CN103578272A - Method and device for recognizing abnormal road conditions - Google Patents
Method and device for recognizing abnormal road conditions Download PDFInfo
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- CN103578272A CN103578272A CN201310389172.8A CN201310389172A CN103578272A CN 103578272 A CN103578272 A CN 103578272A CN 201310389172 A CN201310389172 A CN 201310389172A CN 103578272 A CN103578272 A CN 103578272A
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Abstract
The invention discloses a method and device for recognizing abnormal road conditions. The method for recognizing abnormal road conditions includes the steps that in a time interval, GPS number information of vehicles in a current road detection area is acquired; according to the GPS number information of the vehicles in the road detection area, statistics is performed on the probability P1 that the GPS number of the road detection area in the time interval is smaller than or equal to x, wherein the x is a parameter; when the probability P1 is smaller than or equal to a preset abnormal threshold value, in the time interval, GPS number information of vehicles in areas adjacent to and communicated with the current road detection area is acquired; according to the GPS number information of the vehicles in the areas adjacent to and communicated with the current road detection area, statistics is performed on the probability P2 that the GPS number of the areas adjacent to and communicated with the current road detection area in the time interval is smaller than or equal to y, wherein the y is a parameter; when the probability P2 is larger than or equal to a preset normal threshold value, it is prompted that abnormal road conditions happen to the road detection area. According to the method and device, the abnormal road conditions such as temporary traffic control, the condition that a road is in flood or buried and accidents can be recognized, the abnormal road conditions except traffic jams can be recognized, and the abnormal road conditions can be recognized more accurately and comprehensively.
Description
Technical field
The present invention relates to transport information technical field, be specifically related to road conditions identification field, relate in particular to a kind of abnormal road conditions recognition methods and device.
Background technology
Fast development along with social progress, economy, people's living standard improves day by day, industrialization, Development of China's Urbanization accelerate to have promoted the arrival of auto age, and economy is becoming increasingly acute to the contradiction of the contradiction of the demand contradictory of traffic, private car and public transport, traffic and environment.Particularly the level of urbanization improves rapidly, when urban road service facility improves greatly, vehicle increases severely, congested in traffic aggravation, traffic hazard takes place frequently, and life of urban resident quality and satisfaction declines, and the sustainable development in city is restricted, traffic problems more and more become a social hot issue, in the urgent need to the approach of systematically studying and proposing to solve.Meanwhile, due to road traffic abnormal conditions, for example obstruction, accident and have barrier on the road that causes, thus the road traffic accident causing also becomes a significant problem that affects traffic safety.
On some important traffic routes, if exist barrier, must prior notice will pass through the driver here.Driver drives a conveyance when closing on barrier else if, just finds that barrier can cause serious traffic hazard.
Yet, existing GPS navigation system can receive the data parameters that satellite sends for 24 hours incessantly, and then acquisition receives position, direction, speed and the temporal information on ground, and then the road speed of estimation moving vehicle, according to road speed, judge whether to occur blocking up, but cannot find that interim traffic control, road are flooded the abnormal road conditions outside being blocked up by bury, accident etc.
Summary of the invention
The object of the invention is to propose a kind of abnormal road conditions recognition methods and device, the problem of the abnormal road conditions outside blocking up such as solve that the interim traffic control of None-identified, road are buried, accident.
First aspect, the invention provides a kind of abnormal road conditions recognition methods, and described method comprises:
The vehicle GPS quantity information of current detection road area in acquisition time interval;
According to the vehicle GPS quantity information that detects road area, the probability P 1 (GPS quantity <=x| time interval) of adding up described detection road area GPS quantity <=x in this time interval, x is parameter;
When probability P 1 is less than or equal to default abnormal threshold value, current detection road area adjacent be communicated with the vehicle GPS quantity information of road area in acquisition time interval; According to adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 2 (GPS quantity <=y| time interval) of road area GPS quantity <=y in this time interval, y is parameter;
When probability P 2 is more than or equal to default normality threshold, point out described detection road area to occur abnormal road conditions.
