CN102779420B - Road traffic event automatic detection method based on real-time vehicle-mounted GPS (global position system) data - Google Patents

Road traffic event automatic detection method based on real-time vehicle-mounted GPS (global position system) data Download PDF

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CN102779420B
CN102779420B CN201210269040.7A CN201210269040A CN102779420B CN 102779420 B CN102779420 B CN 102779420B CN 201210269040 A CN201210269040 A CN 201210269040A CN 102779420 B CN102779420 B CN 102779420B
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vehicle
speed
occluder
coordinate
road
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CN102779420A (en
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安实
崔建勋
关积珍
王泽�
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Harbin Institute of Technology
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Harbin Institute of Technology
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Abstract

The invention relates to a road traffic event automatic detection method based on real-time vehicle-mounted GPS (global position system) data, belonging to the technical field of road traffic events, and solving the problem that the mounting cost is expansive and the detection range is limited when traffic events are detected by utilizing a constant infrastructure. A vehicle-mounted GPS receiver is used for realizing coordinate information of a located position of the vehicle-mounted GPS receiver and transmitting the coordinate information to a personal digital assistant; the personal digital assistant is used for realizing computed coordinated information of four corners of a vehicle and transmitting four corner coordinates of the vehicle, the altitude of the vehicle, the driving speed of the vehicle, the driving direction of the vehicle, the time of receiving the coordinate information by the vehicle-mounted GPS receivers and vehicle ID (identity) to a gateway server; and the gateway server is used for realizing storage of information transmitted by all personal digital assistants and is further used for obtaining road traffic events of the located road of a corresponding vehicle according to the information. The invention is suitable for automatic detection of road traffic events.

Description

Road traffic accident automatic testing method based on real-time vehicle GPS data
Technical field
The present invention relates to a kind of road traffic accident automatic testing method based on real-time vehicle GPS data, belong to road traffic accident technical field.
Background technology
The quick increase of road Traffic Volume, has caused various societies, environment and economy problem.The generation of traffic events conventionally causes and has aggravated traffic jam.That traffic events refers to that time of origin or place can not Accurate Predictions, cause the interim thing declining of road passage capability, comprising: traffic hazard, vehicle cast anchor, goods is trickled down etc.The generation of traffic events, detects if can access fast, is just conducive to be eliminated fast, and then reduces the traffic congestion in event section.Therefore, in intelligent transportation system ITS field, the research about event automatic detection method is very extensive.
Except the traffic events detection method based on video camera, other traffic event automatic detection method not can direct-detection event, but will on the impact of traffic flow, carry out indirect detection by them.Event detecting method based on video imaging, again because needs are installed video detecting device in fixed location, causes installation cost costliness and the very limited shortcoming of sensing range.
At present, for traffic events being detected automatically to the method for the collection data that adopt, be mainly divided into 2 classes: (1) is arranged on the static infrastructure sensor outside car, for example inductive coil, magnetometer and video camera; (2) in-vehicle information pick-up unit, for example vehicle GPS.Because various fixed detectors all have self technical limitation and applicable elements, and setup and manage fixedly the work of traffic data checkout equipment is very complicated, will cause expense very expensive.Along with the progress of GPS location technology, the setting accuracy of GPS has obtained great lifting, and installation cost has also obtained larger decline, and this is widely used vehicle GPS.
Summary of the invention
The present invention adopts static infrastructure to detect traffic events in order to solve, and installation cost costliness and the limited problem of sensing range of existence, provide a kind of road traffic accident automatic testing method based on real-time vehicle GPS data.
Road traffic accident automatic testing method based on real-time vehicle GPS data of the present invention, it is realized based on personal digital assistant, GPS receiver and gateway server, and this road traffic accident automatic testing method comprises the steps:
GPS receiver is used for realizing the coordinate information that receives its present position, and this coordinate information is sent to personal digital assistant's step;
Personal digital assistant calculates for realizing the coordinate information that obtains four jiaos, vehicle, and the sea level elevation of the four angular coordinate of this vehicle, vehicle, Vehicle Speed, vehicle heading, GPS receiver are received to the time of coordinate information and the step that vehicle ID sends to gateway server;
Gateway server is for the step of the information that realizes all personal digital assistants that storing received arrives and send, also for realizing according to the step of the road traffic accident in section, described information acquisition corresponding vehicle place.
