CN111652410B - Method and device for predicting number of motor vehicles on expressway - Google Patents

Method and device for predicting number of motor vehicles on expressway Download PDF

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CN111652410B
CN111652410B CN202010366347.3A CN202010366347A CN111652410B CN 111652410 B CN111652410 B CN 111652410B CN 202010366347 A CN202010366347 A CN 202010366347A CN 111652410 B CN111652410 B CN 111652410B
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CN111652410A (en
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姜廷顺
李萌
陆建
王家捷
朱林
李颖宏
刘杰
尹胜超
顾怀中
薛军
林拥军
戴帅
谭塈元
张军
郭娅明
邹平
宋志洪
贾兴无
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Anhui Keli Information Industry Co Ltd
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Abstract

The invention provides a method and a device for predicting the number of motor vehicles on a highway, wherein the method comprises the following steps: acquiring motor vehicle information of a plurality of target motor vehicles positioned at any moment upstream of a predicted position, wherein the motor vehicle information comprises position information and speed information of the target motor vehicles; determining target time for each target motor vehicle to reach a predicted position according to motor vehicle information of the plurality of target motor vehicles at any moment, and predicting the first motor vehicle quantity which is driven to the predicted position when reaching the target time in real time; acquiring the number of second motor vehicles which travel to the predicted position when reaching the target time; and determining the accuracy of the predicting result of the first motor vehicle number according to the first motor vehicle number and the second motor vehicle number. By implementing the invention, the accuracy evaluation of the predicted result can be realized, so that the traffic management department can timely know whether the predicted result is accurate, thereby realizing the supervision of the predicted result and ensuring the credibility of the predicted result.

Description

Method and device for predicting number of motor vehicles on expressway
Technical Field
The invention relates to the field of public security traffic management, in particular to a method and a device for predicting the number of motor vehicles on a highway.
Background
Along with the rapid development of economy, the automobile industry is promoted to synchronously and rapidly develop, the traffic demand of people for reaching a destination rapidly and timely is continuously increased, and the travel through a expressway is normal, but in practice, road congestion frequently occurs in the road, so that the traffic demand of people for reaching the destination rapidly and timely cannot be met. In the related art, only a method for predicting the congestion position is provided, the prediction result is not analyzed accurately, and supervision on the prediction result is lacked, so that the accuracy of the prediction result cannot be judged, and the reliability of the prediction result is influenced for a long time.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the defect that the accuracy of the predicted result cannot be judged due to lack of supervision on the predicted result in the prior art, and the reliability of the predicted result is influenced for a long time, so that the method and the device for predicting the number of the motor vehicles on the expressway are provided.
According to a first aspect, the present embodiment provides a method for predicting the number of vehicles on a highway, including the steps of: acquiring motor vehicle information of a plurality of target motor vehicles positioned at any moment upstream of a predicted position, wherein the motor vehicle information comprises position information and speed information of the target motor vehicles; determining target time for each target motor vehicle to reach a predicted position according to motor vehicle information of the plurality of target motor vehicles at any moment, and predicting the first motor vehicle quantity which is driven to the predicted position when reaching the target time in real time; acquiring the number of second motor vehicles which travel to the predicted position when reaching the target time; and determining the accuracy of the predicting result of the first motor vehicle number according to the first motor vehicle number and the second motor vehicle number.
Optionally, the method further comprises: and when the accuracy of the prediction result is lower than a preset threshold value, sending out alarm information.
Optionally, the determining, according to the vehicle information of the plurality of target vehicles at any moment, the target time when each target vehicle reaches the predicted position and predicting, in real time, the first number of vehicles that travel to the predicted position when reaching the target time includes: determining the distance between any target motor vehicle and the adjacent motor vehicle in front when other motor vehicles exist between any target motor vehicle and the predicted position; determining a first time for the any target motor vehicle to reach the position of the front adjacent motor vehicle according to the speed of the any target motor vehicle and the distance between the any target motor vehicle and the front adjacent motor vehicle; acquiring a second time for the front adjacent vehicle to reach the predicted position; determining a target time for any target motor vehicle to reach the predicted position according to the first time and the second time; and predicting a first number of motor vehicles which travel to the predicted position when reaching the target time according to the target time when a plurality of target motor vehicles reach the predicted position, and taking the first number of motor vehicles as a first motor vehicle number.
Optionally, the method further comprises: determining the distance from the target motor vehicle to the predicted position and the speed of the target motor vehicle when no other motor vehicle exists between any target motor vehicle and the predicted position; determining a target time for the target motor vehicle to reach the predicted position according to the distance from the target motor vehicle to the predicted position and the speed of the target motor vehicle; predicting a second number of vehicles traveling to the predicted location when the target time is reached according to the target time when the target vehicle reaches the predicted location; and predicting the first number of the motor vehicles which travel to the predicted position when reaching the target time according to the first number of the motor vehicles and the second number of the motor vehicles.
Optionally, the method further comprises: obtaining license plate number information of each motor vehicle when the vehicle enters the detection road section; and associating the license plate number information with the corresponding motor vehicle and synchronously displaying the license plate number information and the acquired running track of the motor vehicle.