Second aspect, the present invention also provides a kind of abnormal road conditions recognition device, and described device comprises:
Detect road area vehicle GPS quantity information acquisition module, for the vehicle GPS quantity information of detection road area current in acquisition time interval;
Detect road area vehicle GPS quantity information statistical module, be used for according to the vehicle GPS quantity information that detects road area, the probability P 1 (GPS quantity <=x| time interval) of adding up described detection road area GPS quantity <=x in this time interval, x is parameter;
Adjacent and be communicated with road area vehicle GPS quantity information module, when being less than or equal to default abnormal threshold value when probability P 1, current detection road area adjacent be communicated with the vehicle GPS quantity information of road area in acquisition time interval; According to adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 2 (GPS quantity <=y| time interval) of road area GPS quantity <=y in this time interval, y is parameter;
Abnormal road conditions identification module, while presetting normality threshold for being more than or equal to when probability P 2, points out described detection road area to occur abnormal road conditions.
The present invention by according to the vehicle GPS quantity information of the vehicle GPS quantity information of current detection road area, historical current detection road area and current adjacent and be communicated with the vehicle GPS quantity information of road area, historical current vehicle GPS quantity information adjacent and that be communicated with road area judges detecting the road conditions of road area, identify interim traffic control, road is flooded the abnormal road conditions outside being blocked up by bury, accident etc., can identify more exactly, all sidedly abnormal road conditions.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of the abnormal road conditions recognition methods in first embodiment of the invention.
Fig. 2 a is the interval quantity histogram of the vehicle location number statistics in the embodiment of the present invention.
Fig. 2 b is the probability distribution graph of the vehicle location number in the embodiment of the present invention.
Fig. 3 is the process flow diagram of the abnormal road conditions recognition methods in second embodiment of the invention.
Fig. 4 a-Fig. 4 f is the design sketch of pointing out abnormal road conditions in second embodiment of the invention.
Fig. 5 is the structural drawing of the abnormal road conditions recognition device in third embodiment of the invention.
Embodiment
Below in conjunction with drawings and Examples, the present invention is described in further detail.Be understandable that, specific embodiment described herein is only for explaining the present invention, but not limitation of the invention.It also should be noted that, for convenience of description, in accompanying drawing, only show part related to the present invention but not entire infrastructure.
Figure 1 illustrates the first embodiment of the present invention.
Fig. 1 is the realization flow 100 of the abnormal road conditions recognition methods in first embodiment of the invention, and details are as follows for this realization flow 100:
The vehicle GPS quantity information of current detection road area in step 101, acquisition time interval.
Particularly, obtain the gps data information that in detection road area current in certain hour interval, vehicle is uploaded, and count vehicle GPS quantity information.Described vehicle GPS quantity information gathers by being applied to the client of navigation feature, described client comprises GPS (Global Position System) Position Fixing Navigation System, such as the positioning service client of automatic navigator, mobile phone, Baidu's map of mobile phone-downloaded etc.Described vehicle comprises by the taxi of GPS Position Fixing Navigation System, private car, bus etc.Described gps data comprises longitude and latitude, speed, time and direction.
In the present embodiment, moving vehicle in the process of moving, when Baidu's map client of use automatic navigator or mobile phone-downloaded is carried out enquiry navigation, returns gps data to server end in real time, server end is added up the gps data of all passbacks, and counts vehicle GPS quantity information.Described time interval is for to be divided into one of them time interval in 12 time intervals by 24 hourly averages in a day.
In a preferred implementation of the present embodiment, our interval access time is 8 point-9 points, and detecting road area is that Zizhu Flyover is to the road between the bridge of garden.For example, we use between 8 o'clock to the 9 o'clock morning that the client of navigation feature obtains returning by moving vehicle, and Zizhu Flyover is deposited into server end to the gps data between two bridges of garden bridge.Server end counts vehicle GPS quantity information according to all gps datas.
Step 102, according to the vehicle GPS quantity information that detects road area, the probability P 1 (GPS quantity <=x| time interval) of adding up described detection road area GPS quantity <=x in this time interval, x is parameter.
Particularly, the probability distribution of the vehicle GPS quantity information of the historical detection road area in the vehicle GPS quantity information of the detection road area counting according to above-mentioned steps and time interval, the probability P 1 (GPS quantity <=x| time interval) of adding up described detection road area GPS quantity <=x in this time interval, x is parameter.
In the present embodiment, the vehicle GPS quantity information of the historical detection road area in described time interval is the vehicle GPS quantity information of the detection road area of the last week in time interval.
