Calculation method for abnormal release state of entrance lane

Abstract

The invention discloses a calculation method for an abnormal release state of an entrance lane, and the method comprises the steps: calculating a stage-lane expectation correlation index of each lane, so as to form a stage-lane expectation correlation index vector, and constructing a stage-lane expectation correlation index matrix of an intersection; calculating a stage-lane actual association index of each lane to form a stage-lane actual association index vector, and constructing a stage-lane actual association index matrix of the intersection; and based on the stage-lane expectation association index matrix and the stage-lane actual association index matrix, calculating a correlation coefficient of a lane-stage expectation association index vector and a lane-stage actual association index vector of each lane, and analyzing whether an abnormal release state exists or not to obtain an abnormal release state result. According to the invention, automatic detection of conditions of lane association relationship disorder, lamp group wiring disorder and the like caused by lane association relationship configuration errors and system updating is realized, and the workload of manual parameter configuration verification is reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of intelligent control of traffic signals, and in particular relates to a method for calculating the abnormal release state of an entrance road. Background Art

[0002] At present, all parts of the country are vigorously building traffic information collection systems, recording massive amounts of lane-level traffic information data, and using the collected lane-level traffic information data to perform inductive control and adaptive control of traffic signals. In the process of using the traffic information collection system, on the one hand, since the traffic signal control system and the traffic information collection system use independent lane numbering systems, the lane association between the systems is often manually configured, and the configuration process occasionally produces lane association configuration errors. Manual inspection often requires the use of video surveillance systems to check the lane matching of the actual passing data of each lane between the systems one by one, which requires a lot of effort. On the other hand, the information collection equipment in the traffic information collection system will be upgraded or replaced with firmware from time to time, which may cause the system monitoring lane number to change, and then cause the lane association between the systems to be disordered, causing the inductive control and adaptive control to fail. In addition, in actual control, there will be a phenomenon that the signal light group wiring is maliciously misconnected, resulting in the simultaneous release of conflicting traffic and the chaotic release of opposite traffic, which is prone to traffic accidents and traffic congestion, and has a bad impact. Therefore, a calculation method is needed that can automatically diagnose the abnormal release status of vehicles on the import lane, automatically detect lane association configuration errors, lane association disorder caused by system updates, light group wiring disorder, etc., and effectively improve the fault tolerance of traffic signal control.

[0003] The existing Chinese invention patent application number is CN202310276329.X and is titled "Traffic Data Anomaly Detection Method, Device and Traffic Operation and Maintenance System", which discloses that by analyzing the headway threshold test, traffic flow parameter consistency test, and traffic flow distribution law test, whether the traffic data is abnormal is determined. The Chinese invention patent application number is CN202310552311.8 and is titled "A Radar Video Integrated Traffic Flow Data Anomaly Detection Method and System", which discloses that by comparing real-time data with historical data and analyzing data volume characteristics, whether the traffic data to be detected is abnormal is determined. However, the existing technology focuses more on analyzing the integrity, timeliness, and effectiveness of traffic detection data, and does not mention automatic detection methods for situations such as disordered lane associations and disordered light group wiring. Summary of the invention

[0004] In view of the above-mentioned deficiencies in the prior art, an object of the present invention is to provide a method for calculating the abnormal release status of an import lane, so as to solve the technical defect in the prior art that the release status of the import lane cannot be monitored.

[0005] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A method for calculating the abnormal release state of an inlet channel of the present invention comprises the following steps:

[0007] 1) Determine whether the phase sequence of the i-th signal cycle at the end of the i-th signal cycle is consistent with the phase sequence of the i-1-th signal cycle. If they are consistent, the phase-lane expectation association index matrix of the i-th signal cycle is equal to the phase-lane expectation association index matrix of the i-1-th signal cycle, and enter step 2); if they are inconsistent or i=1, the phase-lane expectation association index of each lane is calculated based on the relationship between the signal phase and the lane release state to form a phase-lane expectation association index vector, and complete the construction of the phase-lane expectation association index matrix of the intersection;

[0008] 2) Calculate the actual phase-lane correlation index of each lane at the end of the i-th signal cycle phase sj to form a phase-lane actual correlation index vector, and complete the construction of the phase-lane actual correlation index matrix of the intersection at the end of the i-th signal cycle;

[0009] 3) Based on the stage-lane expected correlation index matrix and the stage-lane actual correlation index matrix, calculate the correlation coefficient between the lane-stage expected correlation index vector and the lane-stage actual correlation index vector of lane k, analyze whether there is an abnormal release state, and obtain the abnormal release state result.

