CN102779420A - 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 PDFInfo
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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
Technical field
The present invention relates to a kind of road traffic accident automatic testing method, belong to the road traffic accident technical field based on real-time vehicle GPS data.
Background technology
The quick increase of road Traffic Volume has caused various societies, environment and economic problems.The generation of traffic events causes usually and has aggravated traffic jam.That traffic events is meant is that time of origin or place can not accurately be predicted, cause the interim thing that descends of road passage capability, and comprising: traffic hazard, vehicle cast anchor, goods is trickled down etc.The generation of traffic events detects if can access fast, just helps being eliminated fast, and then the traffic congestion in the incident of reduction highway section.Therefore, the research about event automatic detection method is very extensive in the intelligent transportation system ITS field.
Except the traffic events detection method based on video camera, other traffic event automatic detection method is not directly to detect incident, but will carry out indirect detection to the influence of traffic flow through them.Based on the event detecting method of video imaging, owing to need video detecting device be installed, cause the shortcoming that installation cost is expensive and sensing range is very limited again in the fixed location.
At present, for the method that traffic events is detected automatically the collection data that adopt mainly is divided into 2 types: (1) is installed in the outer static infrastructure sensor of 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 install and manage the fixedly work ten minutes complicacy of traffic data checkout equipment, 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 bigger decline, and this makes that vehicle GPS has obtained using widely.
Summary of the invention
The present invention adopts static infrastructure to detect traffic events in order to solve, and the expensive and limited problem of sensing range of the installation cost of existence provides 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 according to the invention, it realizes that based on personal digital assistant, vehicle GPS receiver and gateway server this road traffic accident automatic testing method comprises the steps:
The vehicle GPS receiver is used to realize receiving the coordinate information of its present position, and this coordinate information is sent to personal digital assistant's step;
The personal digital assistant is used to realize calculating the coordinate information that obtains four jiaos on vehicle, and four angular coordinate, the sea level elevation of vehicle, Vehicle Speed, vehicle heading, the vehicle GPS receiver of this vehicle received the time of coordinate information and the step that vehicle ID sends to gateway server;
Gateway server is used to realize storing the step of the information that all personal digital assistants of receiving send, and also is used to realize the step according to the road traffic accident in highway section, said information acquisition corresponding vehicle place.
Gateway server is used to realize storing the step of the information that all personal digital assistants of receiving send, and also is used to realize according to the detailed process of the step of the road traffic accident in highway section, said information acquisition corresponding vehicle place be:
Step 1: is isometric highway section with road to be detected according to the grade classification of road, and the shared zone passage coordinate in each highway section is represented; Direction according to wagon flow is updrift side and downstream direction with said road, confirms corresponding vehicle present located highway section according to the coordinate information of four jiaos on each vehicle that receives;
Step 2:, calculate to obtain the average overall travel speed of current vehicle on the given wagon flow direction in corresponding highway section to be detected according to all vehicle headings in each highway section to be detected that receives and Vehicle Speed information;
Step 3: the average speed in this highway section under the average overall travel speed of the current vehicle that obtains in the step 2 and the similar environmental baseline is compared; The average speed that is lower than this highway section under the similar environmental baseline when the average overall travel speed of current vehicle surpasses the demarcation threshold value that presets, then with this highway section as demarcating the highway section;
Step 4: the average speed that the average overall travel speed that will demarcate the current vehicle in highway section is adjacent the highway section compares, and the minimum highway section of selection speed is as the priority processing highway section;
Step 5: relatively with the average speed in the average overall travel speed of the vehicle in priority processing highway section and former and later two adjacent highway sections; If the speed of a motor vehicle in adjacent highway section, travel direction the place ahead is higher than the speed of a motor vehicle in the adjacent highway section in priority processing highway section and travel direction rear and surpasses the obstruction threshold value that presets, then with the priority processing highway section as doubtful congested link;
Step 6: doubtful congested link is divided into 10 sub-highway sections, the occluder highway section according to step 2 last mode of judging the doubtful congested link of acquisition in step 5, is confirmed in 10 sub-highway sections;
Step 7: all have the unusual vehicle of one of following characteristic in the identification occluder highway section:
The July 1st, the speed of a motor vehicle are lower than the average speed in this occluder highway section;
Seven or two, be in halted state;
Seven or three, headstock is towards in the opposite direction with current wagon flow;
Seven or four, the position from the reference position in occluder highway section near;
Step 8: judge by map datum, this occluder highway section whether comprise place that needs stop or from the distance location of needs parking less than the stop threshold value that presets, if enter into step 9; Otherwise, enter into step 10;
Step 9: the type in the place of stopping as required, confirm the blocking time that this place that need stop can be caused, if after surpassing blocking time, the unusual vehicle behavior that identification obtains in the step 7 still exists, and gets into step 10;
Step 10: judge whether one of following situation takes place in the occluder highway section:
11, in the occluder highway section, the average speed that the average velocity of all vehicles all is lower than this sub-highway section under the normal condition surpasses the low speed threshold value that presets;
12, in the occluder highway section, the speed that the average velocity of vehicle descends surpasses the falling-threshold value that presets, thereby causes exception parking;
13, in the occluder highway section distance on the border of the coordinate at a certain vehicle angle and adjacent vehicle less than 2 meters;
Step 11: suspend five minutes, and then calculate the average speed in this occluder highway section, if do not change, then with on the map datum in the gateway server, indicating this occluder highway section is the traffic events highway section, and triggers alarm.
