CN111627219B - 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 PDFInfo
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- CN111627219B CN111627219B CN202010569306.4A CN202010569306A CN111627219B CN 111627219 B CN111627219 B CN 111627219B CN 202010569306 A CN202010569306 A CN 202010569306A CN 111627219 B CN111627219 B CN 111627219B
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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
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 predicts the algorithm according to the running speed of the vehicle in the curve, the algorithm of the position of the vehicle in the curve and the algorithm of the position of the vehicle in the curveVehicle separation algorithm calculation t0Time 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; 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.
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 }tThe T belongs to T, and T is the driving time of the automobile at the curve as the automobile speed data in the time TCollecting;
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;
TABLE 1
To be provided with
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:
a3, vehicle speed at t0At time in state n, t1The velocity transition probability for the time transition to state m is:
then t1The velocity transition matrix of time is:
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
The velocity recurrence formula of (c) is:
when k is 1, the initial vehicle speed is defined as
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
Obtaining time points by a detector
Starting to time to obtain the driving time of the t-hour automobile i
The current longitudinal driving position of the curve of the automobile i at the time point t can be predicted
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
The longitudinal position of the curve corresponding to the automobile j at the time point t is predicted as follows:
the front-rear vehicle distance is predicted as:
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
If the result of the calculation of the longitudinal position of the vehicle
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
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
Obtaining distance to preceding vehicle
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 belongs to T, and T is the running time of the automobile at the curve is an automobile speed data set within 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;
TABLE 1
To be provided with
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:
a3, vehicle speed at t0At time in state n, t1The velocity transition probability for the time transition to state m is:
then t1The velocity transition matrix of time is:
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
The velocity recurrence formula of (c) is:
when k is 1, the initial vehicle speed is defined as
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
Obtaining time points by a detector
Starting to time to obtain the driving time of the t-hour automobile i
The current longitudinal driving position of the curve of the automobile i at the time point t can be predicted
In this embodiment, the distance algorithm for the vehicle in the curve specifically includes the following steps:
the time when the current automobile j passes by can be obtained by the electronic identification detectorDot
The longitudinal position of the curve corresponding to the automobile j at the time point t is predicted as follows:
the front-rear vehicle distance is predicted as:
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
If the result of the calculation of the longitudinal position of the vehicle
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
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
Obtaining distance to preceding vehicle
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 (3)
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 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 position02Detection time t0The state information of other 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 laneL01The 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 vehicle information in the same curve area to the vehicle V according to the information cooperation method01；
S9, the control center predicts the automobile V01Position information, beyond the longitudinal length of the curve, ending the alignment of the vehicle V01Pushing information;
the vehicle running speed prediction algorithm specifically comprises the following steps:
a1, using the automobile random variable Vt: v0, V1, … and Vt, which form a vehicle speed data chain, wherein { Vt, T belongs to T, T is the driving time of the vehicle at the curve } is a vehicle speed data set in the time T;
a2, calculating the vehicle speed state transition probability:
because weather, illumination external environment influence, continuous speed transition probability matrix can change along with time, weather environment, and the speed change is 3 kinds of 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;
TABLE 1
To be provided with
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:
a3, vehicle speed at t0At time in state n, t1The velocity transition probability for the time transition to state m is:
then t1The velocity transition matrix of time is:
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
The velocity recurrence formula of (c) is:
when k is 1, the initial vehicle speed is defined as
The algorithm for the automobile position in the curve 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
Obtaining time points by a detector
Start timing, t time automobile i driving time
The current longitudinal driving position of the curve of the automobile i at the time point t can be predicted
The automobile distance algorithm in the curve specifically comprises the following steps:
the time point when the current automobile j passes by can be obtained by the electronic identification detector
The longitudinal position of the curve corresponding to the automobile j at the time point t is predicted as follows:
the front-rear vehicle distance is predicted as:
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
If the result of the calculation of the longitudinal position of the vehicle
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 vehicle is calculatedResults
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
Obtaining distance to preceding vehicle
2. The vehicle cooperation method for detecting curved driving information by using electronic automobile identification as claimed in claim 1, wherein the information pushed to the automobile V01 by the control center adopts text and map information, and the text information shows that the automobile V01The number of vehicles on the current driving route, the average running speed of the vehicles and the average vehicle distance information; the map information represents the automobile by adopting a 2D or 3D wire frame diagram, simultaneously dynamically marks the automobile on an automobile digital map in real time, and displays a 2D or 3D automobile line diagram, the average speed of the automobile and the distance information between the automobiles on the current lane.
3. A system for realizing a vehicle cooperation method for detecting curve driving information by using an automobile electronic identifier is characterized by comprising a detector and a control center, wherein the detector is an automobile electronic identifier detector, a plurality of detectors are uniformly arranged at an entrance of a curve, and the detectors are in wireless connection with the control center; the control center runs a vehicle running speed prediction algorithm, an in-curve vehicle position algorithm, an in-curve vehicle distance algorithm and an information cooperation method;
the vehicle running speed prediction algorithm specifically comprises the following steps:
a1, using the automobile random variable Vt: v0, V1, … and Vt, which form a vehicle speed data chain, wherein { Vt, T belongs to T, T is the driving time of the vehicle at the curve } is a vehicle speed data set in the time T;
a2, calculating the vehicle speed state transition probability:
because weather, illumination external environment influence, continuous speed transition probability matrix can change along with time, weather environment, and the speed change is 3 kinds of 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;
TABLE 1
To be provided with
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:
a3, vehicle speed at t0At time in state n, t1The velocity transition probability for the time transition to state m is:
then t1The velocity transition matrix of time is:
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
The velocity recurrence formula of (c) is:
when k is 1, the initial vehicle speed is defined as
The algorithm for the automobile position in the curve 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
Obtaining time points by a detector
Start timing, t time automobile i driving time
The current longitudinal driving position of the curve of the automobile i at the time point t can be predicted
The automobile distance algorithm in the curve specifically comprises the following steps:
the time point when the current automobile j passes by can be obtained by the electronic identification detector
The longitudinal position of the curve corresponding to the automobile j at the time point t is predicted as follows:
the front-rear vehicle distance is predicted as:
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
If the result of the calculation of the longitudinal position of the vehicle
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
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
Obtaining distance to preceding vehicle
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| AU2007224206A1 (en) * | 2006-03-03 | 2007-09-13 | Inrix, Inc. | 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 |
| US9142127B1 (en) * | 2014-04-29 | 2015-09-22 | 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 |
| CN111216731B (en) * | 2020-01-23 | 2021-04-30 | 上海丰豹商务咨询有限公司 | Active sensing system for cooperative automatic driving of vehicle and road |
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