[0010] Furthermore, the step 1) specifically includes:

[0011] 11) Determine whether the phase sequence of the i-th signal cycle at the end of the i-th signal cycle is consistent with the phase sequence of the i-1-th signal cycle. If they are consistent, the phase-lane expected correlation index matrix W of the i-th signal cycle is i Equal to the phase-lane expected correlation index matrix W of the i-1th signal cycle i-1 , proceed to step 2); if not consistent or the i-1th signal cycle does not exist, proceed to step 12);

[0012] 12) Based on the relationship between the signal stage and the lane release status, the stage-lane expected correlation index of each lane is calculated to form the stage-lane expected correlation index vector W sj =[w sj,1 w sj,2 …w sj,k …w sj,n ], where w sj,k represents the phase-lane expected association index between lane k and phase sj. When phase sj allows vehicles in lane k to pass, w sj,k =1; when the vehicle in lane k is prohibited from passing in stage sj, wsj,k = 0; when stage sj allows vehicles in lane k to enter the waiting area or waiting to turn area, w sj,k =L pt / (L pt +L ca ), k is the lane number, sj is the stage number, L pt is the length of the waiting area or waiting transfer area, L ca is the length of the channelization section;

[0013] 13) Based on the phase-lane expected association index vector, construct the phase-lane expected association index matrix W of the intersection i =[W s1 ; W s2 ;…;W sj ;…;W sm ].

[0014] Furthermore, the step 2) specifically includes:

[0015] 21) Record the end time of the stage sj at the end of the i-th signal cycle stage and release time Where i is the signal cycle number;

[0016] 22) Collection period The vehicle passing data of each lane is used to calculate the actual correlation index of the stage-lane, as follows:

[0017]

[0018] in, represents the actual phase-lane correlation index between lane k and phase sj in the i-th signal cycle; μ, ε, θ are weight coefficients, μ+ε+θ=1; represents the saturation of lane k in the i-th signal cycle sj stage, represents the time when the mth vehicle passes in lane k during the i-th signal cycle sj, H k is the average headway time of lane k under saturated traffic flow conditions; (considering that in the case of non-saturation, vehicles usually pass through the front part of the stage, and the vehicles passing through the back part of the stage are relatively scattered and random) the stage-lane actual correlation index is positively correlated with the passing order of vehicles in the stage. Compared with vehicles passing later in the stage, the influence factor of vehicles passing earlier is greater; the stage-lane actual correlation index is related to the average passing interval. The closer the average passing interval is to the saturated headway time, the more obvious the continuity of passing vehicles is, and the stronger the correlation between lane and stage; the stage-lane actual correlation index is related to lane saturation. The higher the lane saturation, the stronger the correlation between lane and stage.

[0019] 23) Based on the actual correlation index of stage-lane Forming the stage-lane actual association index vector of stage sj

[0020] 24) Based on the phase-lane actual correlation index vector, construct the phase-lane actual correlation index matrix at the end of the signal cycle

[0021] Furthermore, the step 3) specifically includes:

[0022] 31) Based on the stage-lane expected correlation index matrix W i and the stage-lane actual association index matrix R i , extract the lane-phase expected association index vector of lane k in the i-th signal cycle Extract the lane-phase actual correlation index vector of lane k in the i-th signal cycle

[0023] 32) Calculate the correlation coefficient between the lane-stage expected correlation index vector and the lane-stage actual correlation index vector of lane k at the end of each signal cycle. as follows:

[0024]

[0025] in, W k and The covariance of is the average expected correlation index of lane k in the i-th signal cycle stage, is the variance of the expected correlation index of lane k in the i-th signal cycle stage; is the average actual correlation index of lane k in the i-th signal cycle stage, is the variance of the actual correlation index of lane k in the i-th signal cycle stage;

[0026] 33) Determine whether there is an abnormal release state. If the correlation coefficient Indicates that the lane and stage association is incorrect, indicating that the lane association is configured incorrectly and needs to be checked; if It indicates that the correlation coefficient jumps and the lane association relationship changes, which means that the lane association relationship may be disordered or the light group wiring may be disordered due to system updates and other reasons. The signal period i where the jump occurs is recorded and a timely warning is issued; β is the minimum correlation coefficient for judging the normal association relationship between the lane and the stage, and γ is the jump coefficient for judging the change of the association relationship.

