CN113570870A - Distributed intersection average delay estimation method, device, equipment and storage medium - Google Patents
Distributed intersection average delay estimation method, device, equipment and storage medium Download PDFInfo
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- CN113570870A CN113570870A CN202111137499.7A CN202111137499A CN113570870A CN 113570870 A CN113570870 A CN 113570870A CN 202111137499 A CN202111137499 A CN 202111137499A CN 113570870 A CN113570870 A CN 113570870A
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- G08—SIGNALLING
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
Abstract
The invention discloses a distributed crossing average delay estimation method, a device, equipment and a storage medium, wherein the method acquires the position information of intelligent networked vehicles in real time; matching the position information with a preset high-precision map, and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result; when the intelligent networked vehicle enters the preset intersection range, the average speed of the intelligent networked vehicle running in the preset intersection range is obtained, the average delay time of the intersection is estimated according to the average speed, the average delay time of the intersection can be accurately estimated in real time, and the traffic situation requirements of real-time perception and accurate perception are met, so that the running state of the intersection is accurately estimated in real time, and the vehicle is guided to run efficiently.
Description
Technical Field
The invention relates to the technical field of intelligent traffic, in particular to a distributed intersection average delay estimation method, device, equipment and storage medium.
Background
With the continuous development of intelligent transportation technology and the continuous promotion of policies, the intelligent internet automobiles have slowly driven from a test field to a public demonstration road; based on the running of the current intelligent networked automobile and the development of communication technology, the construction of smart intersections and smart roads becomes the main direction for constructing smart cities at present; the intersection is one of the most complex environments in the process of vehicle passing as a connection point of urban roads.
The average delay time of the intersection is used as an important judgment index of the operation efficiency and the service level of the signalized intersection, and not only reflects the time loss in the vehicle driving process, but also reflects the rationality of signal control design; the traditional method for obtaining intersection delay is a field statistical experiment method and a formula calculation method, but the actual statistical experiment method is troublesome and labor-consuming, and the formula calculation method needs to obtain parameters of intersection signal lamps; the delay obtained by the two conventional methods is not very accurate and has certain limitations.
The existing scheme is that GPS data of a floating vehicle is used for calculating the delay of an intersection, although the defects in the traditional method can be overcome, the problem of matching of the return information of the floating vehicle and an electronic map can cause that the calculation delay is greatly deviated from an actual value, the accuracy requirement cannot be met, and the requirement on the real-time performance under the condition of normal traffic operation cannot be met due to the adoption of a central data processing mode.
Disclosure of Invention
The invention mainly aims to provide a distributed crossing average delay estimation method, a device, equipment and a storage medium, and aims to solve the technical problems that in the prior art, the delay of a crossing calculated by using GPS data of a floating car is greatly deviated, the accuracy requirement cannot be met, and the requirement on real-time performance under the condition of normalized traffic operation cannot be met.
In a first aspect, the present invention provides a distributed intersection average delay estimation method, including the following steps:
acquiring the position information of the intelligent networked vehicle in real time;
matching the position information with a preset high-precision map, and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result;
when the intelligent networked vehicle enters the preset intersection range, the average speed of the intelligent networked vehicle running in the preset intersection range is obtained, and the average delay time of the intersection is estimated according to the average speed.
Optionally, the matching the position information with a preset high-precision map, and determining whether the intelligent internet vehicle enters a preset intersection range according to a matching result includes:
matching the position information with a preset high-precision map to generate a matching result;
when the matching result is that the position information is matched with the preset high-precision map, generating a real-time position, and judging whether the intelligent networked vehicle enters a preset intersection range according to whether the real-time position is in the preset intersection range;
and when the matching result is that the position information is not matched with the preset high-precision map, whether the intelligent networked vehicle enters the preset intersection range or not is judged according to whether the current position corresponding to the position information is within the preset intersection range or not.
Optionally, when the matching result is that the position information matches the preset high-precision map, generating a real-time position, and determining whether the intelligent internet vehicle enters a preset intersection range according to whether the real-time position is within the preset intersection range, including:
when the matching result is that the position information is matched with the preset high-precision map, generating a real-time position, and matching the real-time position with the preset intersection range;
when the real-time position is within the range of the preset intersection, judging that the intelligent networked vehicle enters the range of the preset intersection;
and when the real-time position is out of the range of the preset intersection, judging that the intelligent networked vehicle does not enter the range of the preset intersection.
Optionally, when the matching result is that the position information is not matched with the preset high-precision map, whether the intelligent internet vehicle enters the preset intersection range according to whether the current position corresponding to the position information is within the preset intersection range or not includes:
when the matching result is that the position information is not matched with the preset high-precision map, acquiring a current position corresponding to the position information, and matching the current position with the preset intersection range;
when the current position is within the preset intersection range, judging that the intelligent networked vehicle enters the preset intersection range;
and when the current position is out of the preset intersection range, judging that the intelligent network connection vehicle does not enter the preset intersection range.
Optionally, the obtaining an average vehicle speed of the intelligent networked vehicle traveling within the preset intersection range when the intelligent networked vehicle enters the preset intersection range, and estimating an average delay duration of the intersection according to the average vehicle speed includes:
when the intelligent networked vehicle enters the preset intersection range, acquiring the vehicle speed information of the intelligent networked vehicle in a preset statistical period, and acquiring the average vehicle speed of the intelligent networked vehicle running in the preset intersection range according to the vehicle speed information;
and acquiring the range length of the intersection, and estimating the average delay time of the intersection according to the range length of the intersection and the average vehicle speed.
