A method for analyzing the reliability of path travel time considering the characteristics of headway between vehicles

Abstract

The present invention discloses a method for analyzing the reliability of path travel time considering the headway time characteristics, and the steps include: Step S01. Obtain the moments when vehicles in each lane of the target section pass through the upstream and downstream detection points to obtain the passing time data of each vehicle; Step S02. Calculate the headway time of each vehicle passing through the upstream and downstream detection points in the section according to the passing time data of each vehicle; Step S03. According to the headway time of each vehicle passing through the upstream and downstream detection points in the section, use the pre-constructed path travel time budget model to calculate the path travel time budget value. In the path travel time budget model, the mean and variance of the path travel time are calculated respectively using the headway time of each vehicle passing through the upstream and downstream detection points in the section; Step S04. Obtain the reliability condition of the path travel time according to the path travel time budget value. The present invention has the advantages of simple implementation method, small calculation amount, high analysis efficiency and high accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of road traffic operation analysis, and in particular, to a method for analyzing the reliability of path travel time considering the characteristics of headway. Background Art

[0002] By analyzing the microscopic parameters of traffic flow, the operation rules of road traffic can be obtained. Currently, the analysis methods for the reliability of path travel time usually use the convolution formula as an analysis tool. By integrating the statistical distribution characteristics of section travel time, the reliability of path travel time is obtained. However, there are numerous paths in the road network and the section composition is complex. The calculation efficiency of the convolution integral formula will gradually decrease as the path length increases. Therefore, the traditional analysis method using the convolution formula is not only complex to implement, has a large amount of calculation, but also has low calculation efficiency, and it is difficult to quickly analyze the reliability of path travel time. In addition, the vehicles in motion are also affected by the entry and exit of other vehicles upstream and downstream of the section, and this influence has obvious random characteristics. For example, the headway of traffic flow has random fluctuation characteristics, which also leads to obvious random characteristics of the travel time of vehicles in the section. However, the traditional analysis method for the reliability of section travel time based on the convolution formula does not consider the problem of the influence of this random characteristic, and cannot effectively quantify the influence of this random characteristic on the reliability of path travel time. Therefore, it is difficult to accurately characterize the reliability of path travel time, resulting in low actual analysis accuracy. Therefore, there is an urgent need to provide a method that can accurately and quickly analyze the reliability of path travel time. Summary of the Invention

[0003] The technical problem to be solved by the present invention is: aiming at the technical problems existing in the prior art, the present invention provides a method for analyzing the reliability of path travel time considering the characteristics of headway, which has a simple implementation method, a small amount of calculation, and high analysis efficiency and accuracy.

[0004] To solve the above technical problems, the technical solution proposed by the present invention is as follows:

[0005] A method for analyzing the reliability of path travel time considering the characteristics of headway, the steps include:

[0006] Step S01. Obtain the moments when the vehicles in each lane of the target section pass through the upstream and downstream detection points, and obtain the passing vehicle time data of each vehicle;

[0007] Step S02. Calculate the headway of each vehicle passing through the upstream and downstream detection points in the section according to the passing vehicle time data of each vehicle;

[0008] Step S03. Calculate the path travel time budget value according to the headway of each vehicle passing through the upstream and downstream detection points in the section, using the pre-constructed path travel time budget model. In the path travel time budget model, the mean and variance of the path travel time are used to calculate the path travel time budget value, and the mean and variance of the path travel time are calculated respectively using the headway of each vehicle passing through the upstream and downstream detection points in the section;

[0009] Step S04. Obtain the reliability condition of the path travel time according to the path travel time budget value to analyze the reliability of the path travel time. The reliability condition is that the path travel time needs to be less than the path travel time budget value.

[0010] Further, the construction steps of the path travel time budget model are as follows:

[0011] Construct a first relationship model between the headway of each vehicle passing through the upstream and downstream detection points and the travel time between the upstream and downstream nodes of the section;

[0012] According to the relationship between the variance of the travel time between the upstream and downstream nodes of the section and the travel time between the upstream and downstream nodes of the section and the first relationship model, construct a second relationship model between the variance of the travel time between the upstream and downstream nodes of the section and the headway of each vehicle passing through the upstream and downstream detection points;

[0013] According to the second relationship model, construct a calculation model for calculating the mean and variance of the path travel time respectively using the headway of each vehicle passing through the upstream and downstream detection points in the section. Based on the calculation model, use the mean and variance of the path travel time to calculate the path travel time budget value, and construct the final path travel time budget model.

[0014] Further, in the first relationship model, the travel time between the upstream and downstream nodes of the section is calculated using the travel time of the leading vehicle and the time intervals between the following vehicles and the leading vehicle when they reach the upstream and downstream detection points respectively.