In a preferred implementation of the present embodiment, we add up its probability distribution according to the vehicle GPS quantity information of historical detection road area, specifically comprise: the vehicle GPS quantity information to described detection road area carries out interval statistics, obtain interval frequency and interval quantity histogram; Described interval quantity histogram is smoothly formed to the probability distribution that densimetric curve obtains the vehicle GPS quantity information of described detection road area, described interval quantity histogram is carried out to level and smooth method and can adopt interpolation method, described interval can be 5 or 10, such as to 0-10,10-20, the intervals such as 20-30 are added up.
Histogram density Estimation is that to apply be also the density estimation method being most widely used the earliest, it is the classical way by one group of sample architecture probability density: under one-dimensional case, real axis is divided into some equal-sized cells, the image of estimating on each cell is a stepped appearance, if make vertical line from each end points to base to form rectangle, obtain some and come by upright rectangle the histogram forming together.
Particularly, to detecting the vehicle GPS quantity information of road area, divide a lot of interval statistics quantity, what for example quantity was 0-10 has 100,10-20 has 300, by that analogy, can calculate the frequency that certain detects the vehicle GPS quantity information interval of road area, in the situation that statistical magnitude is larger, level off to distribution probability, interval quantity histogram as shown in Figure 2 a, is then undertaken smoothly by the method for estimation in some statistics, form a rod density curve, obtain its probability distribution graph, as shown in Figure 2 b, interval probability can be by the acquisition of quadraturing.According to can the check probable value p (GPS number | 8 point-9 points) of the vehicle GPS quantity information of surveying road area of Fig. 2 b.In this preferred implementation, described interval quantity histogram is carried out to level and smooth method and adopt interpolation method.
Again according to the vehicle GPS quantity information of current detection road area, statistics GPS quantity is less than or equal to the probability P 1 of x, and wherein x is the vehicle GPS quantity information of current detection road area.We use between 8 o'clock to the 9 o'clock morning that the client of navigation feature obtains returning by moving vehicle, the vehicle GPS quantity information of current detection road area is 10, according to the probability distribution (as shown in Figure 2 b) of the vehicle GPS quantity information of historical detection road area, calculate between 8 o'clock to 9 o'clock morning, the p (x<=10|8 point-9 point) that detects road area is p (GPS counts <=10|8 point-9 point), wherein p is probable value, and x is the vehicle GPS quantity information of current detection road area.Under concrete scene, with current data identification, be to exist to lag behind, the P1 just now obtaining can determine the road conditions of 9 in morning.And if we obtain the P1 of 8 in morning, this GPS number is the GPS number of returning between point-8 mornings 7, and historical data is the probability distribution of the vehicle GPS quantity information of the detection road area between time interval corresponding thereto.Obtaining of the vehicle GPS quantity information of current detection road area generally has two kinds of modes: static state is obtained and Dynamic Acquisition.Backstage obtains the current time GPS number in Preset Time forward, and static state is obtained; And this GPS number upgrades or dynamic calculation according to predetermined period, the window data by current time and forward hour calculates, and is exactly Dynamic Acquisition.
Step 103, when probability P 1 is less than or equal to default abnormal threshold value, current detection road area adjacent be communicated with the vehicle GPS quantity information of road area in acquisition time interval; According to described adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 2 (GPS quantity <=y| time interval) of road area GPS quantity <=y in this time interval, y is parameter.
Particularly, judge whether the probability P 1 drawing in above-mentioned steps is less than or equal to default abnormal threshold value, when probability P 1 is less than or equal to default abnormal threshold value, current detection road area adjacent be communicated with the vehicle GPS quantity information of road area in acquisition time interval, and according to described adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 2 (GPS quantity <=y| time interval) of road area GPS quantity <=y in this time interval, y is parameter.
In the present embodiment, the probability P 4*25% of described default abnormal threshold value for calculating by the following method: the vehicle GPS quantity information of historical detection road area in acquisition time interval; According to the vehicle GPS quantity information that detects road area, the probability P 4 (GPS quantity <=n| time interval) of adding up described detection road area GPS quantity <=n in this time interval, n is preset parameter.Add up described adjacent and to be communicated with the method for probability P 2 (GPS quantity <=y| time interval) of road area GPS quantity <=y in this time interval the same with the method for probability P 1 (GPS quantity <=x| time interval) of adding up described detection road area GPS quantity <=x in this time interval in above-mentioned steps 102, do not repeat them here.
Step 104, when P2 is more than or equal to default normality threshold, point out described detection road area to occur abnormal road conditions.