Optionally, when the intelligent networked vehicle enters the preset intersection range, acquiring vehicle speed information of the intelligent networked vehicle in a preset statistical period, and obtaining an average vehicle speed of the intelligent networked vehicle running in the preset intersection range according to the vehicle speed information, includes:
when the intelligent networked vehicle enters the preset intersection range, acquiring the average speed of the p-th intelligent networked vehicle passing through the intersection in a preset statistical period, acquiring the speed of the p-th intelligent networked vehicle passing through the intersection for the kth time, and counting the total times;
according to the average speed of the p intelligent networked vehicle passing through the intersection, the speed of the p intelligent networked vehicle passing through the intersection is obtained for the k time, and the counted total times are used for obtaining the average speed of the intelligent networked vehicle running in the preset intersection range through the following formula:
wherein the content of the first and second substances,
the average speed of the p-th intelligent networked vehicle passing through the intersection is calculated,
is as follows
The speed of the p-th intelligent networked vehicle passing through the intersection is obtained,
is the total number of times of statistics, and is obtained by the following formula:
wherein the content of the first and second substances,
is the time period of a preset statistical period,
and reporting the cycle duration of the vehicle speed for the intelligent networked vehicle.
Optionally, the obtaining the intersection range length, and estimating an average delay duration of the intersection according to the intersection range length and the average vehicle speed includes:
acquiring the range length of the intersection and the free flow speed of the vehicle passing through the intersection;
and estimating the average delay time of the intersection according to the intersection range length, the free flow vehicle speed and the average vehicle speed by the following formula:
wherein the content of the first and second substances,
the average delay time of the intersection is,
the length of the range of the intersection is,
the free-stream speed of the vehicle passing through the intersection;
the average speed of the vehicle passing through the intersection.
In a second aspect, to achieve the above object, the present invention further provides a distributed intersection average delay estimation apparatus, including:
the position acquisition module is used for acquiring the position information of the intelligent networked vehicle in real time;
the judging module is used for matching the position information with a preset high-precision map and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result;
and the estimation module is used for acquiring the average speed of the intelligent networked vehicle running in the preset intersection range when the intelligent networked vehicle enters the preset intersection range, and estimating the average delay time of the intersection according to the average speed.
In a third aspect, to achieve the above object, the present invention further provides a distributed intersection average delay estimation device, where the distributed intersection average delay estimation device includes: the system comprises a memory, a processor and a distributed crossing average delay estimation program stored on the memory and capable of running on the processor, wherein the distributed crossing average delay estimation program is configured to realize the steps of the distributed crossing average delay estimation method.
In a fourth aspect, to achieve the above object, the present invention further provides a storage medium, where a distributed intersection average delay estimation program is stored, and when executed by a processor, the distributed intersection average delay estimation program implements the steps of the distributed intersection average delay estimation method as described above.
The distributed crossing average delay estimation method provided by the invention obtains the position information of the intelligent networked vehicle in real time; matching the position information with a preset high-precision map, and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result; when the intelligent networked vehicle enters the preset intersection range, the average speed of the intelligent networked vehicle running in the preset intersection range is obtained, the average delay time of the intersection is estimated according to the average speed, the average delay time of the intersection can be accurately estimated in real time, and the traffic situation requirements of real-time perception and accurate perception are met, so that the running state of the intersection is accurately estimated in real time, and the vehicle is guided to run efficiently.
Drawings
FIG. 1 is a schematic diagram of an apparatus architecture of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a distributed crossing average delay estimation method according to a first embodiment of the present invention;
FIG. 3 is a flowchart illustrating a second embodiment of a distributed intersection average delay estimation method according to the present invention;
FIG. 4 is a flowchart illustrating a distributed crossing average delay estimation method according to a third embodiment of the present invention;
FIG. 5 is a schematic flow chart of a fourth embodiment of the distributed intersection average delay estimation method according to the present invention;
FIG. 6 is a schematic flow chart of a fifth embodiment of a distributed intersection average delay estimation method according to the present invention;
fig. 7 is a functional block diagram of a distributed intersection average delay estimation device according to a first embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The solution of the embodiment of the invention is mainly as follows: the position information of the intelligent networked vehicle is obtained in real time; matching the position information with a preset high-precision map, and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result; when the intelligent networked vehicle enters the preset intersection range, the average speed of the intelligent networked vehicle running in the preset intersection range is obtained, the average delay time of the intersection is estimated according to the average speed, the average delay time of the intersection can be accurately estimated in real time, and the traffic situation requirements of real-time perception and accurate perception are met, so that the road operation state is accurately evaluated in real time, the vehicle is guided to run efficiently, and the technical problems that in the prior art, the delay of the intersection calculated by using the GPS data of a floating vehicle has large deviation, the accuracy requirement cannot be met, and the real-time requirement under the condition of normal traffic operation cannot be met are solved.
Referring to fig. 1, fig. 1 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the apparatus may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., a Wi-Fi interface). The Memory 1005 may be a high-speed RAM Memory or a Non-Volatile Memory (Non-Volatile Memory), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration of the apparatus shown in fig. 1 is not intended to be limiting of the apparatus and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a distributed intersection average delay estimation program.
