CN103903439B - The place recognition methods of passenger stock illegal parking and system - Google Patents
The place recognition methods of passenger stock illegal parking and system Download PDFInfo
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- CN103903439B CN103903439B CN201410095232.XA CN201410095232A CN103903439B CN 103903439 B CN103903439 B CN 103903439B CN 201410095232 A CN201410095232 A CN 201410095232A CN 103903439 B CN103903439 B CN 103903439B
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Abstract
The present invention relates to a kind of passenger stock illegal parking place recognition methods, comprise the steps: the gps data obtaining arbitrary vehicle; According to the gps data obtained, identify the parking area repeatedly of this vehicle; Screening is carried out to the parking area repeatedly of this vehicle identified and obtains suspicious parking area; Suspicious intensity grade division is carried out to suspicious parking area.The invention still further relates to a kind of passenger stock illegal parking location identifying system.The present invention significantly can reduce erroneous judgement, improves the recognition accuracy in suspicious illegal parking place, reduces the human cost of supervision illegal parking.
Description
Technical field
The present invention relates to a kind of passenger stock illegal parking place recognition methods and system.
Background technology
Under national economy sustainable growth, the demand of resident to intercity trip grows with each passing day, and expressway construction is also rapidly developed, and corresponding coach passenger transport market obtains lasting flourish.But, coach run time, the phenomenon of ubiquity illegal parking.Illegal parking normally carries out attracting customers outside station, and this behavior exists huge potential safety hazard: on the one hand, and outer attracting customers of standing easily causes overload, and overload is the main cause causing traffic hazard; On the other hand, the luggage of the outside upper visitor that stands, not through the investigation of regular upper visitor's point, likely comprises the violated article carried, and then forms serious potential safety hazard.Therefore, the behavior of supervision illegal parking is the important process in long-distance passenger transportation industry.
For a long time, domestic relevant departments mainly rely on on-the-spot method of scouting investigate illegal parking and enforce the law.In recent years, each main cities, using the watch-dog that GPS must install as long-distance passenger transportation vehicle, progressively starts the coach supervisory system based on GPS.This type systematic has the function for monitoring unlawful practice such as vehicle location tracking, driving trace playback, overspeed alarming, geofence, the warning of parking time-out usually at present.Wherein, mainly geofence and time-out of stopping report to the police two with the closely-related function of discovery illegal parking behavior.Geofence function needs the planning travel route arranging coach, once find that it departs from planning travel route certain distance, reports to the police.The overtime warning function that stops needs to arrange threshold value down time, once find to exceed setting threshold value its down time, reports to the police.
Illegal parking is carried out on-the-spot scouting the protracted experience needing to rely on law enfrocement official, and at substantial manpower and time cost.For illegal parking behavior, all there is obvious deficiency in the geofence function in existing coach supervisory system and the overtime warning function that stops.One, geofence function, once find that vehicle in use departs from planning travel route certain distance, is reported to the police.But, coach in actual travel, when especially travelling in city, the traffic (such as, traffic jam, traffic control etc.) of change can cause driver and conductor to select non-programme path to travel, and then causes erroneous judgement, interference management works, and reduces system actual utility.Its two, in reality operation, the outer behavior of attracting customers in a large amount of station occurs in programme path on the way, and geofence function then cannot monitor the behavior of the type.Its three, outer phenomenon down time under many circumstances very of short duration (such as, tens seconds or one or two minute) that attracts customers of standing.If stopped, the time of fire alarming threshold value of overtime warning function arranges higher (such as, 30 minutes), and the parking that attracts customers outside so a large amount of stations can't cause time-out of stopping to report to the police.And the time of fire alarming threshold value of the overtime warning function that stops arranges lower (such as, 2 minutes), so a large amount of reasonable parkings (such as, waiting traffic lights) then can cause erroneous judgement.Therefore, there is a large amount of erroneous judgements and careless omission in existing illegal parking place recognition technology.
Summary of the invention
In view of this, be necessary to provide a kind of passenger stock illegal parking place recognition methods and system.
The invention provides a kind of passenger stock illegal parking place recognition methods, the method comprises the steps: that a. obtains the gps data of arbitrary, car; B. according to the gps data obtained, the parking area repeatedly of this vehicle is identified; C. screening is carried out to the parking area repeatedly of this vehicle identified and obtain suspicious parking area; D. suspicious intensity grade division is carried out to suspicious parking area.
Wherein, described step b comprises: carry out pre-service to described gps data; Parking is extracted according to pretreated gps data; Parking according to extracting finds parking area repeatedly.