[0015] Further, the first relationship model is specifically:

[0016]

[0017] Among them, is the average travel time of the section, T1 is the travel time of the leading vehicle, n is the total number of vehicles detected at the upstream u point and downstream d point of the section, τ d1i is the time interval between the i-th vehicle and the leading vehicle when reaching the downstream detection point, that is, the headway of the vehicle passing through the downstream detection point in the section, τ u1i is the time interval between the i-th vehicle and the leading vehicle when reaching the upstream detection point, that is, the headway of the vehicle passing through the upstream detection point.

[0018] Further, the specific form of the second relational model is as follows:

[0019]

[0020] where D(T) is the variance of the travel time between the upstream and downstream nodes of the road segment, and τ d1 is the data set of the headway between the first vehicle and the subsequent vehicles at the downstream node, and τ u1 is the data set of the headway between the first vehicle and the subsequent vehicles at the upstream node. D(τ d1 ) is the variance of the headway at the downstream node, D(τ u1 ) is the variance of the headway at the upstream node, and cov(τ d1 , τ u1 ) is the covariance between τ d1 and τ u1 .

[0021] Further, constructing the calculation model of the mean and variance of the path travel time includes:

[0022] Constructing the calculation model of the path travel time T r is as follows:

[0023]

[0024] where is the road segment correlation parameter of each associated road segment a, and T is the travel time of each associated road segment a;

[0025] According to the fact that the path travel time follows a normal distribution, the expectation E(T r ) and the variance are respectively:

[0026]

[0027]

[0028]

[0029] where E(T) is the expectation of the travel time between the upstream and downstream nodes of each associated road segment, and D(T) is the variance of the travel time between the upstream and downstream nodes of each associated road segment.

[0030] Further, the path travel time budget model is:

[0031]

[0032] where TTB is the path travel time budget value, and E(T r ) is the path travel time Tr The expectation is the path travel time T r The variance, λ is the reliability parameter, is the link correlation parameter, E(T a ) is the mean of the travel time between the upstream and downstream nodes of the associated link a, var(T a ) is the variance of the travel time between the upstream and downstream nodes of the associated link a, T1 is the travel time of the leading vehicle, n is the number of vehicles detected at the upstream u point and downstream d point of the link, τ d1i is the time interval between the arrival of the i-th vehicle and the leading vehicle at the downstream detection point, that is, the headway when the vehicle passes the head of the downstream detection point in the link, τ u1i is the time interval between the arrival of the i-th vehicle and the leading vehicle at the upstream detection point, that is, the headway when the vehicle passes the upstream detection point, τ d1 is the data set of headways between the first vehicle and subsequent vehicles at the downstream node, τ u1 is the data set of headways between the first vehicle and subsequent vehicles at the upstream node, D(τ d1 ) is the headway variance at the downstream node, D(τ u1 ) is the headway variance at the upstream node, cov(τ d1 , τ u1 ) is the covariance between τ d1 and τ u1 .

[0033] Furthermore, the reliability condition is:

[0034]

[0035]

[0036] Wherein, E(T r ) is the mean of the path travel time T r , is the variance of the path travel time T r , is the probability calculation formula that the path travel time is less than the path travel time budget value, p is the probability value that the path travel time is less than the path travel time budget value, and λ is the reliability parameter.

[0037] A path travel time reliability analysis device considering headway characteristics, comprising:

[0038] An acquisition module, configured to acquire the moments when vehicles in each lane of the target link pass through the upstream and downstream detection points, and obtain the passing vehicle moment data of each vehicle;

[0039] A headway calculation module, configured to calculate the headways of vehicles passing through the upstream and downstream detection points in the link according to the passing vehicle moment data of each vehicle;

[0040] A path travel time budget module, configured to calculate a path travel time budget value according to the headway times of vehicles passing through upstream and downstream detection points in the road section, by using a pre-constructed path travel time budget model. In the path travel time budget model, the mean and variance of the path travel time are used to calculate the path travel time budget value, and the mean and variance of the path travel time are respectively calculated by using the headway times of vehicles passing through upstream and downstream detection points in the road section;

[0041] A reliability analysis module, configured to obtain the reliability condition of the path travel time according to the path travel time budget value, so as to analyze the reliability of the path travel time. The reliability condition is that the path travel time needs to be less than the path travel time budget value.

[0042] A computer-readable storage medium storing a computer program, where the computer program, when executed, implements the method as described above.