Gateway server, for the step of the information that realizes all personal digital assistants that storing received arrives and send, for realizing according to the detailed process of the step of the road traffic accident in section, described information acquisition corresponding vehicle place is also:
Step 1: be isometric section by road to be detected according to the grade classification of road, shared region, each section represents by coordinate; According to the direction of wagon flow, by described road, be updrift side and downstream direction, according to the coordinate information of four jiaos, each vehicle receiving, determine the current residing section of corresponding vehicle;
Step 2: according to all vehicle headings in each section to be detected receiving and Vehicle Speed information, calculate the average overall travel speed of the fooled vehicle in front of given wagon flow direction that obtains corresponding section to be detected;
Step 3: the average overall travel speed when vehicle in front obtaining in step 2 is compared to the average speed in this section under similar environmental baseline, when when the average overall travel speed of vehicle in front lower than similar environmental baseline under the average speed in this section surpass the demarcation threshold value presetting, using this section as demarcating section;
Step 4: the average speed that the average overall travel speed when vehicle in front of demarcating section is adjacent to section compares, the minimum section of selection speed is as priority processing section;
Step 5: by the average speed comparison in the average overall travel speed of the vehicle in priority processing section and former and later two adjacent sections, if the speed of a motor vehicle in adjacent section, travel direction the place ahead surpasses higher than the speed of a motor vehicle in the adjacent section in priority processing section and travel direction rear the obstruction threshold value presetting, using priority processing section as doubtful congested link;
Step 6: doubtful congested link is divided into 10 sub-sections, by 10 sub-sections according to step 2 until finally in step 5 judge the mode that obtains doubtful congested link, determine occluder section;
Step 7: all abnormal vehicles with one of following characteristic in identification occluder section:
The July 1st, the speed of a motor vehicle are lower than the average speed in this occluder section;
Seven or two, in halted state;
Seven or three, headstock towards with current wagon flow opposite direction;
Seven or four, position is close from the reference position in occluder section;
Step 8: judged by map datum, whether this occluder section comprises the place that needs stop or the distance location stopping from needs is less than the stop threshold value presetting, and if so, enters into step 9; Otherwise, enter into step 10;
Step 9: the type in the place of stopping as required, determine the blocking time that this place that need to stop can be caused, if surpass after blocking time, the abnormal vehicle behavior that in step 7, identification obtains still exists, and enters step 10;
Step 10: judge whether one of following situation occurs in occluder section:
11,, in occluder section, the average velocity of all vehicles all surpasses lower than the average speed in this sub-section under normal condition the low speed threshold value presetting;
12,, in occluder section, the speed that the average velocity of vehicle declines surpasses the falling-threshold value presetting, thereby causes exception parking;
13, in occluder section, the distance on a certain vehicle coordinate at angle and the border of adjacent vehicle is less than 2 meters;
Step 11: suspend five minutes, and then calculate the average speed in this occluder section, if do not changed, by the map datum in gateway server, indicating this occluder section is traffic events section, and triggers alarm.
Personal digital assistant uses the coordinate information of the NMEA agreement GPS receiver transmission that conversion once receives in every 3 seconds, and uses NMEA protocol processes data.
Personal digital assistant sends data acquisition to gateway server and encodes with XML form, by GPRS mode, sends.
The method that personal digital assistant calculates the coordinate information that obtains four jiaos, vehicle is:
According to the coordinate information of GPS receiver present position, and GPS receiver apart from the horizontal range X1 of the tailstock, GPS receiver horizontal range Y1 and the Y2 apart from horizontal range X2, GPS receiver and the lateral direction of car both sides of headstock, determine the coordinate as four jiaos of A, B, C and D of vehicle in front, i.e. A angular coordinate: A longitude, A latitude; B angular coordinate: B longitude, B latitude; C angular coordinate: C longitude, C latitude; D angular coordinate: D longitude, D latitude.
In described step 1, by road to be detected, according to the grade classification of road, be isometric section, described isometric section is 500 meters.
