CN109559507A - A kind of about vehicle excess speed event recognition methods of the net based on history GPS track data - Google Patents
A kind of about vehicle excess speed event recognition methods of the net based on history GPS track data Download PDFInfo
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- CN109559507A CN109559507A CN201811362709.0A CN201811362709A CN109559507A CN 109559507 A CN109559507 A CN 109559507A CN 201811362709 A CN201811362709 A CN 201811362709A CN 109559507 A CN109559507 A CN 109559507A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
- G08G1/054—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed photographing overspeeding vehicles
Abstract
The invention discloses a kind of 1, about vehicle excess speed event recognition methods of the net based on history GPS track data, comprising: S1: the road information in the net about track data of vehicle order is stored；Road information includes but is not limited to link name, road speed limit value and road by crossing coordinate；S2: latitude and longitude coordinates under historical trajectory data GCJ coordinate system are converted to the latitude and longitude coordinates under WGS84 coordinate system, reduce offset, guarantee precision；S3: using the about vehicle order track data of the net after coordinate transformation, track point data adjacent in order is successively obtained, section mean speed is then calculated；S4: using road information obtained in S1, path adaptation is carried out, obtains road name and its road speed limit value；S5: comparing section mean speed and obtained road speed limit value, if overall speed is greater than road speed limit value, determines that it is hypervelocity section.
Description
Technical field
The present invention relates to the overspeed of vehicle monitoring technical fields based on big data technology, specially a kind of to be based on history GPS
The about vehicle excess speed event recognition methods of the net of track data.
Background technique
In recent years, with the rise and popularization of net about vehicle, resident trip can reserve special train right place by cell phone application and connect
It send, high degree alleviates difficult problem of calling a taxi, and keeps urban transportation trip more convenient.Net about vehicle facilitates the same of resident trip
When, also because its monitoring management, incentive system is not perfect the problems such as, cause part net Yue Che driver be sent to fastly, more orders and disobey
Anti- traffic rules, wherein it is especially prominent to drive over the speed limit；It drives over the speed limit to seem and saves the time, it is hidden virtually but to increase more safety
Suffer from；Show that there are about three in lethal vehicle collision accident according to National Highway Traffic safety management bureau (NHTSA) report in 2016
/ mono- is related to driving over the speed limit, and causes 10,111 people dead, accounts for about a quarter of current year all toll on traffics.
Currently, most cities intersection is equipped with road speed(-)limit sign board and speed measuring and monitoring camera, part is about
The beam behavior of driving over the speed limit of vehicle driver, but speed measuring and monitoring limited coverage area, and at this stage detection method is mostly thunder
Up to detection and Coil Detector, it can only detect the instantaneous velocity of locality vehicle, vehicle can not be judged in whole driving trace
On whether generate the behavior of driving over the speed limit.Meanwhile most of net about vehicle driver relevant traffic awareness of safety is weaker, and in no prison
Control or the outer section of monitoring range can not detect the behavior of driving over the speed limit of driver.Under present road traffic environment, speed monitoring
And hypervelocity behavior determines that there are still many difficulties.
From 2005, GPS track data were widely used in real-time monitoring driver and drive over the speed limit behavior, in order to sufficiently divide
Net about vehicle hypervelocity reason and its possible security risk are analysed, need to be fully understanded super in net about vehicle history GPS track data
Fast situation.With the development of GPS technology and the opening of major map developer platform, so that in conjunction with API and utilizing GPS track number
It is possibly realized according to the identification behavior of driving over the speed limit.It studies now and judges to surpass using the speed of most only 1 GPS track point of voucher
Speed, thus caused error is larger and is also easy to produce false judgment.Therefore, it needs to probe into a kind of based on history GPS track data
Net about vehicle excess speed event recognition methods.