[0043] Compared with the prior art, the advantages of the present invention are as follows:

[0044] 1. By introducing the random characteristics of the headway times of upstream and downstream nodes of the road section into the calculation process of the mean and variance of the lane-level travel time of the road section, the present invention introduces the random change characteristics of the headway times of the road section into the process of analyzing the reliability of the road section travel time, quantitatively analyzes the influence of the driving-in and driving-out rules of vehicles at upstream and downstream nodes of the road section on the road section travel time, and obtains the reliability characteristics of the path travel time, which can effectively improve the calculation efficiency of the reliability analysis of the path travel time, solve the problem that the formula for estimating the path travel time in the traditional method is too complex, and at the same time, based on the effective quantification of the influence of the random characteristics of the headway time on the reliability of the travel time, can improve the accuracy of the reliability analysis of the path travel time, so as to achieve fast and accurate reliability analysis of the path travel time.

[0045] 2. Aiming at the spatio-temporal characteristics of the driving trajectories of vehicles in the road section, considering the influence of the driving-in and driving-out of upstream and downstream vehicles in the road section on the road section travel time, and combining the spatio-temporal rules of the driving trajectories of vehicles in the road section, the present invention constructs a relationship model among the headway times and travel times of upstream and downstream nodes in the road section, which can introduce the random characteristics of the headway times of upstream and downstream nodes of the road section into the calculation process of the mean and variance of the lane-level travel time of the road section, so as to effectively and quantitatively analyze the influence of the driving-in and driving-out rules of vehicles at upstream and downstream nodes of the road section on the road section travel time.

[0046] 3. By considering the relationship between the road section travel time and the headway times of upstream and downstream of the road section, and combining the relevant parameters of the road section and the path, the present invention can effectively analyze the reliability characteristics of the road section travel time and the path travel time, and at the same time solve the problem that the formula for estimating the path travel time in the traditional method is too complex. Description of the Drawings

[0047] Figure 1 It is a schematic diagram of the implementation process of the path travel time reliability analysis method considering the headway characteristics at the vehicle head in this embodiment.

[0048] Figure 2 It is a schematic diagram of the following - vehicle principle of lateral interference vehicles in a two - lane scenario in a specific application embodiment of the present invention.

[0049] Figure 3 It is a schematic diagram of the path travel time reliability analysis result obtained in a specific application embodiment of the present invention. Detailed implementation manners

[0050] The present invention will be further described below in conjunction with the accompanying drawings of the specification and specific preferred embodiments, but the protection scope of the present invention is not limited thereby.

[0051] For travelers, the road traffic operation state is one of the factors affecting travelers' path selection, and it is also an important indicator for travelers to evaluate the reliability of path travel. By analyzing key parameters such as headway, the variation laws of road traffic operation states such as sections and intersections can be effectively obtained. Therefore, based on headway parameters, the influence of random characteristics on the reliability of path travel time can be effectively quantified. Based on the above considerations, the present invention introduces the random characteristics of headway at the upstream and downstream nodes of a section into the calculation process of the mean and variance of the lane - level travel time of the section, so as to introduce the random variation characteristics of headway at the section into the process of section travel time reliability analysis, quantitatively analyze the influence of the entry and exit laws of vehicles at the upstream and downstream nodes of the section on the section travel time, obtain the reliability characteristics of path travel time, effectively improve the calculation efficiency of path travel time reliability analysis, solve the problem that the formula for estimating path travel time in traditional methods is too complex, and at the same time, based on the effective quantification of the influence of the random characteristics of headway on travel time reliability, the accuracy of path travel time reliability analysis can be improved, thus realizing fast and accurate path travel time reliability analysis.

[0052] As Figure 1 shown, the steps of the path travel time reliability analysis method considering headway characteristics in this embodiment include:

[0053] Step S01. Obtain the moments when vehicles in each lane of the target section pass through the upstream and downstream detection points to obtain the passing - vehicle - moment data of each vehicle;

[0054] Step S02. Calculate the headway of each vehicle passing through the upstream and downstream detection points in the section according to the passing - vehicle - moment data of each vehicle;

[0055] Step S03. According to the headway of each vehicle passing through the upstream and downstream detection points within the road section, use the pre-constructed path travel time budget model to calculate the path travel time budget value. In the path travel time budget model, the mean and variance of the path travel time are used to calculate the path travel time budget value, where the mean and variance of the path travel time are calculated respectively using the headway of each vehicle passing through the upstream and downstream detection points within the road section;

[0056] Step S04. Obtain the reliability condition of the path travel time based on the path travel time budget value to analyze the reliability of the path travel time. The reliability condition is that the path travel time needs to be less than the path travel time budget value.