Advantage of the present invention is: the enforcement of the inventive method, can make the Detection accuracy of road traffic accident be greatly improved, simultaneously because the data detection method of GPS is without fixed test infrastructure is installed, therefore sensing range is wider, the cost of installation and maintenance is simultaneously lower, can meet the fast detecting of the traffic events of highway, city main roads.
Detection method of the present invention, the fast detecting and the emergency action that contribute to improve road traffic accident, thus improve safety and the unimpeded characteristic of road traffic operation.
Detection method of the present invention is also applicable to all vehicles that are mounted with GPS receiver to carry out the automatic detection of road traffic time.
Accompanying drawing explanation
Fig. 1 be the inventive method based on hardware principle schematic diagram;
Fig. 2 is the coordinate schematic diagram of four jiaos, vehicle in embodiment four;
Fig. 3 is for being the division schematic diagram in isometric section according to the grade classification of road by road to be detected;
Fig. 4 is the form schematic diagram in occluder section.
Embodiment
Embodiment one: present embodiment is described below in conjunction with Fig. 1 to Fig. 4, road traffic accident automatic testing method based on real-time vehicle GPS data described in present embodiment, it is realized based on personal digital assistant 1, GPS receiver 2 and gateway server 3, and this road traffic accident automatic testing method comprises the steps:
GPS receiver 2 is for realizing the coordinate information that receives its present position, and this coordinate information sent to personal digital assistant 1 step;
Personal digital assistant 1 calculates for realizing the coordinate information that obtains four jiaos, vehicle, and the sea level elevation of the four angular coordinate of this vehicle, vehicle, Vehicle Speed, vehicle heading, GPS receiver 2 are received to the time of coordinate information and the step that vehicle ID sends to gateway server 3;
The step of the information that gateway server 3 sends for all personal digital assistants 1 that realize storing received and arrive, also for realizing according to the step of the road traffic accident in section, described information acquisition corresponding vehicle place.
Embodiment two: present embodiment is described below in conjunction with Fig. 1 to Fig. 4, present embodiment is further illustrating embodiment one, the step of the information that gateway server 3 sends for all personal digital assistants 1 that realize storing received and arrive, for realizing according to the detailed process of the step of the road traffic accident in section, described information acquisition corresponding vehicle place is also:
Step 1: be isometric section by road to be detected according to the grade classification of road, shared region, each section represents by coordinate; According to the direction of wagon flow, by described road, be updrift side and downstream direction, according to the coordinate information of four jiaos, each vehicle receiving, determine the current residing section of corresponding vehicle;
Step 2: according to all vehicle headings in each section to be detected receiving and Vehicle Speed information, calculate the average overall travel speed of the fooled vehicle in front of given wagon flow direction that obtains corresponding section to be detected;
Step 3: the average overall travel speed when vehicle in front obtaining in step 2 is compared to the average speed in this section under similar environmental baseline, when when the average overall travel speed of vehicle in front lower than similar environmental baseline under the average speed in this section surpass the demarcation threshold value presetting, using this section as demarcating section;
Step 4: the average speed that the average overall travel speed when vehicle in front of demarcating section is adjacent to section compares, the minimum section of selection speed is as priority processing section;
Step 5: by the average speed comparison in the average overall travel speed of the vehicle in priority processing section and former and later two adjacent sections, if the speed of a motor vehicle in adjacent section, travel direction the place ahead surpasses higher than the speed of a motor vehicle in the adjacent section in priority processing section and travel direction rear the obstruction threshold value presetting, using priority processing section as doubtful congested link;
Step 6: doubtful congested link is divided into 10 sub-sections, by 10 sub-sections according to step 2 until finally in step 5 judge the mode that obtains doubtful congested link, determine occluder section;
Step 7: all abnormal vehicles with one of following characteristic in identification occluder section:
The July 1st, the speed of a motor vehicle are lower than the average speed in this occluder section;
Seven or two, in halted state;
Seven or three, headstock towards with current wagon flow opposite direction;
Seven or four, position is close from the reference position in occluder section;
Step 8: judged by map datum, whether this occluder section comprises the place that needs stop or the distance location stopping from needs is less than the stop threshold value presetting, and if so, enters into step 9; Otherwise, enter into step 10;
Step 9: the type in the place of stopping as required, determine the blocking time that this place that need to stop can be caused, if surpass after blocking time, the abnormal vehicle behavior that in step 7, identification obtains still exists, and enters step 10;
Step 10: judge whether one of following situation occurs in occluder section:
11,, in occluder section, the average velocity of all vehicles all surpasses lower than the average speed in this sub-section under normal condition the low speed threshold value presetting;
12,, in occluder section, the speed that the average velocity of vehicle declines surpasses the falling-threshold value presetting, thereby causes exception parking;
13, in occluder section, the distance on a certain vehicle coordinate at angle and the border of adjacent vehicle is less than 2 meters;
Step 11: suspend five minutes, and then calculate the average speed in this occluder section, if do not changed, by the map datum in gateway server 3, indicating this occluder section is traffic events section, and triggers alarm.
