CN111627219A - Vehicle cooperation method for detecting curve driving information by using vehicle electronic identification - Google Patents

Vehicle cooperation method for detecting curve driving information by using vehicle electronic identification Download PDF

Info

Publication number
CN111627219A
CN111627219A CN202010569306.4A CN202010569306A CN111627219A CN 111627219 A CN111627219 A CN 111627219A CN 202010569306 A CN202010569306 A CN 202010569306A CN 111627219 A CN111627219 A CN 111627219A
Authority
CN
China
Prior art keywords
vehicle
curve
information
automobile
time
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202010569306.4A
Other languages
Chinese (zh)
Other versions
CN111627219B (en
Inventor
肖金坚
刘晓峰
侯海晶
张蕊
王少华
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tianjin University of Technology and Education China Vocational Training Instructor Training Center
Original Assignee
Tianjin University of Technology and Education China Vocational Training Instructor Training Center
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tianjin University of Technology and Education China Vocational Training Instructor Training Center filed Critical Tianjin University of Technology and Education China Vocational Training Instructor Training Center
Priority to CN202010569306.4A priority Critical patent/CN111627219B/en
Publication of CN111627219A publication Critical patent/CN111627219A/en
Application granted granted Critical
Publication of CN111627219B publication Critical patent/CN111627219B/en
Expired - Fee Related legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/017Detecting movement of traffic to be counted or controlled identifying vehicles
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/01Detecting movement of traffic to be counted or controlled
    • G08G1/052Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/09Arrangements for giving variable traffic instructions
    • G08G1/0962Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0967Systems involving transmission of highway information, e.g. weather, speed limits
    • GPHYSICS
    • G08SIGNALLING
    • G08GTRAFFIC CONTROL SYSTEMS
    • G08G1/00Traffic control systems for road vehicles
    • G08G1/09Arrangements for giving variable traffic instructions
    • G08G1/0962Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968Systems involving transmission of navigation instructions to the vehicle
    • G08G1/0969Systems involving transmission of navigation instructions to the vehicle having a display in the form of a map

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Atmospheric Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention provides a vehicle cooperation method for detecting curve driving information by using an automobile electronic mark, which mainly comprises the steps of installing an automobile electronic mark detection device at an intersection of a curve road section, realizing the acquisition of vehicle information such as the type, the space size and the like of a vehicle driving in the curve, establishing a curve traffic state presumption algorithm of a cloud network, presuming the traffic state in the curve road section such as the position, the speed, the distance and the like of the vehicle driving, broadcasting the presumption information to the vehicle about to enter the curve by using cloud broadcasting, realizing the information cooperative and interactive utilization between the vehicle and the vehicle at the curve road section, realizing the real-time acquisition of the traffic state in the curve by a driver, making psychological preparation aiming at the running condition of the vehicle in the curve in advance, selecting proper driving operation, reducing the driving safety problem caused by insufficient information, driving blind spots and the like, and effectively solving the driving safety hidden trouble under the condition that the sight distance of, the safety of road driving is improved, can use widely.