Summary of the invention
The purpose of the present invention is to provide it is a kind of raising excess speed event detection reliability and accuracy based on history GPS rail
The about vehicle excess speed event recognition methods of the net of mark data both can overcome the disadvantages that existing overspeed testing apparatus can not reflect system-wide section hypervelocity feelings
Condition take single-point speed as the problem of the unreliable inaccuracy of foundation judgement hypervelocity, and can obtain target track by path adaptation algorithm
Road speed-limiting messages determine hypervelocity section by comparing section average speed and speed-limiting messages, and then integrate two continuous hypervelocity areas
Between be a new hypervelocity section, determine excess speed event together, identified to be conducive to excess speed event, improve net about vehicle road driving
Safety embodies practical application value.
In order to solve the above-mentioned technical problem, the technical solution adopted by the present invention is as follows
A kind of about vehicle excess speed event recognition methods of the net based on history GPS track data, comprising the following steps:
S1: the road information in the net about track data of vehicle order is stored；Road information include but is not limited to link name,
Road speed limit value and road are by crossing coordinate；
S2: latitude and longitude coordinates under historical trajectory data GCJ coordinate system are converted to the longitude and latitude under WGS84 coordinate system and are sat
Mark reduces offset, guarantees precision；
S3: using the about vehicle order track data of the net after coordinate transformation, successively obtaining track point data adjacent in order,
Then section mean speed is calculated；
S4: using road information obtained in S1, path adaptation is carried out, obtains road name and its road speed limit value；
S5: comparing section mean speed and obtained road speed limit value, if overall speed is greater than road speed limit value, determines it
For section of exceeding the speed limit.
As a kind of optimal technical scheme, in above-mentioned steps S5, if hypervelocity behavior occurs in continuous two sections,
Two hypervelocity sections are integrated into a hypervelocity section, are confirmed as excess speed event together, and are exceeded the speed limit section after recalculating merging
Average speed.
As a kind of optimal technical scheme, in above-mentioned steps S1, utilize the net about track data of vehicle order and Gao De open
Platform web " grabbing road service " API, is spliced into HTTP request URL for longitude, latitude, order ID, the timestamp in track data,
It receives the JSON formatted data that HTTP request returns and parses, the road information in data is stored in road information file.
As a kind of optimal technical scheme, the step S1 is realized by following procedure:
S101: all historical trajectory datas in a certain order are read；
S102: longitude, latitude, order ID, timestamp in track data collectively constitute the longitude and latitude in required parameter, vehicle
Unique identification, GPS time, driving direction and travel speed in default request parameter are respectively 30 and 20；
Address of service required parameter: being spliced into the URL of HTTP request by S103, and sends request；
S104: receiving the JSON data that HTTP request returns, and JSON data is parsed, by the link name in JSON data, road
Road speed limit value and road are by the coordinate storage at crossing in road information file；
S105: repeated data is removed using program, the source data as path adaptation.
As a kind of optimal technical scheme, the step S2 is realized by following procedure:
S201: certain row track data is read from historical trajectory data file, therefrom intercepts out longitude and latitude conduct
lon0And lat0；
S202: dlon and dlat are obtained using latitude and longitude coordinates conversion function, by parameter dlon, dlat and lon0、lat0Into
New longitude and latitude lon is calculated in row as follows1And lat1；
lon1=2*lon0- dlon, lat1=2*lat0-dlat
S203: the latitude and longitude coordinates information in former track data is updated.
As a kind of optimal technical scheme, the step S3 is realized by following procedure:
S301: track point data adjacent in the about vehicle order of the net after coordinate is converted successively is obtained；
S302: spherical distance computational algorithm is derived using haversine formula and its recurrence formula, calculates two adjacent tracks
Point distance L (m)；
S303: using original timestamp information in order, the time difference Δ t of two adjacent tracing points is accurately calculated
(s)；
S304: pass through formulaAverage speed is calculated, and in track of vehicle data
Middle addition section mean speed.
