CN111681430B - Method for predicting number of stop lines of signal lamp intersection in future in real time - Google Patents
Method for predicting number of stop lines of signal lamp intersection in future in real time Download PDFInfo
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- CN111681430B CN111681430B CN202010367909.6A CN202010367909A CN111681430B CN 111681430 B CN111681430 B CN 111681430B CN 202010367909 A CN202010367909 A CN 202010367909A CN 111681430 B CN111681430 B CN 111681430B
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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Abstract
The invention discloses a method for predicting the number of stop lines of a signal lamp intersection in real time when a future motor vehicle arrives, which comprises the following steps: acquiring first running information of a target motor vehicle in a prediction road section range, target information of the target motor vehicle to a prediction point and position information of the prediction point, wherein the target information comprises the number of motor vehicles included between any target motor vehicle and the prediction point and signal lamp information of an upstream intersection of the prediction point; determining the time of each target motor vehicle reaching the prediction point according to the first running information, the target information and the position information of the prediction point; and determining the number of the motor vehicles reaching the prediction point at the prediction time according to the time of each target motor vehicle reaching the prediction point. The method determines the time of each target motor vehicle reaching the predicted point in the preset road section range in real time according to the running information and the position information of the predicted point of the target motor vehicles, and predicts the number of the motor vehicles according to the time of each target motor vehicle reaching the predicted point so as to control signal lamps in time.
Description
Technical Field
The invention relates to the field of intelligent traffic, in particular to a method for predicting the number of stop lines of a signal lamp intersection when a future motor vehicle arrives in real time.
Background
In a road network of an area, an intersection is a key node for restricting the traffic efficiency of the road network, and signal lamp control is the guarantee of the safety and the smoothness of the intersection. In order to improve the motor vehicle passing efficiency of the signal lamp control intersection, the signal lamp control performance is continuously improved by various means so as to meet the requirements of people on safety and rapid passing. Therefore, it is urgently needed to provide a method for predicting the number of stop lines of a signal lamp intersection when a future motor vehicle arrives in real time so as to predict the number of motor vehicles at the intersection and control the signal lamp in time.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the defects that in the prior art, the time for the motor vehicle to reach the predicted point is calculated inaccurately according to the time for the video tracking device to obtain the motor vehicle position, and the accuracy of the motor vehicle number prediction is influenced, because the video tracking device obtains the motor vehicle position, so that the method for predicting the number of the motor vehicles reaching the stop line of the signal lamp intersection in real time is provided.
According to a first aspect, the invention discloses a method for predicting the number of stop lines of a signal lamp intersection for future motor vehicles in real time, which comprises the following steps: acquiring first running information of a target motor vehicle in a prediction road section range, target information of the target motor vehicle to a prediction point and position information of the prediction point, wherein the target information comprises the number of motor vehicles included between any target motor vehicle and the prediction point and signal lamp information of an upstream intersection of the prediction point; determining the time of each target motor vehicle reaching the prediction point according to the first running information, the target information and the position information of the prediction point; and determining the number of the motor vehicles reaching the prediction point at the prediction time according to the time of each target motor vehicle reaching the prediction point.
With reference to the first aspect, in a first embodiment of the first aspect, the acquiring first driving information of a target vehicle within a predicted road segment includes: continuously tracking and detecting first driving information of a target motor vehicle in a predicted road section range by utilizing a plurality of video tracking devices, wherein the plurality of video tracking devices are sequentially arranged in the predicted road section range and are used for continuously tracking and detecting the motor vehicle information in a detection interval; acquiring first driving information detected by any two adjacent video tracking devices; when the first travel information of any two adjacent video tracking devices contains the same information, clearing the same information in any one of the two adjacent video tracking devices.
With reference to the first aspect, in a second embodiment of the first aspect, the target information is that the number of vehicles from the target vehicle to the predicted point is zero and no signal lamp is included, or the number of vehicles from the target vehicle to the predicted point is zero and the signal lamp information is in a traffic state; determining the time of each target motor vehicle reaching the predicted point according to the first driving information, the target information and the position information of the predicted point, comprising: obtaining a first distance between the target motor vehicle and the prediction point according to first position information in the first running information of the target motor vehicle and the position information of the prediction point; and determining the time when the target motor vehicle reaches the predicted point according to the first distance and the first speed information in the first running information of the target motor vehicle.
With reference to the first aspect, in a third implementation manner of the first aspect, the target information is that the number of vehicles from the target vehicle to the predicted point is not zero and does not include a signal lamp, or the number of vehicles from the target vehicle to the predicted point is not zero and the signal lamp information is in a traffic state; determining the time of each target motor vehicle reaching the predicted point according to the first driving information, the target information and the position information of the predicted point, comprising: acquiring second position information of a front motor vehicle adjacent to the target motor vehicle and first time when the front motor vehicle reaches a predicted point; determining a second distance between the target motor vehicle and an adjacent front motor vehicle according to the second position information and first position information in the first running information of the target motor vehicle; determining a second time when the target motor vehicle reaches the position of the front motor vehicle according to the second distance and the first speed information in the first running information; and determining the time when the target motor vehicle reaches the predicted point according to the first time and the second time.
