CN110675630A - Method for determining minimum coverage rate of networked vehicles - Google Patents

Method for determining minimum coverage rate of networked vehicles Download PDF

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CN110675630A
CN110675630A CN201910950109.4A CN201910950109A CN110675630A CN 110675630 A CN110675630 A CN 110675630A CN 201910950109 A CN201910950109 A CN 201910950109A CN 110675630 A CN110675630 A CN 110675630A
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road network
mfd
coverage rate
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林晓辉
曹成涛
黄�良
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Guangdong Communications Polytechnic
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    • G—PHYSICS
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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
    • G08G1/0125—Traffic data processing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
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Abstract

The invention discloses a method for determining minimum coverage rate of networked vehicles based on MFD (Multi-function peripheral) in incomplete vehicle networking environment. The method comprises the steps of firstly utilizing a built vehicle networking simulation platform to allow the networking vehicle coverage rate P to gradually increase from a first preset value, estimating road network MFD under different coverage rates, then comparing the estimated road network MFD with the networking vehicle coverage rate of 100%, calculating the average absolute percentage error (MAPE) of road network MFD parameters under different coverage rates, determining the functional relation between the networking vehicle coverage rate P and the MAPE, taking MAPE not more than epsilon as a precision target, and finally determining the minimum coverage rate P of the networking vehiclemin。

Description

Method for determining minimum coverage rate of networked vehicles
Technical Field
The invention belongs to the technical field of road network traffic, and particularly relates to a method for determining the minimum coverage rate of a networked vehicle.
Background
With the rapid increase of automobile holding capacity, road supply cannot keep pace with the rise of traffic demand, the current situation of traffic jam is more and more severe, and the problem of how to relieve urban traffic jam becomes a worldwide problem. Recent studies have shown that there is a certain inherent link between the weighted traffic flow of the road network and the weighted traffic density of the road network, called MFDs (macroscopic fundamental maps). Through analysis and research of a large amount of actual data, the MFD of the road network is found to be closely related to the structure of the road network and is an inherent attribute of the road network.
The MFD is applied to the aspects of road network traffic state judgment, oversaturated road network control, congestion charging and the like by some scholars, so that urban traffic congestion is effectively prevented and relieved, but the MFD is accurately estimated on the premise of application.
The current MFD estimation methods include a fixed detector estimation method (LDD estimation method for short) and a floating car estimation method (FCD estimation method for short).
The LDD estimation method estimates the road network MFD based on the theory related to the road network MFD using traffic data collected by fixed detectors such as video detectors. The FCD estimation method estimates the MFD of the road network by using traffic data collected by floating cars (such as taxis, buses, etc.) and by using a driving track estimation method.
However, the application range of both the two estimation methods has certain limitations, for example, the LDD estimation method can only obtain traffic data of a part of main road sections, cannot obtain traffic data of road sections without fixed detectors, and has data loss; the low coverage of the floating car can affect the accuracy of the FCD estimation method.
In recent years, the Vehicle networking (CVN) has been rapidly developed, and a strong technical support is provided for more accurately estimating the MFD of the road Network. The vehicle networking realizes real-time information interaction between vehicles (V2V), vehicle and roadside facilities (V2R) and vehicle and intelligent command center (V2C) by means of various sensors, sensing equipment such as satellite positioning and the like, DSRC (Dedicated Short Range Communications, 5G and other communication technologies; the computer technology is adopted to store, analyze and process the traffic big data, carry out comprehensive intelligent monitoring, scheduling and management on people, vehicles and roads, and complete the application functions of traffic information release, traffic guidance, traffic management and control and the like.
Theoretically, all networked vehicles upload information such as positions, speeds and the like to a command center in real time through satellite positioning vehicle-mounted equipment in a vehicle networking environment, the networked vehicles are essentially floating vehicles with the coverage rate of 100%, but the networked vehicles cannot achieve full coverage of the vehicle networking at present, or partial networked vehicles become non-networked vehicles due to manual turning off of vehicle-mounted terminals, so that the situation that the networked vehicles and the non-networked vehicles coexist is caused, and the situation is defined as an incomplete vehicle networking environment.