As a kind of optimal technical scheme, the step S4 is realized by following procedure:
S401: road name, road speed limit and road in road information file are read and and is established by the coordinate at crossing
Tables of data；
S402: road name, road speed limit and road are written in database by the coordinate at crossing, according to phase Tongfang
Database is written in order ID, driver ID, timestamp, longitude and latitude by formula processing；
S403: reading corresponding data, is based on Geohash algorithm, and two-dimentional latitude and longitude coordinates is made to be converted to coding convenient for vehicle
The path adaptation of tracing point；
S404: road name and speed-limiting messages are added in the track of vehicle data of successful match, by two neighboring vehicle
A speed restrictive block is used as between tracing point；If the speed limit of two neighboring track of vehicle point is identical, the road speed limit in the section
For two track of vehicle point speed limits；If the speed limit of two neighboring track of vehicle point is different, take in two neighboring track of vehicle point
Speed limit of the biggish speed limit as the section.
As a kind of optimal technical scheme, the step S5 is realized by following procedure:
S501: the speed-limiting messages for comparing section mean speed and being obtained by path adaptation；
S502: if meetingThen judge it for section of exceeding the speed limit；Otherwise, hypervelocity behavior does not occur for vehicle；
S503: if existing simultaneouslyThen by two continuous hypervelocity sections be integrated into one it is new
Hypervelocity section, is determined as excess speed event together, and recalculate the section mean speed of the event
S504: return step A judges whether next section occurs hypervelocity behavior, until the last one section of order terminates
Judgement.
Detailed description of the invention
Fig. 1 is general flow chart of the invention.
Fig. 2 is the flow chart that speed-limiting messages are obtained using high moral API.
Fig. 3 is the diagram of effect after coordinate transformation.
Fig. 4 is the flow chart for calculating point-to-point transmission average speed.
Fig. 5 is the flow chart that path adaptation obtains speed-limiting messages.
Fig. 6 is to determine excess speed event schematic diagram based on continuous hypervelocity GPS track point.
Specific embodiment
The present invention is described in further details in the following with reference to the drawings and specific embodiments.The present embodiment is that one kind is based on going through
The about vehicle excess speed event recognition methods of the net of history GPS track data obtains history GPS track data section by path adaptation algorithm
Speed limit value, compares calculating gained section mean speed and road speed limit value, identification hypervelocity section, and then by two continuous hypervelocity sections
It merges into a new section and is confirmed as excess speed event together.By coordinate transformation, Gao De API obtain speed limit, path adaptation,
Speed calculates, hypervelocity judges five crucial operating procedures, realizes that the about vehicle excess speed event of the net based on history GPS track data is known
Not, as shown in Figure 1, the specific steps are as follows:
S1: " road is grabbed to service " API using the net about track data of vehicle order and Gao De open platform web, by track data
In longitude, latitude, order ID, timestamp be spliced into HTTP request URL, receive JSON formatted data that HTTP request returns simultaneously
Parsing, by link name, road speed limit value and the road in data by crossing coordinate storage in road information file, track number
According to format such as following table；
Further, as shown in Fig. 2, speed limit acquisition methods specifically include:
S101: all historical trajectory datas in a certain order are read；
S102: longitude, latitude, order ID, timestamp in track data collectively constitute the longitude and latitude in required parameter, vehicle
Unique identification, GPS time, driving direction and travel speed in default request parameter are respectively 30 and 20.
Address of service required parameter: being spliced into the URL of HTTP request by S103, and sends request；
S104: receiving the JSON data that HTTP request returns, and JSON data is parsed, by the link name in JSON data, road
Road speed limit value and road are by the coordinate storage at crossing in road information file；
S105: repeated data is removed using program, the source data as path adaptation.