The personal digital assistant uses the coordinate information of the NMEA agreement vehicle GPS receiver transmission that conversion once receives in per 3 seconds, and uses NMEA protocol processes data.
The personal digital assistant sends The data XML form to gateway server and encodes, and sends through the GPRS mode.
The method that the personal digital assistant calculates the coordinate information that obtains four jiaos on vehicle is:
Coordinate information according to vehicle GPS receiver present position; And the vehicle GPS receiver is apart from the horizontal range X1 of the tailstock, vehicle GPS receiver horizontal range Y1 and the Y2 apart from horizontal range X2, vehicle GPS receiver and the lateral direction of car both sides of headstock; Confirm the coordinate of four jiaos of A, B, C and D of current vehicle, i.e. the 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.
Be isometric highway section with road to be detected according to the grade classification of road in the said step 1, said isometric highway section is 500 meters.
Advantage of the present invention is: the enforcement of the inventive method; Can make the detection accuracy rate of road traffic accident be greatly improved; Simultaneously because the Data Detection method of GPS need not to install and fix detection infrastructure; Therefore sensing range is wider, and the cost of installation and maintenance simultaneously is lower, can satisfy the fast detecting of the traffic events of highway, city main roads.
Detection method according to the invention, the fast detecting and the emergency action that help to improve road traffic accident, thus improve the safety and the unimpeded characteristic of road traffic operation.
Detection method according to the invention also is applicable to carries out the automatic detection of road traffic time to all vehicles that is mounted with the vehicle GPS receiver.
Description of drawings
Fig. 1 be the inventive method based on the hardware principle synoptic diagram;
Fig. 2 is the coordinate synoptic diagram of four jiaos on vehicle in the embodiment four;
Fig. 3 is for being the division synoptic diagram in isometric highway section according to the grade classification of road with road to be detected;
Fig. 4 is the form synoptic diagram in occluder highway section.