[0057] The travel time refers to the total time experienced by a vehicle from the starting point to the destination. According to the range of the road on which the vehicle travels, the travel time includes the road section travel time and the path travel time. Among them, the road section travel time is the time required for the vehicle to pass through a certain road section on the road, and the path travel time is the time required for the traveler to start from the starting point, select a certain path and pass through different road sections to reach the destination. In this embodiment, the mean and variance of the path travel time are pre-used to construct a path travel time budget model to calculate the path travel time budget value. At the same time, the headway of each vehicle passing through the upstream and downstream detection points within the road section is introduced to estimate the mean and variance of the path travel time respectively, and then an accurate path travel time budget value can be quickly obtained, realizing the reliability analysis of the path travel time, and effectively improving the analysis efficiency and accuracy of the reliability of the path travel time.

[0058] In step S01 of this embodiment, license plate data can be specifically used to extract the moments when each lane vehicle passes through the upstream and downstream detectors within the road section by means of radio frequency identification, video identification, etc., so as to obtain the passing vehicle moment data of each vehicle within the road section. The headway is the time difference between the fronts of two consecutive vehicles passing through the same point. Based on the passing vehicle moment data of each vehicle within the road section, the travel time and headway of each vehicle can be determined, and then the headway is used to calculate the path travel time.

[0059] In this embodiment, the specific construction steps of the path travel time budget model are as follows:

[0060] Construct a first relationship model between the headway of each vehicle passing through the upstream and downstream detection points and the travel time between the upstream and downstream nodes of the road section;

[0061] According to the relationship between the variance of the travel time between the upstream and downstream nodes of the road section and the travel time between the upstream and downstream nodes of the road section, and the first relationship model, construct a second relationship model between the variance of the travel time between the upstream and downstream nodes of the road section and the headway of each vehicle passing through the upstream and downstream detection points;

[0062] According to the second relational model, a calculation model is constructed to calculate the mean and variance of the path travel time respectively based on the headway of each vehicle passing through the upstream and downstream detection points within the used road section. Based on the calculation model, the path travel time budget value is calculated using the mean and variance of the path travel time, and the final path travel time budget model is constructed.

[0063] Extract the headway of vehicles in each lane within the road section. Considering the spatio-temporal trajectory law of vehicles, the relational calculation formula between the headway of vehicles passing through the upstream and downstream and the travel time is obtained. In this embodiment, in the first relational model, the travel time of the leading vehicle and the time intervals between the following vehicles arriving at the upstream and downstream detection points and the leading vehicle are used to calculate the travel time between the upstream and downstream nodes of the road section.

[0064] In this embodiment, the specific form of the first relational model between the headway of each vehicle passing through the upstream and downstream detection points and the travel time between the upstream and downstream nodes of the road section is as follows:

[0065]

[0066] Where, is the average travel time of the road section, T1 is the travel time of the leading vehicle, n is the number of vehicles detected at the upstream u point and downstream d point of the road section, τ d1i is the time interval between the i-th vehicle and the leading vehicle arriving at the downstream detection point, that is, the headway of the vehicle passing through the downstream detection point within the road section, and τ u1i is the time interval between the i-th vehicle and the leading vehicle arriving at the upstream detection point, that is, the headway of the vehicle passing through the upstream detection point.

[0067] The specific process of constructing the first relational model between the headway of each vehicle passing through the upstream and downstream detection points and the travel time between the upstream and downstream nodes of the road section is as follows:

[0068] Assume that the vehicles are traveling in sequence without overtaking. A total of n vehicles are detected at the upstream u point and downstream d point of the road section. The detection time record pair of the first vehicle is (t u1 , t d1 ), and the detection time record pair of the n-th vehicle is (t un , t dn ). The travel time of any vehicle v i is T i . Assume that the average speed of the vehicle is The average travel time of the road section The headway of the vehicle at the upstream and downstream detection points is (τ ui , τ di ).

[0069] Taking the detection time of the first vehicle and the time interval between the first vehicle and the subsequent arriving vehicle n as analysis parameters, a recurrence formula is obtained, as shown in Equation (1).

[0070]

[0071] Analysis of the above recurrence formula (2) shows that the travel time between upstream and downstream nodes can be represented by three parameters: the travel time of the leading vehicle and the time intervals between the following vehicle and the leading vehicle when the following vehicle arrives at the upstream and downstream detection points. Thus, an expression for the travel time of the section between nodes with n vehicles collected per unit time can be obtained:

[0072]

[0073] From the above formula (3), the calculation expression for the expected value of the travel time between the upstream and downstream nodes of the section can be obtained, as shown in formula (1), that is

[0074] From formula (1), the relationship between the headway of each vehicle passing through the upstream and downstream detection points and the travel time between the upstream and downstream nodes of the section can be obtained.

