CN111581538A - Highway charging data-based high-speed traffic flow state inference method - Google Patents

Highway charging data-based high-speed traffic flow state inference method Download PDF

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CN111581538A
CN111581538A CN202010276712.1A CN202010276712A CN111581538A CN 111581538 A CN111581538 A CN 111581538A CN 202010276712 A CN202010276712 A CN 202010276712A CN 111581538 A CN111581538 A CN 111581538A
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翁小雄
廖浩霖
谢志鹏
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South China University of Technology SCUT
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Abstract

The invention provides a high-speed traffic flow state inference method based on highway charging data, which comprises the following steps: restoring a vehicle running path according to the information of the entrance and the exit and the identification station in the charging data; decomposing the running state of the vehicles and solving the average speed of each vehicle on the main line; obtaining traffic flow of each road section; calculating the average speed of all vehicles in each road section; and (4) deducing the traffic flow state by combining the traffic flow of each road section and the average speed of all vehicles in each road section. The running route condition of the vehicle is restored by using the charging data, and then the position information of the vehicle is estimated according to the running mileage and the time, so that the position conditions of different road sections in different time periods of all vehicles are obtained, and the traffic flow state on the expressway network is deduced. The invention considers the conditions of ramp, intercommunication and the like, reduces the error caused by the limitation of the charging data, and can obtain more accurate traffic flow state.

Description

Highway charging data-based high-speed traffic flow state inference method
Technical Field
The invention relates to highway traffic state inference, in particular to a highway traffic flow state inference method based on highway charging data.
Background
With the development of national transportation, the highway network has become an important passenger flow logistics channel in the transportation system. With the coming of the information-oriented era, people increasingly demand information services such as highway conditions and the like, and the information utilization of the highway is more and more important. Evaluating the high-speed traffic flow state is a way to make the road condition more clearly reflected.
Traffic flow mainly includes flow, speed and density. The flow, speed and density of each road section in different time periods are obtained, and the traffic state of the road section can be judged through an evaluation method. The traffic state can provide a path decision for road users on one hand to avoid overlarge long-term flow of certain road sections, and on the other hand can provide a basis for decision of related departments, and policies such as differentiated charging and the like are provided by utilizing the traffic state to guide vehicles to avoid the road sections which are congested all the year round, so that a proper amount of loss is reduced for high speed of loss operation.
Highway toll data is a common source of data for which high-speed research has been conducted in recent years. But how to make correct use of the charging data is important. The charging data generally includes information on the names and times of entrance stations, the names and times of exit stations, route identification station information, vehicle types, and vehicle types. The current method in common use is to assume that the vehicle is traveling on the shortest path at high speed or to study only certain high speeds. The conditions of ramp, intercommunication and the like are not generally considered when the journey is researched, and the deviation always exists because the charging data is difficult to embody.
Therefore, it is necessary to design a method for restoring the actual driving path of the vehicle, finding information of ramp and intercommunication by restoring the path condition, and reducing the error caused by the limitation of the charging data, so as to more accurately obtain the traffic flow state of the expressway network and provide basis for better decision making.
Disclosure of Invention
The invention provides a highway charging data-based high-speed traffic flow state inference method, which completes the driving track of vehicles, restores the driving condition of each vehicle and obtains the traffic flow states of different road sections of a highway in different time periods through calculation.
The purpose of the invention is realized by the following technical scheme.
A high-speed traffic flow state inference method based on highway charging data comprises the following steps:
restoring a vehicle running path according to the information of the entrance and the exit and the identification station in the charging data;
decomposing the running state of the vehicles and solving the average speed of each vehicle on the main line;
obtaining traffic flow of each road section;
calculating the average speed of all vehicles in each road section;
and (4) deducing the traffic flow state by combining the traffic flow of each road section and the average speed of all vehicles in each road section.
Further, the restoring the vehicle path information according to the entrance and exit information and the identification station information in the charging data specifically includes:
and establishing a vehicle travel list by using the information of the entrance and the exit of the charging data and the identification station, searching possible paths for the adjacent high speed and entrance and exit in the travel list through a breadth-first search algorithm, finally summarizing the possible paths into a possible path set from all the entrances to the exits, and selecting one path as a real path in the possible path set according to the path mileage.
