain second compressed data, and the second compressed data is separately stored based on time sequence; in addition, in the embodiment, two storage partitions are provided to respectively store the running data when the vehicle normally runs and the running data when the vehicle abnormally runs, and the specific steps of hierarchically storing the first compressed data corresponding to the running data when the vehicle abnormally runs are as follows:
s1, carrying out priority calculation on the overall data in the multiple driving process by using the overall error degree, specifically, the overall error degree under all abnormal driving states in each driving bookSumming, sorting all the summed values in ascending order, and obtaining the overall error degreeThe single driving process corresponding to the minimum value of the summation value shows that the total amount of the driving data is less, so the storage priority is lowest; degree of integral errorThe single driving process corresponding to the maximum value of the summation value shows that the total amount of the driving data is large, and all the storage priorities are highest.
S2, calculating the storage priority of the running data based on the abnormal degree of all the running data in each running process, specifically, calculating the integral error degree corresponding to the running data generated in all the abnormal running statesSorting in ascending order and the overall error degreeThe storage priority of the driving data generated in the maximum abnormal driving state is highest; degree of integral errorThe running data generated in the minimum abnormal running state is stored with the lowest priority.
S3, calculating the storage level of the running data generated in each abnormal running state, specifically, the abnormal course of the running data corresponding to the single abnormal sectionDegree of rotationSorting in ascending order, and determining the degree of abnormality of the running data in the abnormal sectionThe storage priority of the running data corresponding to the largest abnormal section is highest, and the abnormal degree of the running data of the abnormal sectionThe storage priority of the travel data corresponding to the smallest abnormal section is the lowest.
S4, finally, performing priority-based layered storage on all driving data, specifically, establishing a first priority storage layer, establishing a second priority storage layer in each layer of the first priority storage layer, establishing a third priority storage layer in each layer of the second priority storage layer, storing single driving data with the highest priority in S1 in the highest layer of the first priority storage layer, and then performing layered storage according to priority descending order until the single driving data with the lowest priority are stored in the lowest layer; the highest layer in the second priority layer stores the driving data generated in the abnormal driving state with the highest priority in the S2, and then the driving data is stored in a layered manner according to the descending order of the priority until the lowest layer stores the driving data generated in the abnormal driving state with the lowest priority; the highest layer in the third priority storage layer stores the driving data corresponding to the priority with the highest priority in the S3, and then the driving data are stored in a layered mode according to the descending order of the priority until the driving data with the lowest priority are stored in the lowest layer.
And the playback module is used for reconstructing the track of each driving of the vehicle after decompressing the stored compressed data and transmitting the track to the display end for playback. In this embodiment, in order to play back a certain trajectory of a vehicle, first compressed data and second compressed data corresponding to a driving process of the vehicle are retrieved from the compressed storage module, the first compressed data and the second compressed data are sorted based on the time sequence, the driving data during normal driving is directly decompressed and played back, and the driving data during abnormal driving is corrected by combining with the historical data, and then the trajectory is reconstructed and played back. In the present embodiment, a large data correction method or a leveling correction method is used for the travel data correction.
In summary, the invention provides a system for intelligently replaying a driving track of a mobile phone digital car key, which obtains driving data of abnormal driving of a vehicle through a data acquisition module, analyzes the whole error of the abnormal driving of the vehicle for the driving data of the abnormal driving of the vehicle to reflect the whole error of each abnormal driving track to the maximum extent, divides each abnormal driving track into abnormal intervals through inflection points, analyzes the abnormal intervals, distributes errors according to the analysis result, judges the running path length of each abnormal interval and the accumulation condition of the errors, so as to obtain the abnormal degree of each abnormal interval, further performs lossless compression on the driving data of each abnormal interval in the abnormal driving tracks by using a Manhough coding algorithm according to the abnormal degree of the abnormal intervals, the larger the abnormal degree is, the shorter the coding is, the higher the safety is, the completeness of the driving data in the whole abnormal driving track can be ensured, and the situation that the data is more abnormal due to the fact that the driving data is originally abnormal in the compression process is avoided; the data with small memory space is realized, and the occupation of the memory space is reduced; in addition, the invention also carries out priority level layer storage on the driving data according to the abnormal degree, improves the subsequent retrieval efficiency, and can quickly retrieve the driving data of the abnormal driving track, thereby realizing the playback of the driving track with small storage data and high retrieval efficiency.
It should be noted that: the precedence order of the above embodiments of the present invention is only for description, and does not represent the merits of the embodiments. And specific embodiments thereof have been described above. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that are within the spirit of the present invention are intended to be included therein.