[0075] In this embodiment, using the travel time variance calculation formula and the calculation formula (1) obtained in the above steps, a second relationship model between the headway and the section travel time variance is further obtained. The specific form of this second relationship model is:

[0076]

[0077] where D(T) is the variance of the travel time between the upstream and downstream detection nodes of the section, τ d1 is the headway data set between the first vehicle at the downstream node and the following vehicles, τ u1 is the headway data set between the first vehicle at the upstream node and the following vehicles, D(τ d1 ) is the headway variance at the downstream node, D(τ u1 ) is the headway variance at the upstream node, cov(τ d1 , τ u1 ) is the covariance between τ d1 and τ u1 .

[0078] From the above formula (4), the relationship between the headway of the vehicles passing through the upstream and downstream detection points in the section and the path travel time variance can be obtained. After obtaining the headway of the vehicles passing through the upstream and downstream detection points in the section, the variance of the path travel time can be calculated.

[0079] In this embodiment, it is assumed that parameters such as the travel time and traffic capacity between sections are independent of each other. Then the travel time T r of the path can be expressed as the sum of the travel times of the associated sections, as shown in formula (5). The specific calculation model for constructing the travel time T r of the path is:

[0080]

[0081] Among them, is the road section correlation parameter of each associated road section a, and T is the travel time of each associated road section a.

[0082] Further based on the central limit theorem, assuming that the path travel time follows a normal distribution, the expectation E(T r ) and variance can be expressed by Equation (6):

[0083]

[0084]

[0085]

[0086] Among them, E(T) is the expectation of the travel time between the upstream and downstream nodes of each associated road section, and D(T) is the variance of the travel time between the upstream and downstream nodes of each associated road section.

[0087] From the above Equations (5) and (6), the calculation model of the path travel time T r can be obtained. Among them, the mean value of the path travel time is obtained from the mean values of the travel times of each associated road section, and the variance of the path travel time is obtained from the variances of the travel times of each associated road section. The mean value and variance of the travel time of a road section can be calculated through the headway between vehicles passing through the upstream and downstream nodes within the road section (as shown in Equations (3) and (4)). Thus, the headway parameter can be correlated with the path travel time, and the relationship between the road section travel time and the headway between the upstream and downstream of the road section can be obtained. Combining the road section and path correlation parameters, the reliability characteristics of the road section travel time and the path travel time can be effectively analyzed, and the problem that the formula for estimating the path travel time in the traditional method is too complex can be solved.

[0088] Based on the reliability characteristics of the travel time, the path travel time budget value (TTB) can be obtained from the sum of the expected path travel time and the path travel time reservation. Using the above Equations (3) and (4), the specific path travel time budget model is as follows:

[0089]

[0090] Among them, TTB is the path travel time budget value, E(T r ) is the expectation of the path travel time T r , is the variance of the path travel time T r , λ is the reliability parameter, and its value range is 0.1 - 3.0. is the road segment correlation parameter, E(T a ) is the mean of the travel time between the upstream and downstream nodes of the associated road segment a, var(T a ) is the variance of the travel time between the upstream and downstream nodes of the associated road segment a, T1 is the travel time of the leading vehicle, n is the number of vehicles detected at the upstream u point and the downstream d point of the road segment, T d1i is the time interval between the arrival of the i-th vehicle and the leading vehicle at the downstream detection point, that is, the headway when the vehicle in the road segment passes the head of the downstream detection point, T u1i is the time interval between the arrival of the i-th vehicle and the leading vehicle at the upstream detection point, that is, the headway when the vehicle passes the upstream detection point, τ d1 is the headway data set between the first vehicle and the subsequent vehicles at the downstream node, τ u1 is the headway data set between the first vehicle and the subsequent vehicles at the upstream node, D(τ d1 ) is the headway variance at the downstream node, D(τ u1 ) is the headway variance at the upstream node, cov(τ d1 , τ u1 ) is the covariance between τ d1 and τ u1 .

[0091] In this embodiment, the headway statistical parameters derived from the road segment are used to simplify the calculation formula of the travel time budget value (such as formula (7)), and further combined with the analysis process of the statistical distribution inverse function of the travel time reliability and the travel time budget value, the analysis result of the path travel time reliability is obtained. This embodiment assumes that the travel times of road segments are independent of each other. Specifically, by calculating the probability that the path travel time is less than the travel time budget value, it is defined as the reliability of the path travel time. Among them, the path travel time is obtained by combining the correlation parameters of the road segment and the path, and the corresponding reliability calculation expression is:

[0092]

[0093]

[0094] Among them, E(T r ) is the expectation of the path travel time T r , is the variance of the path travel time T r , P() is the probability calculation formula that the path travel time is less than the path travel time budget value, p is the probability value that the path travel time is less than the path travel time budget value, and λ is the reliability parameter.