Further, the breadth-first search algorithm is that each path stores its own passed node, and sets a search stop threshold, when an effective path is searched, records the number of traversal layers, i.e., the number of steps, and then continues to search for 2-3 layers, if no new effective path can be found under the branch, the branch search is stopped, and when all branches reach the threshold, the path search is ended.
And further, respectively calculating the mileage of each route in the possible route set, comparing the mileage with the vehicle driving mileage in the data, wherein the obtained route with the minimum mileage difference value is the final real route to be selected, the mileage difference value is +/-500 m, if the mileage difference value is not within the range, the correct real route cannot be found, and the data is judged to be abnormal.
Further, the running states of the vehicles on different road sections are divided according to different acceleration, and the average speed of each vehicle on the main line is calculated by combining travel time and speed information recorded in the charging data.
Further, the running states of the vehicle on different road sections include: the vehicle starts to perform uniform acceleration movement from the entrance toll station and reaches the main line running speed after the main line is accelerated; when the vehicle leaves the high speed, the vehicle starts to uniformly decelerate a certain distance before entering an exit ramp until entering an exit toll station through the exit ramp, and then exits the station or leaves the station through an ETC channel after queuing; when a vehicle is to transfer high speed through an interchange, the vehicle starts to decelerate before reaching a ramp, runs at a constant speed in the ramp, and accelerates to a main line running speed after leaving the ramp, wherein the main line average running speed value is not calculated, an initial value is set for the accelerated main line running speed value according to the type of the vehicle, the initial value is used for carrying out first calculation to obtain the main line average speed, and then the main line average speed is brought into the accelerated main line running speed, so that the set final speed of accelerated motion and the average main line speed are closer to each other through two calculations, and the actual running process is more consistent;
the vehicle charging mode on the expressway comprises cash charging and Electronic Toll Collection (ETC), the time of the vehicle passing through a toll station is recorded in charging data, and the time of high speed access is calculated as follows:
Figure BDA0002445044190000021
Figure BDA0002445044190000031
wherein the time for entering the high speed is tenTime t from high speedexThe number of the exit artificial lanes is n, the charging time of each vehicle is s seconds, the flow of the artificial charging vehicles is Q, the length of a main line is m meters when the speed is increased or reduced, and the length of an entrance ramp is renThe length of the exit ramp is rexETC lane speed limit v0The final acceleration speed and the initial deceleration speed are vt，
Let the vehicle running speed of interchange be vsTo calculate the time t required for passing through the interchangesThe formula is as follows:
Figure BDA0002445044190000032
namely, the running time t of the vehicle on the main line can be calculatedm＝t-ten-tex-tsWhere t represents the total travel time of the vehicle, obtainable from the charging data,
the driving mileage of the vehicle in the charge data includes the mileage of the main line and the access ramp, and if the length of the main line is L and the driving mileage in the charge data is L, L + ren+rex，
Assuming that the vehicle passes c interchange, the average speed v of the vehicle on the main line can be obtained:
Figure BDA0002445044190000033
further, the traffic flow of each road section is obtained, the starting and ending time of the vehicle passing each road section is determined according to the running speed of the vehicle in each road section and the corresponding running time, the time period of the vehicle passing each road section is obtained, and then the number of vehicles of each road section in different time periods, namely the traffic flow, can be calculated.
Further, selecting data of vehicles entering and leaving through one or two toll stations adjacent to a road section needing to be counted, calculating the average speed of each vehicle, then adding speed values into speed sets of road sections passing through different time periods, increasing the counting length if empty sets occur, processing abnormal values of all the speed sets to obtain available sets, averaging to obtain the average speed of the road section
Figure BDA0002445044190000034
Further, the abnormal value is processed by a box diagram method in the interval (Q)3+1.5(Q3-Q1) , + ∞) or [0, Q1-1.5(Q3-Q1) Values within) are abnormal values, Q1Is the lower quartile, Q3Is the upper quartile.