The device of the present invention calls the distributed intersection average delay estimation program stored in the memory 1005 by the processor 1001, and performs the following operations:
acquiring the position information of the intelligent networked vehicle in real time;
matching the position information with a preset high-precision map, and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result;
when the intelligent networked vehicle enters the preset intersection range, the average speed of the intelligent networked vehicle running in the preset intersection range is obtained, and the average delay time of the intersection is estimated according to the average speed.
The apparatus of the present invention calls the distributed intersection average delay estimation program stored in the memory 1005 by the processor 1001, and further performs the following operations:
matching the position information with a preset high-precision map to generate a matching result;
when the matching result is that the position information is matched with the preset high-precision map, generating a real-time position, and judging whether the intelligent networked vehicle enters a preset intersection range according to whether the real-time position is in the preset intersection range;
and when the matching result is that the position information is not matched with the preset high-precision map, whether the intelligent networked vehicle enters the preset intersection range or not is judged according to whether the current position corresponding to the position information is within the preset intersection range or not.
The apparatus of the present invention calls the distributed intersection average delay estimation program stored in the memory 1005 by the processor 1001, and further performs the following operations:
when the matching result is that the position information is matched with the preset high-precision map, generating a real-time position, and matching the real-time position with the preset intersection range;
when the real-time position is within the range of the preset intersection, judging that the intelligent networked vehicle enters the range of the preset intersection;
and when the real-time position is out of the range of the preset intersection, judging that the intelligent networked vehicle does not enter the range of the preset intersection.
The apparatus of the present invention calls the distributed intersection average delay estimation program stored in the memory 1005 by the processor 1001, and further performs the following operations:
when the matching result is that the position information is not matched with the preset high-precision map, acquiring a current position corresponding to the position information, and matching the current position with the preset intersection range;
when the current position is within the preset intersection range, judging that the intelligent networked vehicle enters the preset intersection range;
and when the current position is out of the preset intersection range, judging that the intelligent network connection vehicle does not enter the preset intersection range.
The apparatus of the present invention calls the distributed intersection average delay estimation program stored in the memory 1005 by the processor 1001, and further performs the following operations:
when the intelligent networked vehicle enters the preset intersection range, acquiring the vehicle speed information of the intelligent networked vehicle in a preset statistical period, and acquiring the average vehicle speed of the intelligent networked vehicle running in the preset intersection range according to the vehicle speed information;
and acquiring the range length of the intersection, and estimating the average delay time of the intersection according to the range length of the intersection and the average vehicle speed.
The apparatus of the present invention calls the distributed intersection average delay estimation program stored in the memory 1005 by the processor 1001, and further performs the following operations:
when the intelligent networked vehicle enters the preset intersection range, acquiring the average speed of the p-th intelligent networked vehicle passing through the intersection in a preset statistical period, acquiring the speed of the p-th intelligent networked vehicle passing through the intersection for the kth time, and counting the total times;
according to the average speed of the p intelligent networked vehicle passing through the intersection, the speed of the p intelligent networked vehicle passing through the intersection is obtained for the k time, and the counted total times are used for obtaining the average speed of the intelligent networked vehicle running in the preset intersection range through the following formula:
wherein the content of the first and second substances,
the average speed of the p-th intelligent networked vehicle passing through the intersection is calculated,
is as follows
The speed of the p-th intelligent networked vehicle passing through the intersection is obtained,
is the total number of times of statistics, and is obtained by the following formula:
wherein the content of the first and second substances,
is the time period of a preset statistical period,
reporting cycle duration of vehicle speed for the intelligent networked vehicle。
The apparatus of the present invention calls the distributed intersection average delay estimation program stored in the memory 1005 by the processor 1001, and further performs the following operations:
acquiring the range length of the intersection and the free flow speed of the vehicle passing through the intersection;
and estimating the average delay time of the intersection according to the intersection range length, the free flow vehicle speed and the average vehicle speed by the following formula:
wherein the content of the first and second substances,
the average delay time of the intersection is,
the length of the range of the intersection is,
the free-stream speed of the vehicle passing through the intersection;
the average speed of the vehicle passing through the intersection.
According to the scheme, the position information of the intelligent networked vehicle is obtained in real time; matching the position information with a preset high-precision map, and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result; when the intelligent networked vehicle enters the preset intersection range, the average speed of the intelligent networked vehicle running in the preset intersection range is obtained, the average delay time of the intersection is estimated according to the average speed, the average delay time of the intersection can be accurately estimated in real time, and the traffic situation requirements of real-time perception and accurate perception are met, so that the running state of the intersection is accurately estimated in real time, and the vehicle is guided to run efficiently.
Based on the hardware structure, the embodiment of the distributed intersection average delay estimation method is provided.
Referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of the distributed intersection average delay estimation method of the present invention.
In a first embodiment, the distributed intersection average delay estimation method comprises the following steps:
and step S10, acquiring the position information of the intelligent networked vehicle in real time.
It should be noted that the position information is a real-time position of the intelligent internet vehicle in the road.
And step S20, matching the position information with a preset high-precision map, and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result.
It can be understood that the preset high-precision map is a preset map with high-precision map data, and whether the intelligent networked vehicle enters a preset intersection range can be determined by performing high-precision map matching on the intelligent networked vehicle, where the preset intersection range is a preset intersection plane range in a certain range, and generally may be a circular area with an intersection center as a circle center, or a cross plane area, or a corresponding range area set according to the type of an intersection, which is not limited in this embodiment.
And step S30, when the intelligent networked vehicle enters the preset intersection range, acquiring the average speed of the intelligent networked vehicle in the preset intersection range, and estimating the average delay time of the intersection according to the average speed.