Optionally, the determining, according to the vehicle information of the plurality of target vehicles at any moment, the target time when each target vehicle reaches the predicted position and predicting, in real time, the first vehicle number that travels to the predicted position when reaching the target time includes: determining target time for each target motor vehicle to reach a predicted position according to motor vehicle information of a plurality of target motor vehicles associated with license plate number information at any moment, and predicting the number of first motor vehicles which travel to the predicted position when reaching the target time in real time; the determining the accuracy of the predicting result of the first motor vehicle number according to the first motor vehicle number and the second motor vehicle number comprises the following steps: obtaining license plate number information of each motor vehicle when the vehicle reaches a predicted position; and determining the accuracy of the predicting result of the first motor vehicle number according to the first motor vehicle number, the second motor vehicle number and license plate number information of each motor vehicle when the motor vehicles reach the predicting position.
Optionally, the acquiring the vehicle information of the plurality of target vehicles located upstream of the predicted position at any time includes: acquiring the positions and speeds of a plurality of target motor vehicles which are positioned at the upstream of the predicted position at any moment and are detected by a plurality of tracking detection devices; and when any one of the target motor vehicles is in the overlapping area of two adjacent tracking detection devices, clearing the position information and the speed information of the target motor vehicle, which are acquired by any one of the two adjacent tracking detection devices.
According to a second aspect, the present embodiment provides a device for predicting the number of vehicles on a highway, including the steps of: a motor vehicle information acquisition module for acquiring motor vehicle information of a plurality of target motor vehicles located upstream of a predicted position at any one time, wherein the motor vehicle information comprises position information and speed information of the target motor vehicles; the first motor vehicle quantity predicting module is used for determining the target time of each target motor vehicle reaching the predicted position according to the motor vehicle information of the plurality of target motor vehicles at any moment and predicting the first motor vehicle quantity which is driven to the predicted position when reaching the target time in real time; the second motor vehicle quantity acquisition module is used for acquiring the second motor vehicle quantity which runs to the predicted position when reaching the target time; and the accuracy determining module is used for determining the accuracy of the prediction result of the first motor vehicle number according to the first motor vehicle number and the second motor vehicle number.
According to a third aspect, the present embodiment provides an electronic device, including a memory and a processor, where the memory and the processor are communicatively connected to each other, and the memory stores computer instructions, and the processor executes the computer instructions, thereby executing the method for predicting the number of vehicles on a highway according to the first aspect or any implementation manner of the first aspect.
According to a fourth aspect, the present embodiment provides a non-transitory computer readable storage medium storing computer instructions which, when executed by a processor, implement a method of predicting the number of vehicles on a highway according to the first aspect or any implementation of the first aspect.
The technical scheme of the invention has the following advantages:
according to the method/device for predicting the quantity of the motor vehicles on the expressway, accuracy evaluation is carried out on the predicted results, so that a traffic management department can know whether the predicted results are accurate or not in time, supervision on the predicted results is achieved, and reliability of the predicted results is guaranteed.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart showing a specific example of a method for predicting the number of vehicles on a highway according to an embodiment of the present invention;
FIG. 2 is a schematic diagram showing a specific example of a method for predicting the number of vehicles on a highway according to an embodiment of the present invention;
FIG. 3 is a schematic diagram showing a specific example of a method for predicting the number of vehicles on a highway according to an embodiment of the present invention;
FIG. 4 is a schematic block diagram showing a specific example of a device for predicting the number of vehicles on a highway in accordance with an embodiment of the present invention;
fig. 5 is a schematic block diagram of a specific example of an electronic device in an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made apparent and fully in view of the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, 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 the description of the present invention, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; the two components can be directly connected or indirectly connected through an intermediate medium, or can be communicated inside the two components, or can be connected wirelessly or in a wired way. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
In addition, the technical features of the different embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
The embodiment provides a method for predicting the number of motor vehicles on a highway, as shown in fig. 1, comprising the following steps:
s101, acquiring motor vehicle information of a plurality of target motor vehicles located upstream of a predicted position at any moment, wherein the motor vehicle information comprises position information and speed information of the target motor vehicles.
The predicted position may be any position on the road where the number of vehicles needs to be predicted, and in this embodiment, the predicted position may be shown in fig. 2, and the upstream of the predicted position indicates a road section along the running direction of the vehicle, that is, the direction of the arrow in fig. 2, before the vehicle reaches the predicted position. The mode of acquiring the positions and the speeds of a plurality of target motor vehicles positioned at the upstream of the predicted position at any moment can be acquired through tracking detection equipment arranged beside a road, wherein the tracking detection equipment can be radar scanning equipment or video monitoring equipment, and the radar scanning equipment and the video monitoring equipment can be started at the same time, so that the motor vehicle information obtained by the radar scanning equipment and the video monitoring equipment is subjected to data fusion, the fused motor vehicle information is obtained, and the acquired motor vehicle information is ensured to be more accurate. The present embodiment does not limit the manner of acquiring the positions and speeds of the plurality of target vehicles located upstream of the predicted position at any one time, and those skilled in the art can determine the positions and speeds as needed.
S102, determining target time for each target motor vehicle to reach a predicted position according to motor vehicle information of a plurality of target motor vehicles at any moment, and predicting the first motor vehicle quantity which is driven to the predicted position when reaching the target time in real time.