[0027] Beneficial effects of the present invention:

[0028] (1) The present invention realizes automatic detection of lane association configuration errors, lane association disorder caused by system updates, and light group wiring disorder, thereby reducing the workload of manual verification of parameter configuration;

[0029] (2) The present invention avoids the problem of induction control and adaptive control failure caused by lane association disorder due to lane association error configuration and system update, and avoids the problem of chaotic release of traffic flow, traffic accidents and traffic congestion caused by disordered lamp group wiring;

[0030] (3) The method of the present invention is also applicable to intersections with waiting areas or waiting areas for turning; it will not misjudge abnormal release status due to vehicles waiting to go or waiting to turn. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 Schematic diagram of the method of the present invention. DETAILED DESCRIPTION

[0032] In order to facilitate the understanding of those skilled in the art, the present invention is further described below in conjunction with embodiments and drawings. The contents mentioned in the implementation modes are not intended to limit the present invention.

[0033] The data of electric police vehicles passing during the Friday morning rush hour from 7:15:53 ​​to 7:19:22 (the 291st signal cycle) and from 7:19:22 to 7:22:50 (the 292nd signal cycle) at a certain intersection in a certain city in China were selected for analysis.

[0034] Reference Figure 1 As shown, a method for calculating the abnormal release state of an inlet channel of the present invention comprises the following steps:

[0035] 1) Determine whether the phase sequence of the i-th signal cycle at the end of the i-th signal cycle is consistent with the phase sequence of the i-1-th signal cycle. If they are consistent, the phase-lane expectation association index matrix of the i-th signal cycle is equal to the phase-lane expectation association index matrix of the i-1-th signal cycle, and enter step 2); if they are inconsistent or i=1, then based on the relationship between the signal phase and the lane release state, calculate the phase-lane expectation association index of each lane to form a phase-lane expectation association index vector, and complete the construction of the phase-lane expectation association index matrix of the intersection; specifically including:

[0036] 11) Determine whether the phase sequence of the i-th signal cycle at the end of the i-th signal cycle is consistent with the phase sequence of the i-1-th signal cycle. If they are consistent, the phase-lane expected correlation index matrix W of the i-th signal cycle is i Equal to the phase-lane expected correlation index matrix W of the i-1th signal cycle i-1, proceed to step 2); if not consistent or the i-1th signal cycle does not exist, proceed to step 12);

[0037] 12) Based on the release relationship between the signal stage and the lane status, the stage-lane expected correlation index of each lane is calculated to form the stage-lane expected correlation index vector W sj =[w sj,1 w sj,2 …w sj,k …w sj,n ], where w sj,k represents the phase-lane expected association index between lane k and phase sj. When phase sj allows vehicles in lane k to pass, w sj,k =1; when the vehicle in lane k is prohibited from passing in stage sj, w sj,k = 0; when stage sj allows vehicles in lane k to enter the waiting area or waiting to turn area, w sj,k =L pt / (L pt +L ca ), k is the lane number, sj is the stage number, L pt is the length of the waiting area or waiting transfer area, L ca is the length of the channelization section;

[0038] To the north of the intersection, there are north through lane 1 (L1), north through lane 2 (L2), and north left turn lane (L3); to the east, there are east through lane (L4), east left turn lane 1 (L5), east left turn lane 2 (L6), and east left turn lane 3 (L7); to the south, there are south through lane 1 (L8), south through lane 2 (L9), and south left turn lane (L10); to the west, there are west through lane 1 (L11), west through lane 2 (L12), and west left turn lane (L13).

[0039] The release stage during the morning peak period S = {S9, S4, S8, S0}, where S9: east-west straight, S4: east-west left turn, S8: north-south straight, S0: north-south left turn.