With reference to the first aspect, in a fourth embodiment of the first aspect, the target information indicates that the number of vehicles from the target vehicle to the predicted point is zero and the signal light information indicates a no-pass state; determining the time of each target motor vehicle reaching the predicted point according to the first driving information, the target information and the position information of the predicted point, comprising: obtaining a first distance between the target motor vehicle and the prediction point according to first position information in the first running information of the target motor vehicle and the position information of the prediction point; obtaining a third time when the target motor vehicle reaches the predicted point according to the first distance and first speed information in the first running information of the target motor vehicle; acquiring the no-passing time of a signal lamp; and determining the time when the target motor vehicle reaches the predicted point according to the third time and the no-pass time.
With reference to the first aspect, in a fifth embodiment of the first aspect, the target information is that the number of vehicles between the target vehicle and the predicted point is not zero and the signal light information is in a no-pass state; determining the time of each target motor vehicle reaching the predicted point according to the first driving information, the target information and the position information of the predicted point, comprising: acquiring second position information of a front motor vehicle adjacent to the target motor vehicle and first time when the front motor vehicle reaches a predicted point; determining a second distance between the target motor vehicle and an adjacent front motor vehicle according to the second position information and first position information in the first running information of the target motor vehicle; obtaining a second time when the target motor vehicle reaches the position of the front motor vehicle according to the second distance and the first speed information in the first running information; acquiring the no-passing time of a signal lamp; and determining the time when the target motor vehicle reaches the predicted point according to the first time, the second time and the no-pass time.
With reference to the first aspect or any embodiment of the first aspect, in a sixth embodiment of the first aspect, the method further comprises: acquiring the actual number of motor vehicles with the predicted time reaching the predicted point; and obtaining the prediction precision of the number of the motor vehicles according to the number of the predicted motor vehicles and the actual number of the motor vehicles.
With reference to the first embodiment of the first aspect, in a seventh embodiment of the first aspect, the method further includes: and visually displaying the information detected by the video tracking detection equipment.
According to a second aspect, the embodiment of the invention also discloses a device for predicting the number of stop lines of a signal lamp intersection for future motor vehicles in real time, which comprises: the system comprises an acquisition module, a prediction module and a prediction module, wherein the acquisition module is used for acquiring first running information of a target motor vehicle in a prediction road section range, target information of the target motor vehicle to a prediction point and position information of the prediction point, and the target information comprises the number of motor vehicles included between any target motor vehicle and the prediction point and upstream signal lamp information of an intersection of the prediction point; the first determining module is used for determining the time of each target motor vehicle reaching the predicted point according to the first running information, the target information and the position information of the predicted point; and the second determining module is used for determining the number of the motor vehicles reaching the predicted point at the predicted time according to the time of each target motor vehicle reaching the predicted point.
According to a third aspect, an embodiment of the present invention further discloses a computer device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the steps of the method for predicting in real time the number of future vehicles arriving at a signal intersection stop line as described in the first aspect or any of the embodiments of the first aspect.
The technical scheme of the invention has the following advantages:
the invention provides a method and a device for predicting the number of stop lines of a signal lamp intersection for future motor vehicles to arrive in real time, which are used for acquiring first running information of a target motor vehicle in a predicted road section range, target information of the target motor vehicle to a predicted point and position information of the predicted point, determining the time of each target motor vehicle to reach the predicted point according to the first running information, the target information and the position information of the predicted point, and determining the number of motor vehicles to reach the predicted point at the predicted time according to the time of each target motor vehicle to reach the predicted point. By implementing the method, the time of each target motor vehicle reaching the prediction point in the preset road section range is determined in real time according to the running information and the position information of the prediction point of the target motor vehicle, and the number of the motor vehicles is predicted according to the time of each target motor vehicle reaching the prediction point, so that the signal lamp can be controlled in time.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a diagram illustrating an exemplary deployment and detection range of a detection device according to an embodiment of the present invention;
FIG. 2 is a flowchart of a specific example of a method for predicting the number of stop lines of a signal light intersection in real time when a future vehicle arrives in embodiment 1 of the present invention;
FIG. 3 is a diagram illustrating an exemplary embodiment of the detection of the same vehicle information;
FIG. 4 is a diagram illustrating an exemplary embodiment of a prediction of the number of vehicles at a traffic light of an intersection in accordance with the present invention;
FIG. 5 is a schematic block diagram of a specific example of an apparatus for predicting the number of stop lines of a signal light intersection in real time in future vehicles according to embodiment 2 of the present invention;
fig. 6 is a schematic block diagram of a specific example of a computer device in embodiment 3 of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
In the embodiment of the invention, a plurality of detection devices can be arranged in the predicted link range, as shown in fig. 1, J1 and J2 … Jn are both detection devices, Yw represents the position of the predicted point, J1-0 to J1-1 are detection ranges of the detection devices J1, J2-0 to J2-1 are detection ranges of the detection devices J2, and so on, and a detection range of Jn is obtained. The system comprises a data processing module, a signal lamp information acquisition module, a data processing module and a traffic light prediction module, wherein the data processing module is used for receiving the detection information and the signal lamp information of each intersection and acquiring the traffic information of the target motor vehicles, the detection equipment is used for detecting the running information of the target motor vehicles in real time, transmitting the running information detected by the detection equipment and the signal lamp information of each intersection to the data processing module in real time and displaying the running information and the signal lamp information of each intersection on an electronic map, the data processing module is used for calculating the time of each target motor vehicle reaching a prediction point in real time according to the received detection information and the signal lamp information, and the number of the motor vehicles reaching the prediction point at a certain time point or a time period in the future can be predicted according to the time of each target motor vehicle reaching the prediction point, so that the signal lamp can be timely controlled to improve the traffic efficiency of the intersections.