In an incomplete vehicle networking environment, the networking vehicle coverage rate is too low, the precision of data acquisition is reduced, and the estimation accuracy of the MFD is affected. Therefore, on the premise of meeting the estimation accuracy requirement of the road network MFD, determining the minimum coverage rate of the networked vehicles has very important engineering application value.
Disclosure of Invention
The invention aims to provide a method for determining the minimum coverage rate of a networked vehicle so as to meet the requirement of the estimation accuracy of a road network MDF.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for determining minimum coverage of networked vehicles by using a vehicle networking simulation platform comprises the following steps:
calculating the road network MFD when the coverage rate of the networked vehicles is 100%, and marking as the standard road network MFD;
setting the coverage rate of the networked vehicles to be a first preset value;
calculating the road network MFD when the coverage rate of the networked vehicles is a first preset value, and recording as a variable road network MFD;
calculating an error between the standard road network MFD and the variable road network MFD;
judging whether the error is less than or equal to a maximum allowable error value;
if the error is less than or equal to the maximum allowable error value, the current value of the coverage rate of the networked vehicles is the minimum coverage rate;
if the error is larger than the maximum allowable error value, increasing a step preset increment of the networking vehicle coverage rate on the basis of the current value, and then re-calculating the road network MFD when the networking vehicle coverage rate is the current value, and marking as a variable road network MFD;
wherein the initial value of the current value is a first preset value.
Optionally, the calculating an error between the standard road network MFD and the variable road network MFD specifically includes:
the average absolute percentage error between the standard road network MFD and the variable road network MFD is calculated.
Optionally, the first preset value is equal to 1%, and the step preset increment is equal to 1%.
Optionally, the road network MFD is calculated using the following formula:
Figure BDA0002225498880000031
wherein q iswWeighting traffic flows, k, for road networkswWeighting the traffic density, i, l, for the road networkiNumber of road section i and length of the road section qiIs the traffic flow of the ith road section, kiIs the traffic density of the ith road segment.
Optionally, the road network MFD is calculated using the following formula:
Figure BDA0002225498880000032
wherein rho is the proportion of the floating cars in the road network,
Figure BDA0002225498880000033
to utilize the road network weighted traffic density estimated from floating car data,
Figure BDA0002225498880000034
for the road network weighted traffic flow estimated by using the floating car data, n 'is the number of the floating cars recorded in the acquisition period T, r is the total number of the road segments in the road network, T'jFor collecting the driving time l of the jth floating car in the period TiIs the length of road segment i, T is the acquisition period, d'jThe driving distance of the jth vehicle in the period T is acquired.
Optionally, the error between the standard road network MFD and the variable road network MFD is calculated, where the error includes a road network weighted traffic flow error and a road network weighted traffic density error, which are respectively marked as MAPE-qwAnd MAPE-kwSpecifically, the following formula is adopted for calculation:
Figure BDA0002225498880000041
wherein n is the number of the statistical interval time, i is the ith statistical interval time, and P is the current networking vehicle coverage rate;
Figure BDA0002225498880000042
when the networking vehicle coverage rate is 100%, the estimated road network weighted traffic flow of the ith statistical interval time;
Figure BDA0002225498880000043
when the networking vehicle coverage rate is P, the estimated road network weighted traffic flow is calculated at the ith statistical interval time;
Figure BDA0002225498880000044
when the coverage rate of the networked vehicles is 100%, the estimated road network weighted traffic density at the ith statistical interval time;
Figure BDA0002225498880000045
when the networking vehicle coverage rate is P, the estimated road network weighted traffic density of the ith statistical interval time is obtained.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
according to the method for determining the minimum coverage rate of the networked vehicles, provided by the embodiment of the invention, the road network traffic is simulated through the vehicle networking simulation platform, the error between the standard road network MFD and the variable road network MFD is calculated, and the minimum coverage rate of the networked vehicles is finally determined according to the maximum allowable error value, so that the estimation precision requirement of the road network MFD is met in the incomplete vehicle networking environment.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
The structures, ratios, sizes, and the like shown in the present specification are only used for matching with the contents disclosed in the specification, so that those skilled in the art can understand and read the present invention, and do not limit the conditions for implementing the present invention, so that the present invention has no technical significance, and any structural modifications, changes in the ratio relationship, or adjustments of the sizes, without affecting the functions and purposes of the present invention, should still fall within the scope covered by the contents disclosed in the present invention.