S2: latitude and longitude coordinates under historical trajectory data GCJ coordinate system are converted to the longitude and latitude under WGS84 coordinate system and are sat
Mark reduces offset, guarantees precision, and coordinate-system is described as follows；
Further, coordinate transformation specific method includes:
S201: certain row track data is read from historical trajectory data file, therefrom intercepts out longitude and latitude conduct
lon0And lat0；
S202: dlon and dlat are obtained using latitude and longitude coordinates conversion function, by parameter dlon, dlat and lon0、lat0Into
New longitude and latitude lon is calculated in row as follows1And lat1。
lon1=2*lon0- dlon, lat1=2*lat0-dlat
Dlon and dlat by being calculated as follows:
X=lon0-105
Y=lat0-35
RadLat=lat0*0.017453292519943295
Magic=sin (radLat)
Magic=1-0.00669437999013*magic*magic
Lat=Lat* (magic*sqrtMagic) * 0.00000904369477
Dlat=lat0+Lat
Dlon=lon0+Lon
Calculate new longitude and latitude lon1And lat1:
lon1=2*lon0-dlon
lat1=2*lat0-dlat
S203: updating the latitude and longitude coordinates information in former track data, effect after coordinate transformation, as shown in Figure 3.
S3: using the about vehicle order track data of the net after coordinate transformation, successively obtaining track point data adjacent in order,
Distance is calculated by spherical distance computational algorithm, calculates the time difference using timestamp, passes through average speed calculation formula meter
Calculate section mean speed.
Further, as shown in figure 4, the step S3 is specifically included:
S301: track point data adjacent in the about vehicle order of the net after coordinate is converted successively is obtained；
S302: spherical distance computational algorithm is derived using haversine formula and its recurrence formula, calculates two adjacent tracks
Point distance L (m)；
S303: using original timestamp information in order, the time difference Δ t of two adjacent tracing points is accurately calculated
(s)；
S304: pass through formulaAverage speed is calculated, and in track of vehicle data
Middle addition section mean speed
Further, spherical distance computational algorithm includes:
Step A: the central angle θ on sphere between any two points is set are as follows:
Wherein L is the distance between two o'clock (spherical distance), and R is the radius of sphere；
Step B: haversine (haversine) formula is given by:
WhereinIndicate the latitude of point 1 and the latitude of point 2, λ1, λ2Indicate the longitude of point 1 and the longitude of point 2；
Step C: the haversine function (half precision) (applied on the difference of latitude and longitude) of angle, θ is:
Step D: seeking the distance L of two o'clock, will inverse haversine formula hav-1Applied to central angle θ or use arcsin function:
Wherein h=hav (θ)；
(1) formula is substituted into (2) formula:
S4: using road information file obtained in step 1, path adaptation is realized using Geohash algorithm, obtains road
Road title and its speed-limiting messages；.
Further, as shown in figure 5, path adaptation described in step 4 specifically includes:
S401: road name, road speed limit and road in road information file are read and and is established by the coordinate at crossing
Tables of data；
S402: road name, road speed limit and road are written in database by the coordinate at crossing, according to phase Tongfang
Database is written in order ID, driver ID, timestamp, longitude and latitude by formula processing；
S403: reading corresponding data, is based on Geohash algorithm, and two-dimentional latitude and longitude coordinates is made to be converted to coding convenient for vehicle
The path adaptation of tracing point.Such as coordinate (116.389550,39.928167) is encoded to wx4g0ec1, prefix wx4g0e is indicated
Include range bigger including coding wx4g0ec1 etc..The characteristic can be used for searching for place nearby, currently be sat according to user first
Mark calculates Geohash (such as wx4g0ec1) and then its prefix is taken to be inquired (SELECT*FROM place WHERE
Geohash LIKE ' wx4g0e% '), obtain the corresponding region coding wx4g0e, in the zone original encoding (wx4g0ec1) with most
Similar coding is matched；
S404: adding road name and speed-limiting messages in the track of vehicle data of successful match, then will be two neighboring
A speed restrictive block is used as between track of vehicle point.If the speed limit of two neighboring track of vehicle point is identical, the road in the section
Speed limit is two track of vehicle point speed limits；If the speed limit of two neighboring track of vehicle point is different, two neighboring track of vehicle is taken
Speed limit of the biggish speed limit as the section in point.
Further, GeoHash algorithm specific steps described in step 4 include:
What Geohash was indicated is not a point, but a rectangular area.Not only it can be shown that oneself position, but also be unlikely to
The accurate coordinates to stick one's chin out, facilitate secret protection.