Claims (10)
1. The utility model provides a driving track intelligence playback system of cell-phone digital car key which characterized in that includes:
the data acquisition module is used for acquiring the driving data of abnormal driving of the vehicle; acquiring initial coordinates of the starting time and ending coordinates of the abnormal running of the vehicle through a mobile phone digital vehicle key; the driving data comprises position data and vehicle state information which are acquired when the vehicle runs abnormally;
the track division module is used for acquiring the abnormal driving track of the vehicle according to the driving data and fitting to acquire a driving track function; obtaining a plurality of predicted turning position points when the vehicle runs abnormally by performing high-order derivation on the running track function;
acquiring the overall united difference of abnormal vehicle running according to the coordinates of the plurality of predicted position points; screening out a plurality of accurate position points from the plurality of predicted position points according to the coordinates of the plurality of predicted position points and the overall combined difference of abnormal vehicle running;
dividing the abnormal running track into a plurality of abnormal intervals according to a plurality of accurate position points;
the first parameter acquisition module is used for acquiring the distribution weight of each abnormal interval according to the coordinates of the initial accurate position point and the coordinates of the final accurate position point of each abnormal interval and the number of the predicted position points in each abnormal interval;
acquiring the weight value of each abnormal interval according to the distribution weight value of each abnormal interval and the maximum value and the minimum value in the distribution weight values of all the abnormal intervals;
the second parameter acquisition module is used for acquiring a simulation termination coordinate of the abnormal running termination moment of the vehicle according to the running data; acquiring the integral error degree of the abnormal driving track according to the initial coordinate, the termination coordinate and the simulated termination coordinate of the abnormal driving of the vehicle; acquiring an error value of each abnormal interval according to the weight value of each abnormal interval and the integral error degree of the abnormal driving track;
the compression storage module is used for carrying out Huffman coding on the running data in each abnormal interval and carrying out lossless compression to obtain first compression data according to the probability product of the error value of each abnormal interval and the running data in the corresponding abnormal interval as a weight; the mobile phone digital car key is used for acquiring running data of a vehicle when the vehicle normally runs in each running process of the vehicle, performing lossy compression on the running data of the vehicle when the vehicle normally runs to acquire second compressed data, and storing the first compressed data and the second compressed data in the mobile phone digital car key;
and the playback module is used for decompressing the stored second compressed data and then directly playing back the second compressed data, and the first compressed data is corrected and then the vehicle driving track is reconstructed for playing back the first compressed data.
2. The system for intelligently replaying the vehicle track of the mobile phone digital vehicle key according to claim 1, wherein in the track division module, the vehicle track function is fit according to position data collected by a vehicle in an abnormal driving process; the position data comprises longitude and latitude coordinates of the vehicle at each moment in the abnormal driving process; the independent variable of the driving track function is longitude, and the dependent variable is latitude.
3. The system for intelligently replaying the driving track of a mobile phone digital car key according to claim 2, wherein the predicted position points of the plurality of turns are obtained according to the following steps:
obtaining a second derivative function by carrying out second order derivation on the traveling track function; meanwhile, carrying out third-order derivation on the traveling track function to obtain a third-order derivative function;
and taking a plurality of coordinate points corresponding to the driving track function, which enable the second derivative function to be equal to zero and enable the third derivative function not to be equal to zero, as predicted position points of a plurality of turns.
4. The system for intelligently replaying the driving track of a mobile phone digital car key according to claim 1, wherein in the track division module, the plurality of accurate position points are obtained according to the following steps:
according to the coordinate of the first predicted position point in the plurality of predicted position points and the second predicted position pointCalculating the coordinates of the predicted position points to obtain the first predicted position point to the second predicted position pointInterval difference of the predicted position points; when the interval difference is equal to the overall combined difference of abnormal vehicle running, judging whether the interval difference is equal to the overall combined difference of abnormal vehicle runningThe predicted position points are accurate position points;
5. The system for intelligently replaying the driving track of a mobile phone digital vehicle key according to claim 4, wherein the calculation formula of the overall combined difference of abnormal driving of the vehicle is as follows:
6. The system for intelligently replaying the driving track of the mobile phone digital car key according to claim 1, wherein in the first parameter obtaining module, a calculation formula of a distribution weight of each abnormal interval is as follows:
in the formula,is shown asThe distribution weight of each abnormal interval;is shown asCoordinates of initial accurate position points of the abnormal intervals;is shown asCoordinates of the ending accurate position point of each abnormal interval;is a firstThe number of predicted location points within an interval;is as followsThe number of predicted position points and accurate position points are included in the individual interval.
7. The system for intelligently replaying the vehicle track of the mobile phone digital vehicle key according to claim 1, wherein the data acquisition module further comprises driving data for acquiring abnormal driving of the vehicle in a plurality of different time periods during each driving of the vehicle; dividing the abnormal running track corresponding to each time period into a plurality of abnormal intervals according to a track dividing module;
acquiring a weight value of each abnormal interval corresponding to each time period through a first parameter acquisition module;
acquiring the integral error degree of the abnormal running track corresponding to each time period and the error value of each corresponding abnormal interval through a second parameter acquisition module;
performing Huffman coding on the running data in each abnormal interval corresponding to each time period by using a compression storage module to perform lossless compression to obtain first compressed data, wherein the product of the error value of each abnormal interval corresponding to each time period and the probability of the running data in the corresponding abnormal interval is used as a weight; and storing the first compressed data in the mobile phone digital car key.
8. The system for intelligently replaying the driving track of a mobile phone digital vehicle key according to claim 7, wherein in the storage process, the driving data is hierarchically stored according to the overall error degree of the abnormal driving track corresponding to each time period in each driving process of the vehicle and the weight value of each abnormal interval corresponding to each time period.
9. The system for intelligently replaying the driving track of a mobile phone digital car key according to claim 8, wherein the hierarchical storage is performed according to the following steps:
establishing a first priority storage layer, establishing a second priority storage layer in each first priority storage layer, and establishing a third priority storage layer in each second priority storage layer;
sequentially storing the running data of the abnormal running tracks of different time periods of each running in a first priority storage layer according to the sum of the overall error degrees of the abnormal running tracks of the different time periods in the running process of the vehicle;
sequentially storing the running data of the abnormal running track of each time period in a second priority storage layer in the first priority storage layer according to the sum of the error values of each abnormal interval in the abnormal running track of each time period;
and sequentially storing the running data of each abnormal section in a third priority storage layer in the second priority storage layer according to the error value of each abnormal section in the abnormal running track.
10. The system of claim 1, wherein in the playback module, when the vehicle trajectory is played back in the mobile phone digital vehicle key, the first compressed data and the second compressed data of the driving process are retrieved from the compressed storage module, the first compressed data and the second compressed data are sorted based on the time sequence, the driving data during normal driving is directly decompressed and played back, and the driving data during abnormal driving is corrected and the vehicle trajectory is reconstructed for playback.
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