Particularly, P2 and default normality threshold are compared, when P2 is more than or equal to default normality threshold, point out described predeterminable area to occur abnormal road conditions.Described default normality threshold is the probability P 3 that calculates by the following method: the detection road area of history adjacent be communicated with the vehicle GPS quantity information of road area acquisition time interval in; According to adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 3 (GPS quantity <=m| time interval) of road area GPS quantity <=m in this time interval, m is preset parameter.Statistical method is the same with the method for the probability P 1 (GPS quantity <=x| time interval) of the above-mentioned steps 102 described detection road area of statistics GPS quantity <=x in this time interval, does not repeat them here.
First embodiment of the invention by according to the vehicle GPS quantity information of the vehicle GPS quantity information of current detection road area, historical current detection road area and current adjacent and be communicated with the vehicle GPS quantity information of road area, historical current vehicle GPS quantity information adjacent and that be communicated with road area judges detecting the road conditions of road area, identify interim traffic control, road is flooded the abnormal road conditions outside being blocked up by bury, accident etc., can identify more exactly, all sidedly abnormal road conditions.
Figure 3 illustrates the second embodiment of the present invention.
Fig. 3 is the realization flow 300 of the abnormal road conditions recognition methods in second embodiment of the invention, and details are as follows for this realization flow 300:
The vehicle GPS quantity information of current detection road area in step 301, acquisition time interval.
Particularly, obtain the gps data information that in detection road area current in certain hour interval, vehicle is uploaded, and count vehicle GPS quantity information.Described vehicle GPS quantity information gathers by being applied to the client of navigation feature, described client comprises GPS (Global Position System) Position Fixing Navigation System, such as the positioning service client of automatic navigator, mobile phone, Baidu's map of mobile phone-downloaded etc.Described vehicle comprises by the taxi of GPS Position Fixing Navigation System, private car, bus etc.Described gps data comprises longitude and latitude, time and direction.
In the present embodiment, moving vehicle in the process of moving, when Baidu's map client of use automatic navigator or mobile phone-downloaded is carried out enquiry navigation, returns gps data to server end in real time, server end is added up the gps data of all passbacks, and counts vehicle GPS quantity information.Described time interval is for to be divided into one of them time interval in 12 time intervals by 24 hourly averages in a day.Gps data information comprises longitude and latitude, time and direction, and present road can two way, and abnormal road conditions appear in the road in that direction of judgement that can be definite according to directional information.
In a preferred implementation of the present embodiment, our interval access time is 8 point-9 points, and detecting road area is that Zizhu Flyover is to the road between the bridge of garden.For example, we use between 8 o'clock to the 9 o'clock morning that the client of navigation feature obtains returning by moving vehicle, and Zizhu Flyover is deposited into server end to the gps data between two bridges of garden bridge.Server end counts vehicle GPS quantity information according to all gps datas.
In the present embodiment, step 302 is the same with the step 102 in the first embodiment, does not repeat them here.
In the present embodiment, the probability P 4*25% of described default abnormal threshold value for calculating by the following method: the vehicle GPS quantity information of historical detection road area in acquisition time interval; According to the vehicle GPS quantity information that detects road area, the probability P 4 (GPS quantity <=n| time interval) of adding up described detection road area GPS quantity <=n in this time interval, n is preset parameter.
In the present embodiment, add up described adjacent and to be communicated with the method for probability P 2 (GPS quantity <=y| time interval) of road area GPS quantity <=y in this time interval the same with the method for probability P 1 (GPS quantity <=x| time interval) of adding up described detection road area GPS quantity <=x in this time interval in step 102 in the first embodiment, do not repeat them here.
In the present embodiment, probability P 2 and default normality threshold are compared, when probability P 2 is more than or equal to default normality threshold, point out described predeterminable area to occur abnormal road conditions.Described default normality threshold is the probability P 3 that calculates by the following method: the detection road area of history adjacent be communicated with the vehicle GPS quantity information of road area acquisition time interval in; According to adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 3 (GPS quantity <=m| time interval) of road area GPS quantity <=m in this time interval, m is preset parameter.Statistical method is the same with the method for the probability P 1 (GPS quantity <=x| time interval) of the described detection road area of step 102 statistics GPS quantity <=x in this time interval in the first embodiment, does not repeat them here.For example, we counted between 8 o'clock to 9 o'clock morning, Zizhu Flyover is 10 to the vehicle GPS quantity information of the current detection road area between Qiao Liangge crossing, garden, suppose between 8 o'clock to 9 o'clock morning, Zizhu Flyover is 80% to the default normality threshold between Qiao Liangge crossing, garden, when p (x<=10) >=80%, point out Zizhu Flyover to occur abnormal road conditions to the section between the bridge of garden.Point out the mode of abnormal road conditions to comprise voice message, map label prompting.And the mode of map label prompting can comprise colour code, pattern identification, words identification.