In present embodiment, by analyzing vehicle GPS data, can detect abnormal traffic pattern and vehicle behavior on different sections of highway.It has adopted the mode of multilayer: the first stage, identify abnormal traffic pattern section, and then abnormal section is divided into less section, thereby isolate the section that event may occur; Subordinate phase, has carried out the step analysis of vehicle GPS data, uses the rule based on knowledge, detects the generation of abnormal vehicle behavior in abnormal road section scope.
The software and hardware environment of the inventive method operation is as follows:
Hardware environment:
Personal digital assistant PDA, the operation Pocket PC2003 of Microsoft operating system, supports GPRS communication;
GPS receiver, supports wide area expanding system WAAS and differential Global Positioning System DGPS;
Gateway server, has static ip address, can process vehicle GPS data.
Software environment:
PDA application program: the gps signal that adopts NMEA protocol conversion to receive, calculate vehicle longitude and latitude coordinate, data are passed to gateway server;
Gateway server 3:
1), SQL Server 2000 database servers, store car data;
2), the MapPoint2006 of Microsoft, for vehicle tracking, demonstration and map datum reference;
3), detection method application program, inclusion test algorithm, knowledge base, and can carry out alternately with database server and MapPoint map server.
Classification to traffic events:
Identification traffic pattern is very difficult, but it is more difficult to identify individual vehicle behavior, because it depends on the many factors such as time, speed, road type and driver.Traffic pattern is the collection meter performance of individual vehicle behavior, such as average speed and total vehicle number in a certain section.Abnormal vehicle behavior has represented the event with Types Below conventionally:
Car and car collision:
Knock into the back, head-on impact, side hit, side scraping, glancing collision and many cars connect and hit;
Car and thing collision:
Vehicle and roadside object collision, such as line bar, anticollision barrier, trees etc.
Other event:
The roadside that vehicle trouble causes or central parking.
Step 1, to step 6, has realized the detection of the traffic events to causing blocking, and the method for the method based on breaking up one by one, is mainly divided into two Main Stage:
First stage: first, road is divided into section, the length definition in each section depends on the grade of road.For example, highway 500m is mono-section.As shown in Figure 3.
Occupied region, section represents with coordinate.Section has upstream and downstream, represents the trend of wagon flow.The travel direction of vehicle is for determining their whether upstream or downstreams in a certain section.The current coordinate of vehicle is used for determining their current residing sections.
In step 3, if current section is when the average overall travel speed of vehicle in front is largely lower than average speed generally, this section is demarcated to products for further analysis.
In step 5, the minimum speed of a motor vehicle section that doubtful congested link obtains as current judgement, before it, the speed of a motor vehicle in adjacent section is far above this minimum speed of a motor vehicle section.
In step 6, doubtful congested link is divided into 10 less sub-sections, according to step 2, to the determination methods in step 5, can obtains 10 occluder sections in sub-section.
In step 5, obtain the average speed in two sections, front and back of doubtful congested link, be in order to judge whether this doubtful congested link event has occurred or to be only to block up normally.If common blocking up, the average speed in 3 sections should be more approaching so.Yet if what occur is traffic events, the adjacent non-intersection speed before doubtful congested link should be faster than the speed of a motor vehicle in doubtful congested link and its rear adjacent section, and have less vehicle.As shown in Figure 4.