Fig. 1 is a flowchart of a method for determining minimum coverage of a networked vehicle according to an embodiment of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the embodiments described below are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Please refer to fig. 1.
The embodiment provides a method for determining the minimum coverage rate of networked vehicles, which is applied to incomplete vehicle networking environments and determines the minimum coverage rate of networked vehicles by using a vehicle networking simulation platform.
The method for determining the minimum coverage rate of the networked vehicles comprises the following steps:
s10, calculating the road network MFD when the networking vehicle coverage rate is 100%, marking as the standard road network MFD,
s11, setting the coverage rate of the networked vehicles to be a first preset value;
s12, calculating the road network MFD when the coverage rate of the networked vehicles is a first preset value, and recording the road network MFD as a variable road network MFD;
s13, calculating the error between the standard road network MFD and the variable road network MFD;
s14, judging whether the error is less than or equal to the maximum allowable error value;
s15, if the error is less than or equal to the maximum allowable error value, the current value of the coverage rate of the networked vehicles is the minimum coverage rate;
and S16, if the error is larger than the maximum allowable error value, increasing the networking vehicle coverage by a step preset increment on the basis of the current value, and then returning to execute the step S12.
The initial value of the current value is a first preset value.
Because the car networking is still in the research stage at present, it is still difficult to develop experimental research by building a real car networking environment. In the embodiment, an actual road network intersection group is used as a research area, and a vehicle networking simulation platform based on Vissim traffic simulation software is built by collecting basic data such as road network layout conditions, traffic flow data and signal control schemes. And simulating the environment of the Internet of vehicles by reading the information such as the position, the speed and the like of each vehicle in the simulated road network in real time.
In the vehicle networking simulation platform, each vehicle in a road network uploads information such as speed, position and the like to a control center in real time, and then various traffic parameters are acquired, so that the platform does not consider the conditions of vehicle-vehicle communication or vehicle-road cooperation and the like, and is essentially a floating vehicle simulation platform with a high proportion.
Specifically, in step S10, all vehicles are defined as networked vehicles through the simulation platform, i.e., the networked vehicle coverage is equal to 100%.
In step S11, the networking vehicle coverage is set to a first preset value, in this embodiment, the first preset value is equal to 1%, that is, the road network MFD when the networking vehicle coverage is 1% is calculated.
Therefore, in step S10 and step S12, either of the following two methods can be used to calculate the standard road network MFD and the variable road network MFD.
The first method is to calculate the road network MFD by using the following formula:
Figure BDA0002225498880000071
wherein q iswWeighting traffic flow of a road network, wherein the unit is veh/h; k is a radical ofwWeighting traffic density for road network, with unit of veh/km, i, liThe number i of the road section and the length of the road section are respectively, and the unit is km and qiIs the traffic flow of the ith road section and has the unit of veh/h, kiThe unit is the traffic density of the ith road section, and is veh/km.
The second method is to calculate the road network MFD by using the following formula, that is, obtaining the road network MFD by using a floating car data estimation method, assuming that the proportion ρ of the floating cars in the road network is known and is uniformly distributed in each area in the road network:
Figure BDA0002225498880000072
wherein,
Figure BDA0002225498880000073
the road network weighted traffic density estimated by using floating car data is expressed in the unit of veh/km,
Figure BDA0002225498880000074
the road network weighted traffic flow estimated by using the floating car data is given by veh/h, n 'is the number of the floating cars recorded in the acquisition period T, r is the total number of the road segments in the road network, T'jThe running time of the jth floating car in the cycle T is acquired in units of s and liIs the length of the road section i in m, and T is the acquisition period in s, d'jThe unit is m, which is the running distance of the jth vehicle in the acquisition period T.