Description

Vehicle cooperation method for detecting curve driving information by using vehicle electronic identification
Technical Field
The invention belongs to the technical field of traffic engineering, and particularly relates to a vehicle cooperation method for detecting curve driving information by using an automobile electronic identifier.
Background
At present, the existing automobile electronic identification monitoring system mainly utilizes information stored in an electronic identification to acquire information such as automobile numbers, automobile types, purposes, all relations and the like passing through an intersection electronic identification detection device, the system function is limited to the applications such as detection of automobile identity information, positioning of driving road sections, anti-counterfeiting of automobile license plates, electronic fences, the number of vehicles and the like, and the huge potential value of the electronic identification information on reduction of traffic safety accidents is not given. The automobile electronic identification monitoring system also has other functions with practical value and social value to be developed urgently.
Disclosure of Invention
The invention aims to solve the technical problem of providing a vehicle cooperation method for detecting curve driving information by using an electronic identification of a vehicle, which mainly detects the vehicle driving through a curve in real time by using an electronic identification detector, acquires corresponding vehicle information and transmits the detected vehicle information to a control center through a wireless network. The control center utilizes the electronic identification detection information to realize the calculation of parameters such as the vehicle speed prediction, the vehicle curve position calculation, the inter-vehicle distance calculation and the like of the vehicle running in the curve, and utilizes the information cooperation method among the vehicles running in the curve to transmit the information to the vehicle running in the curve, so that the running vehicle can obtain the information of other vehicles which can interfere the running safety of the running vehicle, the driving mode is adjusted in time, and the danger of the running in the curve is reduced.
In order to solve the technical problems, the invention adopts the technical scheme that: a vehicle cooperation method for detecting curve driving information by using an automobile electronic identifier is characterized by comprising the following operation steps:
s1, time t0Time detector C01Detect the car V01By obtaining the detected information MV01
S2, detecting information MV01Uploading to a control center;
s3, the control center detects the information MV01Reconstructing vehicle information using vehicle V01Length, width, height and body color of (1) drawing 3D or 2D frame KV01Representative vehicle V01
S4 criterion detector C01In the position of (1), the frame body KV01Displaying lanes L of corresponding road sections on electronic map01The above step (1);
s5, Detector C disposed at other position02Equal detection time t0The state information of other related vehicles running at the curve is collected to the control center through the mobile network, and the control center reconstructs the generated vehicle information and displays the vehicle information on the corresponding lane;
s6, the control center calculates t according to the prediction algorithm of the vehicle running speed in the curve, the algorithm of the vehicle position in the curve and the algorithm of the vehicle distance in the curve0Time automobile V01In the lane L01The speed, position and distance information of the previous vehicle;
s7, according to the time t1Estimating the vehicle V01Position of obtaining a car V01At a bend L01Real-time dynamic position of the inner;
s8, the control center based on the automobile V01At a bend L01Pushing other related vehicle information in the same curve area to the automobile V according to the information cooperation method by the real-time dynamic position in the automobile V01
S9, the control center predicts the automobile V01Position information, beyond the longitudinal length of the curve, ending the alignment of the vehicle V01And (5) pushing information.
Preferably, the control center pushes to the vehicle V01The information of the vehicle adopts character and map information, and the character information displays the vehicle V01The number of related vehicles on the current driving route, the average running speed of the related vehicles and the average vehicle distance information; groundAnd the graph information represents the automobile by adopting a 2D or 3D wire frame graph, and simultaneously, related vehicles are dynamically marked on the automobile digital map in real time, and the 2D or 3D vehicle graph, the average speed of the automobile and the vehicle distance information on the current lane are displayed.
The system is characterized by comprising a detector and a control center, wherein the detector is an automobile electronic identification detector, a plurality of detectors are uniformly arranged at the entrance of a curve, the detectors are in wireless connection with the control center, and the detector is a remote wireless card reader and is used for reading information in the automobile electronic identification at a fixed position so as to acquire the vehicle information.
Preferably, the vehicle running speed prediction algorithm specifically comprises the following steps:
a1 using automobile random variable Vt:V0,V1,…,Vt… form a vehicle speed data link, { V }tT ∈ T, T is curve automobile running time, and is an automobile speed data set in the time T;
a2, calculating the vehicle speed state transition probability:
because of the influence of external environments such as weather, illumination and the like, the continuous speed transition probability matrix can change along with the environment such as time, weather and the like, and the speed change is 3 states: increase, do not change, reduce; obtaining a vehicle speed change state transition data statistical table shown in table 1 according to the vehicle speed state transition historical record;
Figure BDA0002548868110000031
TABLE 1
To be provided with
Figure BDA0002548868110000032
The estimated value of the transition probability representing the transition of the vehicle speed from the state n to the state m is obtained by collecting the corresponding speed state value on the spot by the speed state table of the table 1 and then calculating the estimated probability value, wherein the calculation formula is as follows:
Figure BDA0002548868110000033
a3, vehicle speed at t0At time in state n, t1The velocity transition probability for the time transition to state m is:
Figure BDA0002548868110000034
then t1The velocity transition matrix of time is:
Figure BDA0002548868110000035
a4, the current speed of the automobile i is in the state n, and the predicted speed of the automobile at the current time point t is obtained after k steps of transfer to the state m
Figure BDA0002548868110000036
The velocity recurrence formula of (c) is:
Figure BDA0002548868110000037
when k is 1, the initial vehicle speed is defined as
Figure BDA0002548868110000041
Preferably, the algorithm for the position of the vehicle in the curve specifically includes the following steps:
obtaining the speed of the automobile i at the current time t by the formula (3) in the vehicle running speed prediction algorithm
Figure BDA0002548868110000042
Obtaining time points by a detector
Figure BDA0002548868110000043
Starting to time to obtain the driving time of the t-hour automobile i
Figure BDA0002548868110000044
The current longitudinal driving position of the curve of the automobile i at the time point t can be predicted
Figure BDA0002548868110000045
Figure BDA0002548868110000046
Preferably, the distance algorithm for vehicles in a curve specifically comprises the following steps:
the time point when the current automobile j passes by can be obtained by the electronic identification detector
Figure BDA0002548868110000047
The longitudinal position of the curve corresponding to the automobile j at the time point t is predicted as follows:
Figure BDA0002548868110000048
the front-rear vehicle distance is predicted as:
Figure BDA0002548868110000049
preferably, the information coordination method specifically includes the following steps:
from the longitudinal length L of the curve(w)And equation (4) can obtain the predicted longitudinal position of all vehicles passing through the electronic mark detector at the time point t
Figure BDA00025488681100000410
If the result of the calculation of the longitudinal position of the vehicle
Figure BDA00025488681100000411
Greater than L(w)If the vehicle is judged to have driven through the current curve, the vehicle does not enter the cooperative process any more;
if the result of the calculation of the longitudinal position of the vehicle
Figure BDA00025488681100000412
Less than L(w)If the vehicle is in the current curve, the vehicle enters the cooperative process, and the vehicle enters the cooperative process at the time point t by using the formula (5)All the same-direction running vehicle positions in the curve in front of the vehicle i
Figure BDA00025488681100000413
Obtaining distance to preceding vehicle
Figure BDA00025488681100000414
Compared with the prior art, the invention has the following advantages:
1. the invention has scientific and reasonable design, realizes the safety protection of the driving at the curve by utilizing the existing automobile electronic identification, has intelligent operation, can clearly obtain the vehicle information of the driving at other curves interfering with the vehicle, is beneficial to the driver to adopt a proper driving operation mode in advance, avoids traffic accidents caused by other illegal behaviors such as curve overtaking and the like or the accident condition of other vehicles, is scientific and effective, and can be popularized and used.
2. The invention mainly detects the running automobile in real time through the electronic identification detector, acquires the corresponding automobile information and transmits the detected automobile information to the control center through the wireless network. The control center utilizes the electronic identification detection information to realize the calculation of parameters such as the vehicle speed prediction, the vehicle curve position calculation, the inter-vehicle distance calculation and the like of the vehicle running in the curve, and utilizes the information cooperation method among the vehicles running in the curve to transmit the information to the vehicle running in the curve, so that the running vehicle can acquire the information of other vehicles which can interfere with the running safety of the driver, the driver can prepare in advance conveniently, the traffic accident which can be avoided can be effectively avoided, and the traffic accident which can not be avoided can be treated in advance in a correct way to minimize the accident injury and the loss.
3. The invention can reasonably mine the effective value of the existing automobile electronic identification system, play the role of network information and further promote the development progress of related technologies.
The present invention will be described in further detail with reference to the accompanying drawings and examples.
Drawings
FIG. 1 is a block diagram of the operational flow of the present invention.
Fig. 2 is a schematic view of the overall technical solution of the present invention.
Detailed Description
As shown in fig. 1 and 2, the present invention includes the following operation steps:
s1, time t0Time detector C01Detect the car V01By obtaining the detected information MV01
S2, detecting information MV01Uploading to a control center;
s3, the control center detects the information MV01Reconstructing vehicle information using vehicle V01Length, width, height and body color of (1) drawing 3D or 2D frame KV01Representative vehicle V01
S4 criterion detector C01In the position of (1), the frame body KV01Displaying lanes L of corresponding road sections on electronic map01The above step (1);
s5, Detector C disposed at other position02Equal detection time t0The state information of other related vehicles running at the curve is collected to the control center through the mobile network, and the control center reconstructs the generated vehicle information and displays the vehicle information on the corresponding lane;
s6, the control center calculates t according to the prediction algorithm of the vehicle running speed in the curve, the algorithm of the vehicle position in the curve and the algorithm of the vehicle distance in the curve0Time automobile V01In the lane L01The speed, position and distance information of the previous vehicle;
s7, according to the time t1Estimating the vehicle V01Position of obtaining a car V01At a bend L01Real-time dynamic position of the inner;
