CN103903438B - 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 PDF

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CN103903438B
CN103903438B CN201410095229.8A CN201410095229A CN103903438B CN 103903438 B CN103903438 B CN 103903438B CN 201410095229 A CN201410095229 A CN 201410095229A CN 103903438 B CN103903438 B CN 103903438B
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parking
suspicious
aggregation zone
gps data
rid
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CN103903438A (en
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尹凌
胡金星
黄练
任鹏
许宁
王倩
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Shenzhen Institute of Advanced Technology of CAS
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Shenzhen Institute of Advanced Technology of CAS
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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 multiple vehicle; According to the gps data obtained, identify the parking aggregation zone of described multiple vehicle; Screening is carried out to the described parking aggregation zone 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

The place recognition methods of passenger stock illegal parking and system
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 multiple vehicle; B. according to the gps data obtained, the parking aggregation zone of described multiple vehicle is identified; C. screening is carried out to the described parking aggregation zone 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 aggregation zone is found according to the Parking extracted.
According to the Parking extracted, described finds that parking aggregation zone adopts cuclear density analytic approach.
Described step c comprises: get rid of planning passenger point; Get rid of and wait traffic lights the parking aggregation zone 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 multiple vehicle; Described identification module is used for, according to the gps data obtained, identifying the parking aggregation zone of described multiple vehicle; Described screening module is used for carrying out screening to the described parking aggregation zone 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 aggregation zone according to the Parking extracted.
According to the Parking extracted, described finds that parking aggregation zone 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 aggregation zone 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 higher according to the suspicious degree in place of multiple vehicle gathering parking, from the driving trace of numerous vehicle, identify that place and feature are assembled in suspicious parking, 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 multiple vehicle.Specifically, from the GPS of multiple even magnanimity vehicle, data are obtained.
Step S402, according to the gps data obtained, identifies the parking aggregation zone of described multiple vehicle.
Specifically: first, pre-service is carried out to described gps data.Pre-service is carried out to the long-distance passenger transportation GPS track data in 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 aggregation zone is found.According to the spacial distribution density of the Parking of multiple vehicle, find parking aggregation zone.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 the precise shapes of parking aggregation zone.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.
f ^ h ( x ) = ΣK i = 1 n ( x - x i h ) nh Formula 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.
K ( u ) = 3 4 ( 1 - u 2 ) , u ∈ [ - 1,1 ] 0 , otherwise Formula 2
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 parking aggregation zone 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 aggregation degree density threshold, extract the grid cell being greater than this threshold value, continuous print grid cell forms a parking aggregation zone.And then the shape of illegal parking aggregation zone can be extracted comparatively accurately.Should be tested aggregation degree density threshold by many experiments in embody rule, select the density threshold of suitable applications scene.
Step S403, screens the parking aggregation zone of the 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 aggregation zone 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.Be set in region near the common illegal parking terrestrial references such as passenger station, bus station, subway station, parking lot, refuelling station, travel agency high suspicious, have same vehicle repeatedly suspicious in being set to of Parking in remaining area, 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.
P ( k > 0 ) = 1 - P ( 0 ) = 1 - λ 0 e - λ 0 ! Formula 3
Verify car plate for emphasis, this project calculates total stop frequency of each car plate in month in each suspicious region.By maximum for total stop frequency and have at least the car plate of 2 times be labeled as emphasis verify car plate.
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 vehicle.Specifically, described acquisition module obtains data from the GPS being arranged on each vehicle.
Described identification module is used for the gps data according to obtaining, and identifies the parking aggregation zone of vehicle.Specific as follows:
First, described identification module carries out pre-service to described gps data.Pre-service is carried out to the long-distance passenger transportation GPS track data in 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 aggregation zone.According to the spacial distribution density of the Parking of multiple vehicle, find the region of assembling of 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 the precise shapes of parking aggregation zone.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.
f ^ h ( x ) = ΣK i = 1 n ( x - x i h ) nh Formula 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.
K ( u ) = 3 4 ( 1 - u 2 ) , u ∈ [ - 1,1 ] 0 , otherwise Formula 2
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 parking aggregation zone 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 aggregation degree density threshold, extract the grid cell being greater than this threshold value, continuous print grid cell forms a parking aggregation zone.And then the shape of illegal parking aggregation zone can be extracted comparatively accurately.Should be tested aggregation degree density threshold by many experiments in embody rule, select the density threshold of suitable applications scene.
Described screening module is used for screening the parking aggregation zone of the 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 aggregation zone 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.Be set in region near the common illegal parking terrestrial references such as passenger station, bus station, subway station, parking lot, refuelling station, travel agency high suspicious, have same vehicle repeatedly suspicious in being set to of Parking in remaining area, 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.
P ( k > 0 ) = 1 - P ( 0 ) = 1 - λ 0 e - λ 0 ! Formula 3
Verify car plate for emphasis, this project calculates total stop frequency of each car plate in month in each suspicious region.By maximum for total stop frequency and have at least the car plate of 2 times be labeled as emphasis verify car plate.
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 multiple vehicle is obtained;
B. according to the gps data obtained, the parking aggregation zone of described multiple vehicle is identified;
C. screening is carried out to the described parking aggregation zone 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 aggregation zone 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 aggregation zone is found according to the Parking extracted.
3. method as claimed in claim 2, is characterized in that, according to the Parking extracted, described finds that parking aggregation zone 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 multiple vehicle;
Described identification module is used for, according to the gps data obtained, identifying the parking aggregation zone of described multiple vehicle;
Described screening module is used for carrying out screening to the described parking aggregation zone 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 aggregation zone 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 aggregation zone according to the Parking extracted.
7. system as claimed in claim 6, is characterized in that, according to the Parking extracted, described finds that parking aggregation zone 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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Families Citing this family (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160035151A1 (en) * 2014-07-31 2016-02-04 Ford Global Technologies, Llc Method and Apparatus for Vehicle Data Gathering and Analysis
CN105206083A (en) * 2015-09-24 2015-12-30 上海车音网络科技有限公司 Designated driving monitoring early warning device, system and method
CN105206082A (en) * 2015-09-24 2015-12-30 上海车音网络科技有限公司 Designated driving management device, system and method
CN105810006B (en) * 2016-03-29 2018-08-21 福建工程学院 The recognition methods of parking position and system
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
CN108122414A (en) * 2016-11-30 2018-06-05 杭州海康威视数字技术股份有限公司 The detection method and device of car on-board and off-board on highway
CN108021625B (en) * 2017-11-21 2021-01-19 深圳广联赛讯股份有限公司 Vehicle abnormal gathering place monitoring method and system, and computer readable storage medium
SE541634C2 (en) * 2018-03-06 2019-11-19 Scania Cv Ab Method and control arrangement for identification of parking areas
CN109656245B (en) * 2018-10-31 2020-10-27 百度在线网络技术(北京)有限公司 Method and device for determining brake position
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
CN110428604B (en) * 2019-07-30 2022-04-22 山东交通学院 Taxi illegal parking monitoring and early warning method based on track and map data
CN112185103A (en) * 2019-09-24 2021-01-05 成都通甲优博科技有限责任公司 Traffic monitoring method and device and electronic equipment
CN111951554A (en) * 2020-08-20 2020-11-17 北京嘀嘀无限科技发展有限公司 Illegal parking road information acquisition method and system
CN112712696A (en) * 2020-12-30 2021-04-27 北京嘀嘀无限科技发展有限公司 Method and device for determining road section with illegal parking