In step S13, an error between the standard road network MFD and the variable road network MFD is calculated. In the present embodiment, the error is an average absolute percentage error between the standard road network MFD and the variable road network MFD.
Specifically, the average absolute percentage error comprises a road network weighted traffic flow error and a road network weighted traffic density error, which are respectively marked as MAPE-qwAnd MAPE-kwIn particular to adoptCalculated using the following formula:
Figure BDA0002225498880000081
wherein n is the number of the statistical interval time, i is the ith statistical interval time, and P is the current networking vehicle coverage rate;
Figure BDA0002225498880000082
when the networking vehicle coverage rate is 100%, the unit of the road network weighted traffic flow estimated by the ith statistical interval time is veh/h;
when the networking vehicle coverage rate is P, the unit of the road network weighted traffic flow estimated by the ith statistical interval time is veh/h;
Figure BDA0002225498880000084
when the coverage rate of the networked vehicles is 100%, the weighted traffic density of the road network estimated by the ith statistical interval time is in a unit of veh/km;
Figure BDA0002225498880000085
when the networking vehicle coverage rate is P, the unit of the weighted traffic density of the road network estimated by the ith statistical interval time is veh/km.
Therefore, it is determined whether the error is equal to or less than the maximum allowable error value through step S14. The maximum allowed error value is expressed as ε, which may be 1%, 2%, 3%, 4%, 5%, and the like.
When the error is smaller than or equal to the maximum allowable error value, namely the average absolute percentage error meets the requirement, the current value of the coverage rate of the networked vehicles is the minimum coverage rate.
When the error is larger than the maximum allowable error value, namely the average absolute percentage error does not meet the requirement, the coverage rate of the networked vehicles needs to be increased so as to carry out the loop iteration calculation.
Specifically, during the loop iteration calculation, the networked vehicle coverage rate is increased by a preset incremental step, and then the step S12 is executed. In this embodiment, the step preset increment is equal to 1%.
In summary, the present application provides a method for determining a minimum coverage rate of a networked vehicle based on an MFD in an incomplete vehicle networking environment. The method comprises the steps of firstly utilizing a built vehicle networking simulation platform to allow the networking vehicle coverage rate P to gradually increase from a first preset value, estimating road network MFD under different coverage rates, then comparing the estimated road network MFD with the networking vehicle coverage rate of 100%, calculating the average absolute percentage error (MAPE) of road network MFD parameters under different coverage rates, determining the functional relation between the networking vehicle coverage rate P and the MAPE, taking MAPE not more than epsilon as a precision target, and finally determining the minimum coverage rate P of the networking vehiclemin。
The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. The terms "comprises," "comprising," "including," and "having" are intended to be inclusive and therefore specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. The method steps, processes, and operations described herein are not to be construed as necessarily requiring their performance in the particular order discussed and illustrated, unless explicitly indicated as an order of performance. It should also be understood that additional or alternative steps may be employed.
When an element or layer is referred to as being "on" … … "," engaged with "… …", "connected to" or "coupled to" another element or layer, it can be directly on, engaged with, connected to or coupled to the other element or layer, or intervening elements or layers may also be present. In contrast, when an element or layer is referred to as being "directly on … …," "directly engaged with … …," "directly connected to" or "directly coupled to" another element or layer, there may be no intervening elements or layers present. Other words used to describe the relationship of elements should be interpreted in a similar manner (e.g., "between … …" and "directly between … …", "adjacent" and "directly adjacent", etc.). As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items. Although the terms first, second, third, etc. may be used herein to describe various elements, components, regions, layers and/or sections, these elements, components, regions, layers and/or sections should not be limited by these terms. These terms may be only used to distinguish one element, component, region or section from another element, component, region or section. Unless clearly indicated by the context, use of terms such as the terms "first," "second," and other numerical values herein does not imply a sequence or order. Thus, a first element, component, region, layer or section discussed below could be termed a second element, component, region, layer or section without departing from the teachings of the example embodiments.