[0095] Among them, TTB is the path travel time budget value, E(T r ) is the expectation of the path travel time T r , is the path travel time Tr The variance, where λ is the reliability parameter with a value range of 0.1 - 3.0, is the road segment association parameter, which takes a value of 0 or 1.

[0096] The present invention focuses on the spatio - temporal characteristics of vehicle driving trajectories within a road segment, considering the influence of vehicles entering and leaving the upstream and downstream of the road segment on the travel time of the road segment. Combining the spatio - temporal laws of vehicle driving trajectories within the road segment, a relationship model between the headway and travel time of upstream and downstream nodes within the road segment is constructed. It can introduce the random characteristics of the headway of upstream and downstream nodes of the road segment into the calculation process of the mean and variance of the lane - level travel time of the road segment, thereby quantitatively analyzing the influence of the entry and exit laws of vehicles at upstream and downstream nodes of the road segment on the travel time of the road segment.

[0097] In a specific application embodiment, when the present invention uses the above - mentioned method for path travel time reliability analysis, a path travel time budget model is constructed in advance. First, combining the spatio - temporal trajectory laws of vehicle driving, a relationship model between the headway of vehicles in each lane within the road segment and the vehicle travel time is obtained (such as Equation (1) or (3)). Then, using the travel time variance calculation formula, a variance calculation model considering the headway of vehicles in each lane within the road segment is obtained, which is the relationship model between the headway and the variance of the road segment travel time (such as Equation (4)); then, based on the assumption that the road segment travel times are independent of each other and the road segment path association parameter, a path travel time budget model considering the mean and variance of the headway of upstream and downstream road segments is obtained (such as Equation (7)); during real - time analysis, first, the moments when vehicles in each lane within the road segment pass through the upstream and downstream detectors are extracted using license plate data, and then the headway when the vehicle passes through the detector is extracted. The path travel time budget is calculated according to Equation (7), and analysis is carried out according to the reliability conditions, thereby realizing the path travel time reliability analysis based on the headway of vehicles in the road segment.

[0098] As Figure 2 shown, assuming that vehicles drive in sequence without overtaking, a total of n vehicles are detected at the upstream detection point 1 (col1) and the downstream detection point 2 (col2) of the road segment. The detection time record pair of the first vehicle is The detection time record pair of the nth vehicle is For any vehicle veh i the travel time is T i , assuming the average speed of the vehicle is The average travel time of the road segment The headways of two consecutive vehicles veh i and veh i+1 at the upstream and downstream detection points 1 and 2 are respectively Integrate the headways at the same detection point together to obtain the headway data set at the detection point location. Taking Figure 2Taking the detection point 1 (upstream detection point u) and detection point 2 (downstream detection point d) as examples, the headway datasets of i vehicles can be obtained (τ ui , τ di ). By analogy, the headway datasets of i vehicles detected at detection point 2 and detection point 3 can be obtained. Through statistical analysis of this dataset, the sample mean of headway, sample variance, and mean travel time can be obtained respectively.

[0099] Taking the reliability analysis of the path travel time of a certain path 11 in a specific application embodiment as an example, the mean headway, headway variance, headway covariance, and mean travel time of the upstream and downstream detection nodes in each time period from 6:00 to 23:00 obtained by the above method are shown in Table 1 and Table 2.

[0100] Table 1 Statistical indicators of mean and variance of path travel time in multiple time periods

[0101]

[0102] Table 2 Statistical analysis of upstream and downstream headways in multiple time periods

[0103]

[0104]

[0105] Using the headway and travel time data in Table 1 and Table 2 (data for the remaining paths are obtained using the same principle as above), the fitting effects of formula (1) or (3) are shown in Table 3. In this embodiment, the mean method is specifically selected to analyze the reliability characteristics of path travel time, where the mean absolute error (MAE) and root mean squared error (RMSE) are selected to compare the fitting accuracy with other traditional methods (theoretical method, interval method). The results show that the mean method proposed by the present invention has lower errors and better fitting accuracy.

[0106] Table 3 Comparison of fitting accuracy

[0107]

[0108] Taking path 11 as an example, the travel time budget results of the path obtained using formula (7) are as Figure 3 shown, and the travel budget values for λ = 0.1 - 3.0 are obtained respectively. From Figure 3 it can be seen that the travel time budget values calculated using the present invention are in line with the comprehensive calculation results of the time period changes of travel time, with high accuracy. That is, compared with traditional analysis methods, the accuracy of the path travel time reliability analysis of the present invention is the highest, that is, it can effectively improve the accuracy of path travel time reliability analysis.