Embodiment
Embodiment one: this embodiment is described below in conjunction with Fig. 1 to Fig. 4; The said road traffic accident automatic testing method of this embodiment based on real-time vehicle GPS data; It realizes that based on personal digital assistant 1, vehicle GPS receiver 2 and gateway server 3 this road traffic accident automatic testing method comprises the steps:
Personal digital assistant 1 is used to realize calculating the coordinate information that obtains four jiaos on vehicle, and four angular coordinate, the sea level elevation of vehicle, Vehicle Speed, vehicle heading, the vehicle GPS receiver 2 of this vehicle received the time of coordinate information and the step that vehicle ID sends to gateway server 3;
Embodiment two: this embodiment is described below in conjunction with Fig. 1 to Fig. 4; This embodiment is further specifying embodiment one; Gateway server 3 is used to realize storing the step of the information that all personal digital assistants 1 of receiving send, and also is used to realize according to the detailed process of the step of the road traffic accident in highway section, said information acquisition corresponding vehicle place be:
Step 1: is isometric highway section with road to be detected according to the grade classification of road, and the shared zone passage coordinate in each highway section is represented; Direction according to wagon flow is updrift side and downstream direction with said road, confirms corresponding vehicle present located highway section according to the coordinate information of four jiaos on each vehicle that receives;
Step 2:, calculate to obtain the average overall travel speed of current vehicle on the given wagon flow direction in corresponding highway section to be detected according to all vehicle headings in each highway section to be detected that receives and Vehicle Speed information;
Step 3: the average speed in this highway section under the average overall travel speed of the current vehicle that obtains in the step 2 and the similar environmental baseline is compared; The average speed that is lower than this highway section under the similar environmental baseline when the average overall travel speed of current vehicle surpasses the demarcation threshold value that presets, then with this highway section as demarcating the highway section;
Step 4: the average speed that the average overall travel speed that will demarcate the current vehicle in highway section is adjacent the highway section compares, and the minimum highway section of selection speed is as the priority processing highway section;
Step 5: relatively with the average speed in the average overall travel speed of the vehicle in priority processing highway section and former and later two adjacent highway sections; If the speed of a motor vehicle in adjacent highway section, travel direction the place ahead is higher than the speed of a motor vehicle in the adjacent highway section in priority processing highway section and travel direction rear and surpasses the obstruction threshold value that presets, then with the priority processing highway section as doubtful congested link;
Step 6: doubtful congested link is divided into 10 sub-highway sections, the occluder highway section according to step 2 last mode of judging the doubtful congested link of acquisition in step 5, is confirmed in 10 sub-highway sections;
Step 7: all have the unusual vehicle of one of following characteristic in the identification occluder highway section:
The July 1st, the speed of a motor vehicle are lower than the average speed in this occluder highway section;
Seven or two, be in halted state;
Seven or three, headstock is towards in the opposite direction with current wagon flow;
Seven or four, the position from the reference position in occluder highway section near;
Step 8: judge by map datum, this occluder highway section whether comprise place that needs stop or from the distance location of needs parking less than the stop threshold value that presets, if enter into step 9; Otherwise, enter into step 10;
Step 9: the type in the place of stopping as required, confirm the blocking time that this place that need stop can be caused, if after surpassing blocking time, the unusual vehicle behavior that identification obtains in the step 7 still exists, and gets into step 10;
Step 10: judge whether one of following situation takes place in the occluder highway section:
11, in the occluder highway section, the average speed that the average velocity of all vehicles all is lower than this sub-highway section under the normal condition surpasses the low speed threshold value that presets;
12, in the occluder highway section, the speed that the average velocity of vehicle descends surpasses the falling-threshold value that presets, thereby causes exception parking;
13, in the occluder highway section distance on the border of the coordinate at a certain vehicle angle and adjacent vehicle less than 2 meters;
Step 11: suspend five minutes, and then calculate the average speed in this occluder highway section, if do not change, then with on the map datum in the gateway server 3, indicating this occluder highway section is the traffic events highway section, and triggers alarm.
In this embodiment,, can detect unusual traffic pattern and vehicle behavior on the different highway sections through analyzing the vehicle GPS data.It has adopted the mode of multilayer: the phase one, discern unusual traffic pattern highway section, and then unusual highway section is divided into littler highway section, thereby isolate the highway section of the incident that possibly take place; Subordinate phase has been carried out the step analysis of vehicle GPS data, uses the rule based on knowledge, in unusual road section scope, detects the generation of unusual vehicle behavior.
The software and hardware environment of the inventive method operation is following:
Hardware environment:
Personal digital assistant PDA, the operation Pocket PC2003 of Microsoft operating system is supported GPRS communication;
The vehicle GPS receiver is supported wide area expanding system WAAS and DGPS DGPS;
Gateway server has static ip address, can handle the vehicle GPS data.
Software environment:
The PDA application program: the gps signal that adopts the 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, the store car data;
2), the MapPoint2006 of Microsoft, be used for vehicle tracking, demonstration and map datum reference;
3), the detection method application program, comprise detection 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 discern the individual vehicle behavior, because it depends on many-sided factors such as time, speed, road type and driver.The traffic pattern is the collection meter performance of individual vehicle behavior, such as average speed and total vehicle number in a certain highway section.The incident of following type has been represented in unusual vehicle behavior usually:
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 are such as line bar, anticollision barrier, trees etc.