Further, the relationship between the flow rate and the average speed of the section is as follows,
Figure BDA0002445044190000041
wherein v isfThe average speed of the vehicle when the vehicle is unblocked, Q is the road section flow, K is the road section density, and whether the road section is blocked or unblocked can be inferred by comparing the road section density with the blocking density of the road section.
Compared with the prior art, the invention has the following beneficial effects:
the method comprises the steps of considering the conditions of ramps, intercommunication and the like, utilizing the charging data to restore the running path condition of the vehicle, reducing errors caused by limitation of the charging data, then estimating the position information of the vehicle according to the running mileage and the time to obtain the position conditions of different road sections of all vehicles in different time periods, thereby estimating the traffic flow state on the expressway network and estimating the congestion condition. The traffic flow state of the expressway network can be obtained more accurately, and basis is provided for better decision making.
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Fig. 1 is a flowchart of a method for inferring a high-speed traffic flow state according to an embodiment of the present invention.
FIG. 2 is a schematic view of a high speed doorway according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a highway section according to an embodiment of the invention.
Detailed Description
And step 1, restoring vehicle path information according to the entrance and exit and identification station information in the charging data.
Step 1.1, Path search
And establishing a vehicle travel list by using the information of the entrance and the exit of the charging data and the identification station, searching possible paths for the adjacent high speed and entrance and exit in the travel list through a breadth-first search algorithm, finally summarizing the possible paths into a possible path set from all the entrances to the exits, and selecting one path as a real path in the possible path set according to the path mileage.
And acquiring the head and the tail of the path by using the information of the entrance and the exit in the record, and supplementing the path condition by the information of the passing identification station. The first two digits of the number of the identification station are the number of the highway section, so that the identification station can be regarded as a high-speed name, and the target from the starting point to the end point is decomposed into a path combination between every two high speeds. The method for path finding is an improved breadth-first search algorithm. The basic breadth-first search method cannot search the remaining adjacent nodes of the previous level or nodes that have been previously searched because a common set of traversed nodes is used. The improved search algorithm considers that each path stores own traversed nodes instead of global traversed nodes, so that each path can be searched without being interfered by other paths. However, this may cause repeated searching of useless paths, resulting in a problem that the search cannot converge, and the search can be stopped only when all paths are searched through the entire network, so that the search stop threshold needs to be increased. When an effective path is searched, the number of traversal layers, namely the number of steps, is recorded, then 2-3 layers are continuously searched, if no new effective path can be found under the branch, the branch search is stopped, and when all the branches stop searching (namely all the branches reach the search stop threshold value), the path search is ended. Before the path is restored, each high speed can be directly reached, a high-speed graph is established, and the execution of a search algorithm is facilitated. The breadth-first search algorithm adopted in this embodiment is the same as the basic breadth-first search algorithm, and is to search for all different reachable paths, where there may be more than one search result for each segment, and all possible situations need to be combined to form a complete path set, and then to perform the next determination.
Step 1.2, path selection:
the path selection is to select the searched path set and find out the path which best accords with the real vehicle path. Because the mileage of different routes is different, and the data contains the mileage, only the mileage in the selected route can be compared with the original data. And respectively calculating the mileage of all the routes in the route set, and then taking the route with the minimum difference value with the vehicle driving mileage in the original data as the finally selected route. The mileage difference is allowed to be ± 500m in consideration of the accumulated error. If the error is exceeded, the correct path is not found, and the data is determined to be abnormal.
Step 2, decomposing the running state of the vehicles and solving the average speed of each vehicle on the main line
Step 2.1, analysis of vehicle running state
Referring to fig. 2, the section of the vehicle traveling at high speed includes an entrance ramp (en1, en2), an exit ramp (ex2, ex3), a high-speed main line (m1, m2), a distance between the same entrance and exit (p2), and an interchange connecting different high speeds.