It should be understood that when it is monitored that the intelligent networked vehicle enters the preset intersection range, the average vehicle speed of the intelligent networked vehicle running in the preset intersection range can be obtained, delay time can be estimated according to the average vehicle speed, and then the average delay time can be obtained, wherein the average vehicle speed is the average vehicle speed measured in real time in the running process of the intelligent networked vehicle entering the preset intersection range.
According to the scheme, the position information of the intelligent networked vehicle is obtained in real time; matching the position information with a preset high-precision map, and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result; when the intelligent networked vehicle enters the preset intersection range, the average speed of the intelligent networked vehicle running in the preset intersection range is obtained, the average delay time of the intersection is estimated according to the average speed, the average delay time of the intersection can be accurately estimated in real time, and the traffic situation requirements of real-time perception and accurate perception are met, so that the running state of the intersection is accurately estimated in real time, and the vehicle is guided to run efficiently.
Further, fig. 3 is a schematic flow chart of a second embodiment of the distributed intersection average delay estimation method of the present invention, and as shown in fig. 3, the second embodiment of the distributed intersection average delay estimation method of the present invention is proposed based on the first embodiment, and in this embodiment, the step S20 specifically includes the following steps:
and step S21, matching the position information with a preset high-precision map to generate a matching result.
The matching result between the corresponding position and the high-precision map is generated by matching the position information with a preset high-precision map.
And step S22, when the matching result is that the position information is matched with the preset high-precision map, generating a real-time position, and judging whether the intelligent networked vehicle enters the preset intersection range according to whether the real-time position is in the preset intersection range.
It can be understood that when the matching result is that the position information is matched with the preset high-precision map, the real-time position of the intelligent internet vehicle at the moment can be determined, and then whether the real-time position is within a preset road condition range can be judged, and whether the intelligent internet vehicle enters the preset intersection range can be determined according to the corresponding judgment result.
And step S23, when the matching result is that the position information is not matched with the preset high-precision map, judging whether the intelligent networked vehicle enters the preset intersection range according to whether the current position corresponding to the position information is in the preset intersection range or not.
It should be understood that, when the matching result is that the position information is not matched with the preset high-precision map, the corresponding current position can be determined according to the position information, so that whether the intelligent internet vehicle enters the preset intersection range is determined according to whether the current position is in the preset intersection range.
According to the scheme, the position information is matched with the preset high-precision map, and a matching result is generated; when the matching result is that the position information is matched with the preset high-precision map, generating a real-time position, and judging whether the intelligent networked vehicle enters a preset intersection range according to whether the real-time position is in the preset intersection range; when the matching result is that the position information is not matched with the preset high-precision map, whether the intelligent networked vehicle enters a preset intersection range or not is judged according to whether the current position corresponding to the position information is within the preset intersection range or not; the method can be combined with a high-precision map to carry out real-time and accurate estimation on the average delay time of the intersection, meets the requirements of real-time perception and accurate perception on the traffic situation, and improves the accuracy of the average delay estimation of the distributed intersection.
Further, fig. 4 is a schematic flow chart of a third embodiment of the distributed intersection average delay estimation method of the present invention, and as shown in fig. 4, the third embodiment of the distributed intersection average delay estimation method of the present invention is proposed based on the second embodiment, in this embodiment, the step S22 specifically includes the following steps:
and step S221, when the matching result is that the position information is matched with the preset high-precision map, generating a real-time position, and matching the real-time position with the preset intersection range.
It should be noted that, when the matching result is that the position information matches the preset high-precision map, a corresponding real-time position may be generated, so as to match the real-time position with the preset intersection range, that is, determine whether the real-time position is within the preset intersection range.
And step S222, when the real-time position is within the preset intersection range, judging that the intelligent networked vehicle enters the preset intersection range.
It can be understood that when the real-time position is within the preset intersection range, it can be determined that the intelligent networked vehicle has entered the preset intersection range.
And S223, when the real-time position is out of the preset intersection range, judging that the intelligent internet vehicle does not enter the preset intersection range.
It should be understood that when the real-time position is outside the preset intersection range, it may be determined that the intelligent networked vehicle does not enter the preset intersection range.
According to the scheme, when the matching result is that the position information is matched with the preset high-precision map, a real-time position is generated, and the real-time position is matched with the preset intersection range; when the real-time position is within the range of the preset intersection, judging that the intelligent networked vehicle enters the range of the preset intersection; when the real-time position is out of the range of the preset intersection, judging that the intelligent networked vehicle does not enter the range of the preset intersection; the method can be combined with a high-precision map to carry out real-time and accurate estimation on the average delay time of the intersection, and meets the requirements of real-time perception and accurate perception on the traffic situation.
Further, fig. 5 is a schematic flow chart of a fourth embodiment of the distributed intersection average delay estimation method of the present invention, and as shown in fig. 5, the fourth embodiment of the distributed intersection average delay estimation method of the present invention is proposed based on the second embodiment, in this embodiment, the step S23 includes the following steps:
and S231, when the matching result is that the position information is not matched with the preset high-precision map, acquiring a current position corresponding to the position information, and matching the current position with the preset intersection range.
It should be noted that, when the matching result is that the position information is not matched with the preset high-precision map, the position corresponding to the position information may be used as the current position, so as to match the current position with the preset intersection range, and determine whether the current position is within the preset intersection range.
And step S232, when the current position is within the preset intersection range, judging that the intelligent internet vehicle enters the preset intersection range.