The calculating step of Geohash algorithm is introduced by taking Beihai park as an example.It is compiled according to calculation of longitude & latitude GeoHash binary system
Code, terrestrial latitude section is [- 90,90], and the latitude of Beihai park is 39.928167, can be by following algorithm to latitude
39.928167 carrying out approach coding:
1) section [- 90,90] carry out two points for [- 90,0), [0,90], referred to as left and right section can determine 39.928167
Belong to right section [0,90], to labeled as 1；
2) then by section [0,90] carry out two points for [0,45), [45,90] can determine that 39.928167 belong to Zuo Qu
Between [0,45), to labeled as 0；
3) the recurrence above process 39.928167 always belongs to some section [a, b].As each iteration section [a, b] is total
It is reducing, and is increasingly approaching 39.928167；
4) if given latitude x (39.928167) belongs to left section, 0 is recorded, records 1 if belonging to right section,
Can generate a sequence 1011100 with algorithm, the length of sequence is related with given interval division number.
Similarly, terrestrial longitude section is [- 180,180], can be encoded to longitude 116.389550.
By above-mentioned calculating, what latitude generated is encoded to 10,111 00011, and what longitude generated is encoded to 11,010 01011.
Even bit is attributed to longitude, and odd number is attributed to latitude, 2 string encoding combination producings is newly gone here and there: 11,100 11,101 00,100 01111.
Finally Base32 coding is carried out using with this 32 letters of 0-9, b-z (removing a, i, l, o).First by 11100
11101 00,100 01111 change into the decimal system, correspond to 28,29,4,15, the corresponding coding of the decimal system is exactly wx4g.Similarly, will
Code conversion at longitude and latitude decoding algorithm in contrast.
S5: comparing calculating gained section mean speed and obtained road speed limit value, if overall speed is greater than road speed limit value,
Then determine that it is hypervelocity section；If hypervelocity behavior occurs in continuous two sections, two hypervelocity sections are confirmed as one
Excess speed event is played, and recalculates the average speed in hypervelocity section after merging.As shown in Figure 6.
Further, excess speed event described in step S5 judges that algorithm specifically includes:
S501: the speed-limiting messages for comparing section mean speed and being obtained by path adaptation；
S502: if meetingThen judge it for section of exceeding the speed limit；Otherwise, hypervelocity behavior does not occur for vehicle；
S503: if existing simultaneouslyTwo continuous hypervelocity sections are then integrated into a new hypervelocity
Excess speed event together is confirmed as in section, and recalculates the section mean speed of the event
S504: return step A judges whether next section occurs hypervelocity behavior, until the last one section of order is tied
Beam.
Claims (8)
1. a kind of about vehicle excess speed event recognition methods of the net based on history GPS track data, which is characterized in that including following step
It is rapid:
S1: the road information in the net about track data of vehicle order is stored；Road information includes but is not limited to link name, road
Speed limit value and road are by crossing coordinate；
S2: latitude and longitude coordinates under historical trajectory data GCJ coordinate system are converted to the latitude and longitude coordinates under WGS84 coordinate system, are subtracted
Few offset, guarantees precision；
S3: using the about vehicle order track data of the net after coordinate transformation, track point data adjacent in order is successively obtained, then
Calculate section mean speed；
S4: using road information obtained in S1, path adaptation is carried out, obtains road name and its road speed limit value；
S5: comparing section mean speed and obtained road speed limit value, if overall speed is greater than road speed limit value, determines that it is super
Fast section.
2. a kind of about vehicle excess speed event recognition methods of the net based on history GPS track data according to claim 1, special
Sign is, in above-mentioned steps S5, if hypervelocity behavior occurs in continuous two sections, two hypervelocity sections are integrated into one
A hypervelocity section, is confirmed as excess speed event together, and recalculates the average speed in hypervelocity section after merging.
3. a kind of about vehicle excess speed event recognition methods of the net based on history GPS track data according to claim 1, special
Sign is, in above-mentioned steps S1, " grabs road to service " API using the net about track data of vehicle order and Gao De open platform web, will
Longitude, latitude, order ID, timestamp in track data are spliced into HTTP request URL, receive the JSON lattice that HTTP request returns
Formula data simultaneously parse, and the road information in data is stored in road information file.