[0109] The path travel time reliability analysis device considering the headway time feature in this embodiment includes:

[0110] An acquisition module, configured to acquire the moments when vehicles in each lane of the target road section pass through the upstream and downstream detection points, so as to obtain the passing time data of each vehicle;

[0111] A headway time calculation module, configured to calculate the headway time when each vehicle in the road section passes through the upstream and downstream detection points according to the passing time data of each vehicle;

[0112] A path travel time budget module, configured to calculate a path travel time budget value by using a pre-constructed path travel time budget model according to the headway time when each vehicle in the road section passes through the upstream and downstream detection points. In the path travel time budget model, the mean and variance of the path travel time are used to calculate the path travel time budget value, wherein the mean and variance of the path travel time are respectively calculated by using the headway time when each vehicle in the road section passes through the upstream and downstream detection points;

[0113] A reliability analysis module, configured to obtain the reliability condition of the path travel time according to the path travel time budget value, so as to analyze the reliability of the path travel time. The reliability condition is that the path travel time needs to be less than the path travel time budget value.

[0114] This embodiment also provides a computer-readable storage medium storing a computer program, and when the computer program is executed, the above method is implemented.

[0115] The above is only a preferred embodiment of the present invention, and does not impose any form of limitation on the present invention. Although the present invention has been disclosed above with the preferred embodiment, it is not intended to limit the present invention. Therefore, any simple modification, equivalent change and modification made to the above embodiment according to the technical essence of the present invention without departing from the technical solution of the present invention shall fall within the scope of the technical solution of the present invention.

Claims

1. A method for analyzing the reliability of path travel time considering the headway characteristics of the vehicle head, characterized in that the steps Including: Step S01. Obtain the moments when vehicles in each lane of the target road section pass through the upstream and downstream detection points, and obtain the passing vehicle moment data of each vehicle; Step S02. Calculate the headway between the upstream and downstream detection points of each vehicle in the road section according to the passing vehicle moment data of each vehicle; Step S03. According to the headway between the upstream and downstream detection points of each vehicle in the road section, use the pre-constructed path travel time budget model to calculate the path travel time budget value. In the path travel time budget model, the mean and variance of the path travel time are used to calculate the path travel time budget value, and the mean and variance of the path travel time are respectively calculated using the headway between the upstream and downstream detection points of each vehicle in the road section; Step S04. Obtain the reliability condition of the path travel time according to the path travel time budget value to analyze the reliability of the path travel time. The reliability condition is that the path travel time needs to be less than the path travel time budget value; The path travel time budget model is: where TTB is the path travel time budget value, E(T r ) is the expectation of the path travel time T r , is the variance of the path travel time T r , λ is the reliability parameter, is the link correlation parameter, E(T a ) is the expectation of the travel time between the upstream and downstream nodes of the associated link a, var(T a ) is the variance of the travel time between the upstream and downstream nodes of the associated link a, T1 is the travel time of the leading vehicle, n is the number of vehicles detected at the upstream u point and the downstream d point of the link, T d1i is the time interval between the arrival of the i-th vehicle and the leading vehicle at the downstream detection point, that is, the headway when the vehicle passes the downstream detection point within the link, T u1i is the time interval between the arrival of the i-th vehicle and the leading vehicle at the upstream detection point, that is, the headway when the vehicle passes the upstream detection point, τ d1 is the headway data set between the first vehicle and the subsequent vehicles at the downstream node, τ u1 is the headway data set between the first vehicle and the subsequent vehicles at the upstream node, D(τ d1 ) is the headway variance at the downstream node, D(τ u1 ) is the headway variance at the upstream node, cov(τ d1 , τ u1 ) is the covariance between τ d1 and τ u1 .​​ 2. The path travel time reliability analysis method considering the headway feature of the vehicle head as described in claim 1, characterized in that, The construction steps of the path travel time budget model are: Construct a first relationship model between the headway of each vehicle passing through the upstream and downstream detection points and the travel time between the upstream and downstream nodes of the road section; According to the relationship between the variance of the travel time between the upstream and downstream nodes of the road section and the travel time between the upstream and downstream nodes of the road section and the first relationship model, construct a second relationship model between the variance of the travel time between the upstream and downstream nodes of the road section and the headway of each vehicle passing through the upstream and downstream detection points; According to the second relationship model, construct a calculation model for calculating the mean and variance of the path travel time using the headway of each vehicle passing through the upstream and downstream detection points in the road section. Based on the calculation model, use the mean and variance of the path travel time to calculate the path travel time budget value, and construct the final path travel time budget model.