According to the Parking extracted, described finds that repeatedly parking area adopts cuclear density analytic approach.
Described step c comprises: get rid of planning passenger point; Get rid of and wait traffic lights the parking area repeatedly caused; Get rid of the jogging region that blocks up; Get rid of other reasonable parking areas.
Described suspicious intensity grade comprise high suspicious, in suspicious, low suspicious.
The present invention also provides a kind of passenger stock illegal parking location identifying system, comprises the acquisition module, identification module, screening module and the division module that are mutually electrically connected, wherein: described acquisition module is for obtaining the gps data of arbitrary vehicle; Described identification module is used for, according to the gps data obtained, identifying the parking area repeatedly of this vehicle; Described screening module is used for carrying out screening to the parking area repeatedly of this vehicle identified and obtains suspicious parking area; Described division module is used for carrying out suspicious intensity grade division to suspicious parking area.
Wherein, described identification module, specifically for carrying out pre-service to described gps data, extracts Parking according to pretreated gps data, and finds parking area repeatedly according to the Parking extracted.
According to the Parking extracted, described finds that repeatedly parking area adopts cuclear density analytic approach.
Described screening module, specifically for getting rid of planning passenger point, is got rid of and is waited traffic lights the parking area repeatedly caused, and gets rid of the jogging region that blocks up, and gets rid of other reasonable parking areas.
Described suspicious intensity grade comprise high suspicious, in suspicious, low suspicious.
Passenger stock illegal parking place recognition methods of the present invention and system, the rule that the suspicious degree of ground point discovery repeatedly stopped according to vehicle is higher, suspicious parking site and feature is identified from the long run track of single vehicle, significantly can reduce erroneous judgement, improve the recognition accuracy in suspicious illegal parking place, reduce the human cost of supervision illegal parking.
Accompanying drawing explanation
Fig. 1 is the process flow diagram of passenger stock illegal parking place recognition methods of the present invention;
Fig. 2 is the hardware structure figure of passenger stock illegal parking location identifying system of the present invention.
Embodiment
Below in conjunction with drawings and the specific embodiments, the present invention is further detailed explanation.
Consulting shown in Fig. 1, is the operation process chart of passenger stock illegal parking place recognition methods preferred embodiment of the present invention.
Step S401, obtains the gps data of arbitrary vehicle.Specifically, from the gps system of certain single unit vehicle, data are obtained.
Step S402, according to the gps data obtained, identifies the parking area repeatedly of this vehicle.
Specifically: first, pre-service is carried out to described gps data.Pre-service is carried out to the GPS track data in this vehicle certain period, removes various invalid record, comprise null value, signal drift etc.
Then, Parking is extracted.Extract the stop of travel speed v=0, the stop of continuous print more than 2 is labeled as a Parking.Calculate the spatial dimension of all stops in this Parking, if longitude or latitude scope exceed certain threshold value (such as, being greater than 0.5 degree), be then labeled as the invalid Parking that error in data causes.For the effective Parking after screening, using the residence time of the time interval of initial stop as Parking, using the geographic coordinate of the average longitude and latitude of stop as Parking.
Finally, parking area is repeatedly found.According to the spacial distribution density of the long-term Parking of single unit vehicle, find the region of repeatedly stopping of this vehicle.This step adopts density clustering analytic approach, filters out the region that parking density is greater than certain threshold value.Specific as follows:
The present embodiment adopts cuclear density analytic approach to extract repeatedly the precise shapes of parking area.Analyzed area is divided into grid cell by described cuclear density analytic approach, then calculates to want vegetarian refreshments, i.e. the density of the coordinate points of Parking around each grid cell.Described grid cell is the most direct the simplest spatial data structure, refers to and earth surface is divided into the adjacent grid array of size uniform close, and each grid is as a basic space cell.According to cuclear density method, each wanting all is covered with a smooth surface above vegetarian refreshments.Point position place face value is the highest, and along with the increase face value of the distance with point reduces gradually, the position face value equaling search radius in the distance with point is zero.The total amount that event that the volume in the space that the plane of curved surface and below surrounds equals this point occurs, namely occurs in the Parking total amount of this coordinate points.The density of each output grid unit is the value sum on all core surfaces being superimposed upon grid cell, raster cell center.Computing method as shown in Equation 1.
Wherein, K is kernel function, x
1, x
2... x
nfor Parking sample set, n is sample size, and h is bandwidth (search radius).Conventional kernel function K comprises Uniform, Epanechikov, Quartic, Gaussian etc.The present embodiment adopts Epanechikov function, as shown in Equation 2.Corresponding kernel function can be selected according to actual conditions in practicing.