It can be understood that, when the current position is within the preset intersection range, it can be determined that the intelligent networked vehicle has entered the preset intersection range, that is, is within the preset intersection range.
And step S233, when the current position is outside the preset intersection range, judging that the intelligent internet vehicle does not enter the preset intersection range.
It should be understood that when the current position is outside the preset intersection range, it can be determined that the intelligent networked vehicle does not enter the preset intersection range.
According to the scheme, when the matching result is that the position information is not matched with the preset high-precision map, the current position corresponding to the position information is obtained, and the current position is matched with the preset intersection range; when the current position is within the preset intersection range, judging that the intelligent networked vehicle enters the preset intersection range; when the current position is out of the preset intersection range, the intelligent networked vehicle is judged not to enter the preset intersection range, the average delay time of the intersection can be estimated accurately in real time, and the traffic situation requirements of real-time perception and accurate perception are met.
Further, fig. 6 is a schematic flow chart of a fifth embodiment of the distributed intersection average delay estimation method of the present invention, and as shown in fig. 6, the fifth embodiment of the distributed intersection average delay estimation method of the present invention is proposed based on the first embodiment, and in this embodiment, the step S30 specifically includes the following steps:
and S31, when the intelligent networked vehicle enters the preset intersection range, acquiring the vehicle speed information of the intelligent networked vehicle in a preset statistical period, and acquiring the average vehicle speed of the intelligent networked vehicle running in the preset intersection range according to the vehicle speed information.
It should be noted that the preset statistical period is a preset statistical period for counting vehicle speed information, and the vehicle speed information of the intelligent networked vehicle is acquired to obtain the vehicle speed corresponding to the intelligent networked vehicle, that is, the average vehicle speed running within the preset intersection range.
Further, the step S31 specifically includes the following steps:
when the intelligent networked vehicle enters the preset intersection range, acquiring the average speed of the p-th intelligent networked vehicle passing through the intersection in a preset statistical period, acquiring the speed of the p-th intelligent networked vehicle passing through the intersection for the kth time, and counting the total times;
according to the average speed of the p intelligent networked vehicle passing through the intersection, the speed of the p intelligent networked vehicle passing through the intersection is obtained for the k time, and the counted total times are used for obtaining the average speed of the intelligent networked vehicle running in the preset intersection range through the following formula:
wherein the content of the first and second substances,
the average speed of the p-th intelligent networked vehicle passing through the intersection is calculated,
is as follows
The speed of the p-th intelligent networked vehicle passing through the intersection is obtained,
is the total number of times of statistics, and is obtained by the following formula:
wherein the content of the first and second substances,
is the time period of a preset statistical period,
and reporting the cycle duration of the vehicle speed for the intelligent networked vehicle.
It can be understood that, for the statistics of the average speed of the intelligent networked vehicles, the time intervals are divided according to the signal period, map matching is performed according to the position information reported by the intelligent networked vehicles, for the intelligent networked vehicles in the intersection range, the movement speed of the intelligent networked vehicles is periodically obtained in real time, then, according to the time length of the vehicle passing through the intersection range as the statistical time length, all the speed values obtained in the time intervals are counted, and the average value is the average value of the intelligent networked vehicles passing through the intersection.
In a particular implementation, the average vehicle speed of a vehicle at an intersection passing through the intersection is estimated using the following formula:
in the above formula, the first and second carbon atoms are,
indicating the first within a statistical period
Average speed of the vehicle passing the intersection;
representing a statistical total number of vehicles;
representing a step function, when a vehicle arrives within a statistical period, thenEstimating according to the average vehicle speed of the vehicle, wherein the value is 1, otherwise, the value is 0, and the estimation cannot be carried out;
and
respectively representing the number of arrived intelligent networked vehicles and the number of arrived common vehicles in a statistical period;
and
respectively indicate the number of times within the statistical period
Average speed and average speed of intelligent networked vehicle
Average vehicle speed of a common vehicle.
Because the speed of ordinary vehicle can't obtain through the car networking technology in real time, consequently, the average speed of a vehicle passing crossing intelligence is estimated through the average speed of networking vehicle, promptly:
dividing both the numerator and denominator of equation (2) by
Then, there are:
from the formula (4), it can be seen that the number of the intelligent networked vehicles increases continuouslyIn a number substantially greater than that of ordinary vehicles, i.e.
At this time
The average vehicle speed calculation formula is formula (3), and the average vehicle speed of the vehicle passing through the intersection can be accurately estimated, so that the average delay of the intersection can be accurately estimated.
The method comprises the steps of counting the average speed of the intelligent networked vehicles, dividing time intervals according to signal periods, carrying out map matching according to position information reported by the intelligent networked vehicles, periodically acquiring the movement speed of the intelligent networked vehicles in an intersection range in real time, counting all speed values acquired in the time intervals according to the time length of the vehicles passing through the intersection as the counting time length, and calculating the average value of the speed values, namely the average value of the intelligent networked vehicles passing through the intersection.
In the above formula, the first and second carbon atoms are,
is shown as
The average speed of the intelligent networked vehicles passing through the intersection;
is shown as
Second obtaining of
The speed of the intelligent networked vehicle passing through the intersection;
the total number of statistics is expressed and is calculated by the following formula:
in the above formula, the first and second carbon atoms are,
a period of time representing the statistics is indicated,
the period duration of reporting the vehicle speed of the intelligent internet vehicle is represented, and is usually 100 milliseconds/time.