Example 1
The embodiment provides a method for predicting the number of stop lines of a signal lamp intersection in real time when a future motor vehicle arrives, as shown in fig. 1, comprising the following steps:
step S11: the method comprises the steps of obtaining first running information of a target motor vehicle in a predicted road section range, target information of the target motor vehicle to a predicted point and position information of the predicted point, wherein the target information comprises the number of motor vehicles included between any target motor vehicle and the predicted point and signal lamp information of an upstream intersection of the predicted point.
For example, the first driving information may include speed information and position information of the target vehicle; the predicted road section range can be an important traffic road section in a city and can also be a road section which is easy to be jammed at peak time. The predicted point can be any position at the upstream of the intersection signal lamp on the predicted road section range, the predicted point is not limited by the embodiment of the invention, and the predicted point can be set by a person skilled in the art according to the actual situation. The position information of the target motor vehicle and the position information of the predicted point can be acquired in real time through video tracking equipment in the detection equipment; the speed information can be obtained by real-time detection of a speed detector integrated in the detection device, and can also be sent to the data processing module by the target motor vehicle in real time. The intersection signal light information can be transmitted to the data processing module by the signal light control system in a wired or wireless mode in real time.
Step S12: and determining the time of each target motor vehicle reaching the prediction point according to the first running information, the target information and the position information of the prediction point.
For example, since the target information includes the number of vehicles included between any one target vehicle and the predicted point and the signal light information of the upstream intersection of the predicted point, the time for each target vehicle to reach the predicted point may be determined by different methods according to the difference between the acquired target information. For example, the time of the target vehicle reaching the predicted point can be determined by the distance between the target vehicle and the predicted point, and the time of each target vehicle reaching the predicted point can be determined by combining the signal lamp setting information (such as whether the signal lamp is included and the current display state of the signal lamp) between the target vehicle and the predicted point.
Step S13: and determining the number of the motor vehicles reaching the prediction point at the prediction time according to the time of each target motor vehicle reaching the prediction point.
The predicted time may be any time point in the future or any time period in the future, and the predicted time is not limited in the embodiment of the present invention and may be set according to actual situations.
Taking the prediction point as the intersection signal lamp position in the prediction road section range as an example, the prediction time can be a time section or a time point at which congestion is easy to occur in one or more time sections of an early peak and/or a late peak, the time of the signal lamp can be flexibly controlled by predicting the time of the target motor vehicle reaching the signal lamp in real time, for example, when the number of motor vehicles reaching the prediction point is large in a certain time, the no-passing time of the signal lamp can be shortened, or the passing time of the signal lamp can be prolonged, and the control performance of the signal lamp can be improved.
The invention provides a method for predicting the number of stop lines of a signal lamp intersection for future motor vehicles to arrive in real time, which is used for acquiring first running information of a target motor vehicle in a predicted road section range, target information of the target motor vehicle to a predicted point and position information of the predicted point, determining the time of each target motor vehicle to arrive at the predicted point according to the first running information, the target information and the position information of the predicted point, and determining the number of motor vehicles to arrive at the predicted point at the predicted time according to the time of each target motor vehicle to arrive at the predicted point. By implementing the method, the time of each target motor vehicle reaching the prediction point in the preset road section range is determined in real time according to the running information and the position information of the prediction point of the target motor vehicle, and the number of the motor vehicles is predicted according to the time of each target motor vehicle reaching the prediction point, so that the signal lamp can be controlled in time.
As an alternative embodiment of the present invention, the first driving information of the target vehicle within the predicted road section range is continuously tracked and detected by using a video tracking device of a plurality of detection devices, the plurality of video tracking devices being sequentially arranged within the predicted road section range for continuously tracking and detecting the vehicle information within the detection section, and the step S11 includes:
first driving information detected by any two adjacent video tracking devices is acquired.