In a preferred implementation of the present embodiment, when Zizhu Flyover occurs abnormal road conditions to bridge section, garden, we adopt the mode of map label prompting to point out appearance abnormal road conditions.Fig. 4 a is can be at this section mark colour code on map, Fig. 4 b is at this section mark pattern identification on map, Fig. 4 c is at this section mark words identification on map, Fig. 4 d is at this section mark colour code and pattern identification on map, Fig. 4 e is at this section mark colour code and words identification on map, Fig. 4 f marks colour code, pattern identification and words identification in this section on map, and to point out this section to occur abnormal road conditions, alerting drivers detours.
Second embodiment of the invention by according to the vehicle GPS quantity information of the vehicle GPS quantity information of current detection road area, historical current detection road area and current adjacent and be communicated with the vehicle GPS quantity information of road area, historical current vehicle GPS quantity information adjacent and that be communicated with road area judges detecting the road conditions of road area, identify interim traffic control, road is flooded the abnormal road conditions outside being blocked up by bury, accident etc., can identify more exactly, all sidedly abnormal road conditions.Compare with the first embodiment, the present embodiment has used the mode of map label prompting to point out abnormal road conditions, makes user can obtain more intuitively traffic information.
Figure 5 illustrates the third embodiment of the present invention.
Fig. 5 is the structural drawing of the abnormal road conditions recognition device in third embodiment of the invention.As shown in Figure 5, this device comprise detect road area vehicle GPS quantity information acquisition module 501, detect road area vehicle GPS quantity information statistical module 502, adjacent and be communicated with road area vehicle GPS quantity information module 503 and abnormal road conditions identification module 504.
Wherein, detect the road area vehicle GPS quantity information acquisition module 501 vehicle GPS quantity informations for detection road area current in acquisition time interval.
In the present embodiment, described vehicle GPS quantity information gathers by being applied to the client of navigation feature, described client comprises GPS (Global Position System) Position Fixing Navigation System, such as the positioning service client of automatic navigator, mobile phone, Baidu's map of mobile phone-downloaded etc.Described vehicle comprises by the taxi of GPS Position Fixing Navigation System, private car, bus etc.Moving vehicle in the process of moving, when Baidu's map client of use automatic navigator or mobile phone-downloaded is carried out enquiry navigation, returns gps data to server end in real time, and server end is added up the gps data of all passbacks, and counts vehicle GPS quantity information.Described gps data comprises longitude and latitude, speed, time and direction.Described time interval is for to be divided into one of them time interval in 12 time intervals by 24 hourly averages in a day.
Detect road area vehicle GPS quantity information statistical module 502 for according to the vehicle GPS quantity information that detects road area, the probability P 1 (GPS quantity <=x| time interval) of adding up described detection road area GPS quantity <=x in this time interval, x is parameter.
In the present embodiment, the vehicle GPS quantity information of the historical detection road area in described time interval is the vehicle GPS quantity information of the detection road area of the last week in time interval.
Adjacent and be communicated with road area vehicle GPS quantity information module 503 when being less than or equal to default abnormal threshold value when probability P 1, current detection road area adjacent be communicated with the vehicle GPS quantity information of road area in acquisition time interval; According to adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 2 (GPS quantity <=y| time interval) of road area GPS quantity <=y in this time interval, y is parameter.
Adjacent and be communicated with road area GPS quantity information module 503 and comprise default abnormal threshold value acquiring unit 5031, comparing unit 5032, adjacent and be communicated with road area GPS quantity information acquiring unit 5033 and adjacent and be communicated with road area GPS quantity information statistic unit 5034, wherein, default abnormal threshold value acquiring unit 5031, vehicle GPS quantity information for detection road area historical in acquisition time interval, according to the vehicle GPS quantity information that detects road area, add up the probability P 4 (GPS quantity <=n| time interval) of described detection road area GPS quantity <=n in this time interval, n is preset parameter, obtain probability P 4*25%, comparing unit 5032, for comparing P1 with default abnormal threshold value, adjacent and be communicated with road area GPS quantity information acquiring unit 5033, when being less than or equal to default abnormal threshold value when probability P 1, current detection road area adjacent be communicated with the vehicle GPS quantity information of road area in acquisition time interval, adjacent and be communicated with road area GPS quantity information statistic unit 5034, for according to adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 2 (GPS quantity <=y| time interval) of road area GPS quantity <=y in this time interval, y is parameter.