For example, the method of determining the target time for each target vehicle to reach the predicted position from the vehicle information of the plurality of target vehicles at any one time may be to calculate the target time for each target vehicle to reach the predicted position from the acquired distances between the plurality of target vehicles and the predicted position and the speeds of the plurality of target vehicles.
The method for predicting the number of the first motor vehicles running to the predicted position when the target time is reached in real time may be to store the number of the predicted motor vehicles reaching the predicted position at any time in a database, and count the motor vehicles reaching the predicted position at the same time to obtain the number of the first motor vehicles.
S103, acquiring the number of second motor vehicles which travel to the predicted position when reaching the target time. The second motor vehicle number acquisition method may be detected by a tracking detection device provided at the predicted position.
S104, determining accuracy of a prediction result of the first motor vehicle number according to the first motor vehicle number and the second motor vehicle number.
For example, the manner in which the accuracy of the prediction result for the first vehicle number is determined from the first vehicle number and the second vehicle number may be obtained by the following formula:
wherein Y is j Representing the accuracy of the predicted result, Y t Representing a first number of vehicles; s is S t Representing a second number of vehicles.
According to the method for predicting the quantity of the motor vehicles on the expressway, accuracy evaluation is carried out on the predicted results, so that a traffic management department can know whether the predicted results are accurate or not in time, supervision on the predicted results is achieved, and reliability of the predicted results is guaranteed.
As an optional implementation manner of this embodiment, the method further includes: and when the accuracy of the prediction result is lower than a preset threshold value, sending out alarm information.
The preset threshold may be 90%, and the size of the preset threshold is not limited in this embodiment, and may be determined by those skilled in the art according to needs. When the accuracy of the predicted result is smaller than the preset threshold, the alarm message may be sent out by displaying the alarm message and the accuracy of the predicted result on the electronic graph, so as to prompt and guide a technician to adjust and correct each tracking detection device with reference to the accuracy of the predicted result. The correction mode for the tracking detection equipment can be to read the data of the radar scanning equipment and the data of the video monitoring equipment which monitor the same road section, judge whether the data of the radar scanning equipment and the data of the video monitoring equipment are consistent, if so, the tracking detection equipment is accurate to detect, if not, the deviation value of the detection data is displayed, whether the tracking detection equipment needs correction is judged through the deviation value, and if the deviation value exceeds the allowable deviation range, the tracking detection equipment is corrected.
The embodiment of the invention provides a method for predicting the number of motor vehicles on a highway, which is used for sending out an alarm when the accuracy of a predicted result is lower than a preset threshold value, reminding a technician to correct and adjust in time according to the accuracy of the predicted result, and being beneficial to improving the accuracy of the predicted result.
As an optional implementation manner of this embodiment, step S102 includes:
first, when there are other vehicles between any target vehicle and the predicted position, the distance between any target vehicle and the preceding adjacent vehicle is determined.
For example, when there are other vehicles between any one target vehicle and the predicted position, whether there is only one or a plurality of vehicles between the target vehicle and the predicted position, only the distance between the target vehicle and the adjacent preceding first vehicle needs to be determined. As shown in fig. 2, the target vehicle may be any one of the vehicles in fig. 2, with the target vehicle 3 as the target vehicle in the present embodiment, and then the front adjacent vehicle as the target vehicle 2. The distance between any one of the target vehicles and the adjacent vehicle in front may be determined according to the positions of the plurality of target vehicles acquired by the detection device beside the road in the step S101, and the distance between any one of the target vehicles and the adjacent vehicle in front may be obtained by performing a difference between the positions of the target vehicle and the adjacent vehicle acquired by the detection device.
Next, a first time for any one of the target vehicles to reach the location of the front adjacent vehicle is determined based on the speed of the any one of the target vehicles and the distance from the front adjacent vehicle.
The first time may be determined according to the target vehicle speed obtained in the step S101 and the distance between any one of the target vehicles and the adjacent vehicle in front, and the specific determination may be calculated by the following formula:wherein S is 1 Representing distance between target motor vehicle and adjacent motor vehicle in frontSeparating; v (V) 1 Indicating target vehicle speed, t 1 Representing a first time.
Then, a second time is obtained at which the front adjacent vehicle arrives at the predicted position.
In this embodiment, all the target vehicles located upstream of the predicted position will obtain the time for the target vehicle to reach the predicted position in real time according to the distance between the target vehicle and the predicted position at all times, the speed of the target vehicle and the running condition of the vehicle in front of the target vehicle, and the time for the adjacent vehicle in front of the target vehicle to reach the predicted position is used as the second time for calculating the target vehicle to reach the predicted position.
And determining the target time for any target motor vehicle to reach the predicted position according to the first time and the second time.
The target time for any target vehicle to reach the predicted position is illustratively determined by summing the first time and the second time, i.e., the target time for any target vehicle to reach the predicted position is the sum of the first time and the second time.
Then, a first number of vehicles traveling to the predicted position when the target time is reached is predicted based on the target times at which the plurality of target vehicles reach the predicted position, and the first number of vehicles is taken as a first number of vehicles.