[0040] 13) Based on the phase-lane expected association index vector, construct the phase-lane expected association index matrix W of the intersection i =[W s1 ; W s2 ;…;W sj ;…;W sm ];

[0041]

[0042] 2) Calculate the actual phase-lane correlation index of each lane at the end of the i-th signal cycle phase sj to form a phase-lane actual correlation index vector, and complete the construction of the phase-lane actual correlation index matrix of the intersection at the end of the i-th signal cycle; specifically include:

[0043] 21) Record the end time of the stage sj at the end of the i-th signal cycle stage and release time Where i is the signal cycle number;

[0044] 22) Collection period The vehicle passing data of each lane is used to calculate the actual correlation index of the stage-lane, as follows:

[0045]

[0046] in, represents the actual phase-lane correlation index between lane k and phase sj in the i-th signal cycle; μ, ε, θ are weight coefficients, μ+ε+θ=1; represents the saturation of lane k in the i-th signal cycle sj stage, represents the time when the mth vehicle passes in lane k during the i-th signal cycle sj, H k is the average headway time of lane k under saturated traffic flow conditions; (considering that in the case of non-saturation, vehicles usually pass through the front part of the stage, and the vehicles passing through the back part of the stage are relatively scattered and random) the stage-lane actual correlation index is positively correlated with the passing order of vehicles in the stage. Compared with vehicles passing later in the stage, the influence factor of vehicles passing earlier is greater; the stage-lane actual correlation index is related to the average passing interval. The closer the average passing interval is to the saturated headway time, the more obvious the continuity of passing vehicles is, and the stronger the correlation between lane and stage; the stage-lane actual correlation index is related to lane saturation. The higher the lane saturation, the stronger the correlation between lane and stage.

[0047] Taking the 291st signal cycle stage S8 as an example,

[0048] Lane L1 has 25 vehicle passing records in stage S8 (7:17:13-7:18:41), and the passing times are:

[0049]

[0050] Calculation phase - lane actual correlation index

[0051] Lane L3 has 3 vehicle passing records in stage S8 (7:17:13-7:18:41), and the passing times are:

[0052] 7:18:07 7:18:26 7:18:29 Calculation phase - lane actual correlation index

[0053] 23) Based on the actual correlation index of stage-lane Forming the stage-lane actual association index vector of stage sj

[0054] 24) Based on the phase-lane actual correlation index vector, construct the phase-lane actual correlation index matrix at the end of the signal cycle

[0055]

[0056] 3) Based on the stage-lane expected correlation index matrix and the stage-lane actual correlation index matrix, the correlation coefficient between the lane-stage expected correlation index vector and the lane-stage actual correlation index vector of lane k is calculated, and whether there is an abnormal release state is analyzed to obtain the abnormal release state result; specifically, it includes:

[0057] 31) Based on the stage-lane expected correlation index matrix W i and the stage-lane actual association index matrix R i , extract the lane-phase expected association index vector of lane k in the i-th signal cycle Extract the lane-phase actual correlation index vector of lane k in the i-th signal cycle

[0058] 32) Calculate the correlation coefficient between the lane-stage expected correlation index vector and the lane-stage actual correlation index vector of lane k at the end of each signal cycle. as follows:

[0059]

[0060] in, W k and The covariance of is the average expected correlation index of lane k in the i-th signal cycle stage, is the variance of the expected correlation index of lane k in the i-th signal cycle stage; is the average actual correlation index of lane k in the i-th signal cycle stage, is the variance of the actual correlation index of lane k in the i-th signal cycle stage;

[0061] ρ 291=[0.75 0.75 0.75 0.75 0.74 0.75 0.74 0.75 0.75 0.75 0.75 0.75 0.75 -0.11]

[0062] ρ 292 =[0.75 0.75 0.75 0.73 0.75 0.75 0.75 0.75 0.75 0.75 0.75 0.74 0.75 -0.11]

[0063] 33) Correlation coefficient and This indicates that the lane-stage correlation is incorrect, and the lane correlation of the left lane of L13 West needs to be checked.

[0064] The present invention has many specific application paths. The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements can be made without departing from the principle of the present invention. These improvements should also be regarded as the protection scope of the present invention.