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101241643A (en) * 2008-03-05 2008-08-13 中科院嘉兴中心微***所分中心 Passenger car monitoring system based on sensor network technology
CN101425225A (en) * 2007-10-30 2009-05-06 厦门雅迅网络股份有限公司 Method for managing automobile line by using GPS technology
CN101800772A (en) * 2010-02-02 2010-08-11 大连海创高科信息技术有限公司 3G vehicle-mounted intelligent monitoring management system
CN102231822A (en) * 2011-06-24 2011-11-02 广州亿程交通信息有限公司 Monitoring system
KR20120109163A (en) * 2011-03-28 2012-10-08 제주대학교 산학협력단 Parking and stopping control system, mobile for official and server used in there, and method therefor
CN103150920A (en) * 2013-01-29 2013-06-12 北京瑞拓电子技术发展有限公司 Vehicle illegal parking remote monitoring system
CN103236182A (en) * 2013-03-29 2013-08-07 安科智慧城市技术(中国)有限公司 Method and system for monitoring traffic safety and monitoring device
CN103440767A (en) * 2013-09-04 2013-12-11 彭博 Highway-driving-information vehicle-mounted terminal, monitoring system and method

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
ITVR20020129A1 (en) * 2002-12-17 2004-06-18 Gianfranco Zanotti INTEGRATED AUTOMATIC SYSTEM FOR MONITORING AND

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101425225A (en) * 2007-10-30 2009-05-06 厦门雅迅网络股份有限公司 Method for managing automobile line by using GPS technology
CN101241643A (en) * 2008-03-05 2008-08-13 中科院嘉兴中心微***所分中心 Passenger car monitoring system based on sensor network technology
CN101800772A (en) * 2010-02-02 2010-08-11 大连海创高科信息技术有限公司 3G vehicle-mounted intelligent monitoring management system
KR20120109163A (en) * 2011-03-28 2012-10-08 제주대학교 산학협력단 Parking and stopping control system, mobile for official and server used in there, and method therefor
CN102231822A (en) * 2011-06-24 2011-11-02 广州亿程交通信息有限公司 Monitoring system
CN103150920A (en) * 2013-01-29 2013-06-12 北京瑞拓电子技术发展有限公司 Vehicle illegal parking remote monitoring system
CN103236182A (en) * 2013-03-29 2013-08-07 安科智慧城市技术(中国)有限公司 Method and system for monitoring traffic safety and monitoring device
CN103440767A (en) * 2013-09-04 2013-12-11 彭博 Highway-driving-information vehicle-mounted terminal, monitoring system and method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
基于GPS定位及3G通信客运车辆监控***设计;李玲 等;《现代电子技术》;20110915;第34卷(第18期);全文 *

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