For example, there may be a plurality of vehicles on the expressway at any time, the target time for the vehicle to reach the predicted position is obtained for all the vehicles located upstream of the predicted position on the expressway monitoring section according to the above method, and by counting the target time for the vehicle to reach the predicted position, it is possible to predict the first number of vehicles traveling to the predicted position when any target time is reached, and the first number of vehicles is regarded as the first number of vehicles. Taking the predicted position at the bifurcation intersection as an example, by determining the time when a plurality of target vehicles positioned at the upstream of the bifurcation intersection at the current moment reach the bifurcation intersection, the number of vehicles reaching the bifurcation intersection when the target time is 5 seconds can be determined. Assuming that 3 vehicles arrive at the bifurcation intersection when the predicted target time of the first branch located upstream of the bifurcation intersection is 5 seconds, and 2 vehicles arrive at the bifurcation intersection when the predicted target time of the second branch located upstream of the bifurcation intersection is 5 seconds, it can be predicted that the number of first vehicles traveling to the predicted position is 5 when five seconds are reached.
According to the method for predicting the number of the motor vehicles on the expressway in real time, when other motor vehicles exist between any target motor vehicle and the predicted position, the total time from the target motor vehicle to the predicted position is obtained by calculating the first time from the target motor vehicle to the position of the adjacent motor vehicle in front and obtaining the second time from the motor vehicle in front to the predicted position, in the process, the situation that other motor vehicles exist between the target motor vehicle and the predicted position is considered, the accuracy of predicting the total time from the target motor vehicle to the predicted position is improved, and therefore the accuracy of predicting the number of motor vehicles at the predicted position at any moment is improved.
As an optional implementation manner of this embodiment, the method further includes:
first, when no other vehicle is present between any of the target vehicles to a predicted location, a distance of the target vehicle to the predicted location and a speed of the target vehicle are determined.
The speed and the position of the target motor vehicle can be determined by acquiring the speed and the position of the target motor vehicle through tracking detection equipment arranged beside a road, and obtaining the distance from the target motor vehicle to the predicted position by making a difference between the predicted position and the acquired position of the target motor vehicle.
Next, a target time for the target vehicle to reach the predicted location is determined based on the distance of the target vehicle from the predicted location and the speed of the target vehicle.
The specific way of determining the time for the target vehicle to reach the predicted position from the distance of the target vehicle to the predicted position and the speed of the target vehicle can be calculated by the following formula:wherein S is 2 Representing a distance of the target motor vehicle from the predicted location; v (V) 2 Indicating target vehicle speed, t 2 Indicating the time the target vehicle reached the predicted position.
Then, a second number of vehicles traveling to the predicted position when the target time is reached is predicted based on the target time when the target vehicle reaches the predicted position.
For example, there may be a plurality of vehicles on the expressway at any one time, the target time for the vehicle to reach the predicted position is obtained by the above method for all vehicles located upstream of the predicted position on the expressway monitoring section, the number of vehicles traveling to the predicted position when the target time is reached can be predicted by counting the target time required for the vehicle to reach the predicted position calculated at any one time, and the number is determined as the second number of vehicles. Still taking the intersection as an example, when the predicted position is at the bifurcation intersection, assuming that 2 vehicles arrive at the bifurcation intersection in the 5 th second after the current time are predicted by the method, 2 vehicles arrive at the bifurcation intersection in the 5 th second after the current time are predicted by the second branch upstream of the bifurcation intersection, then the fifth second after the current time can be determined, and the second number of vehicles arriving at the bifurcation intersection is 4.
Again, the first number of vehicles traveling to the predicted location when the target time is reached is predicted based on the first number of vehicles and the second number of vehicles.
As an example, taking the bifurcation intersection as the predicted position as an example, it is known from the above embodiment that when any one of the target vehicles arrives at the predicted position and there are other vehicles, the first number of vehicles arriving at the predicted position is 5 vehicles when the target time predicted according to the above embodiment is 5 seconds, and the second number of vehicles arriving at the predicted position when the target time predicted according to the present embodiment is 5 seconds and there are no other vehicles, the number of vehicles arriving at the predicted position is 9 vehicles when the target time is 5 seconds, that is, the number of vehicles arriving at the predicted position is 9 vehicles as a whole.
The embodiment of the invention provides a method for predicting the quantity of motor vehicles on a highway, which takes a scheme that no other motor vehicles exist between any target motor vehicle and a predicted position as a supplementary scheme that other motor vehicles exist between any target motor vehicle and the predicted position, thereby further improving the accuracy of motor vehicle quantity prediction.
As an optional implementation manner of this embodiment, the method further includes:
Obtaining license plate number information of each motor vehicle when the vehicle enters the detection road section; and associating the license plate number information with the corresponding motor vehicle and synchronously displaying the license plate number information and the acquired running track of the motor vehicle.
For example, the license plate number information of each motor vehicle when the vehicle enters the detection road section may be obtained by setting a vehicle identification area before the detection road section, setting a detection device in the vehicle identification area, and identifying the license plate number of the motor vehicle when the detection device detects that the motor vehicle is present in the vehicle identification area, so as to obtain the license plate number information of each motor vehicle. The license plate number information can be associated with the corresponding motor vehicle by marking the identified license plate number information on the corresponding motor vehicle and displaying the identified license plate number information on an electronic chart, wherein the license plate number information synchronously follows the running track of the motor vehicle.