The concrete steps of step 6 are:
Step 6 one: according to all vehicle headings and the Vehicle Speed information in each the sub-section to be detected receiving, calculate the average overall travel speed of the fooled vehicle in front of given wagon flow direction that obtains corresponding sub-section to be detected;
Step 6 two: the average overall travel speed when vehicle in front obtaining in step 6 one is compared to the average speed in this sub-section under similar environmental baseline, when when the average overall travel speed of vehicle in front lower than similar environmental baseline under the average speed in this sub-section surpass the demarcation threshold value presetting, using this sub-section as demarcating sub-section;
Step 6 three: the average speed that the average overall travel speed when vehicle in front of demarcating sub-section is adjacent to sub-section compares, the minimum sub-section of selection speed is as the sub-section of priority processing;
Step 6 four: by the average speed comparison in the average overall travel speed of the vehicle in the sub-section of priority processing and former and later two adjacent sub-sections, if the speed of a motor vehicle in adjacent sub-section, travel direction the place ahead surpasses higher than the speed of a motor vehicle in the adjacent sub-section in the sub-section of priority processing and travel direction rear the obstruction threshold value presetting, using the sub-section of priority processing as occluder section.
Subordinate phase: this stage adopts the method for step analysis, analyzes the data of vehicle in occluder section, thus the behavior of identification vehicle abnormality.
Whether step 8 is used for judging existing in occluder section needs the place of stopping as signal lamp or crossing etc., or from these places close to.
In step 9, for the place of exist to need stopping in occluder section or from these places the situation close to, to whether surpassing the judgement of blocking time, signal lamp is approximately waited for 1 minute, no signal is controlled crossing may wait for 5 minutes.
Step 10 12 in, the judgement to vehicle average velocity fall off rate, such as car speed on fastlink drops to 8km/h from 120km/h at 2-3 in second, can think unusual condition.
Embodiment three: present embodiment is further illustrating embodiment one or two, described in present embodiment, personal digital assistant 1 uses the coordinate information of NMEA agreement GPS receiver 2 transmissions that conversion once receives in every 3 seconds, and uses NMEA protocol processes data.
Embodiment four: present embodiment is for to the further illustrating of embodiment one, two or three, personal digital assistant 1 sends data acquisitions to gateway server 3 with XML form, to encode, by GPRS mode, send described in present embodiment.
Embodiment five: below in conjunction with Fig. 2, present embodiment is described, present embodiment is for to the further illustrating of embodiment one, two, three or four, the method that personal digital assistant 1 calculates the coordinate information that obtains four jiaos, vehicle described in present embodiment is:
According to the coordinate information of GPS receiver 2 present positions, and GPS receiver 2 apart from the horizontal range X1 of the tailstock, GPS receiver 2 apart from the horizontal range X2 of headstock, GPS receiver 2 horizontal range Y1 and the Y2 with lateral direction of car both sides, determine the coordinate as four jiaos of A, B, C and D of vehicle in front, i.e. A angular coordinate: A longitude, A latitude; B angular coordinate: B longitude, B latitude; C angular coordinate: C longitude, C latitude; D angular coordinate: D longitude, D latitude.
In present embodiment, the method for GPS receiver 2 being carried out to data processing is as follows:
GPS receiver 2 is connected with personal digital assistant 1PDA, is placed in vehicle a safety, obvious position.PDA application program by the every conversion in 3 seconds of the gps signal receiving once, is then used NMEA agreement to determine original time and the signal quality of the position of vehicle, speed, travel direction and gps signal.Due to the location coordinate information that GPS receiver 2 is received, be only the physical location of receiver, therefore also need to calculate the accurate coordinates of four jiaos, vehicle, thereby could determine the region that vehicle occupies.
Vehicle boundary definition:
PDA application program needs the positional information of length, width, elevation information and the GPS receiver of vehicle, thereby calculates four jiaos, vehicle, the i.e. accurate coordinates of the A shown in Fig. 2, B, C, tetra-positions of D.In order to calculate the coordinate at four angles of vehicle, need the length of X1, X2, Y1 and Y2 in calculating chart 2.