Illustratively, in the embodiment of the present invention, any two adjacent video tracking devices detect the first driving information of the target vehicle in the corresponding detection ranges, the detection ranges of the two adjacent video tracking devices have an overlapping portion, which results in that the first driving information obtained by any two adjacent video tracking devices has the same portion, for example, as shown in fig. 3, Jg1 and Jg2 are 2 video tracking devices, Jg1-0 to Jg1-1 are the detection ranges of the video tracking devices Jg1, Jg2-0 to Jg2-1 are the detection ranges of the video tracking devices Jg2, Jg2-0 to Jg1-1 are the overlapping portions of the detection ranges of the video tracking devices Jg1 and Jg2, and the video tracking devices Jg1 and Jg2 detect the vehicle data information of their corresponding detection ranges in real time.
When the first travel information of any two adjacent video tracking devices contains the same information, the same information is cleared in any one of the two adjacent video tracking devices.
Illustratively, when the video tracking devices Jg1 and Jg2 detect the vehicle data information in their corresponding detection ranges in real time, when the first driving information detected by the first video tracking device Jg1 is the same as the first driving information detected by the second video tracking device Jg2 (i.e. the number of vehicles in the range of Jg2-0 to Jg1-1 is not zero), the same vehicle data in the video tracking device Jg1 or the video tracking device Jg2 can be eliminated, the time of repeatedly calculating the same target vehicle to the predicted point is avoided, and the calculation amount of the data processing module is reduced.
The judgment of whether the same motor vehicle data exist in the adjacent video tracking devices can be carried out according to the comparison of the license plate of the target motor vehicle, and also can be carried out according to the color, the type, the driver and the like of the target motor vehicle.
As an alternative embodiment of the present invention, when the target information is that the number of vehicles between the target vehicle and the predicted point is zero and no traffic light is included, for example, the vehicle Jwd1 shown in fig. 4, or the number of vehicles between the target vehicle and the predicted point is zero and the traffic light information is in a traffic state, for example, the vehicle Jwd4 shown in fig. 4, the step S12 includes:
and obtaining a first distance between the target motor vehicle and the prediction point according to the first position information in the first running information of the target motor vehicle and the position information of the prediction point.
For example, in the embodiment of the present invention, the predicted link range may be regarded as one coordinate axis, the first distance between the target vehicle and the predicted point may be obtained by using a difference between the position information of the target vehicle and the position information of the predicted point, and in order to simplify obtaining the position information of the target vehicle and the position information of the predicted point, the position information of the predicted point may be used as an origin, an upstream direction of the predicted point may be used as a forward direction, and only the position information of the target vehicle is detected, where the position information of the target vehicle is the first distance in the embodiment of the present invention.
And determining the time when the target motor vehicle reaches the predicted point according to the first distance and the first speed information in the first running information of the target motor vehicle.
For example, when the target information indicates that the number of vehicles between the target vehicle and the predicted point is zero and no signal lamp is included, or the number of vehicles between the target vehicle and the predicted point is zero and the signal lamp information is in a traffic state, the time for determining that the target vehicle reaches the predicted point according to the first distance and the first speed information in the first travel information of the target vehicle may be specifically:
JDt1＝Lwd/Jsd，
where JDt1 represents the time from the target vehicle Jwd1 to the predicted point Yw, Lwd represents the first distance from the target vehicle Jwd1 to the predicted point Yw, and Jsd represents the first speed information of the target vehicle Jwd 1.
As an alternative embodiment of the present invention, when the target information is that the number of vehicles between the target vehicle and the predicted point is not zero and does not include a traffic light, for example, the vehicle Jwd2 of fig. 4, or the number of vehicles between the target vehicle and the predicted point is not zero and the traffic light information is in a traffic state, for example, the vehicle Jwd3 of fig. 4, the step S12 includes:
second position information of a preceding vehicle adjacent to the target vehicle and a first time at which the preceding vehicle reaches the predicted point are acquired.
For example, in the embodiment of the present invention, the first time when the front vehicle reaches the predicted point may be calculated in real time by the data processing module; the specific manner of acquiring the second position information of the front vehicle adjacent to the target vehicle is described in the above step S11, and will not be described herein again.
Determining a second distance between the target motor vehicle and an adjacent front motor vehicle according to the second position information and the first position information in the first running information of the target motor vehicle; the specific determination method is described in the above related description of the first distance determining step, and is not described herein again.
Determining second time when the target motor vehicle reaches the position of the front motor vehicle according to the second distance and the first speed information in the first running information; the specific determination method refers to the above description of the step of determining the time for the target vehicle to reach the predicted point, and is not described herein again.
And determining the time when the target motor vehicle reaches the predicted point according to the first time and the second time.
As an example, determining the time at which the target vehicle reaches the predicted point based on the first time and the second time may specifically be:
JDt2＝JDt+JDtq，
where JDt2 denotes a time from the target vehicle Jwd2 to the predicted point Yw, JDtq denotes a first time at which the preceding vehicle Jwd2 adjacent to the target vehicle reaches the predicted point Yw, and JDt denotes a second time at which the target vehicle Jwd2 reaches the position of the preceding vehicle.
As an alternative embodiment of the present invention, when the target information is that the number of vehicles between the target vehicle and the predicted point is zero and the traffic light information is in the no-pass state, for example, Jwd4 shown in fig. 4, step S12 includes:
obtaining a first distance between the target motor vehicle and the prediction point according to first position information in the first running information of the target motor vehicle and position information of the prediction point; the specific determination method is described in the above related description of the first distance determining step, and is not described herein again.