The embodiment of the invention provides a method for predicting the number of motor vehicles on a highway, which is used for identifying license plate number information of each motor vehicle when entering a detection road section and synchronously following the running track of the motor vehicle, so that a plurality of target motor vehicles on the detection road section can be distinguished, the number of predicted positions of the motor vehicles is predicted, and the number of the motor vehicles is positioned on the license plate number of each motor vehicle at the same time, and the judgment standard of the accuracy of a predicted result is further improved.
As an optional implementation manner of this embodiment, step S102 includes:
determining the target time of each target motor vehicle reaching the predicted position according to the motor vehicle information of a plurality of target motor vehicles with license plate number information associated at any moment, and predicting the first motor vehicle quantity which is driven to the predicted position when reaching the target time in real time, wherein the first motor vehicle quantity which is driven to the predicted position when reaching the target time in real time comprises the license plate number information of the motor vehicle.
The step S104 includes: firstly, obtaining license plate number information of each motor vehicle when the vehicle reaches a predicted position; the license plate number information of each motor vehicle can be acquired by a video detection device arranged at the detection position when the vehicle reaches the prediction position.
Secondly, the accuracy of the predicting result of the first motor vehicle number is determined according to the first motor vehicle number, the second motor vehicle number and license plate number information of each motor vehicle when the motor vehicles reach the predicting position.
For example, according to the number of first vehicles, the number of second vehicles, and license plate number information of each vehicle when the vehicle arrives at the predicted position, the manner of determining the accuracy of the predicted result for the number of first vehicles may be to determine the accuracy of the predicted result determined to be determined only with the accuracy of the number of vehicles by the manner of step S104 described above, and then determine whether or not the vehicle actually traveling to the predicted position at the target time is the same vehicle traveling to the predicted position at the predicted target time.
When it is determined that all the vehicles actually traveling to the predicted position at the target time are vehicles traveling to the predicted position at the predicted target time, the accuracy of the predicted result obtained from the number of vehicles is taken as the accuracy of the final predicted result; when it is determined that the motor vehicle actually traveling to the predicted position at the target time is not exactly the motor vehicle traveling to the predicted position at the predicted target time, the accuracy of the predicted result is adjusted, for example, 10 motor vehicles arrive at the predicted position after 5 seconds are predicted, and 10 motor vehicles are actually detected at the predicted position after 5 seconds, at this time, the accuracy of the predicted result determined by the number of motor vehicles is 100%, but by recognizing and detecting the license plate number, it is found that the license plate number of 1 vehicle is not one of the license plate numbers of motor vehicles that arrive at the predicted position after 5 seconds in advance, the accuracy of the predicted result is adjusted to 90%, and the adjustment manner of the accuracy of the predicted result is not limited, and can be determined by those skilled in the art as needed.
The embodiment of the invention provides a method for predicting the number of motor vehicles on a highway, which is characterized in that whether license plate number information is accurate or not is used as an index of the accuracy of a predicted result by comparing the license plate number information, so that the judgment standard of the accuracy of the predicted result is improved, and the accuracy of the predicted result is further improved.
As an alternative implementation manner of this embodiment, step S101 includes:
firstly, acquiring the positions and speeds of a plurality of target motor vehicles which are positioned at the upstream of a predicted position at any moment and are detected by a plurality of tracking detection devices;
for example, a plurality of tracking detection devices are set up on one side or two sides of a road, and in order to completely obtain the running condition of a vehicle on the road, the tracking detection devices need to be set up at intervals, as shown in fig. 3, the interval distance of the tracking detection devices may be 100 meters, and the interval distance of the tracking detection devices is not limited in this embodiment, and can be determined by a person skilled in the art according to needs. And the data information detected by the tracking detection devices is returned to the controller of the processing center, so that the controller of the processing center comprehensively processes the data detected by the tracking detection devices, wherein the data information detected by the tracking detection devices can be the position and speed information of a plurality of target motor vehicles and the license plate number information of the motor vehicles.
And secondly, when any one of the target motor vehicles is in the overlapping area of two adjacent tracking detection devices, clearing the position information and the speed information of the target motor vehicle, which are acquired by any one of the two adjacent tracking detection devices.
For example, the method of determining whether any target vehicle is in the overlapping area of two adjacent tracking detection devices may be to determine whether the controller of the processing center finds the same data information in the data returned by different tracking detection devices, for example, when the vehicles with the same license plate number information are acquired in two tracking detection devices, or when the vehicles enter a expressway, numbering is performed on each vehicle according to the entering sequence, and when the vehicles with the same number are acquired in two tracking detection devices, the vehicles are illustrated to be running in the overlapping area of the detection ranges of the two tracking detection devices. At this time, the controller of the processing center can clear the data of the overlapping area of any tracking detection device, on one hand, the processing data of the controller of the processing center is reduced, and on the other hand, the motor vehicle monitoring data received by the controller is seamlessly connected between two adjacent tracking detection devices, so that the integrity of motor vehicle monitoring and the accuracy of time prediction of the motor vehicle to the predicted position are ensured. The controller of the processing center can also display the information for clearing the position and the speed of the target motor vehicle acquired by any one of the two adjacent tracking and detecting devices on the electronic display device, so that traffic police can visually check the running condition of the expressway motor vehicle.