Wherein, u=(x-xi)/h.
In the process using cuclear density to analyze, arranging bandwidth h is a committed step.Arranging of different bandwidth can cause density Estimation result different, and then it is different to cause repeatedly parking area to extract result.Should be tested bandwidth by many experiments in embody rule, select the bandwidth of suitable applications scene.
After using cuclear density analysis to estimate the continuous density distribution plan of Parking, arrange and repeatedly spend density threshold, extract the grid cell being greater than this threshold value, continuous print grid cell forms a parking area repeatedly.And then the shape of parking area repeatedly arbitrarily can be extracted comparatively accurately.Should be tested repeatedly spending density threshold by many experiments in embody rule, selecting the density threshold of suitable applications scene.
Step S403, screens the parking area repeatedly of this vehicle identified, and sets threshold value to obtain suspicious parking area.Concrete steps are as follows:
Coach there will be various rational parking scene in operation process, comprise through charge station, wait traffic lights, block up, refuel, auto repair, driver and conductor have a rest etc.Thus, various rational stop parking lots scape is contained in the parking area repeatedly extracted.How to distinguish illegal parking region and reasonable parking area is a committed step of the present invention.
The present embodiment adopts exclusive method to realize the discovery in parking offense region, and four kinds of main exclusion programs are as follows:
A () gets rid of planning passenger point.Collect the distributing position of planning passenger point, exclude with the have living space parking area of overlapping relation of planning region, passenger point.Wherein, plan that passenger point comprises regular passenger station and joins objective point.
B () eliminating waits traffic lights the parking aggregation zone caused.Collect traffic lights distributing position, distance traffic lights are necessarily waited for that the parking area in distance excludes.To traffic lights, the present embodiment waits for that distance is tested by many experiments, select the wait distance of suitable applications scene.
C () gets rid of the jogging region that blocks up.Extract along the parking area that road is strip distribution on expressway, major trunk roads, travel speed before and after calculated target point, if average overall travel speed is lower than certain speed threshold value in region, judge that it is for the jogging region that blocks up, then exclude this region.
D () gets rid of other reasonable parking areas.Collect the distributing position of other reasonable parking sites, the parking area having space intersection relation with various reasonable stop is excluded.Wherein, other reasonable parking areas described comprise charge station, inspection post, joint inspection station, motor vehicle inspection station, maintenance factory, automobile fitting, car detailing shop etc.
Step S404, carries out suspicious intensity grade division to suspicious parking area.Region near the common illegal parking terrestrial references such as passenger station, bus station, subway station, parking lot, refuelling station, travel agency is set to high suspicious, in remaining area, Parking sum exceedes in being set to of certain threshold value suspicious (this threshold value adjusts according to practical application) repeatedly, and all the other regions are set to low suspicious.Concrete steps are as follows:
Period is verified for emphasis, first according to one day 24 period, calculates the stop frequency in each period in month.Assuming that Parking follows Poisson distribution, formula 3 is adopted to calculate the probability finding at least 1 Parking in each period.When a random occurrence is with fixing average momentary rate λ (or claiming density) at random and when occurring independently, so the number of times that occurs during unit interval (area or volume) of this event or number just obey Poisson distribution approx.According to the discovery probability of Parking and the needs of practical application, filter out emphasis and verify the period.
Consulting shown in Fig. 2, is the hardware structure figure of passenger stock illegal parking location identifying system of the present invention.This system comprises the acquisition module, identification module, screening module and the division module that are mutually electrically connected.
Described acquisition module is for obtaining the gps data of arbitrary vehicle.Specifically, described acquisition module obtains data from the gps system of certain single unit vehicle.
Described identification module is used for, according to the gps data obtained, identifying the parking area repeatedly of this vehicle.Specific as follows:
First, described identification module carries out pre-service to described gps data.Pre-service is carried out to the GPS track data in this vehicle certain period, removes various invalid record, comprise null value, signal drift etc.
Then, described identification module extracts Parking.Extract the stop of travel speed v=0, the stop of continuous print more than 2 is labeled as a Parking.Calculate the spatial dimension of all stops in this Parking, if longitude or latitude scope exceed certain threshold value (such as, being greater than 0.5 degree), be then labeled as the invalid Parking that error in data causes.For the effective Parking after screening, using the residence time of the time interval of initial stop as Parking, using the geographic coordinate of the average longitude and latitude of stop as Parking.