Obtaining a third time when the target motor vehicle reaches the predicted point according to the first distance and the first speed information in the first running information of the target motor vehicle; the specific determination method refers to the above description of the step of determining the time for the target vehicle to reach the predicted point, and is not described herein again.
Acquiring the no-passing time of a signal lamp; the traffic prohibition time of the signal lamp can be transmitted to the data processing module by the signal lamp control system in a wired or wireless manner in real time.
And determining the time when the target motor vehicle reaches the predicted point according to the third time and the no-pass time. The specific determination method refers to the above description of the step of determining the time when the target vehicle reaches the predicted point according to the first time and the second time, which is not described herein again.
As an alternative embodiment of the present invention, when the target information is that the number of vehicles between the target vehicle and the predicted point is not zero and the traffic light information is in the no-pass state, for example, Jwd3 shown in fig. 4, the step S12 includes:
acquiring second position information of a front motor vehicle adjacent to the target motor vehicle and first time when the front motor vehicle reaches the prediction point; the detailed description of the steps above is omitted here for brevity.
Determining a second distance between the target motor vehicle and an adjacent front motor vehicle according to the second position information and the first position information in the first running information of the target motor vehicle; the detailed description of the steps above is omitted here for brevity.
Obtaining second time when the target motor vehicle reaches the position of the front motor vehicle according to the second distance and the first speed information in the first running information; the detailed description of the steps above is omitted here for brevity.
Acquiring the no-passing time of a signal lamp; the specific determination method is described in the above related steps, and is not described in detail here.
And determining the time of the target motor vehicle reaching the predicted point according to the first time, the second time and the no-pass time, and adding the first time, the second time and the no-pass time to obtain the time of the target motor vehicle reaching the predicted point.
As an optional embodiment of the present invention, the method for predicting the number of stop lines of a signal light intersection in real time for a future motor vehicle further comprises:
and acquiring the actual number of motor vehicles of which the predicted time reaches the predicted point.
For example, in the implementation of the present invention, the actual number of motor vehicles reaching the predicted point is obtained at the predicted time, the actual number of motor vehicles may be obtained by obtaining the position information of the target motor vehicle according to the video tracking device, and the specific manner of obtaining the position information of the target motor vehicle, which is described in step S11, for how many motor vehicles are obtained at the predicted time is referred to, and is not described herein again.
And obtaining the precision of predicting the number of the future motor vehicles reaching the stop line of the signal lamp intersection in real time according to the predicted number of the motor vehicles and the actual number of the motor vehicles.
Illustratively, in the embodiment of the present invention, the accuracy of predicting the number of future vehicles reaching the stop line of the signal light intersection in real time according to the predicted number of vehicles and the actual number of vehicles may be:
Yj＝(Yt-St)/St，
where Yj denotes the prediction accuracy, Yt denotes the number of predicted vehicles, and St denotes the number of actual vehicles.
As an optional embodiment of the present invention, the method for predicting the number of stop lines of a signal light intersection in real time for a future motor vehicle further comprises: and visually displaying the information detected by the video tracking detection equipment.
Illustratively, the information may include location information of the target motor vehicle, location information of the predicted point, a predicted link range length, signal light status information, and the like. The information detected by the video tracking detection equipment is displayed on the electronic map in real time, so that the accuracy of the information obtained by video tracking can be verified in real time through the display data and the field data of the electronic map, and the detection precision is improved.
Example 2
The embodiment of the invention provides a device for predicting the number of stop lines of a signal lamp intersection in real time when a future motor vehicle arrives, as shown in figure 5, comprising:
the acquisition module 21 is configured to acquire first driving information of a target vehicle in a predicted road section range, target information from the target vehicle to a predicted point, and position information of the predicted point, where the target information includes the number of vehicles included between any target vehicle and the predicted point and signal light information of an upstream intersection of the predicted point; the specific implementation manner is described in relation to step S11 in embodiment 1, and is not described herein again.
The first determining module 22 is configured to determine, according to the first driving information, the target information, and the position information of the predicted point, a time when each target motor vehicle reaches the predicted point; the specific implementation manner is described in relation to step S12 in embodiment 1, and is not described herein again.
And a second determining module 23, configured to determine, according to the time when each target vehicle reaches the predicted point, the number of vehicles reaching the predicted point at the predicted time. The specific implementation manner is described in relation to step S13 in embodiment 1, and is not described herein again.
The device for predicting the number of stop lines of a signal lamp intersection when the future motor vehicles arrive in real time acquires first running information of target motor vehicles in a predicted road section range, target information of the target motor vehicles to a predicted point and position information of the predicted point, determines the time of each target motor vehicle reaching the predicted point according to the first running information, the target information and the position information of the predicted point, and determines the number of motor vehicles reaching the predicted point at the predicted time according to the time of each target motor vehicle reaching the predicted point. By implementing the method, the time of each target motor vehicle reaching the prediction point in the preset road section range is determined in real time according to the running information and the position information of the prediction point of the target motor vehicle, and the number of the motor vehicles is predicted according to the time of each target motor vehicle reaching the prediction point, so that the signal lamp can be controlled in time.