And step S32, acquiring the range length of the intersection, and estimating the average delay time of the intersection according to the range length of the intersection and the average vehicle speed.
In the concrete implementation, the length of the intersection range is the actual distance of the vehicle running in the intersection range, and the average delay time of the intersection can be estimated according to the length of the intersection range and the average vehicle speed.
Further, the step S32 includes the following steps:
acquiring the range length of the intersection and the free flow speed of the vehicle passing through the intersection;
and estimating the average delay time of the intersection according to the intersection range length, the free flow vehicle speed and the average vehicle speed by the following formula:
wherein the content of the first and second substances,
the average delay time of the intersection is,
the length of the range of the intersection is,
the free-stream speed of the vehicle passing through the intersection;
the average speed of the vehicle passing through the intersection.
It can be understood that the delay of the vehicle passing through the intersection occurs in the process from the beginning of the vehicle entering the intersection range to the end of the vehicle leaving the intersection, wherein the leaving means the range of the center point of the intersection from which the vehicle leaves; setting the intersection range length as L, and performing high-precision map matching on the intelligent networked vehicle according to the position information uploaded by the intelligent networked vehicle in real time; when the intelligent networked vehicle enters the intersection range, the vehicle speed of the intelligent networked vehicle starts to be counted in real time, the average vehicle speed of the intelligent networked vehicle passing the intersection is calculated according to the counted vehicle speed, and the delay time of the vehicle passing the intersection is estimated according to the time difference between the average vehicle speed and the free stream vehicle speed passing the intersection range.
According to the scheme, when the intelligent networked vehicle enters the preset intersection range, the vehicle speed information of the intelligent networked vehicle in a preset statistical period is collected, and the average vehicle speed of the intelligent networked vehicle running in the preset intersection range is obtained according to the vehicle speed information; the method comprises the steps of obtaining the range length of the intersection, estimating the average delay time of the intersection according to the range length of the intersection and the average vehicle speed, estimating the delay time of the vehicle passing through the intersection according to the time difference between the average vehicle speed and the free flow vehicle speed passing through the range length of the intersection, and meeting the traffic situation requirements of real-time sensing and accurate sensing, thereby carrying out real-time and accurate estimation on the running state of the intersection and guiding the vehicle to run efficiently.
Correspondingly, the invention further provides a distributed crossing average delay estimation device.
Referring to fig. 7, fig. 7 is a functional block diagram of a distributed intersection average delay estimation apparatus according to a first embodiment of the present invention.
In a first embodiment of the distributed intersection average delay estimation apparatus of the present invention, the distributed intersection average delay estimation apparatus includes:
and the position acquisition module 10 is used for acquiring the position information of the intelligent networked vehicle in real time.
And the judging module 20 is configured to match the position information with a preset high-precision map, and judge whether the intelligent internet vehicle enters a preset intersection range according to a matching result.
And the estimation module 30 is configured to obtain an average vehicle speed of the intelligent networked vehicle traveling within the preset intersection range when the intelligent networked vehicle enters the preset intersection range, and estimate an average delay time of the intersection according to the average vehicle speed.
The judging module 20 is further configured to match the position information with a preset high-precision map to generate a matching result; when the matching result is that the position information is matched with the preset high-precision map, generating a real-time position, and judging whether the intelligent networked vehicle enters a preset intersection range according to whether the real-time position is in the preset intersection range; and when the matching result is that the position information is not matched with the preset high-precision map, whether the intelligent networked vehicle enters the preset intersection range or not is judged according to whether the current position corresponding to the position information is within the preset intersection range or not.
The judging module 20 is further configured to generate a real-time position when the matching result is that the position information matches the preset high-precision map, and match the real-time position with the preset intersection range; when the real-time position is within the range of the preset intersection, judging that the intelligent networked vehicle enters the range of the preset intersection; and when the real-time position is out of the range of the preset intersection, judging that the intelligent networked vehicle does not enter the range of the preset intersection.
The judging module 20 is further configured to, when the matching result is that the position information is not matched with the preset high-precision map, obtain a current position corresponding to the position information, and match the current position with the preset intersection range; when the current position is within the preset intersection range, judging that the intelligent networked vehicle enters the preset intersection range; and when the current position is out of the preset intersection range, judging that the intelligent network connection vehicle does not enter the preset intersection range.
The estimation module 30 is further configured to acquire vehicle speed information of the intelligent networked vehicle within a preset statistical period when the intelligent networked vehicle enters the preset intersection range, and obtain an average vehicle speed of the intelligent networked vehicle running within the preset intersection range according to the vehicle speed information; and acquiring the range length of the intersection, and estimating the average delay time of the intersection according to the range length of the intersection and the average vehicle speed.
The estimation module 30 is further configured to acquire an average speed of the p-th intelligent networked vehicle passing through the intersection in a preset statistical period when the intelligent networked vehicle enters the preset intersection range, obtain the speed of the p-th intelligent networked vehicle passing through the intersection at the kth time, and count the total times;
according to the average speed of the p intelligent networked vehicle passing through the intersection, the speed of the p intelligent networked vehicle passing through the intersection is obtained for the k time, and the counted total times are used for obtaining the average speed of the intelligent networked vehicle running in the preset intersection range through the following formula:
wherein the content of the first and second substances,
the average speed of the p-th intelligent networked vehicle passing through the intersection is calculated,
is as follows
The speed of the p-th intelligent networked vehicle passing through the intersection is obtained,
is the total number of times of statistics, and is obtained by the following formula:
wherein the content of the first and second substances,
is the time period of a preset statistical period,
and reporting the cycle duration of the vehicle speed for the intelligent networked vehicle.