Determine that area size that vehicle occupies depends on the size of vehicle self.The calculating that vehicle occupies region contributes to calculate the actual range between vehicle, is directed to the different vehicle behavior that detects, and for example collision is very important information.Through calculating, PDA application program has obtained the accurate coordinates of four jiaos, vehicle, and this accurate coordinates adopts WGS-84 form.The coordinate information of these calculating, together with the unique ID of vehicle sea level elevation, speed, travel direction, time and vehicle, all, with the time interval in 3 seconds, constantly sends to gateway server.Server is storage file in vehicle data storehouse, and user can constantly access these files.
Embodiment six: present embodiment is described below in conjunction with Fig. 3, present embodiment is further illustrating embodiment one, two, three, four or five, described in present embodiment, in step 1, by road to be detected, according to the grade classification of road, be isometric section, described isometric section is 500 meters.
Below the estimate of situation under concrete situation is described for example:
One, the discriminating to rear-end collision:
Suppose a car other car that knocked into the back, and be parked on road.In step 7, first analyze the gps data of vehicle in this section, thereby obtain acceleration and the travel direction of vehicle.In the situation that knocking into the back, the speed of a motor vehicle declines very fast.In addition, can there is rotation to a certain degree in vehicle, thereby cause travel direction to change.In step 8, the examination result of map datum shows, there is no to need the often place of parking, so step 9 is skipped in this section.Because vehicle collides with each other, the distance that can detect in step 10 between the coordinate at certain angle of vehicle can be in risk distance.Now, vehicle acceleration abnormal, drive the abnormal vehicle of direction and be demarcated as possible collision vehicle.Step 10 continues to detect a period of time for a moment, if this abnormal transportation condition does not change, is likely collision accident has occurred.
Two, the side accident of hitting is differentiated:
A car hits in the side of another car, causes non-normal stop.
First detect the abnormal acceleration of vehicle or the variation of direction;
Then data according to the map, determine whether this section comprises or the frequent parking site of contiguous a certain needs.If no, enter step 10.If have such as frequent parking sites such as crossings, enter step 9;
Step 9: after latent period, if this road section traffic volume condition does not still change, enter step 10;
Step 10: due to vehicle collision, therefore exist the coordinate between certain angle of vehicle to overlap.Now, the vehicle of abnormal deceleration, angle overlap coordinate and travel direction abnormal change will be demarcated as accident vehicle;
Step 11: continue to observe certain hour, if transportation condition does not change, activate accident alarm.
Three, vehicle casts anchor or bumps against with object:
Vehicle casts anchor in road, and reason may be mechanical disorder or bump against with roadside object.
Step 7: an independent vehicle does not have acceleration in certain section, other vehicle heading generation minor alteration in section;
Step 8: skip;
Step 9: skip;
Step 10: do not identify collision accident;
Step 11: transportation condition does not still change within a certain period of time.
An independent vehicle does not have acceleration in certain section, and in certain hour, certain change occurs travel direction, represents that this vehicle casts anchor in road.

Claims (5)

1. the road traffic accident automatic testing method based on real-time vehicle GPS data, it is realized based on personal digital assistant (1), GPS receiver (2) and gateway server (3), and this road traffic accident automatic testing method comprises the steps:
GPS receiver (2) is for realizing the coordinate information that receives its present position, and this coordinate information sent to the step of personal digital assistant (1);
Personal digital assistant (1) calculates for realizing the coordinate information that obtains four jiaos, vehicle, and the sea level elevation of the four angular coordinate of this vehicle, vehicle, Vehicle Speed, vehicle heading, GPS receiver (2) are received to the time of coordinate information and the step that vehicle ID sends to gateway server (3);
The step of the information that gateway server (3) sends for all personal digital assistants (1) that realize storing received and arrive, also for realizing according to the step of the road traffic accident in section, described information acquisition corresponding vehicle place;
It is characterized in that: the step of the information that gateway server (3) sends for all personal digital assistants (1) that realize storing received and arrive, for realizing according to the detailed process of the step of the road traffic accident in section, described information acquisition corresponding vehicle place is also:
Step 1: be isometric section by road to be detected according to the grade classification of road, shared region, each section represents by coordinate; According to the direction of wagon flow, by described road, be updrift side and downstream direction, according to the coordinate information of four jiaos, each vehicle receiving, determine the current residing section of corresponding vehicle;