Claims

1. A method for calculating the abnormal release state of an inlet channel, characterized in that: Here are the steps: 1) Determine whether the phase sequence of the i-th signal cycle at the end of the i-th signal cycle is consistent with the phase sequence of the i-1-th signal cycle. If they are consistent, the phase-lane expected association index matrix of the i-th signal cycle is equal to the phase-lane expected association index matrix of the i-1-th signal cycle, and enter step 2); if they are inconsistent or i=1, the phase-lane expected association index of each lane is calculated based on the relationship between the signal phase and the lane release state to form a phase-lane expected association index vector, and complete the construction of the phase-lane expected association index matrix of the intersection; 2) Calculate the actual phase-lane correlation index of each lane at the end of the i-th signal cycle phase sj to form a phase-lane actual correlation index vector, and complete the construction of the phase-lane actual correlation index matrix of the intersection at the end of the i-th signal cycle; 3) Based on the stage-lane expected correlation index matrix and the stage-lane actual correlation index matrix, calculate the correlation coefficient between the lane-stage expected correlation index vector and the lane-stage actual correlation index vector of lane k, analyze whether there is an abnormal release state, and obtain the abnormal release state result.

2. The calculation method of abnormal release status of the entrance channel according to claim 1 is characterized in that: The step 1) specifically includes: 11) Determine whether the phase sequence of the i-th signal cycle at the end of the i-th signal cycle is consistent with the phase sequence of the i-1-th signal cycle. If they are consistent, the phase-lane expected correlation index matrix W of the i-th signal cycle is i Equal to the phase-lane expected correlation index matrix W of the i-1th signal cycle i-1 , proceed to step 2); if not consistent or the i-1th signal cycle does not exist, proceed to step 12); 12) Based on the relationship between the signal stage and the lane release status, the stage-lane expected correlation index of each lane is calculated to form the stage-lane expected correlation index vector W sj =[w sj,1 w sj,2 ... sj,k ... sj,n ], where w sj,k represents the phase-lane expected association index between lane k and phase sj. When phase sj allows vehicles in lane k to pass, w sj,k =1; when the vehicle in lane k is prohibited from passing in stage sj, w sj,k = 0; when stage sj allows vehicles in lane k to enter the waiting area or waiting to turn, w sj,k =L pt / (L pt +L ca ), k is the lane number, sj is the stage number, L pt is the length of the waiting area or waiting transfer area, L ca is the length of the channelization section; 13) Based on the phase-lane expected association index vector, construct the phase-lane expected association index matrix W of the intersection i =[W s1 ; W s2 ;...;W sj ;...;W sm ].

3. The calculation method of abnormal release status of the entrance channel according to claim 1 is characterized in that: The step 2) specifically includes: 21) Record the end time of the stage sj at the end of the i-th signal cycle stage and release time Where i is the signal cycle number; 22) Collection period The vehicle passing data of each lane and the actual lane correlation index are calculated as follows: in, represents the actual phase-lane correlation index between lane k and phase sj in the i-th signal cycle; μ, ε, θ are weight coefficients, μ+ε+θ=1; represents the saturation of lane k in the i-th signal cycle sj stage, represents the time when the mth vehicle passes in the i-th signal cycle sj in lane k, H k is the average headway time of lane k under saturated traffic flow conditions; 23) Based on the actual correlation index of stage-lane Forming the stage-lane actual association index vector of stage sj 24) Based on the phase-lane actual correlation index vector, construct the phase-lane actual correlation index matrix at the end of the signal cycle 4. The calculation method of abnormal release status of the entrance channel according to claim 3 is characterized in that: The step 3) specifically includes: 31) Based on the stage-lane expected correlation index matrix W i and the stage-lane actual association index matrix R i , extract the lane-phase expected association index vector of lane k in the i-th signal cycle Extract the lane-phase actual correlation index vector of lane k in the i-th signal cycle 32) Calculate the correlation coefficient between the lane-stage expected correlation index vector and the lane-stage actual correlation index vector of lane k at the end of each signal cycle. as follows: in, W k and The covariance of is the average expected correlation index of lane k in the i-th signal cycle stage, is the variance of the expected correlation index of lane k in the i-th signal cycle stage; is the average actual correlation index of lane k in the i-th signal cycle stage, is the variance of the actual correlation index of lane k in the i-th signal cycle stage; 33) Determine whether there is an abnormal release state. If the correlation coefficient Indicates that the lane and stage association is incorrect, indicating that the lane association is configured incorrectly and needs to be checked; if It indicates that the correlation coefficient jumps and the lane association relationship changes, which means that the lane association relationship may be disordered or the light group wiring may be disordered due to system updates and other reasons. The signal period i where the jump occurs is recorded and a timely warning is issued; β is the minimum correlation coefficient for judging the normal association relationship between the lane and the stage, and γ is the jump coefficient for judging the change of the lane association relationship.

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