The vehicle is in uniform acceleration running before entering the main line, and in uniform deceleration running after leaving the main line. Because neither the entrance ramp nor the interchange can reach the speed of the main line at a constant speed, the acceleration and deceleration process is realized in the ramp range and occupies part of the road section of the main line. The interchange is different from the entrance ramp, because of the speed limit, the vehicle can be considered to run at a constant speed in the ramp, and the acceleration and deceleration are carried out before entering the interchange and after leaving the interchange. The method specifically comprises the following steps: the vehicle starts to perform uniform acceleration movement from the entrance toll station and reaches the main line running speed after the main line is accelerated; when the vehicle leaves the high speed, the vehicle starts to uniformly decelerate a certain distance before entering an exit ramp until entering an exit toll station through the exit ramp, and then exits the station or leaves the station through an ETC channel after queuing; when the vehicle is to transfer high speed through the interchange, the vehicle starts to decelerate before reaching the ramp, runs at a constant speed in the ramp, and accelerates to a main line running speed after leaving the ramp, wherein the main line average running speed value is not calculated, an initial value is set for the accelerated main line running speed value according to the type of the vehicle, the initial value is used for carrying out first calculation to obtain the main line average speed, and then the main line average speed is substituted into the accelerated main line running speed.
Step 2.2, vehicle travel time analysis
The vehicle charging method is classified into cash charging and Electronic Toll Collection (ETC). The time when the vehicle passes the toll station, i.e. the moment when the vehicle passes the lifting bar, is recorded in the toll data. ETC toll collection vehicles have the characteristic of no parking and pass through toll stations according to the speed limit of ETC channels. The cash charging needs to enter a manual charging channel to queue for card taking and payment. Because the time of the data recording and the queuing payment time of the outlet are calculated in the total travel time, the cash charging vehicle needs to calculate the queuing time in addition to the time mentioned above. The time for high speed of entrance and exit can be obtained by the following equation.
Figure BDA0002445044190000061
Figure BDA0002445044190000062
Wherein the time for entering the high speed is tenHigh speed departure time texThe number of the exit artificial lanes is n, the charging time of each vehicle is s seconds, the flow of the artificial charging vehicles is Q, the length of a main line is m meters when the speed is increased or reduced, and the length of an entrance ramp is renThe length of the exit ramp is rexETC lane speed limit v0The final acceleration speed and the initial deceleration speed are vt。
Let the vehicle running speed of interchange be vsThe length of the interchange is rsTo calculate the time t required for passing through the interchanges。
Figure BDA0002445044190000063
Calculating the time of non-main line, total travel time in data, and main line running time tmNaturally comes out.
tm＝t-ten-tex-ts
Step 2.3, analyzing and calculating the driving speed of the bicycle:
because the initial and final speeds of the speed changing process are set, the running speed of the interchange is limited, and calculation is not needed. The speed is obtained under the condition of known time, and the driving mileage of a main line of the vehicle needs to be obtained.
Unlike the travel time, the driving mileage in the data is not the mileage on the main line nor the complete distance between the toll station landing bars, but includes the main line and the entrance ramp, and does not include the mileage of the interchange length. Let the length of the main line be L and the mileage in the data be L, there is the following equation.
L＝l+ren+rex
According to the kinematic formula, and assuming that the vehicle passes through c interchange, the average speed of the vehicle on the main line can be obtained.
Figure BDA0002445044190000064
Step 3, solving the traffic flow of each road section:
and determining the starting and ending moments when the vehicle passes through each road section according to the running speed of the vehicle on each road section and the corresponding running time, and obtaining the time period when the vehicle passes through each road section. All vehicles are counted by the same method, and the number of vehicles in each road section in different time periods is obtained, namely the traffic flow. The method comprises the following specific steps:
the time that the vehicle passes through the road section can be deduced according to the running speed of the vehicle at each road section and the time of entering the road section. The details are as follows.