Finally, described identification module finds parking area repeatedly.According to the spacial distribution density of the Parking of vehicle commander's phase, find the region of repeatedly stopping.This step adopts density clustering analytic approach, filters out the region that parking density is greater than certain threshold value.Specific as follows:
The present embodiment adopts cuclear density analytic approach to extract repeatedly the precise shapes of parking area.Analyzed area is divided into grid cell by described cuclear density analytic approach, then calculates to want vegetarian refreshments, i.e. the density of the coordinate points of Parking around each grid cell.Described grid cell is the most direct the simplest spatial data structure, refers to and earth surface is divided into the adjacent grid array of size uniform close, and each grid is as a basic space cell.According to cuclear density method, each wanting all is covered with a smooth surface above vegetarian refreshments.Point position place face value is the highest, and along with the increase face value of the distance with point reduces gradually, the position face value equaling search radius in the distance with point is zero.The total amount that event that the volume in the space that the plane of curved surface and below surrounds equals this point occurs, namely occurs in the Parking total amount of this coordinate points.The density of each output grid unit is the value sum on all core surfaces being superimposed upon grid cell, raster cell center.Computing method as shown in Equation 1.
Wherein, K is kernel function, x
1, x
2... x
nfor Parking sample set, n is sample size, and h is bandwidth (search radius).Conventional kernel function K comprises Uniform, Epanechikov, Quartic, Gaussian etc.The present embodiment adopts Epanechikov function, as shown in Equation 2.Corresponding kernel function can be selected according to actual conditions in practicing.
Wherein, u=(x-xi)/h.
In the process using cuclear density to analyze, arranging bandwidth h is a committed step.Arranging of different bandwidth can cause density Estimation result different, and then it is different to cause repeatedly parking area to extract result.Should be tested bandwidth by many experiments in embody rule, select the bandwidth of suitable applications scene.
After using cuclear density analysis to estimate the continuous density distribution plan of Parking, arrange and repeatedly spend density threshold, extract the grid cell being greater than this threshold value, continuous print grid cell forms a parking area repeatedly.And then the shape of parking area repeatedly arbitrarily can be extracted comparatively accurately.Should be tested repeatedly spending density threshold by many experiments in embody rule, selecting the density threshold of suitable applications scene.
Described screening module is used for screening the parking area repeatedly of this vehicle identified, and sets threshold value to obtain suspicious parking area.Specific as follows:
Coach there will be various rational parking scene in operation process, comprise through charge station, wait traffic lights, block up, refuel, auto repair, driver and conductor have a rest etc.Thus, various rational stop parking lots scape is contained in the parking area repeatedly extracted.How to distinguish illegal parking region and reasonable parking area is a committed step of the present invention.
The present embodiment adopts exclusive method to realize the discovery in parking offense region, and four kinds of main exclusion programs are as follows:
A () gets rid of planning passenger point.Collect the distributing position of planning passenger point, exclude with the have living space parking area of overlapping relation of planning region, passenger point.Wherein, plan that passenger point comprises regular passenger station and joins objective point.
B () eliminating waits traffic lights the parking aggregation zone caused.Collect traffic lights distributing position, distance traffic lights are necessarily waited for that the parking area in distance excludes.To traffic lights, the present embodiment waits for that distance is tested by many experiments, select the wait distance of suitable applications scene.
C () gets rid of the jogging region that blocks up.Extract along the parking area that road is strip distribution on expressway, major trunk roads, travel speed before and after calculated target point, if average overall travel speed is lower than certain speed threshold value in region, judge that it is for the jogging region that blocks up, then exclude this region.
D () gets rid of other reasonable parking areas.Collect the distributing position of other reasonable parking sites, the parking area having space intersection relation with various reasonable stop is excluded.Wherein, other reasonable parking areas described comprise charge station, inspection post, joint inspection station, motor vehicle inspection station, maintenance factory, automobile fitting, car detailing shop etc.
Described division module is used for carrying out suspicious intensity grade division to suspicious parking area.Region near the common illegal parking terrestrial references such as passenger station, bus station, subway station, parking lot, refuelling station, travel agency is set to high suspicious, in remaining area, Parking sum exceedes in being set to of certain threshold value suspicious (this threshold value adjusts according to practical application) repeatedly, and all the other regions are set to low suspicious.Specific as follows:
Period is verified for emphasis, first according to one day 24 period, calculates the stop frequency in each period in month.Assuming that Parking follows Poisson distribution, formula 3 is adopted to calculate the probability finding at least 1 Parking in each period.When a random occurrence is with fixing average momentary rate λ (or claiming density) at random and when occurring independently, so the number of times that occurs during unit interval (area or volume) of this event or number just obey Poisson distribution approx.According to the discovery probability of Parking and the needs of practical application, filter out emphasis and verify the period.