The estimation module 30 is further configured to obtain a range length of the intersection and a free-flow vehicle speed of the vehicle passing through the intersection;
and estimating the average delay time of the intersection according to the intersection range length, the free flow vehicle speed and the average vehicle speed by the following formula:
wherein the content of the first and second substances,
the average delay time of the intersection is,
the length of the range of the intersection is,
the free-stream speed of the vehicle passing through the intersection;
the average speed of the vehicle passing through the intersection.
The steps implemented by each functional module of the distributed intersection average delay estimation device can refer to each embodiment of the distributed intersection average delay estimation method of the present invention, and are not described herein again.
In addition, an embodiment of the present invention further provides a storage medium, where a distributed intersection average delay estimation program is stored on the storage medium, and when executed by a processor, the distributed intersection average delay estimation program implements the following operations:
acquiring the position information of the intelligent networked vehicle in real time;
matching the position information with a preset high-precision map, and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result;
when the intelligent networked vehicle enters the preset intersection range, the average speed of the intelligent networked vehicle running in the preset intersection range is obtained, and the average delay time of the intersection is estimated according to the average speed.
Further, when executed by the processor, the distributed intersection average delay estimation program further implements the following operations:
matching the position information with a preset high-precision map to generate a matching result;
when the matching result is that the position information is matched with the preset high-precision map, generating a real-time position, and judging whether the intelligent networked vehicle enters a preset intersection range according to whether the real-time position is in the preset intersection range;
and when the matching result is that the position information is not matched with the preset high-precision map, whether the intelligent networked vehicle enters the preset intersection range or not is judged according to whether the current position corresponding to the position information is within the preset intersection range or not.
Further, when executed by the processor, the distributed intersection average delay estimation program further implements the following operations:
when the matching result is that the position information is matched with the preset high-precision map, generating a real-time position, and matching the real-time position with the preset intersection range;
when the real-time position is within the range of the preset intersection, judging that the intelligent networked vehicle enters the range of the preset intersection;
and when the real-time position is out of the range of the preset intersection, judging that the intelligent networked vehicle does not enter the range of the preset intersection.
Further, when executed by the processor, the distributed intersection average delay estimation program further implements the following operations:
when the matching result is that the position information is not matched with the preset high-precision map, acquiring a current position corresponding to the position information, and matching the current position with the preset intersection range;
when the current position is within the preset intersection range, judging that the intelligent networked vehicle enters the preset intersection range;
and when the current position is out of the preset intersection range, judging that the intelligent network connection vehicle does not enter the preset intersection range.
Further, when executed by the processor, the distributed intersection average delay estimation program further implements the following operations:
when the intelligent networked vehicle enters the preset intersection range, acquiring the vehicle speed information of the intelligent networked vehicle in a preset statistical period, and acquiring the average vehicle speed of the intelligent networked vehicle running in the preset intersection range according to the vehicle speed information;
and acquiring the range length of the intersection, and estimating the average delay time of the intersection according to the range length of the intersection and the average vehicle speed.
Further, when executed by the processor, the distributed intersection average delay estimation program further implements the following operations:
when the intelligent networked vehicle enters the preset intersection range, acquiring the average speed of the p-th intelligent networked vehicle passing through the intersection in a preset statistical period, acquiring the speed of the p-th intelligent networked vehicle passing through the intersection for the kth time, and counting the total times;
according to the average speed of the p intelligent networked vehicle passing through the intersection, the speed of the p intelligent networked vehicle passing through the intersection is obtained for the k time, and the counted total times are used for obtaining the average speed of the intelligent networked vehicle running in the preset intersection range through the following formula:
wherein the content of the first and second substances,
the average speed of the p-th intelligent networked vehicle passing through the intersection is calculated,
for the kth time, the speed of the p-th intelligent networked vehicle passing through the intersection is obtained,
is the total number of times of statistics, and is obtained by the following formula:
wherein the content of the first and second substances,
is the time period of a preset statistical period,
and reporting the cycle duration of the vehicle speed for the intelligent networked vehicle.
Further, when executed by the processor, the distributed intersection average delay estimation program further implements the following operations:
acquiring the range length of the intersection and the free flow speed of the vehicle passing through the intersection;
and estimating the average delay time of the intersection according to the intersection range length, the free flow vehicle speed and the average vehicle speed by the following formula:
wherein the content of the first and second substances,
the average delay time of the intersection is,
the length of the range of the intersection is,
the free-stream speed of the vehicle passing through the intersection;
the average speed of the vehicle passing through the intersection.
According to the scheme, the position information of the intelligent networked vehicle is obtained in real time; matching the position information with a preset high-precision map, and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result; when the intelligent networked vehicle enters the preset intersection range, the average speed of the intelligent networked vehicle running in the preset intersection range is obtained, the average delay time of the intersection is estimated according to the average speed, the average delay time of the intersection can be accurately estimated in real time, and the traffic situation requirements of real-time perception and accurate perception are met, so that the running state of the intersection is accurately estimated in real time, and the vehicle is guided to run efficiently.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A distributed intersection average delay estimation method is characterized by comprising the following steps:
acquiring the position information of the intelligent networked vehicle in real time;
matching the position information with a preset high-precision map, and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result;
when the intelligent networked vehicle enters the preset intersection range, the average speed of the intelligent networked vehicle running in the preset intersection range is obtained, and the average delay time of the intersection is estimated according to the average speed.