As an optional embodiment of the present invention, the first driving information of the target vehicle in the predicted road section range is continuously tracked and detected by using a plurality of video tracking devices, the plurality of video tracking devices are sequentially arranged in the predicted road section range and are used for continuously tracking and detecting the vehicle information in the detection interval, and the obtaining module 21 includes:
the first acquisition submodule is used for acquiring first driving information detected by any two adjacent video tracking devices; the specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
And the clearing module is used for clearing the same information in any one of the two adjacent video tracking devices when the first driving information of any two adjacent video tracking devices contains the same information. The specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
As an optional embodiment of the present invention, the first determining module 22 includes:
the first distance obtaining module is used for obtaining a first distance between the target motor vehicle and the prediction point according to first position information in the first running information of the target motor vehicle and position information of the prediction point; the specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
And the first determining submodule is used for determining the time when the target motor vehicle reaches the predicted point according to the first distance and the first speed information in the first running information of the target motor vehicle. The specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
As an optional embodiment of the present invention, the first determining module 22 includes:
the second obtaining submodule is used for obtaining second position information of a front motor vehicle adjacent to the target motor vehicle and first time when the front motor vehicle reaches the prediction point; the specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
The second distance determination submodule is used for determining a second distance between the target motor vehicle and the adjacent front motor vehicle according to the second position information and the first position information in the first running information of the target motor vehicle; the specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
The second time determination submodule is used for determining second time when the target motor vehicle reaches the position of the front motor vehicle according to the second distance and the first speed information in the first running information; the specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
And the second determining submodule is used for determining the time when the target motor vehicle reaches the predicted point according to the first time and the second time. The specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
As an optional embodiment of the present invention, the first determining module 22 includes:
the third obtaining submodule is used for obtaining a first distance between the target motor vehicle and the prediction point according to the first position information in the first running information of the target motor vehicle and the position information of the prediction point; the specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
The third time obtaining submodule is used for obtaining third time when the target motor vehicle reaches the predicted point according to the first distance and the first speed information in the first running information of the target motor vehicle; the specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
The traffic prohibition time acquisition module is used for acquiring the traffic prohibition time of the signal lamp; the specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
And the third determining submodule is used for determining the time when the target motor vehicle reaches the predicted point according to the third time and the no-passing time. The specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
As an optional embodiment of the present invention, the first determining module 22 includes:
the fourth obtaining submodule is used for obtaining second position information of a front motor vehicle adjacent to the target motor vehicle and first time when the front motor vehicle reaches the prediction point; the specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
The second distance determination submodule is used for determining a second distance between the target motor vehicle and the adjacent front motor vehicle according to the second position information and the first position information in the first running information of the target motor vehicle; the specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
The second time determination submodule is used for obtaining second time when the target motor vehicle reaches the position of the front motor vehicle according to the second distance and the first speed information in the first running information; the specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
The traffic prohibition time acquisition module is used for acquiring the traffic prohibition time of the signal lamp; the specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
And the fourth determining submodule is used for determining the time when the target motor vehicle reaches the predicted point according to the first time, the second time and the no-pass time. The specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
As an optional embodiment of the present invention, the apparatus for predicting the number of stop lines of a signal light intersection in real time for a future vehicle further comprises:
and the actual number of motor vehicles acquiring module is used for acquiring the actual number of motor vehicles of which the predicted time reaches the predicted point. The specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
And the prediction precision obtaining module is used for obtaining the prediction precision of the number of the motor vehicles according to the number of the predicted motor vehicles and the actual number of the motor vehicles. The specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
As an optional embodiment of the present invention, the apparatus for predicting the number of stop lines of a signal light intersection in real time for a future vehicle further comprises:
and the display module is used for visually displaying the information detected by the video tracking detection equipment. The specific implementation manner is described in association with corresponding steps in embodiment 1, and is not described herein again.
Example 3
An embodiment of the present invention further provides a computer device, as shown in fig. 6, the computer device may include a processor 31 and a memory 32, where the processor 31 and the memory 32 may be connected by a bus or in another manner, and fig. 6 illustrates an example of a connection by a bus.
The processor 31 may be a Central Processing Unit (CPU). The Processor 31 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or combinations thereof.
The memory 32 is a non-transitory computer readable storage medium, and can be used for storing non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the method for predicting the number of future vehicles reaching the stop line of the signal intersection in real time in the embodiment of the present invention (for example, the obtaining module 21, the first determining module 22, and the second determining module 23 shown in fig. 5). The processor 31 executes various functional applications and data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory 32, namely, the method for predicting the number of future vehicles reaching the stop line of the signal light intersection in real time in the above method embodiment is realized.