3. The path travel time reliability analysis method considering the headway feature of the vehicle head as described in claim 2, wherein In the first relationship model, the travel time between the upstream and downstream nodes of the road section is calculated using the travel time of the leading vehicle and the time intervals between the following vehicles and the leading vehicle when they reach the upstream and downstream detection points respectively.

4. The path travel time reliability analysis method considering the headway feature of the vehicle head as claimed in claim 3, wherein The first relationship model is specifically: Among them, is the average travel time of the road section, T1 is the travel time of the leading vehicle, n is the number of vehicles detected at the upstream u point and downstream d point of the road section, and τ d1i is the time interval between the arrival of the i-th vehicle and the leading vehicle at the downstream detection point, that is, the headway of vehicles passing through the downstream detection point within the road section, and τ u1i is the time interval between the arrival of the i-th vehicle and the leading vehicle at the upstream detection point, that is, the headway of vehicles passing through the upstream detection point.

5. The path travel time reliability analysis method considering the headway feature of the vehicle head as described in claim 2, wherein The second relationship model is specifically: where D(T) is the variance of the travel time between the upstream and downstream nodes of the road section, τ d1 is the data set of the headway between the first vehicle and the following vehicles at the downstream node, τ u1 is the data set of the headway between the first vehicle and the following vehicles at the upstream node, D(τ d1 ) is the variance of the headway at the downstream node, D(τ u1 ) is the variance of the headway at the upstream node, cov(τ d1 , τ u1 ) is the covariance between τ d1 and τ u1 .

6. The method for analyzing the reliability of path travel time considering the headway characteristics of the vehicle head as claimed in claim 2, wherein Constructing the calculation model for the mean and variance of the path travel time includes: Build the calculation model for the path travel time T r as follows: Among them, is the road segment correlation parameter of each associated road segment a, and T is the travel time of each associated road segment a; According to the fact that the path travel time follows a normal distribution, the expectation E(T r ) and variance are respectively as follows: Where, E(T) is the expectation of the travel time between the upstream and downstream nodes of each associated road section, and D(T) is the variance of the travel time between the upstream and downstream nodes of each associated road section.

7. The path travel time reliability analysis method considering the headway feature of the vehicle head as described in any one of claims 1 to 6, characterized in that The reliability condition is: Among them, E(T r ) is the expectation of the path travel time T r , is the variance of the path travel time T r , P() is the probability calculation formula that the path travel time is less than the path travel time budget value, p is the probability value that the path travel time is less than the path travel time budget value, and λ is the reliability parameter.

8. An analysis device for the reliability of path travel time considering the headway characteristics of the vehicle head, characterized in that, Including: An acquisition module, configured to obtain the moments when vehicles in each lane of the target road section pass through the upstream and downstream detection points, and obtain the passing vehicle moment data of each vehicle; A headway calculation module, configured to calculate the headway between the upstream and downstream detection points of each vehicle in the road section according to the passing vehicle moment data of each vehicle; A path travel time budget module, configured to calculate a path travel time budget value according to the headway time of each vehicle passing through upstream and downstream detection points within the road section, by using a pre-constructed path travel time budget model. In the path travel time budget model, the mean and variance of the path travel time are used to calculate the path travel time budget value, wherein the mean and variance of the path travel time are respectively calculated by using the headway time of each vehicle passing through the upstream and downstream detection points within the road section; A reliability analysis module, configured to obtain the reliability condition of the path travel time according to the path travel time budget value, so as to analyze the reliability of the path travel time. The reliability condition is that the path travel time needs to be less than the path travel time budget value; The path travel time budget model is as follows: where TTB is the path travel time budget value, E(T r ) is the expectation of the path travel time T r , is the variance of the path travel time T r , λ is the reliability parameter, is the link association parameter, E(T a ) is the expectation of the travel time between the upstream and downstream nodes of the associated link a, var(T a ) is the variance of the travel time between the upstream and downstream nodes of the associated link a, T1 is the travel time of the leading vehicle, n is the number of vehicles detected at the upstream u point and the downstream d point of the link, T d1i is the time interval between the arrival of the i-th vehicle and the leading vehicle at the downstream detection point, that is, the headway when the vehicle in the link passes the downstream detection point, T u1i is the time interval between the arrival of the i-th vehicle and the leading vehicle at the upstream detection point, that is, the headway when the vehicle passes the upstream detection point, τ d1 is the headway data set between the first vehicle and the subsequent vehicles at the downstream node, τ u1 is the headway data set between the first vehicle and the subsequent vehicles at the upstream node, D(τ d1 ) is the headway variance at the downstream node, D(τ u1 ) is the headway variance at the upstream node, cov(τ d1 , τ u1 ) is the covariance between τ d1 and τ u1 .​​ 9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program runs, it implements the method according to any one of claims 1 to 7.

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