Other incident:
Roadside that vehicle trouble causes or central parking.
Phase one: at first, road is divided into the highway section, the length definition in each highway section depends on the grade of road.For example, highway 500m is one section.As shown in Figure 3.
Occupied zone, highway section is represented with coordinate.The highway section has upstream and downstream, represents the trend of wagon flow.The travel direction of vehicle is used for confirming whether they are in the upper reaches or the downstream in a certain highway section.The current coordinate of vehicle is used for confirming their present located highway sections.
In the step 3,, then this highway section is demarcated the products for further analysis if the average overall travel speed of current highway section current vehicle is lower than average speed generally speaking largely.
In the step 5, doubtful congested link is as judge the minimum speed of a motor vehicle highway section that obtains at present, and the speed of a motor vehicle in its adjacent highway section, front is far above this minimum speed of a motor vehicle highway section.
In the step 6, doubtful congested link is divided into 10 littler sub-highway sections,, can obtains 10 occluder highway sections in the sub-highway section according to the determination methods in step 2 to the step 5.
In step 5, obtain the average speed in two highway sections, front and back of doubtful congested link, be in order to judge whether this doubtful congested link incident has taken place or only to be to block up normally.Iff is common blocking up, and the average speed in 3 highway sections should be more approaching so.Yet if generation is traffic events, the adjacent non-intersection speed of doubtful congested link front should be faster than the speed of a motor vehicle in doubtful congested link and its rear adjacent highway section, and have less vehicle.As shown in Figure 4.
The concrete steps of step 6 are:
Step 6 one:, calculate to obtain the average overall travel speed of current vehicle on the given wagon flow direction in corresponding sub-highway section to be detected according to all vehicle headings and the Vehicle Speed information in each the sub-highway section to be detected that receives;
Step 6 two: the average speed in this sub-highway section under the average overall travel speed of the current vehicle that obtains in the step 6 one and the similar environmental baseline is compared; The average speed that is lower than this sub-highway section under the similar environmental baseline when the average overall travel speed of current vehicle surpasses the demarcation threshold value that presets, then should sub-highway section as the sub-highway section of demarcation;
Step 6 three: the average speed that the average overall travel speed that will demarcate the current vehicle in sub-highway section is adjacent sub-highway section compares, and the minimum sub-highway section of selection speed is as the sub-highway section of priority processing;
Step 6 four: relatively with the average speed in the average overall travel speed of the vehicle in the sub-highway section of priority processing and former and later two adjacent sub-highway sections; If the speed of a motor vehicle in adjacent sub-highway section, travel direction the place ahead is higher than the speed of a motor vehicle in the adjacent sub-highway section in sub-highway section of priority processing and travel direction rear and surpasses the obstruction threshold value that presets, then with the sub-highway section of priority processing as the occluder highway section.
Subordinate phase: this stage is adopted the method for step analysis, analyzes the data of vehicle in the occluder highway section, thus the behavior of identification vehicle abnormality.
Step 8 is used for judging whether have the place of stopping like needs such as signal lamp or crossings in the occluder highway section, and is perhaps nearer from these places.
In the step 9, the place of need stopping to existence in the occluder highway section or from the nearer situation in these places, to whether surpassing the judgement of blocking time, signal lamp is approximately waited for 1 minute, no signal control crossing possibly waited for 5 minutes.
Step 10 12 in, to the judgement of vehicle average velocity fall off rate, drop to 8km/h from 120km/h at 2-3 in second such as car speed on the fastlink, can think unusual condition.
Embodiment three: this embodiment is further specifying embodiment one or two; The said personal digital assistant 1 of this embodiment uses the coordinate information of NMEA agreement vehicle GPS receiver 2 transmissions that conversion once receives in per 3 seconds, and uses NMEA protocol processes data.
Embodiment four: this embodiment is for to the further specifying of embodiment one, two or three, and the said personal digital assistant 1 of this embodiment sends The data XML forms for gateway server 3 and encodes, and sends through the GPRS mode.