The memory 32 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created by the processor 31, and the like. Further, the memory 32 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 32 may optionally include memory located remotely from the processor 31, and these remote memories may be connected to the processor 31 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory 32 and, when executed by the processor 31, perform a method for predicting the number of future vehicles arriving at a signal intersection stop line in real time as in the embodiment of fig. 2.
The details of the computer device can be understood by referring to the corresponding related description and effects in the embodiment shown in fig. 2, and are not described herein again.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.
Claims (3)
1. A method for predicting the number of stop lines of a signal lamp intersection for future motor vehicles in real time is characterized by comprising the following steps:
acquiring first running information of a target motor vehicle in a prediction road section range, target information of the target motor vehicle to a prediction point and position information of the prediction point, wherein the target information comprises the number of motor vehicles included between any target motor vehicle and the prediction point and signal lamp information of an upstream intersection of the prediction point;
determining the time of each target motor vehicle reaching the prediction point according to the first running information, the target information and the position information of the prediction point;
determining the number of motor vehicles reaching the prediction point at the prediction time according to the time of each target motor vehicle reaching the prediction point;
the acquiring of the first driving information of the target motor vehicle within the predicted road section range comprises:
continuously tracking and detecting first driving information of a target motor vehicle in a predicted road section range by utilizing a plurality of video tracking devices, wherein the plurality of video tracking devices are sequentially arranged in the predicted road section range and are used for continuously tracking and detecting the motor vehicle information in a detection interval;
acquiring first driving information detected by any two adjacent video tracking devices;
when the first travel information of any two adjacent video tracking devices contains the same information, clearing the same information in any one of the two adjacent video tracking devices; judging whether the first running information of any two adjacent video tracking devices contains the same information or not according to the license plate, the color and the type of the target motor vehicle and comparison of a driver to the target motor vehicle in any two adjacent video tracking devices;
when the target information is that the number of motor vehicles between the target motor vehicle and the prediction point is zero and no signal lamp is included, or the number of motor vehicles between the target motor vehicle and the prediction point is zero and the signal lamp information is in a traffic state, determining the time of each target motor vehicle reaching the prediction point according to the first running information, the target information and the position information of the prediction point, and the method comprises the following steps: obtaining a first distance between the target motor vehicle and the prediction point according to first position information in the first running information of the target motor vehicle and the position information of the prediction point; determining the time when the target motor vehicle reaches the predicted point according to the first distance and first speed information in the first running information of the target motor vehicle;
when the target information indicates that the number of motor vehicles between the target motor vehicle and the prediction point is not zero and does not include a signal lamp, or the number of motor vehicles between the target motor vehicle and the prediction point is not zero and the signal lamp information is in a traffic state, determining the time for each target motor vehicle to reach the prediction point according to the first running information, the target information and the position information of the prediction point, and the method comprises the following steps: acquiring second position information of a front motor vehicle adjacent to the target motor vehicle and first time when the front motor vehicle reaches a predicted point; determining a second distance between the target motor vehicle and an adjacent front motor vehicle according to the second position information and first position information in the first running information of the target motor vehicle; determining a second time when the target motor vehicle reaches the position of the front motor vehicle according to the second distance and the first speed information in the first running information; determining the time when the target motor vehicle reaches the predicted point according to the first time and the second time;
when the target information indicates that the number of the motor vehicles between the target motor vehicle and the prediction point is zero and the signal lamp information is in a no-pass state, determining the time of each target motor vehicle reaching the prediction point according to the first running information, the target information and the position information of the prediction point, wherein the method comprises the following steps: obtaining a first distance between the target motor vehicle and the prediction point according to first position information in the first running information of the target motor vehicle and the position information of the prediction point; obtaining a third time when the target motor vehicle reaches the predicted point according to the first distance and first speed information in the first running information of the target motor vehicle; acquiring the no-passing time of a signal lamp; determining the time when the target motor vehicle reaches the predicted point according to the third time and the no-pass time;
when the target information is that the number of motor vehicles between the target motor vehicle and the prediction point is not zero and the signal lamp information is in a no-pass state, determining the time of each target motor vehicle reaching the prediction point according to the first running information, the target information and the position information of the prediction point, and the method comprises the following steps: acquiring second position information of a front motor vehicle adjacent to the target motor vehicle and first time when the front motor vehicle reaches a predicted point; determining a second distance between the target motor vehicle and an adjacent front motor vehicle according to the second position information and first position information in the first running information of the target motor vehicle; obtaining a second time when the target motor vehicle reaches the position of the front motor vehicle according to the second distance and the first speed information in the first running information; acquiring the no-passing time of a signal lamp; determining the time when the target motor vehicle reaches the predicted point according to the first time, the second time and the no-pass time;
the method for predicting the number of stop lines of a signal lamp intersection for future motor vehicles in real time further comprises the following steps:
acquiring the actual number of motor vehicles with the predicted time reaching the predicted point;
obtaining the prediction precision of the number of motor vehicles according to the number of the predicted motor vehicles and the actual number of the motor vehicles;
the method for predicting the number of stop lines of a signal lamp intersection for future motor vehicles in real time further comprises the following steps: and visually displaying the information detected by the video tracking detection equipment.