s8, the control center based on the automobile V01At a bend L01Pushing other related vehicle information in the same curve area to the automobile V according to the information cooperation method by the real-time dynamic position in the automobile V01
S9, the control center predicts the automobile V01Position information, beyond the longitudinal length of the curve, ending the alignment of the vehicle V01And (5) pushing information.
In this embodiment, the control center pushes the vehicle V01The information of the vehicle adopts character and map information, and the character information displays the vehicle V01The number of related vehicles on the current driving route, the average running speed of the related vehicles and the average vehicle distance information; the map information represents the automobile by adopting a 2D or 3D wire frame diagram, simultaneously, related vehicles are dynamically marked on the automobile digital map in real time, and the 2D or 3D vehicle line diagram, the average speed of the automobile and the vehicle distance information on the current lane are displayed.
The system is characterized by comprising a detector and a control center, wherein the detector is an automobile electronic identification detector, a plurality of detectors are uniformly arranged at the entrance of a curve, the detectors are in wireless connection with the control center, and the detector is a remote wireless card reader and is used for reading information in the automobile electronic identification at a fixed position so as to acquire the vehicle information.
In this embodiment, the vehicle operation speed prediction algorithm specifically includes the following steps:
a1 using automobile random variable Vt:V0,V1,…,Vt… form a vehicle speed data link, { V }tT ∈ T, T is curve automobile running time, and is an automobile speed data set in the time T;
a2, calculating the vehicle speed state transition probability:
because of the influence of external environments such as weather, illumination and the like, the continuous speed transition probability matrix can change along with the environment such as time, weather and the like, and the speed change is 3 states: increase, do not change, reduce; obtaining a vehicle speed change state transition data statistical table shown in table 1 according to the vehicle speed state transition historical record;
Figure BDA0002548868110000071
TABLE 1
To be provided with
Figure BDA0002548868110000072
The estimated value of the transition probability representing the transition of the vehicle speed from the state n to the state m is obtained by collecting the corresponding speed state value on the spot by the speed state table of the table 1 and then calculating the estimated probability value, wherein the calculation formula is as follows:
Figure BDA0002548868110000073
a3, vehicle speed at t0At time in state n, t1The velocity transition probability for the time transition to state m is:
Figure BDA0002548868110000074
then t1The velocity transition matrix of time is:
Figure BDA0002548868110000075
a4, the current speed of the automobile i is in the state n, and the predicted speed of the automobile at the current time point t is obtained after k steps of transfer to the state m
Figure BDA0002548868110000076
The velocity recurrence formula of (c) is:
Figure BDA0002548868110000077
when k is 1, the initial vehicle speed is defined as
Figure BDA0002548868110000078
In this embodiment, the algorithm for the position of the vehicle in the curve specifically includes the following steps:
obtaining the speed of the automobile i at the current time t by the formula (3) in the vehicle running speed prediction algorithm
Figure BDA0002548868110000079
Obtaining time points by a detector
Figure BDA00025488681100000710
The timing is started and the time is counted,obtaining the driving time of the t-hour automobile i
Figure BDA00025488681100000711
The current longitudinal driving position of the curve of the automobile i at the time point t can be predicted
Figure BDA00025488681100000712
Figure BDA00025488681100000713
In this embodiment, the distance algorithm for the vehicle in the curve specifically includes the following steps:
the time point when the current automobile j passes by can be obtained by the electronic identification detector
Figure BDA0002548868110000081
The longitudinal position of the curve corresponding to the automobile j at the time point t is predicted as follows:
Figure BDA0002548868110000082
the front-rear vehicle distance is predicted as:
Figure BDA0002548868110000083
in this embodiment, the information coordination method specifically includes the following steps:
from the longitudinal length L of the curve(w)And equation (4) can obtain the predicted longitudinal position of all vehicles passing through the electronic mark detector at the time point t
Figure BDA0002548868110000084
If the result of the calculation of the longitudinal position of the vehicle
Figure BDA0002548868110000085
Greater than L(w)If the vehicle is judged to have driven through the current curve, the vehicle does not enter the cooperative process any more;
if the longitudinal position of the carCalculation results
Figure BDA0002548868110000086
Less than L(w)If the vehicle is in the current curve, the vehicle enters the cooperative process, and the positions of all the vehicles in the same direction in the curve in front of the vehicle i are calculated by using the formula (5) when the time point t is calculated
Figure BDA0002548868110000087
Obtaining distance to preceding vehicle
Figure BDA0002548868110000088
When the invention is actually used, when a driver drives a vehicle A to pass through a curve, a detector at the entrance of the curve detects the relevant information of the vehicle A and uploads the relevant information to the control center, the control center obtains other vehicle information which interferes with the driving of the vehicle A through the combined application of a plurality of algorithms and pushes the other vehicle information to the vehicle A, so that the driver of the vehicle A can clearly and intuitively obtain the driving information of other vehicles under the condition of limited visual field, thereby preparing psychological preparation in advance, adopting corresponding driving operation and safely passing through the curve of the road.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the present invention in any way. Any simple modification, change and equivalent changes of the above embodiments according to the technical essence of the invention are still within the protection scope of the technical solution of the invention.