Referring to fig. 3, assume that the vehicle enters a high speed at point 1 and leaves the high speed at point 6 in fig. 3. Let the time of the vehicle at point i be TiDistance between two points by da,bTo express, it can be known that the high speed main line length that the vehicle passes through is d16We need to ask the vehicle to be in d12、d34、d34And d56Which Δ T periods, i.e. the time at which each point in the map needs to be obtained, have elapsed. On the premise that the vehicle performs uniform motion on the main line, the following formula can be provided:
Figure BDA0002445044190000071
wherein, Ti+1The departure time of the link, i.e. the starting time of the next link, T, is indicatediIndicates the starting time of the road section, di,i+1Indicating the distance of this road segment.
Namely, the time when the crossing is passed can be obtained only by knowing the time when the crossing is passed. E.g. dj,j+1The following time calculation formula can be obtained by combining the physical kinematics formula according to the method mentioned above and by using a section of interchange (including acceleration and deceleration road sections) passed by the vehicle:
Figure BDA0002445044190000072
where m is the acceleration and deceleration distance of the main line occupied by the vehicle, vrIs the average speed of the vehicle in the overpass, Tj+1Shows the departure time, T, of the linkjIndicating the starting moment of this section.
By combining the two formulas, the traffic of the different road sections can be known by traversing the vehicles in the records on which road sections the vehicles are in different time periods.
And 4, calculating the average speed of all vehicles in each road section.
The average speed is calculated using vehicles entering and exiting one to two toll booths before and after the section of road.
The link average speed refers to the average speed of the overall traffic flow on the link. Vehicles traveling at high speeds over a stretch of road are many, including long and short haul. The long-distance vehicle may not reach the expected speed due to many reasons, such as traffic jam, service area rest, emergency stop, etc. due to the distance. Therefore, only vehicles entering and exiting from toll stations adjacent to the road section are extracted for calculation when the average speed is calculated. Selecting data of vehicles entering and leaving through one or two toll stations adjacent to a road section needing to be counted, calculating the average speed of each vehicle, and then adding the speed value to the speed of the road section passing through different time periodsIn the degree set, if an empty set appears, the statistical length is increased, all speed sets are processed by abnormal values to obtain an available set, and the average value is obtained to obtain the average speed of the road section
Figure BDA0002445044190000081
Since the data is full sample data, data with a large error inevitably exists, and it is necessary to exclude an abnormal speed vehicle so as not to affect the overall situation. Here a box graph is used to reject outliers.
Let the quarter-quantile of the velocity set be Q1Three quarters digit of Q3From the properties of the box chart, the interval in which the abnormal value can be obtained is (Q)3+1.5(Q3-Q1) , + ∞) or [0, Q1-1.5(Q3-Q1))。
Using section di,i+1The speed of the OD traveling vehicles at the two toll stations and the downstream toll station is processed by abnormal values to determine the average speed of the vehicles on the road section,
Figure BDA0002445044190000082
s is the number of vehicles in the normal speed range, viRespectively representing the velocity value of each vehicle.
Step 5, deducing the traffic flow state
And deducing the state of the road section through the relation between the road section flow and the average speed. The density, flow rate and average speed have the following relations
Figure BDA0002445044190000083
Wherein v isfThe average speed of the vehicle when the vehicle is smooth, Q is the road section flow, and K is the road section density.
And comparing the K value with the blocking density of the road section, wherein if the K value is larger or smaller, the road section can be concluded to belong to blocking, and if the K value is smaller, the road section can be concluded to belong to unblocked. The road section blocking density is determined according to the number of lanes of the road section, generally, the single lane blocking density is 20veh/km (veh refers to the number of vehicles), and the road section blocking density is 20veh/km multiplied by the corresponding number of lanes.
For better understanding, the present embodiment selects data of 26 expressways in the bay area, and performs traffic flow status inference on each road segment of the wide, clear and high speed.
A case includes the following steps:
step 1, data processing is carried out, and path information is added
Finding out the entrance and exit information of each piece of data and the passing identification station information, establishing a path list of the vehicle, then searching possible paths for adjacent high speed and entrance and exit in the list through a breadth-first search algorithm, finally summarizing into a possible path set from all entrances to exits, and selecting the path which best meets the condition as a real path according to the path mileage.
And extracting fields containing vehicle information, access and mileage fields, and forming a new data table with two new fields of a path and a mileage difference. Finding out the data with wide, clear and high speed in the path for further processing.