In the present embodiment, the vehicle GPS quantity information of historical detection road area in described time interval, is the vehicle GPS quantity information of the detection road area of the last week in time interval.
Abnormal road conditions identification module 504, while presetting normality threshold for being more than or equal to when probability P 2, points out described detection road area to occur abnormal road conditions.
Abnormal road conditions identification module comprises default normality threshold acquiring unit 5041, judging unit 5042 and abnormal road condition advisory unit 5043, wherein, default normality threshold acquiring unit 5041, for the adjacent of the detection road area of history in acquisition time interval and be communicated with the vehicle GPS quantity information of road area and according to adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 3 (GPS quantity <=m| time interval) of road area GPS quantity <=m in this time interval, m is preset parameter, judging unit 5042, for comparing P2 and default normality threshold P3, abnormal road condition advisory unit 5043, while presetting normality threshold for being more than or equal to as P2, points out described detection road area to occur abnormal road conditions.
In the present embodiment, judging unit 5042 compares P2 and default normality threshold P3; Abnormal road condition advisory unit 5043, when probability P 2 is more than or equal to default normality threshold, points out described detection road area to occur abnormal road conditions.The detection road area of history adjacent be communicated with the vehicle GPS quantity information of road area and according to adjacent and be communicated with the vehicle GPS quantity information of road area in default normality threshold acquiring unit 5041 acquisition time intervals, add up described adjacent and be communicated with the probability P 3 (GPS quantity <=m| time interval) of road area GPS quantity <=m in this time interval, m is preset parameter.For example, we counted between 8 o'clock to 9 o'clock morning, Zizhu Flyover is 10 to the vehicle GPS quantity information of the current detection road area between Qiao Liangge crossing, garden, suppose between 8 o'clock to 9 o'clock morning, Zizhu Flyover is 80% to the default normality threshold between Qiao Liangge crossing, garden, when p (x<=10) >=80%, point out Zizhu Flyover to occur abnormal road conditions to the section between the bridge of garden.Point out the mode of abnormal road conditions to comprise voice message, map label prompting.And the mode of map label prompting can comprise colour code, pattern identification, words identification.
Third embodiment of the invention is obtained vehicle GPS quantity information by detecting road area vehicle GPS quantity information acquisition module, detect the probability P 1 of road area vehicle GPS quantity information statistical module counts vehicle GPS <=x, then probability P 1 and default abnormal threshold value are compared, when probability P 1 is less than or equal to default abnormal threshold value, adjacent and be communicated with road area vehicle GPS quantity information module and obtain adjacent and be communicated with road area vehicle GPS quantity information and count adjacent and be communicated with the probability P 2 of road area, compare with default normality threshold, identify interim traffic control, road is flooded to be buried, the abnormal road conditions outside blocking up such as accident, can be more accurate, identify all sidedly abnormal road conditions.
Note, above are only preferred embodiment of the present invention and institute's application technology principle.Skilled person in the art will appreciate that and the invention is not restricted to specific embodiment described here, can carry out for a person skilled in the art various obvious variations, readjust and substitute and can not depart from protection scope of the present invention.Therefore, although the present invention is described in further detail by above embodiment, the present invention is not limited only to above embodiment, in the situation that not departing from the present invention's design, can also comprise more other equivalent embodiment, and scope of the present invention is determined by appended claim scope.
Claims (6)
1. an abnormal road conditions recognition methods, is characterized in that, described method comprises:
The vehicle GPS quantity information of current detection road area in acquisition time interval;
According to the vehicle GPS quantity information that detects road area, the probability P 1 (GPS quantity <=x| time interval) of adding up described detection road area GPS quantity <=x in this time interval, x is parameter;
When probability P 1 is less than or equal to default abnormal threshold value, current detection road area adjacent be communicated with the vehicle GPS quantity information of road area in acquisition time interval; According to adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 2 (GPS quantity <=y| time interval) of road area GPS quantity <=y in this time interval, y is parameter;
When probability P 2 is more than or equal to default normality threshold, point out described detection road area to occur abnormal road conditions.