Spatially relative terms, such as "inner," "outer," "below," "… …," "lower," "above," "upper," and the like, may be used herein for ease of description to describe a relationship between one element or feature and one or more other elements or features as illustrated in the figures. Spatially relative terms may be intended to encompass different orientations of the device in addition to the orientation depicted in the figures. For example, if the device in the figures is turned over, elements described as "below" or "beneath" other elements or features would then be oriented "above" the other elements or features. Thus, the example term "below … …" can encompass both an orientation of facing upward and downward. The device may be otherwise oriented (rotated 90 degrees or at other orientations) and the spatially relative descriptors used herein interpreted.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (6)

1. A method for determining minimum coverage of networked vehicles is characterized in that the minimum coverage of networked vehicles is determined by using a vehicle networking simulation platform, and the method comprises the following steps:
calculating the road network MFD when the coverage rate of the networked vehicles is 100%, and marking as the standard road network MFD;
setting the coverage rate of the networked vehicles to be a first preset value;
calculating the road network MFD when the coverage rate of the networked vehicles is a first preset value, and recording as a variable road network MFD;
calculating an error between the standard road network MFD and the variable road network MFD;
judging whether the error is less than or equal to a maximum allowable error value;
if the error is less than or equal to the maximum allowable error value, the current value of the coverage rate of the networked vehicles is the minimum coverage rate;
if the error is larger than the maximum allowable error value, increasing a step preset increment of the networking vehicle coverage rate on the basis of the current value, and then re-calculating the road network MFD when the networking vehicle coverage rate is the current value, and marking as a variable road network MFD;
wherein the initial value of the current value is a first preset value.
2. The method as claimed in claim 1, wherein said calculating an error between said standard road network MFD and said variable road network MFD is specifically:
the average absolute percentage error between the standard road network MFD and the variable road network MFD is calculated.
3. The method as claimed in claim 1, wherein the first preset value is equal to 1%, and the step preset increment is equal to 1%.
4. The method for determining the minimum coverage of the networked vehicles according to claim 1, wherein the road network MFD is calculated by adopting the following formula:
Figure FDA0002225498870000011
wherein q iswWeighting traffic flows, k, for road networkswWeighting the traffic density, i, l, for the road networkiNumber of road section i and length of the road section qiIs the traffic flow of the ith road section, kiIs the traffic density of the ith road segment.
5. The method for determining the minimum coverage of the networked vehicles according to claim 1, wherein the road network MFD is calculated by adopting the following formula:
Figure FDA0002225498870000021
wherein rho is the proportion of the floating cars in the road network,to utilize the road network weighted traffic density estimated from floating car data,
Figure FDA0002225498870000025
for the road network weighted traffic flow estimated by using the floating car data, n 'is the number of the floating cars recorded in the acquisition period T, r is the total number of the road segments in the road network, T'jFor collecting the driving time l of the jth floating car in the period TiIs the length of the section i, TIs the collection period, d'jThe driving distance of the jth vehicle in the period T is acquired.
6. The method as claimed in claim 1, wherein said calculating error between said standard MFD and said variable MFD comprises road network weighted traffic flow error and road network weighted traffic density error, respectively labeled MAPE-qwAnd MAPE-kwSpecifically, the following formula is adopted for calculation:
wherein n is the number of the statistical interval time, i is the ith statistical interval time, and P is the current networking vehicle coverage rate;
Figure FDA0002225498870000031
when the networking vehicle coverage rate is 100%, the estimated road network weighted traffic flow of the ith statistical interval time;
Figure FDA0002225498870000032
when the networking vehicle coverage rate is P, the estimated road network weighted traffic flow is calculated at the ith statistical interval time;
Figure FDA0002225498870000033
when the coverage rate of the networked vehicles is 100%, the estimated road network weighted traffic density at the ith statistical interval time;
Figure FDA0002225498870000034
when the networking vehicle coverage rate is P, the estimated road network weighted traffic density of the ith statistical interval time is obtained.
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