The present embodiment provides a device for predicting the number of vehicles on a highway, as shown in fig. 4, including:
a vehicle information acquisition module 201 for acquiring vehicle information of a plurality of target vehicles located upstream of the predicted position at any one time, the vehicle information including position information and speed information of the target vehicles; for details, see the corresponding parts of the method step S101 in the above embodiment, and are not described herein again.
A first vehicle number prediction module 202, configured to determine a target time for each target vehicle to reach a predicted position according to vehicle information of the plurality of target vehicles at any time, and predict in real time a first vehicle number that travels to the predicted position when the target time is reached; for details, see the corresponding parts of the method step S102 in the above embodiment, and are not described herein again.
A second vehicle number acquisition module 203 for acquiring a second vehicle number that travels to the predicted position when the target time is reached; for details, see the corresponding parts of the method step S103 in the above embodiment, and are not described herein again.
An accuracy determination module 204 for determining a predicted outcome accuracy for the first number of vehicles based on the first number of vehicles and the second number of vehicles. For details, see the corresponding parts of the method step S104 in the above embodiment, and the details are not repeated here.
As an alternative implementation of this embodiment, the foregoing apparatus further includes: and the alarm module is used for sending out alarm information when the accuracy of the prediction result is lower than a preset threshold value. The specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
As an alternative implementation of the present embodiment, the first vehicle number prediction module 202 includes:
the distance determining module is used for determining the distance between any target motor vehicle and the adjacent motor vehicle in front when other motor vehicles exist between any target motor vehicle and the predicted position; the specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
A first time determining module, configured to determine a first time when the any one target vehicle arrives at a position of a front neighboring vehicle according to a speed of the any one target vehicle and a distance between the target vehicle and the front neighboring vehicle; the specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
A second time acquisition module for acquiring a second time when the front adjacent motor vehicle arrives at the predicted position; the specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
A first target time determining module, configured to determine a target time for any target vehicle to reach the predicted position according to the first time and the second time; the specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
The first quantity determining module is used for predicting a first quantity of the motor vehicles which travel to the predicted position when reaching the target time according to the target time when the plurality of target motor vehicles reach the predicted position, and taking the first quantity of the motor vehicles as a first motor vehicle quantity. The specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
As an alternative implementation of this embodiment, the foregoing apparatus further includes:
a parameter determining module for determining a distance from any one of the target vehicles to a predicted location and a speed of the target vehicle when no other vehicle is present between the target vehicle and the predicted location; the specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
A second target time determining module, configured to determine a target time for the target vehicle to reach the predicted location according to a distance from the target vehicle to the predicted location and a speed of the target vehicle; the specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
A second number determining module for predicting a second number of vehicles traveling to the predicted position when the target time is reached, based on a target time when the target vehicle reaches the predicted position; the specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
The first motor vehicle number determining module is used for predicting the first motor vehicle number which is driven to the predicted position when the target time is reached according to the first motor vehicle number and the second motor vehicle number. The specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
As an alternative implementation of this embodiment, the foregoing apparatus further includes:
the first license plate information acquisition module is used for acquiring license plate information of each motor vehicle when the vehicle enters the detection road section; the specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
And the association module is used for associating the license plate number information with the corresponding motor vehicle and synchronously displaying the license plate number information and the acquired running track of the motor vehicle. The specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
As an alternative implementation of the present embodiment, the first vehicle number prediction module 202 includes:
The motor vehicle quantity predicting module is used for determining the target time of each target motor vehicle reaching the predicted position according to motor vehicle information of a plurality of target motor vehicles associated with license plate number information at any moment and predicting the first motor vehicle quantity which is driven to the predicted position when reaching the target time in real time; the specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
As an optional implementation manner of this embodiment, the accuracy determining module 204 includes:
the second license plate information acquisition module is used for acquiring license plate information of each motor vehicle when the vehicle reaches the predicted position; the specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
And the accuracy determination submodule is used for determining accuracy of a predicted result of the first motor vehicle number according to the first motor vehicle number, the second motor vehicle number and license plate number information of each motor vehicle when the motor vehicle reaches a predicted position. The specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
As an alternative implementation manner of this embodiment, the above-mentioned motor vehicle information acquisition module 201 includes:
the parameter acquisition module is used for acquiring the positions and the speeds of a plurality of target motor vehicles which are positioned at the upstream of the predicted position at any moment and are detected by a plurality of tracking detection devices; the specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
And the overlapping clearing module is used for clearing the position information and the speed information of the target motor vehicle acquired by any one of the two adjacent tracking and detecting equipment when any one of the target motor vehicle is in an overlapping area of the two adjacent tracking and detecting equipment. The specific content refers to the corresponding parts of the method in the above embodiment, and will not be repeated here.
Embodiments of the present application also provide an electronic device, as shown in fig. 5, a processor 310 and a memory 320, where the processor 310 and the memory 320 may be connected by a bus or other means.
The processor 310 may be a central processing unit (Central Processing Unit, CPU). The processor 310 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSPs), application specific integrated circuits (Application Specific Integrated Circuit, ASICs), field programmable gate arrays (Field-Programmable Gate Array, FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above.