Step 2: according to all vehicle headings in each section to be detected receiving and Vehicle Speed information, calculate the average overall travel speed of the fooled vehicle in front of given wagon flow direction that obtains corresponding section to be detected;
Step 3: the average overall travel speed when vehicle in front obtaining in step 2 is compared to the average speed in this section under similar environmental baseline, when when the average overall travel speed of vehicle in front lower than similar environmental baseline under the average speed in this section surpass the demarcation threshold value presetting, using this section as demarcating section;
Step 4: the average speed that the average overall travel speed when vehicle in front of demarcating section is adjacent to section compares, the minimum section of selection speed is as priority processing section;
Step 5: by the average speed comparison in the average overall travel speed of the vehicle in priority processing section and former and later two adjacent sections, if the speed of a motor vehicle in adjacent section, travel direction the place ahead surpasses higher than the speed of a motor vehicle in the adjacent section in priority processing section and travel direction rear the obstruction threshold value presetting, using priority processing section as doubtful congested link;
Step 6: doubtful congested link is divided into 10 sub-sections, by 10 sub-sections according to step 2 until finally in step 5 judge the mode that obtains doubtful congested link, determine occluder section;
Step 7: all abnormal vehicles with one of following characteristic in identification occluder section:
The July 1st, the speed of a motor vehicle are lower than the average speed in this occluder section;
Seven or two, in halted state;
Seven or three, headstock towards with current wagon flow opposite direction;
Seven or four, position is close from the reference position in occluder section;
Step 8: judged by map datum, whether this occluder section comprises the place that needs stop or the distance location stopping from needs is less than the stop threshold value presetting, and if so, enters into step 9; Otherwise, enter into step 10;
Step 9: the type in the place of stopping as required, determine the blocking time that this place that need to stop can be caused, if surpass after blocking time, the abnormal vehicle behavior that in step 7, identification obtains still exists, and enters step 10;
Step 10: judge whether one of following situation occurs in occluder section:
11,, in occluder section, the average velocity of all vehicles all surpasses lower than the average speed in this sub-section under normal condition the low speed threshold value presetting;
12,, in occluder section, the speed that the average velocity of vehicle declines surpasses the falling-threshold value presetting, thereby causes exception parking;
13, in occluder section, the distance on a certain vehicle coordinate at angle and the border of adjacent vehicle is less than 2 meters;
Step 11: suspend five minutes, and then calculate the average speed in this occluder section, if do not changed,, by the map datum in gateway server (3), indicating this occluder section is traffic events section, and triggers alarm.
2. the road traffic accident automatic testing method based on real-time vehicle GPS data according to claim 1, it is characterized in that: personal digital assistant (1) uses the coordinate information of NMEA agreement GPS receiver (2) transmission that conversion once receives in every 3 seconds, and uses NMEA protocol processes data.
3. the road traffic accident automatic testing method based on real-time vehicle GPS data according to claim 1, is characterized in that: personal digital assistant (1) sends data acquisition to gateway server (3) and encodes with XML form, by GPRS mode, sends.
4. the road traffic accident automatic testing method based on real-time vehicle GPS data according to claim 1, is characterized in that: the method that personal digital assistant (1) calculates the coordinate information that obtains four jiaos, vehicle is:
According to the coordinate information of GPS receiver (2) present position, and GPS receiver (2) apart from the horizontal range X1 of the tailstock, GPS receiver (2) apart from the horizontal range X2 of headstock, GPS receiver (2) horizontal range Y1 and the Y2 with lateral direction of car both sides, determine the coordinate as four jiaos of A, B, C and D of vehicle in front, i.e. A angular coordinate: A longitude, A latitude; B angular coordinate: B longitude, B latitude; C angular coordinate: C longitude, C latitude; D angular coordinate: D longitude, D latitude.
5. the road traffic accident automatic testing method based on real-time vehicle GPS data according to claim 1, is characterized in that: in described step 1, by road to be detected, according to the grade classification of road, be isometric section, described isometric section is 500 meters.
CN201210269040.7A 2012-07-31 2012-07-31 Road traffic event automatic detection method based on real-time vehicle-mounted GPS (global position system) data Expired - Fee Related CN102779420B (en)

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