Embodiment five: below in conjunction with Fig. 2 this embodiment is described, this embodiment is for to the further specifying of embodiment one, two, three or four, and the method that the said personal digital assistant 1 of this embodiment calculates the coordinate information that obtains four jiaos on vehicle is:
Coordinate information according to vehicle GPS receiver 2 present positions; And vehicle GPS receiver 2 apart from the horizontal range X1 of the tailstock, vehicle GPS receiver 2 apart from the horizontal range X2 of headstock, vehicle GPS receiver 2 horizontal range Y1 and Y2 with the lateral direction of car both sides; Confirm the coordinate of four jiaos of A, B, C and D of current vehicle, i.e. the 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 this embodiment, the method for vehicle GPS receiver 2 being carried out data processing is following:
The vehicle boundary definition:
The PDA application program needs the positional information of length, width, elevation information and the vehicle GPS receiver of vehicle, thereby calculates four jiaos on vehicle, the accurate coordinates of A promptly shown in Figure 2, B, C, four positions of D.In order to calculate the coordinate at four angles of vehicle, need the length of X1, X2, Y1 and Y2 in the calculating chart 2.
Confirm that area size that vehicle occupies depends on the size of vehicle self.The calculating that vehicle occupies the zone helps to calculate the actual range between the vehicle, is directed to the different vehicle behavior that detects, and for example collision is crucial information.Through calculating, the PDA application program has obtained the accurate coordinates of four jiaos on vehicle, and this accurate coordinates adopts the 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 the vehicle data storehouse, and the user can constantly visit these files.
Embodiment six: this embodiment is described below in conjunction with Fig. 3; This embodiment is further specifying embodiment one, two, three, four or five; Be isometric highway section with road to be detected according to the grade classification of road in the said step 1 of this embodiment, said isometric highway section is 500 meters.
Below the estimate of situation under the concrete situation is described for example:
One, to the discriminating of rear-end collision:
Suppose a car other car that knocked into the back, and be parked on the road.In step 7, at first analyze the gps data of vehicle in this highway section, thereby obtain the acceleration and the travel direction of vehicle.Under situation about knocking into the back, the speed of a motor vehicle descends very fast.In addition, rotation to a certain degree can take place in vehicle, thereby causes travel direction to change.In step 8, the examination result of map datum shows, need not have the often place of parking in this highway section, so step 9 is skipped.Because vehicle runs foul of each other, the distance that can detect in the step 10 between the coordinate at certain angle of vehicle can be in risk distance.At this moment, vehicle acceleration is unusual, the unusual vehicle of driving direction is demarcated is possible collision vehicle.Step 10 continues to detect a period of time for a moment, if this unusual transportation condition does not change, then is likely collision accident has taken place.
Two, the side accident of hitting is differentiated:
A car hits in the side of another car, causes improper parking.
At first detect the unusual acceleration of vehicle or the variation of direction;
Data according to the map confirm whether this highway section comprises or the frequent parking site of contiguous a certain needs then.If no, get into step 10.If have such as frequent parking sites such as crossings, then get into step 9;
Step 9: after latent period,, then get into step 10 if this road section traffic volume condition does not still change;
Step 10: because therefore vehicle collision exists the coordinate between certain angle of vehicle to overlap.At this moment, the vehicle of unusual deceleration, angle overlap coordinate and travel direction abnormal change will be demarcated and is accident vehicle;
Step 11: continue to observe certain hour,, then activate accident alarm if transportation condition does not change.
Three, vehicle casts anchor or bumps against with object:
Vehicle casts anchor in the road, and reason possibly be mechanical disorder or bump against with the roadside object.
Step 7: an independent vehicle does not have acceleration in certain highway section, other vehicle heading generation minor alteration in the highway 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 highway section, and certain change takes place travel direction in the certain hour, representes that this vehicle casts anchor in the road.
Claims (6)
1. road traffic accident automatic testing method based on real-time vehicle GPS data; It realizes that based on personal digital assistant (1), vehicle GPS receiver (2) and gateway server (3) it is characterized in that: this road traffic accident automatic testing method comprises the steps:
Vehicle GPS receiver (2) is used to realize receiving the coordinate information of its present position, and this coordinate information is sent to the step of personal digital assistant (1);
Personal digital assistant (1) is used to realize calculating the coordinate information that obtains four jiaos on vehicle, and four angular coordinate, the sea level elevation of vehicle, Vehicle Speed, vehicle heading, the vehicle GPS receiver (2) of this vehicle received the time of coordinate information and the step that vehicle ID sends to gateway server (3);
Gateway server (3) is used to realize storing the step of the information that all personal digital assistants (1) of receiving send, and also is used to realize the step according to the road traffic accident in highway section, said information acquisition corresponding vehicle place.