2. abnormal road conditions recognition methods according to claim 1, it is characterized in that, described default normality threshold is the probability P 3 that calculates by the following method: the detection road area of history adjacent be communicated with the vehicle GPS quantity information of road area acquisition time interval in; According to adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 3 (GPS quantity <=m| time interval) of road area GPS quantity <=m in this time interval, m is preset parameter.
3. abnormal road conditions recognition methods according to claim 1 and 2, is characterized in that, the probability P 4*25% of described default abnormal threshold value for calculating by the following method: the vehicle GPS quantity information of historical detection road area in acquisition time interval; According to the vehicle GPS quantity information that detects road area, the probability P 4 (GPS quantity <=n| time interval) of adding up described detection road area GPS quantity <=n in this time interval, n is preset parameter.
4. an abnormal road conditions recognition device, is characterized in that, this device comprises:
Detect road area vehicle GPS quantity information acquisition module, for the vehicle GPS quantity information of detection road area current in acquisition time interval;
Detect road area vehicle GPS quantity information statistical module, be used for according to the vehicle GPS quantity information that detects road area, the probability P 1 (GPS quantity <=x| time interval) of adding up described detection road area GPS quantity <=x in this time interval, x is parameter;
Adjacent and be communicated with road area vehicle GPS quantity information module, when being less than or equal to default abnormal threshold value when probability P 1, current detection road area adjacent be communicated with the vehicle GPS quantity information of road area in acquisition time interval; According to adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 2 (GPS quantity <=y| time interval) of road area GPS quantity <=y in this time interval, y is parameter;
Abnormal road conditions identification module, while presetting normality threshold for being more than or equal to when probability P 2, points out described detection road area to occur abnormal road conditions.
5. abnormal road conditions recognition device according to claim 9, it is characterized in that, described abnormal road conditions identification module comprises default normality threshold acquiring unit, judging unit and abnormal road condition advisory unit, wherein, default normality threshold acquiring unit, for the adjacent of the detection road area of history in acquisition time interval and be communicated with the vehicle GPS quantity information of road area and according to adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 3 (GPS quantity <=m| time interval) of road area GPS quantity <=m in this time interval, m is preset parameter, judging unit, for comparing P2 and default normality threshold P3, abnormal road condition advisory unit, while presetting normality threshold for being more than or equal to when probability P 2, points out described detection road area to occur abnormal road conditions.
6. according to the abnormal road conditions recognition device described in claim 4 or 5, it is characterized in that, described adjacent and be communicated with road area GPS quantity information module and comprise default abnormal threshold value acquiring unit, comparing unit, adjacent and be communicated with road area GPS quantity information acquiring unit and adjacent and be communicated with road area GPS quantity information statistic unit, wherein, default abnormal threshold value acquiring unit, vehicle GPS quantity information for detection road area historical in acquisition time interval, according to the vehicle GPS quantity information that detects road area, add up the probability P 4 (GPS quantity <=n| time interval) of described detection road area GPS quantity <=n in this time interval, n is preset parameter, obtain probability P 4*25%, comparing unit, for comparing P1 with default abnormal threshold value, adjacent and be communicated with road area GPS quantity information acquiring unit, when being less than or equal to default abnormal threshold value when probability P 1, current detection road area adjacent be communicated with the vehicle GPS quantity information of road area in acquisition time interval, adjacent and be communicated with road area GPS quantity information statistic unit, for according to adjacent and be communicated with the vehicle GPS quantity information of road area, add up described adjacent and be communicated with the probability P 2 (GPS quantity <=y| time interval) of road area GPS quantity <=y in this time interval, y is parameter.
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| CN201310389172.8A CN103578272B (en) | 2013-08-30 | 2013-08-30 | Method and device for recognizing abnormal road conditions |
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| CN201310389172.8A CN103578272B (en) | 2013-08-30 | 2013-08-30 | Method and device for recognizing abnormal road conditions |
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| CN109961631B (en) * | 2017-12-22 | 2023-12-26 | 深圳市城市交通规划设计研究中心有限公司 | Road water accumulation point identification method and road water accumulation point identification system |
| CN108320502A (en) * | 2017-12-27 | 2018-07-24 | 福建工程学院 | A kind of urban waterlogging detection method and terminal based on floating car technology |
| CN108320502B (en) * | 2017-12-27 | 2021-10-26 | 福建工程学院 | Urban waterlogging detection method and terminal based on floating car technology |
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