The memory 320 is used as a non-transitory computer readable storage medium, and can be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the navigation system-based operation parameter correction threshold determination method in the embodiment of the present application. The processor executes various functional applications of the processor and data processing by running non-transitory software programs, instructions, and modules stored in memory.
Memory 320 may include a storage program area that may store an operating system, at least one application program required for functionality, and a storage data area; the storage data area may store data created by the processor, etc. In addition, the memory 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, memory 320 may optionally include memory located remotely from the processor, which may be connected to the processor 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 320 and when executed by the processor 310 perform the navigation system based operating parameter modification threshold determination method of the embodiment shown in fig. 1.
The details of the above electronic device may be understood correspondingly with respect to the corresponding related descriptions and effects in the embodiment shown in fig. 1, which are not repeated herein.
The present embodiment also provides a computer storage medium storing computer executable instructions, where the computer executable instructions may perform the method for determining the correction threshold based on the operation parameter of the navigation system in any of the above method embodiments. Wherein the storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a Flash Memory (Flash Memory), a Hard Disk (HDD), or a Solid State Drive (SSD); the storage medium may also comprise a combination of memories of the kind described above.
It is apparent that the above examples are given by way of illustration only and are not limiting of the embodiments. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. While still being apparent from variations or modifications that may be made by those skilled in the art are within the scope of the invention.

Claims (4)

1. The method for predicting the number of the motor vehicles on the expressway is characterized by comprising the following steps of:
acquiring motor vehicle information of a plurality of target motor vehicles positioned at any moment upstream of a predicted position, wherein the motor vehicle information comprises position information and speed information of the target motor vehicles, and the motor vehicle information is acquired through tracking detection equipment arranged beside a road;
determining target time for each target motor vehicle to reach a predicted position according to motor vehicle information of the plurality of target motor vehicles at any moment, and predicting the first motor vehicle quantity which is driven to the predicted position when reaching the target time in real time;
acquiring a second motor vehicle number which runs to a predicted position when reaching a target time, wherein tracking detection equipment arranged beside a road of the second motor vehicle number acquires the second motor vehicle number;
Determining accuracy of a prediction result of the first motor vehicle number according to the first motor vehicle number and the second motor vehicle number;
the accuracy of the prediction result of the first motor vehicle number is determined according to the first motor vehicle number and the second motor vehicle number, and the prediction result is obtained through the following formula:
wherein Y is j Representing the accuracy of the predicted result, Y t Representing a first number of vehicles; s is S t Representing a second number of vehicles;
the method further comprises the steps of:
when the accuracy of the prediction result is lower than a preset threshold value, sending out alarm information;
the method for determining the target time of each target motor vehicle reaching the predicted position according to the motor vehicle information of the plurality of target motor vehicles at any moment and predicting the first motor vehicle quantity which is driven to the predicted position when reaching the target time in real time comprises the following steps:
determining the distance between any target motor vehicle and the adjacent motor vehicle in front when other motor vehicles exist between any target motor vehicle and the predicted position;
determining a first time for the any target motor vehicle to reach the position of the front adjacent motor vehicle according to the speed of the any target motor vehicle and the distance between the any target motor vehicle and the front adjacent motor vehicle;
acquiring a second time for the front adjacent vehicle to reach the predicted position;
Determining a target time for any target motor vehicle to reach the predicted position according to the first time and the second time;
predicting a first number of motor vehicles which travel to a predicted position when reaching the target time according to the target time when a plurality of target motor vehicles reach the predicted position, and taking the first number of motor vehicles as a first motor vehicle number;
further comprises:
determining the distance from the target motor vehicle to the predicted position and the speed of the target motor vehicle when no other motor vehicle exists between any target motor vehicle and the predicted position;
determining a target time for the target motor vehicle to reach the predicted position according to the distance from the target motor vehicle to the predicted position and the speed of the target motor vehicle;
predicting a second number of vehicles traveling to the predicted location when the target time is reached according to the target time when the target vehicle reaches the predicted location;
predicting a first number of vehicles traveling to a predicted location when a target time is reached based on the first number of vehicles and the second number of vehicles;
further comprises:
obtaining license plate number information of each motor vehicle when the vehicle enters the detection road section;
The license plate number information is associated with the corresponding motor vehicle and is synchronously displayed with the acquired running track of the motor vehicle;
determining a target time for each target vehicle to reach a predicted position based on vehicle information of the plurality of target vehicles at any one time and predicting in real time a first number of vehicles traveling to the predicted position when the target time is reached includes:
determining target time for each target motor vehicle to reach a predicted position according to motor vehicle information of a plurality of target motor vehicles associated with license plate number information at any moment, and predicting the number of first motor vehicles which travel to the predicted position when reaching the target time in real time;
the determining the accuracy of the predicting result of the first motor vehicle number according to the first motor vehicle number and the second motor vehicle number comprises the following steps:
obtaining license plate number information of each motor vehicle when the vehicle reaches a predicted position;
determining the accuracy of a predicted result of the first motor vehicle number according to the first motor vehicle number, the second motor vehicle number and license plate number information of each motor vehicle when the motor vehicles reach a predicted position;
the acquiring the motor vehicle information of a plurality of target motor vehicles located at any moment upstream of the predicted position comprises:
Acquiring the positions and speeds of a plurality of target motor vehicles which are positioned at the upstream of the predicted position at any moment and are detected by a plurality of tracking detection devices;
and when any one of the target motor vehicles is in the overlapping area of two adjacent tracking detection devices, clearing the position information and the speed information of the target motor vehicle, which are acquired by any one of the two adjacent tracking detection devices.