Step 2, obtaining the average speed of the main line of each vehicle
According to the path of each vehicle, the interchange condition of the vehicle path is calculated, the length of a main line occupied by acceleration and deceleration of the vehicle is calculated, and the time consumption condition of the vehicle in the processes of acceleration and deceleration and interchange is calculated. And substituting all the time and the length values into a formula to calculate the average speed of the vehicle.
Step 3, obtaining the flow of each high-speed road section
Step 3.1, calculating the entering and exiting time of the vehicle on the road section
In step 2, the average speed of the main line of each vehicle and the time required for acceleration and deceleration are obtained. And the inbound time is taken as an initial time, after the entry acceleration process, the time is superposed to the initial time to obtain the initial time of the first section of the main line section, the superposition is continued when the vehicle passes through the next section of the main line section, and the superposed time is used as the ratio of the length of the section of the main line section to the average speed to obtain the ending time of the previous section and the initial time of the next section. This superposition process is repeated over and over again to obtain a series of time instants. The road sections where the vehicle is located at different times are known.
Step 3.2, road section flow rate inference:
using 15 minutes as a time period, dividing one day into 96 sections, obtaining the time period of the vehicle passing through a certain road section according to the entering and exiting time of the vehicle at the certain road section, adding one to the corresponding time period statistic value, and finally obtaining the statistic value of the full sample data, wherein the inferred value of the flow is considered to be the same as the statistic value.
The wide-definition high-speed northbound traffic for two time periods of 3:30-5:30 and 17:00-19:00 is selected as an example, and the results are as follows:
table 13: 30-5:30 northbound flow
Tab.1Northbound traffic volume from3:30to 5:30
Unit: veh/h
Figure BDA0002445044190000091
Meter 217: 00-19:00 northbound flow
Tab.2Northbound traffic volume from17:00to 19:00
Unit: veh/h
Figure BDA0002445044190000101
Step 4, calculating the average speed of the road section
Section di,i+1The average speed of the main line is calculated by selecting all OD data in the upstream and downstream toll stations. All the data obtained by each section of road are subjected to box diagram to remove abnormal values, and then an average value is obtained.
The results are given in the table below.
TABLE 33 average speed in northbound direction 30: 5:30
Tab.3Northbound speed from3:30to 5:30
Unit: km/h
Figure BDA0002445044190000102
TABLE 417: 00-19:00 average speed in northbound direction
Tab.4Northbound speed from17:00to 19:00
Unit: km/h
Figure BDA0002445044190000111
Step 5, traffic flow state judgment:
according to the relation between the flow and the speed, the road sections can be found to be in the unblocked state through calculation.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.

Claims (10)

1. A high-speed traffic flow state inference method based on highway charging data is characterized by comprising the following steps:
restoring a vehicle running path according to the information of the entrance and the exit and the identification station in the charging data;
decomposing the running state of the vehicles and solving the average speed of each vehicle on the main line;
obtaining traffic flow of each road section;
calculating the average speed of all vehicles in each road section;
and (4) deducing the traffic flow state by combining the traffic flow of each road section and the average speed of all vehicles in each road section.
2. The method for inferring the status of a high-speed traffic flow based on highway toll data according to claim 1, wherein the step of restoring the vehicle path information according to the entrance and exit information and the identification station information in the toll data specifically comprises the steps of:
and establishing a vehicle travel list by using the information of the entrance and the exit of the charging data and the identification station, searching possible paths for the adjacent high speed and entrance and exit in the travel list through a breadth-first search algorithm, finally summarizing the possible paths into a possible path set from all the entrances to the exits, and selecting one path as a real path in the possible path set according to the path mileage.
3. The method according to claim 2, wherein the breadth-first search algorithm is to store the node that has passed through for each route, set a search stop threshold, record the number of traversal layers, i.e., the number of steps, when an effective route is searched, then continue searching for 2-3 layers, if no new effective route can be found under the branch, stop the branch search, and when all branches reach the threshold, the route search ends.