Claims (7)

1. A vehicle cooperation method for detecting curve driving information by using an automobile electronic identifier is characterized by comprising the following operation steps:
s1, time t0Time detector C01Detect the car V01By obtaining the detected information MV01
S2, detecting information MV01Uploading to a control center;
s3, the control center detects the information MV01Reconstructing vehicle information using vehicle V01Length, width, height and bodyColor rendering 3D or 2D frame KV01Representative vehicle V01
S4 criterion detector C01In the position of (1), the frame body KV01Displaying lanes L of corresponding road sections on electronic map01The above step (1);
s5, Detector C disposed at other position02Equal detection time t0The state information of other related vehicles running at the curve is collected to the control center through the mobile network, and the control center reconstructs the generated vehicle information and displays the vehicle information on the corresponding lane;
s6, the control center calculates t according to the prediction algorithm of the vehicle running speed in the curve, the algorithm of the vehicle position in the curve and the algorithm of the vehicle distance in the curve0Time automobile V01In the lane L01The speed, position and distance information of the previous vehicle;
s7, according to the time t1Estimating the vehicle V01Position of obtaining a car V01At a bend L01Real-time dynamic position of the inner;
s8, the control center based on the automobile V01At a bend L01Pushing other related vehicle information in the same curve area to the automobile V according to the information cooperation method by the real-time dynamic position in the automobile V01
S9, the control center predicts the automobile V01Position information, beyond the longitudinal length of the curve, ending the alignment of the vehicle V01And (5) pushing information.
2. The vehicle cooperation method for detecting curved driving information by using electronic automobile identification as claimed in claim 1, wherein the control center pushes the driving information to the vehicle V01The information of the vehicle adopts character and map information, and the character information displays the vehicle V01The number of related vehicles on the current driving route, the average running speed of the related vehicles and the average vehicle distance information; the map information represents the automobile by adopting a 2D or 3D wire frame diagram, simultaneously, related vehicles are dynamically marked on the automobile digital map in real time, and the 2D or 3D vehicle line diagram, the average speed of the automobile and the vehicle distance information on the current lane are displayed.
3. The system is characterized by comprising a detector and a control center, wherein the detector is an automobile electronic identification detector, a plurality of detectors are uniformly arranged at the entrance of a curve, and the detectors are in wireless connection with the control center.
4. The vehicle cooperation method for detecting curve driving information by using the electronic automobile identification as claimed in claim 1, wherein the vehicle running speed prediction algorithm specifically comprises the following steps:
a1 using automobile random variable Vt:V0,V1,…,Vt… form a vehicle speed data link, { V }tT ∈ T, T is curve automobile running time, and is an automobile speed data set in the time T;
a2, calculating the vehicle speed state transition probability:
because of the influence of external environments such as weather, illumination and the like, the continuous speed transition probability matrix can change along with the environment such as time, weather and the like, and the speed change is 3 states: increase, do not change, reduce; obtaining a vehicle speed change state transition data statistical table shown in table 1 according to the vehicle speed state transition historical record;
Figure FDA0002548868100000021
TABLE 1
To be provided with
Figure FDA0002548868100000022
The estimated value of the transition probability representing the transition of the vehicle speed from the state n to the state m is obtained by collecting the corresponding speed state value on the spot by the speed state table of the table 1 and then calculating the estimated probability value, wherein the calculation formula is as follows:
Figure FDA0002548868100000023
a3, vehicle speed at t0At time in state n, t1The velocity transition probability for the time transition to state m is:
Figure FDA0002548868100000031
then t1The velocity transition matrix of time is:
Figure FDA0002548868100000032
a4, the current speed of the automobile i is in the state n, and the predicted speed of the automobile at the current time point t is obtained after k steps of transfer to the state m
Figure FDA0002548868100000033
The velocity recurrence formula of (c) is:
Figure FDA0002548868100000034
when k is 1, the initial vehicle speed is defined as
Figure FDA0002548868100000035
5. The vehicle cooperation method for detecting curve driving information by using the vehicle electronic identification as claimed in claim 4, wherein the vehicle position in the curve algorithm specifically comprises the following steps:
obtaining the speed of the automobile i at the current time t by the formula (3) in the vehicle running speed prediction algorithm
Figure FDA0002548868100000036
Obtaining time points by a detector
Figure FDA0002548868100000037
Start timing, t time automobile i driving time
Figure FDA0002548868100000038
The current longitudinal driving position of the curve of the automobile i at the time point t can be predicted
Figure FDA0002548868100000039
Figure FDA00025488681000000310
6. The vehicle cooperation method for detecting curve driving information by using the electronic automobile identification as claimed in claim 5, wherein the curve inter-vehicle distance algorithm specifically comprises the following steps:
the time point when the current automobile j passes by can be obtained by the electronic identification detector
Figure FDA00025488681000000311
The longitudinal position of the curve corresponding to the automobile j at the time point t is predicted as follows:
Figure FDA00025488681000000312
the front-rear vehicle distance is predicted as:
Figure FDA00025488681000000313
7. the vehicle cooperation method for detecting curve driving information by using the electronic automobile identifier as claimed in claim 6, wherein the information cooperation method specifically comprises the following steps:
from the longitudinal length L of the curve(w)And equation (4) can obtain the predicted longitudinal position of all vehicles passing through the electronic mark detector at the time point t
Figure FDA00025488681000000314
If the result of the calculation of the longitudinal position of the vehicle
Figure FDA00025488681000000315
Greater than L(w)If the vehicle is judged to have driven through the current curve, the vehicle does not enter the cooperative process any more;
if the result of the calculation of the longitudinal position of the vehicle
Figure FDA0002548868100000041
Less than L(w)If the vehicle is in the current curve, the vehicle enters the cooperative process, and the positions of all the vehicles in the same direction in the curve in front of the vehicle i are calculated by using the formula (5) when the time point t is calculated
Figure FDA0002548868100000042
Obtaining distance to preceding vehicle
Figure FDA0002548868100000043
CN202010569306.4A 2020-06-20 2020-06-20 Vehicle cooperation method for detecting curve driving information by using vehicle electronic identification Expired - Fee Related CN111627219B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010569306.4A CN111627219B (en) 2020-06-20 2020-06-20 Vehicle cooperation method for detecting curve driving information by using vehicle electronic identification