2. A rapid-road motor vehicle quantity prediction apparatus, characterized by comprising:
the motor vehicle information acquisition module is used for acquiring motor vehicle information of a plurality of target motor vehicles positioned at any moment upstream of the predicted position, wherein the motor vehicle information comprises position information and speed information of the target motor vehicles, and the motor vehicle information is acquired through tracking detection equipment arranged beside a road;
the first motor vehicle quantity predicting module is used for determining the target time of each target motor vehicle reaching the predicted position according to the motor vehicle information of the plurality of target motor vehicles at any moment and predicting the first motor vehicle quantity which is driven to the predicted position when reaching the target time in real time;
the second motor vehicle quantity acquisition module is used for acquiring the second motor vehicle quantity which runs to the predicted position when reaching the target time, and tracking detection equipment arranged beside the road of the second motor vehicle quantity is used for acquiring the second motor vehicle quantity;
An accuracy determining module for determining accuracy of a prediction result of the first motor vehicle number according to the first motor vehicle number and the second motor vehicle number;
the accuracy of the prediction result of the first motor vehicle number is determined according to the first motor vehicle number and the second motor vehicle number, and the prediction result is obtained through the following formula:
wherein Y is j Representing the accuracy of the predicted result, Y t Representing a first number of vehicles; s is S t Representing a second number of vehicles;
the apparatus further comprises: the alarm module is used for sending alarm information when the accuracy of the prediction result is lower than a preset threshold value;
the first motor vehicle number prediction module includes:
the distance determining module is used for determining the distance between any target motor vehicle and the adjacent motor vehicle in front when other motor vehicles exist between any target motor vehicle and the predicted position;
a first time determining module, configured to determine a first time when the any one target vehicle arrives at a position of a front neighboring vehicle according to a speed of the any one target vehicle and a distance between the target vehicle and the front neighboring vehicle;
a second time acquisition module for acquiring a second time when the front adjacent motor vehicle arrives at the predicted position;
A first target time determining module, configured to determine a target time for any target vehicle to reach the predicted position according to the first time and the second time;
the first quantity determining module is used for predicting the first quantity of the motor vehicles which travel to the predicted position when reaching the target time according to the target time when the plurality of target motor vehicles reach the predicted position, and taking the first quantity of the motor vehicles as the first motor vehicle quantity;
the apparatus further comprises:
a parameter determining module for determining a distance from any one of the target vehicles to a predicted location and a speed of the target vehicle when no other vehicle is present between the target vehicle and the predicted location;
a second target time determining module, configured to determine a target time for the target vehicle to reach the predicted location according to a distance from the target vehicle to the predicted location and a speed of the target vehicle;
a second number determining module for predicting a second number of vehicles traveling to the predicted position when the target time is reached, based on a target time when the target vehicle reaches the predicted position;
a first vehicle number determining module for predicting a first vehicle number that travels to a predicted position when reaching a target time based on the first vehicle number and the second vehicle number;
The apparatus further comprises:
the first license plate information acquisition module is used for acquiring license plate information of each motor vehicle when the vehicle enters the detection road section;
the association module is used for associating the license plate number information with the corresponding motor vehicle and synchronously displaying the license plate number information and the acquired running track of the motor vehicle;
the first motor vehicle number prediction module includes:
the motor vehicle quantity predicting module is used for determining the target time of each target motor vehicle reaching the predicted position according to motor vehicle information of a plurality of target motor vehicles associated with license plate number information at any moment and predicting the first motor vehicle quantity which is driven to the predicted position when reaching the target time in real time;
the accuracy determination module includes:
the second license plate information acquisition module is used for acquiring license plate information of each motor vehicle when the vehicle reaches the predicted position;
an accuracy determination submodule, configured to determine accuracy of a result of predicting the number of the first motor vehicle according to the number of the first motor vehicle, the number of the second motor vehicle, and license plate number information of each motor vehicle when the vehicle arrives at the predicted position;
the motor vehicle information acquisition module comprises:
the parameter acquisition module is used for acquiring the positions and the speeds of a plurality of target motor vehicles which are positioned at the upstream of the predicted position at any moment and are detected by a plurality of tracking detection devices;
And the overlapping clearing module is used for clearing the position information and the speed information of the target motor vehicle acquired by any one of the two adjacent tracking and detecting equipment when any one of the target motor vehicle is in an overlapping area of the two adjacent tracking and detecting equipment.
3. An electronic device comprising a memory and a processor, said memory and said processor being communicatively coupled to each other, said memory having stored therein computer instructions, said processor executing said computer instructions to perform the method of predicting the number of vehicles on a highway according to claim 1.
4. A non-transitory computer readable storage medium storing computer instructions which, when executed by a processor, implement the express way motor vehicle quantity prediction method of claim 1.
CN202010366347.3A 2020-04-30 2020-04-30 Method and device for predicting number of motor vehicles on expressway Active CN111652410B (en)

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