Although the present invention is described with reference to current better embodiment; but those skilled in the art will be understood that; above-mentioned better embodiment is only used for the present invention is described; not be used for limiting protection scope of the present invention; any within the spirit and principles in the present invention scope; any modification of doing, equivalence replacement, improvement etc., all should be included within the scope of the present invention.
Claims (8)
1. the recognition methods of passenger stock illegal parking place, is characterized in that, the method comprises the steps:
A. the gps data of arbitrary vehicle is obtained;
B. according to the gps data obtained, the parking area repeatedly of this vehicle is identified;
C. screening is carried out to the parking area repeatedly of this vehicle identified and obtain suspicious parking area;
D. suspicious intensity grade division is carried out to suspicious parking area;
Wherein, described step c comprises:
Get rid of planning passenger point;
Get rid of and wait traffic lights the parking area repeatedly caused;
Get rid of the jogging region that blocks up;
Get rid of other reasonable parking areas, other reasonable parking areas described comprise charge station, inspection post, joint inspection station, motor vehicle inspection station, maintenance factory, automobile fitting and car detailing shop.
2. the method for claim 1, is characterized in that, described step b comprises:
Pre-service is carried out to described gps data;
Parking is extracted according to pretreated gps data;
Parking according to extracting finds parking area repeatedly.
3. method as claimed in claim 2, is characterized in that, according to the Parking extracted, described finds that repeatedly parking area adopts cuclear density analytic approach.
4. the method for claim 1, is characterized in that, described suspicious intensity grade comprise high suspicious, in suspicious and low suspicious.
5. a passenger stock illegal parking location identifying system, is characterized in that, this system comprises the acquisition module, identification module, screening module and the division module that are mutually electrically connected, wherein:
Described acquisition module is for obtaining the gps data of arbitrary vehicle;
Described identification module is used for, according to the gps data obtained, identifying the parking area repeatedly of this vehicle;
Described screening module is used for carrying out screening to the parking area repeatedly of this vehicle identified and obtains suspicious parking area;
Described division module is used for carrying out suspicious intensity grade division to suspicious parking area;
Wherein, described screening module is specifically for getting rid of planning passenger point; Get rid of and wait traffic lights the parking area repeatedly caused; Get rid of the jogging region that blocks up; And get rid of other reasonable parking areas, other reasonable parking areas described comprise charge station, inspection post, joint inspection station, motor vehicle inspection station, maintenance factory, automobile fitting and car detailing shop.
6. system as claimed in claim 5, is characterized in that, described identification module, specifically for carrying out pre-service to described gps data, extracts Parking according to pretreated gps data, and finds parking area repeatedly according to the Parking extracted.
7. system as claimed in claim 6, is characterized in that, according to the Parking extracted, described finds that repeatedly parking area adopts cuclear density analytic approach.
8. system as claimed in claim 5, is characterized in that, described suspicious intensity grade comprise high suspicious, in suspicious and low suspicious.
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| CN105608889B (en) * | 2015-09-07 | 2018-10-26 | 华迪计算机集团有限公司 | A kind of stoppage of vehicle analysis method |
| CN105702043B (en) * | 2016-04-22 | 2018-07-06 | 北京国交信通科技发展有限公司 | To the method for early warning of emphasis commerial vehicle parking offense on a highway |
| CN107730873A (en) * | 2017-09-14 | 2018-02-23 | 王淑芳 | A kind of emphasis commerial vehicle abnormal behaviour monitoring method and system |
| SG11201811630XA (en) | 2018-09-18 | 2020-04-29 | Beijing Didi Infinity Technology & Development Co Ltd | Artificial intelligent systems and methods for predicting traffic accident locations |
| CN111179578A (en) * | 2018-11-09 | 2020-05-19 | 北京嘀嘀无限科技发展有限公司 | Method and system for determining parking place limitation |
| CN109544968A (en) * | 2018-12-06 | 2019-03-29 | 成都路行通信息技术有限公司 | A method of judging whether vehicle occurs trans-regional behavior |
| CN111383448A (en) * | 2018-12-29 | 2020-07-07 | 阿里巴巴集团控股有限公司 | Traffic information processing method and device based on road section |
| CN109887285B (en) * | 2019-03-15 | 2021-04-20 | 北京经纬恒润科技股份有限公司 | Method and device for determining parking reason |
| CN111105622B (en) * | 2019-12-23 | 2021-11-02 | 北京中交兴路车联网科技有限公司 | Illegal parking correction method and device and storage medium |
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