2. A device for predicting the number of stop lines of a signal lamp intersection for future motor vehicles in real time is characterized by comprising the following components:
the system comprises an acquisition module, a prediction module and a prediction module, wherein the acquisition module is used for acquiring first running information of a target motor vehicle in a prediction road section range, target information of the target motor vehicle to a prediction point and position information of the prediction point, and the target information comprises the number of motor vehicles included between any target motor vehicle and the prediction point and upstream signal lamp information of an intersection of the prediction point;
the first determining module is used for determining the time of each target motor vehicle reaching the predicted point according to the first running information, the target information and the position information of the predicted point;
the second determining module is used for determining the number of the motor vehicles reaching the prediction point at the prediction time according to the time of each target motor vehicle reaching the prediction point;
the acquiring of the first driving information of the target motor vehicle within the predicted road section range comprises:
continuously tracking and detecting first driving information of a target motor vehicle in a predicted road section range by utilizing a plurality of video tracking devices, wherein the plurality of video tracking devices are sequentially arranged in the predicted road section range and are used for continuously tracking and detecting the motor vehicle information in a detection interval;
acquiring first driving information detected by any two adjacent video tracking devices;
when the first travel information of any two adjacent video tracking devices contains the same information, clearing the same information in any one of the two adjacent video tracking devices; judging whether the first running information of any two adjacent video tracking devices contains the same information or not according to the license plate, the color and the type of the target motor vehicle and comparison of a driver to the target motor vehicle in any two adjacent video tracking devices;
when the target information is that the number of motor vehicles between the target motor vehicle and the prediction point is zero and no signal lamp is included, or the number of motor vehicles between the target motor vehicle and the prediction point is zero and the signal lamp information is in a traffic state, determining the time of each target motor vehicle reaching the prediction point according to the first running information, the target information and the position information of the prediction point, and the method comprises the following steps: obtaining a first distance between the target motor vehicle and the prediction point according to first position information in the first running information of the target motor vehicle and the position information of the prediction point; determining the time when the target motor vehicle reaches the predicted point according to the first distance and first speed information in the first running information of the target motor vehicle;
when the target information indicates that the number of motor vehicles between the target motor vehicle and the prediction point is not zero and does not include a signal lamp, or the number of motor vehicles between the target motor vehicle and the prediction point is not zero and the signal lamp information is in a traffic state, determining the time for each target motor vehicle to reach the prediction point according to the first running information, the target information and the position information of the prediction point, and the method comprises the following steps: acquiring second position information of a front motor vehicle adjacent to the target motor vehicle and first time when the front motor vehicle reaches a predicted point; determining a second distance between the target motor vehicle and an adjacent front motor vehicle according to the second position information and first position information in the first running information of the target motor vehicle; determining a second time when the target motor vehicle reaches the position of the front motor vehicle according to the second distance and the first speed information in the first running information; determining the time when the target motor vehicle reaches the predicted point according to the first time and the second time;
when the target information indicates that the number of the motor vehicles between the target motor vehicle and the prediction point is zero and the signal lamp information is in a no-pass state, determining the time of each target motor vehicle reaching the prediction point according to the first running information, the target information and the position information of the prediction point, wherein the method comprises the following steps: obtaining a first distance between the target motor vehicle and the prediction point according to first position information in the first running information of the target motor vehicle and the position information of the prediction point; obtaining a third time when the target motor vehicle reaches the predicted point according to the first distance and first speed information in the first running information of the target motor vehicle; acquiring the no-passing time of a signal lamp; determining the time when the target motor vehicle reaches the predicted point according to the third time and the no-pass time;
when the target information is that the number of motor vehicles between the target motor vehicle and the prediction point is not zero and the signal lamp information is in a no-pass state, determining the time of each target motor vehicle reaching the prediction point according to the first running information, the target information and the position information of the prediction point, and the method comprises the following steps: acquiring second position information of a front motor vehicle adjacent to the target motor vehicle and first time when the front motor vehicle reaches a predicted point; determining a second distance between the target motor vehicle and an adjacent front motor vehicle according to the second position information and first position information in the first running information of the target motor vehicle; obtaining a second time when the target motor vehicle reaches the position of the front motor vehicle according to the second distance and the first speed information in the first running information; acquiring the no-passing time of a signal lamp; determining the time when the target motor vehicle reaches the predicted point according to the first time, the second time and the no-pass time;
the device for predicting the number of stop lines of the future motor vehicles reaching the signal lamp intersection in real time is also used for:
acquiring the actual number of motor vehicles with the predicted time reaching the predicted point;
obtaining the prediction precision of the number of motor vehicles according to the number of the predicted motor vehicles and the actual number of the motor vehicles;
the device for predicting the number of stop lines of the future motor vehicles reaching the signal lamp intersection in real time is also used for: and visually displaying the information detected by the video tracking detection equipment.
3. A computer device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the steps of the method for predicting in real time the number of future vehicles arriving at a signal intersection stop line as recited in claim 1.
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