2. The distributed intersection average delay estimation method according to claim 1, wherein the step of matching the position information with a preset high-precision map and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result comprises the steps of:
matching the position information with a preset high-precision map to generate a matching result;
when the matching result is that the position information is matched with the preset high-precision map, generating a real-time position, and judging whether the intelligent networked vehicle enters a preset intersection range according to whether the real-time position is in the preset intersection range;
and when the matching result is that the position information is not matched with the preset high-precision map, whether the intelligent networked vehicle enters the preset intersection range or not is judged according to whether the current position corresponding to the position information is within the preset intersection range or not.
3. The distributed intersection average delay estimation method according to claim 2, wherein when the matching result is that the position information matches the preset high-precision map, a real-time position is generated, and whether the intelligent internet-connected vehicle enters the preset intersection range is determined according to whether the real-time position is within the preset intersection range or not, the method comprises the following steps:
when the matching result is that the position information is matched with the preset high-precision map, generating a real-time position, and matching the real-time position with the preset intersection range;
when the real-time position is within the range of the preset intersection, judging that the intelligent networked vehicle enters the range of the preset intersection;
and when the real-time position is out of the range of the preset intersection, judging that the intelligent networked vehicle does not enter the range of the preset intersection.
4. The distributed intersection average delay estimation method according to claim 2, wherein when the matching result is that the position information is not matched with the preset high-precision map, according to whether the current position corresponding to the position information is within a preset intersection range or not, whether the intelligent internet vehicle enters the preset intersection range or not, comprises:
when the matching result is that the position information is not matched with the preset high-precision map, acquiring a current position corresponding to the position information, and matching the current position with the preset intersection range;
when the current position is within the preset intersection range, judging that the intelligent networked vehicle enters the preset intersection range;
and when the current position is out of the preset intersection range, judging that the intelligent network connection vehicle does not enter the preset intersection range.
5. The distributed intersection average delay estimation method according to claim 1, wherein when the intelligent networked vehicle enters the preset intersection range, acquiring an average vehicle speed of the intelligent networked vehicle traveling in the preset intersection range, and estimating an average delay duration of an intersection according to the average vehicle speed comprises:
when the intelligent networked vehicle enters the preset intersection range, acquiring the vehicle speed information of the intelligent networked vehicle in a preset statistical period, and acquiring the average vehicle speed of the intelligent networked vehicle running in the preset intersection range according to the vehicle speed information;
and acquiring the range length of the intersection, and estimating the average delay time of the intersection according to the range length of the intersection and the average vehicle speed.
6. The distributed intersection average delay estimation method according to claim 5, wherein when the intelligent networked vehicle enters the preset intersection range, acquiring vehicle speed information of the intelligent networked vehicle in a preset statistical period, and obtaining an average vehicle speed of the intelligent networked vehicle running in the preset intersection range according to the vehicle speed information comprises:
when the intelligent networked vehicle enters the preset intersection range, acquiring the average speed of the p-th intelligent networked vehicle passing through the intersection in a preset statistical period, acquiring the speed of the p-th intelligent networked vehicle passing through the intersection for the kth time, and counting the total times;
according to the average speed of the p intelligent networked vehicle passing through the intersection, the speed of the p intelligent networked vehicle passing through the intersection is obtained for the k time, and the counted total times are used for obtaining the average speed of the intelligent networked vehicle running in the preset intersection range through the following formula:
wherein the content of the first and second substances,
the average speed of the p-th intelligent networked vehicle passing through the intersection is calculated,
is as follows
The speed of the p-th intelligent networked vehicle passing through the intersection is obtained,
is the total number of times of statistics, and is obtained by the following formula:
wherein the content of the first and second substances,
is the time period of a preset statistical period,
and reporting the cycle duration of the vehicle speed for the intelligent networked vehicle.
7. The distributed intersection average delay estimation method according to claim 5, wherein the obtaining of the intersection range length and the estimation of the average delay duration of the intersection according to the intersection range length and the average vehicle speed comprise:
acquiring the range length of the intersection and the free flow speed of the vehicle passing through the intersection;
and estimating the average delay time of the intersection according to the intersection range length, the free flow vehicle speed and the average vehicle speed by the following formula:
wherein the content of the first and second substances,
the average delay time of the intersection is,
the length of the range of the intersection is,
the free-stream speed of the vehicle passing through the intersection;
the average speed of the vehicle passing through the intersection.
8. A distributed intersection average delay estimation device is characterized by comprising:
the position acquisition module is used for acquiring the position information of the intelligent networked vehicle in real time;
the judging module is used for matching the position information with a preset high-precision map and judging whether the intelligent networked vehicle enters a preset intersection range according to a matching result;
and the estimation module is used for acquiring the average speed of the intelligent networked vehicle running in the preset intersection range when the intelligent networked vehicle enters the preset intersection range, and estimating the average delay time of the intersection according to the average speed.
9. A distributed intersection average delay estimation device, characterized in that the distributed intersection average delay estimation device comprises: a memory, a processor and a distributed intersection average delay estimation program stored on the memory and executable on the processor, the distributed intersection average delay estimation program configured to implement the steps of the distributed intersection average delay estimation method according to any one of claims 1 to 7.
10. A storage medium having stored thereon a distributed intersection average delay estimation program, which when executed by a processor implements the steps of the distributed intersection average delay estimation method according to any one of claims 1 to 7.
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