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010569306.4A CN111627219B (en) 2020-06-20 2020-06-20 Vehicle cooperation method for detecting curve driving information by using vehicle electronic identification

Publications (2)

Publication Number Publication Date
CN111627219A true CN111627219A (en) 2020-09-04
CN111627219B CN111627219B (en) 2021-07-09

Family

ID=72271567

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010569306.4A Expired - Fee Related CN111627219B (en) 2020-06-20 2020-06-20 Vehicle cooperation method for detecting curve driving information by using vehicle electronic identification

Country Status (1)

Country Link
CN (1) CN111627219B (en)

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102289935A (en) * 2006-03-03 2011-12-21 因瑞克斯有限公司 Assessing road traffic conditions using data from mobile data sources
CN103606270A (en) * 2013-11-27 2014-02-26 重庆邮电大学 Vehicle-road cooperative communication method and system
US20160035221A1 (en) * 2014-04-29 2016-02-04 Maxwell Consulting, LLC Systems and Methods for Traffic Guidance Nodes and Traffic Navigating Entities
CN105739305A (en) * 2016-01-29 2016-07-06 北京理工大学 Crawler control method
CN106056974A (en) * 2016-07-14 2016-10-26 清华大学苏州汽车研究院(吴江) Active safety early warning device based on vehicle infrastructure integration
CN108765940A (en) * 2018-05-28 2018-11-06 南京邮电大学 Road congestion based on high-order Markov model finds method
CN109544991A (en) * 2018-12-17 2019-03-29 安徽百诚慧通科技有限公司 A kind of bus or train route collaboration bend vehicle meeting early warning system and control method
CN110211372A (en) * 2019-04-18 2019-09-06 深圳中集智能科技有限公司 Bus or train route cooperated integration perceives control system and method
CN111216731A (en) * 2020-01-23 2020-06-02 南京锦和佳鑫信息科技有限公司 Active sensing system for cooperative automatic driving of vehicle and road