4. a kind of about vehicle excess speed event recognition methods of the net based on history GPS track data according to claim 3, special
Sign is that the step S1 is realized by following procedure:
S101: all historical trajectory datas in a certain order are read；
S102: longitude, latitude, order ID, timestamp in track data collectively constitute the longitude and latitude in required parameter, and vehicle is only
One mark, GPS time, in addition the driving direction in required parameter and travel speed are defaulted as 30 and 20 respectively；
Address of service required parameter: being spliced into the URL of HTTP request by S103, and sends request；
S104: receiving the JSON data that HTTP request returns, and parses JSON data, and the link name in JSON data, road are limited
Speed value and road are by the coordinate storage at crossing in road information file；
S105: repeated data is removed using program, the source data as path adaptation.
5. a kind of about vehicle excess speed event recognition methods of the net based on history GPS track data according to claim 1, special
Sign is that the step S2 is realized by following procedure:
S201: reading certain row track data from historical trajectory data file, therefrom intercepts out longitude and latitude as lon0With
lat0；
S202: dlon and dlat are obtained using latitude and longitude coordinates conversion function, by parameter dlon, dlat and lon0、lat0It carries out such as
Under new longitude and latitude lon is calculated1And lat1；
lon1=2*lon0- dlon, lat1=2*lat0-dlat
S203: the latitude and longitude coordinates information in former track data is updated.
6. a kind of about vehicle excess speed event recognition methods of the net based on history GPS track data according to claim 1, special
Sign is that the step S3 is realized by following procedure:
S301: track point data adjacent in the about vehicle order of the net after coordinate is converted successively is obtained；
S302: deriving spherical distance computational algorithm using haversine formula and its recurrence formula, calculate two adjacent tracing points away from
From L (m)；
S303: using original timestamp information in order, the time difference Δ t (s) of two adjacent tracing points is accurately calculated；
S304: pass through formulaAverage speed is calculated, and is added in track of vehicle data
Section mean speed.
7. a kind of about vehicle excess speed event recognition methods of the net based on history GPS track data according to claim 1, special
Sign is that the step S4 is realized by following procedure:
S401: road name, road speed limit and road in road information file are read and and establishes data by the coordinate at crossing
Table；
S402: road name, road speed limit and road are written in database by the coordinate at crossing, at same way
Database is written in order ID, driver ID, timestamp, longitude and latitude by reason；
S403: reading corresponding data, is based on Geohash algorithm, and two-dimentional latitude and longitude coordinates is made to be converted to coding convenient for track of vehicle
The path adaptation of point；
S404: road name and speed-limiting messages are added in the track of vehicle data of successful match, by two neighboring track of vehicle
A speed restrictive block is used as between point；If the speed limit of two neighboring track of vehicle point is identical, the road speed limit in the section is two
A track of vehicle point speed limit；If the speed limit of two neighboring track of vehicle point is different, take larger in two neighboring track of vehicle point
Speed limit of the speed limit as the section.
8. a kind of about vehicle excess speed event recognition methods of the net based on history GPS track data according to claim 2, special
Sign is that the step S5 is realized by following procedure:
S501: the speed-limiting messages for comparing section mean speed and being obtained by path adaptation；
S502: if meetingThen judge it for section of exceeding the speed limit；Otherwise, hypervelocity behavior does not occur for vehicle；
S503: if existing simultaneouslyTwo continuous hypervelocity sections are then integrated into a new hypervelocity area
Between, it is determined as excess speed event together, and recalculate the section mean speed of the event
S504: return step A judges whether next section occurs hypervelocity behavior, until the last one section of order terminates to sentence
It is disconnected.
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| CN113554891A (en) * | 2021-07-19 | 2021-10-26 | 江苏南大苏富特智能交通科技有限公司 | Method for constructing electronic map road network based on bus GPS track |
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