4. The method according to claim 2, wherein the mileage of each route in the set of possible routes is calculated and compared with the vehicle mileage in the data, and the route with the smallest difference in mileage is the final real route to be selected, and the difference in mileage is ± 500m, and if the difference is not within the range, the data is determined to be abnormal.
5. The method as claimed in claim 1, wherein the driving state of the vehicle on different road sections is divided according to the acceleration, and the average speed of each vehicle on the main line is calculated by combining the travel time and the speed information recorded in the charging data.
6. The method for inferring the status of a high-speed traffic flow based on highway toll data according to claim 5,
the running states of the vehicle on different road sections comprise: the vehicle starts to perform uniform acceleration movement from the entrance toll station and reaches the main line running speed after the main line is accelerated; when the vehicle leaves the high speed, the vehicle starts to uniformly decelerate a certain distance before entering an exit ramp until entering an exit toll station through the exit ramp, and then exits the station or leaves the station through an ETC channel after queuing; when the vehicle is going to transfer high speed through the interchange, the vehicle starts to decelerate before reaching the ramp, runs at a constant speed in the ramp, accelerates to a main line running speed after leaving the ramp, wherein the main line average running speed value is not calculated, the accelerated main line running speed value sets an initial value according to the vehicle type, after the initial value is used for carrying out the first calculation to obtain the main line average speed, the main line average speed is substituted into the accelerated main line running speed,
the vehicle charging mode on the expressway comprises cash charging and Electronic Toll Collection (ETC), the time of the vehicle passing through a toll station is recorded in charging data, and the time of high speed access is calculated as follows:
Figure FDA0002445044180000021
Figure FDA0002445044180000022
wherein the time for entering the high speed is tenTime t from high speedexThe number of the exit artificial lanes is n, the charging time of each vehicle is s seconds, the flow of the artificial charging vehicles is Q, the length of a main line is m meters when the speed is increased or reduced, and the length of an entrance ramp is renThe length of the exit ramp is rexETC lane speed limit v0The final acceleration speed and the initial deceleration speed are vt，
Let the vehicle running speed of interchange be vsTo calculate the time t required for passing through the interchangesThe formula is as follows:
Figure FDA0002445044180000023
namely, the running time t of the vehicle on the main line can be calculatedm＝t-ten-tex-tsWhere t represents the total travel time of the vehicle, obtainable from the charging data,
the driving mileage of the vehicle in the charge data includes the mileage of the main line and the access ramp, and if the length of the main line is L and the driving mileage in the charge data is L, L + ren+rex，
Assuming that the vehicle passes c interchange, the average speed v of the vehicle on the main line can be obtained:
Figure FDA0002445044180000024
7. the method as claimed in claim 6, wherein the traffic flow of each road section is obtained, the starting and ending time of the vehicle passing each road section is determined according to the driving speed of the vehicle in each road section and the corresponding driving time, the time period of the vehicle passing each road section is obtained, and the number of vehicles in each road section in different time periods, namely the traffic flow, can be calculated.
8. The method as claimed in claim 1, wherein the method comprises selecting data of vehicles entering and leaving through two toll stations adjacent to a road section to be counted, calculating average speed of each vehicle, adding speed value into speed set of road section passing through different time periods, increasing statistical length if empty set appears, processing abnormal value of all speed sets to obtain usable set, averaging to obtain average speed of road section
Figure FDA0002445044180000031
9. The method of claim 8, wherein the abnormal value is processed by a box diagram method in a section (Q)3+1.5(Q3-Q1) , + ∞) or [0, Q1-1.5(Q3-Q1) Values within) are abnormal values, Q1Is the lower quartile, Q3Is the upper quartile.
10. The method of inferring a status of a high speed traffic flow based on highway toll data according to claim 8, wherein a relationship between a flow rate and an average speed of a link is as follows,
Figure FDA0002445044180000032
wherein v isfThe average speed of the vehicle when the vehicle is unblocked, Q is the road section flow, K is the road section density, and whether the road section is blocked or unblocked can be inferred by comparing the road section density with the blocking density of the road section.
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