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102289935A (en) * 2006-03-03 2011-12-21 因瑞克斯有限公司 Assessing road traffic conditions using data from mobile data sources
CN103606270A (en) * 2013-11-27 2014-02-26 重庆邮电大学 Vehicle-road cooperative communication method and system
US20160035221A1 (en) * 2014-04-29 2016-02-04 Maxwell Consulting, LLC Systems and Methods for Traffic Guidance Nodes and Traffic Navigating Entities
CN105739305A (en) * 2016-01-29 2016-07-06 北京理工大学 Crawler control method
CN106056974A (en) * 2016-07-14 2016-10-26 清华大学苏州汽车研究院(吴江) Active safety early warning device based on vehicle infrastructure integration
CN108765940A (en) * 2018-05-28 2018-11-06 南京邮电大学 Road congestion based on high-order Markov model finds method
CN109544991A (en) * 2018-12-17 2019-03-29 安徽百诚慧通科技有限公司 A kind of bus or train route collaboration bend vehicle meeting early warning system and control method
CN110211372A (en) * 2019-04-18 2019-09-06 深圳中集智能科技有限公司 Bus or train route cooperated integration perceives control system and method
CN111216731A (en) * 2020-01-23 2020-06-02 南京锦和佳鑫信息科技有限公司 Active sensing system for cooperative automatic driving of vehicle and road

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
曹磊,等: "基于马尔可夫链的汽车行驶工况预测", 《内燃机与动力装置》 *
王晓蒙,等: "基于稀疏浮动车数据的城市路网交通流速度估计", 《测绘学报》 *
罗笑冰,等: "模型转移概率自适应的交互式多模型跟踪算法", 《电子与信息学报》 *

Also Published As

Publication number Publication date
CN111627219B (en) 2021-07-09

Similar Documents

Publication Publication Date Title
EP3533681B1 (en) Method for detecting safety of driving behavior, apparatus and storage medium
CN103871242B (en) A kind of driving behavior overall evaluation system and method
CN110400478A (en) A kind of road condition notification method and device
CN103723096B (en) With the drive assist system of radio communication function
KR101859402B1 (en) The object tracking and lane changing vehicles detection method between linked cameras in tunnel
CN104417550B (en) The rear side of vehicle is to warning system and its alarm control method
Saiprasert et al. Driver behaviour profiling using smartphone sensory data in a V2I environment
CN107301776A (en) Track road conditions processing and dissemination method based on video detection technology
CN108460968A (en) A kind of method and device obtaining traffic information based on car networking
CN111231965B (en) Method and device for adjusting vehicle control mode and unmanned vehicle
CN108966145A (en) Hit-and-run criminal is tracked using V2X communication
JP6392735B2 (en) Information processing apparatus, information processing method, vehicle control apparatus, and vehicle control method
CN104157160B (en) Vehicle travel control method, device and vehicle
CN107229906A (en) A kind of automobile overtaking's method for early warning based on units of variance model algorithm
CN115877343B (en) Man-car matching method and device based on radar target tracking and electronic equipment
CN113851017A (en) Pedestrian and vehicle identification and early warning multifunctional system based on road side RSU
CN104574993A (en) Road monitoring method and device
CN110930715A (en) Method and system for identifying red light running of non-motor vehicle and violation processing platform
CN111260915B (en) Early warning reminding method for pedestrian stay in expressway traffic abnormal area
CN111932889A (en) Traffic dispersion system based on vehicle-road cooperation
JP4961305B2 (en) Vehicle monitoring device for toll road automatic toll booth
CN114906136A (en) Vehicle blind area pedestrian sensing and early warning method and system based on V2X
CN104268859A (en) Image preprocessing method for night lane line detection
JPH0830892A (en) Traffic monitoring system and automobile with car number recognition device
CN111627219B (en) Vehicle cooperation method for detecting curve driving information by using vehicle electronic identification

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20210709