2. the road traffic accident automatic testing method based on real-time vehicle GPS data according to claim 1; It is characterized in that: gateway server (3) is used to realize storing the step of the information that all personal digital assistants (1) of receiving send, and also is used to realize according to the detailed process of the step of the road traffic accident in highway section, said information acquisition corresponding vehicle place be:
Step 1: is isometric highway section with road to be detected according to the grade classification of road, and the shared zone passage coordinate in each highway section is represented; Direction according to wagon flow is updrift side and downstream direction with said road, confirms corresponding vehicle present located highway section according to the coordinate information of four jiaos on each vehicle that receives;
Step 2:, calculate to obtain the average overall travel speed of current vehicle on the given wagon flow direction in corresponding highway section to be detected according to all vehicle headings in each highway section to be detected that receives and Vehicle Speed information;
Step 3: the average speed in this highway section under the average overall travel speed of the current vehicle that obtains in the step 2 and the similar environmental baseline is compared; The average speed that is lower than this highway section under the similar environmental baseline when the average overall travel speed of current vehicle surpasses the demarcation threshold value that presets, then with this highway section as demarcating the highway section;
Step 4: the average speed that the average overall travel speed that will demarcate the current vehicle in highway section is adjacent the highway section compares, and the minimum highway section of selection speed is as the priority processing highway section;
Step 5: relatively with the average speed in the average overall travel speed of the vehicle in priority processing highway section and former and later two adjacent highway sections; If the speed of a motor vehicle in adjacent highway section, travel direction the place ahead is higher than the speed of a motor vehicle in the adjacent highway section in priority processing highway section and travel direction rear and surpasses the obstruction threshold value that presets, then with the priority processing highway section as doubtful congested link;
Step 6: doubtful congested link is divided into 10 sub-highway sections, the occluder highway section according to step 2 last mode of judging the doubtful congested link of acquisition in step 5, is confirmed in 10 sub-highway sections;
Step 7: all have the unusual vehicle of one of following characteristic in the identification occluder highway section:
The July 1st, the speed of a motor vehicle are lower than the average speed in this occluder highway section;
Seven or two, be in halted state;
Seven or three, headstock is towards in the opposite direction with current wagon flow;
Seven or four, the position from the reference position in occluder highway section near;
Step 8: judge by map datum, this occluder highway section whether comprise place that needs stop or from the distance location of needs parking less than the stop threshold value that presets, if enter into step 9; Otherwise, enter into step 10;
Step 9: the type in the place of stopping as required, confirm the blocking time that this place that need stop can be caused, if after surpassing blocking time, the unusual vehicle behavior that identification obtains in the step 7 still exists, and gets into step 10;
Step 10: judge whether one of following situation takes place in the occluder highway section:
11, in the occluder highway section, the average speed that the average velocity of all vehicles all is lower than this sub-highway section under the normal condition surpasses the low speed threshold value that presets;
12, in the occluder highway section, the speed that the average velocity of vehicle descends surpasses the falling-threshold value that presets, thereby causes exception parking;
13, in the occluder highway section distance on the border of the coordinate at a certain vehicle angle and adjacent vehicle less than 2 meters;
Step 11: suspend five minutes, and then calculate the average speed in this occluder highway section, if do not change, then with on the map datum in the gateway server (3), indicating this occluder highway section is the traffic events highway section, and triggers alarm.
3. the road traffic accident automatic testing method based on real-time vehicle GPS data according to claim 1 and 2; It is characterized in that: personal digital assistant (1) uses the coordinate information of NMEA agreement vehicle GPS receiver (2) transmission that conversion once receives in per 3 seconds, and uses NMEA protocol processes data.
4. the road traffic accident automatic testing method based on real-time vehicle GPS data according to claim 1 and 2; It is characterized in that: personal digital assistant (1) sends The data XML form for gateway server (3) and encodes, and sends through the GPRS mode.
5. the road traffic accident automatic testing method based on real-time vehicle GPS data according to claim 1 and 2 is characterized in that: the method that personal digital assistant (1) calculates the coordinate information that obtains four jiaos on vehicle is:
Coordinate information according to vehicle GPS receiver (2) present position; And vehicle GPS receiver (2) apart from the horizontal range X1 of the tailstock, vehicle GPS receiver (2) apart from the horizontal range X2 of headstock, vehicle GPS receiver (2) horizontal range Y1 and Y2 with the lateral direction of car both sides; Confirm the coordinate of four jiaos of A, B, C and D of current vehicle, i.e. the 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.
6. the road traffic accident automatic testing method based on real-time vehicle GPS data according to claim 2 is characterized in that: be isometric highway section with road to be detected according to the grade classification of road in the said step 1, said isometric highway section is 500 meters.
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| CN103139287A (en) * | 2012-12-11 | 2013-06-05 | 厦门雅迅网络股份有限公司 | Map aggregation vehicle refreshing method based on distributed calculating |
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| CN109214835A (en) * | 2018-09-26 | 2019-01-15 | 蜜小蜂智慧（北京）科技有限公司 | A kind of method and apparatus identifying vehicle driving behavior |
| CN109285349A (en) * | 2018-11-02 | 2019-01-29 | 中电海康集团有限公司 | Freeway traffic event detection method and early warning system under bus or train route cooperative surroundings |
| CN110766937A (en) * | 2019-05-22 | 2020-02-07 | 北京嘀嘀无限科技发展有限公司 | Parking spot identification method and device, electronic equipment and readable storage medium |
| CN111047861A (en) * | 2019-12-04 | 2020-04-21 | 支付宝(杭州)信息技术有限公司 | Traffic accident processing method and device and electronic equipment |
| CN114323143A (en) * | 2021-12-30 | 2022-04-12 | 上海商汤临港智能科技有限公司 | Vehicle data detection method and device, computer equipment and storage medium |
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| CN103139287A (en) * | 2012-12-11 | 2013-06-05 | 厦门雅迅网络股份有限公司 | Map aggregation vehicle refreshing method based on distributed calculating |
| CN103139287B (en) * | 2012-12-11 | 2018-05-11 | 厦门雅迅网络股份有限公司 | A kind of map aggregation vehicle method for refreshing based on Distributed Calculation |
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| CN106341789A (en) * | 2015-07-07 | 2017-01-18 | 丰田自动车株式会社 | A mobile computer atmospheric barometric pressure system |
| CN106355876A (en) * | 2015-07-15 | 2017-01-25 | 福特全球技术公司 | Crowdsourced Event Reporting and Reconstruction |
| CN106846806A (en) * | 2017-03-07 | 2017-06-13 | 北京工业大学 | Urban highway traffic method for detecting abnormality based on Isolation Forest |
| CN107128251A (en) * | 2017-05-11 | 2017-09-05 | 张家港工领信息科技有限公司 | A kind of collision prevention of vehicle control method |
| WO2018218408A1 (en) * | 2017-05-27 | 2018-12-06 | 深圳市乃斯网络科技有限公司 | Application method and system for obstacle detection in intelligent traffic |
| CN108332979A (en) * | 2018-02-08 | 2018-07-27 | 青岛慧拓智能机器有限公司 | A kind of vehicle crimping detection method |
| CN109214835A (en) * | 2018-09-26 | 2019-01-15 | 蜜小蜂智慧（北京）科技有限公司 | A kind of method and apparatus identifying vehicle driving behavior |
| CN109285349A (en) * | 2018-11-02 | 2019-01-29 | 中电海康集团有限公司 | Freeway traffic event detection method and early warning system under bus or train route cooperative surroundings |
| CN109285349B (en) * | 2018-11-02 | 2020-09-22 | 浙江海康智联科技有限公司 | Method for detecting highway traffic incident under cooperative vehicle and road environment and early warning system |
| CN110766937A (en) * | 2019-05-22 | 2020-02-07 | 北京嘀嘀无限科技发展有限公司 | Parking spot identification method and device, electronic equipment and readable storage medium |
| CN111047861A (en) * | 2019-12-04 | 2020-04-21 | 支付宝(杭州)信息技术有限公司 | Traffic accident processing method and device and electronic equipment |
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