Urban trunk traffic signal control effect evaluation method based on single vehicle theory

Abstract

According to the method for evaluating the urban trunk traffic signal control effect based on the single-vehicle theory provided by the invention, the obtained gate data is used for deducing to obtain a time theoretical value sequence for all vehicles on a certain lane to arrive at a downstream intersection within a certain time period needing phase positioning; and further obtaining a green light phase arrival proportion and an upstream intersection signal control phase evaluation index. According to the evaluation method provided by the invention, the Platon Ratio index calculation model which is more suitable for the actual situation and is based on the bicycle identification data is provided; the theoretical arrival time of the vehicle arriving at the parking line at the intersection is deduced by using the vehicle matching characteristics of the single vehicle identification data, and the new model has practical guiding significance; the TAD trunk line coordination evaluation index based on the single vehicle identification data is provided, the PCD index for evaluating the trunk line coordination control effect provided in the prior art and a calculation method are improved, the limitation of the PCD index in domestic application is improved, and the method has more practical guiding significance in China.

Description

Technical Field

[0001] The present invention relates to the field of media communication technology, and in particular to an evaluation method for urban arterial traffic signal control effects based on a bicycle theory. Background Art

[0002] While the development of motorization brings convenience to everyone involved in traffic, the contradiction between traffic supply and demand is becoming increasingly acute. Signal control is one of the effective means to reduce traffic problems such as vehicle delays and queues at signalized intersections. How to distinguish different signal control strategies and implement effective traffic management has become a key focus for traffic managers. Furthermore, with the advancement of detection technology, traffic detection data is becoming more accessible. In-depth mining of this data is a highly effective way to gain a comprehensive understanding of traffic operations.

[0003] When evaluating and even optimizing signal control, it's crucial not only to focus on the operational status of individual intersections but also, more importantly, to assess the traffic flow along the entire arterial route. Among arterial evaluation metrics, travel time is crucial for both drivers and traffic engineers. It not only helps drivers decide on their travel plans but also serves as an indicator of the overall road network's operational status. Furthermore, travel time calculations can be used to derive other metrics, such as average speed, delays, and service levels.

[0004] Extensive research has been conducted both domestically and internationally on using travel time for evaluation. Many studies abroad use the floating vehicle method to calculate travel time by collecting the time it takes a vehicle to reach the starting point of a trunk route and the time it takes to pass the stop line at the end of the route. The average travel time is then used to measure the effectiveness of trunk coordination. However, due to the limited sample size of floating vehicles, the data collected at each sample point is intermittent, making it difficult to generalize from a single point to the entire picture, making it difficult to represent the actual operating status of every vehicle, or even a majority of vehicles, on the road. Domestic studies have also used the GPS positioning system of floating vehicles to calculate travel time. Li Yamin, based on the positioning and speed characteristics of floating vehicle data, developed Kalman filter and neural network models to calculate segment travel time and provide short-term travel time predictions. Zuo Qing combined bus and taxi data as two types of floating vehicle data, expanding the sample size from the original taxi data alone. Using the individual vehicle travel time calculated from these two types of floating vehicle data to estimate segment travel time, he demonstrated improved accuracy compared to existing estimation algorithms. However, similar to international studies on travel time based on floating vehicle data, domestic studies are limited by sample size, resulting in only qualitative results.

[0005] In China, the calculation model of travel time has been relatively perfected based on the advantage of single-vehicle identification data in matching upstream and downstream vehicles. The average travel time of a section has also become an important indicator for the coordination evaluation of arterial lines. However, for travelers, it is not enough to only obtain information on the average travel time of a section. Travelers are more concerned about when the travel time is guaranteed, or how much the guaranteed travel time is at a certain time. Therefore, the research on the reliability of travel time is becoming more and more important. It characterizes the probability of arrival between ODs under a given time interval and the required service level. First, the collected single-vehicle identification data is used to match the license plates of vehicles at the exit and entrance of the arterial line. After obtaining the travel time of all successfully matched vehicles, the reliability index of the travel time can be calculated. Commonly used reliability indexes include 90 th and 95 th Percentile travel time, buffer time, buffer time coefficient, planned travel time, planned travel time index.

[0006] Christopher M. Day and others from Purdue University used high-precision vehicle passing data collected by a front detector located 120 meters before the stop line, combined with the status of intersection traffic lights, to propose the PCD graph as an evaluation indicator to improve the evaluation efficiency of arterial coordination.

[0007] The PCD diagram is an effective indicator for evaluating the coordination effect of arterial lines. It graphically displays the quality of vehicle operation during the study period. Figure 5 and Figure 6 As shown in the PCD diagram, each point represents the time a vehicle arrives at the front detector and the time within a cycle. Therefore, the larger the vertical coordinate of a point, the later the vehicle it represents arrives within the cycle; correspondingly, the larger the horizontal coordinate of a point, the later the vehicle it represents arrives during the day. The locations of densely packed points represent the arrival times of the majority of the convoy. The green line represents the time when the green light turns on, and the red line represents the time when the red light turns on. By observing and analyzing the locations of densely packed points, the effectiveness of arterial coordination can be evaluated. Figure 5 The dense point band is located between the green and red lines, which means that most vehicles arrive during the green light period. Figure 5 The trunk coordination shown is excellent, while Figure 6 The densely packed band shown is below the green line, meaning that most vehicles arrive during red light periods, thus representing poor arterial coordination.

[0008] TAD map and PCD Figure 1The horizontal axis represents the time of day, and the vertical axis represents the time of the cycle. To represent vehicles detected by checkpoint data in the form of PCDs, the problem of accurately estimating the theoretical time a vehicle reaches the stop line must be solved. Checkpoints record information about vehicles crossing the stop line during green light periods. However, vehicles arriving during red light phases must wait in line for the green light to illuminate before passing through the intersection. Alternatively, vehicles arriving during green light phases must wait for the intersection queue to clear before passing through. At this time, the checkpoint system cannot record the theoretical time these vehicles arrive at the intersection. Therefore, obtaining the theoretical time a vehicle reaches the stop line is crucial. Summary of the Invention

[0009] The embodiment of the present invention provides an evaluation method for the control effect of urban arterial traffic signals based on the bicycle theory, which is used to solve the technical problems existing in the prior art.

[0010] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions.

[0011] The evaluation method of urban arterial traffic signal control effect based on the bicycle theory includes:

[0012] S1 obtains the theoretical time sequence of all vehicles on a single lane arriving at the downstream intersection within a certain time period requiring phase positioning based on the checkpoint data of the upstream intersection;

[0013] S2 sets the initial values ​​of vehicles arriving at the green light phase interval and the red light phase interval in a certain period, and determines the theoretical value sequence of the time for all vehicles in the single lane to arrive at the downstream intersection within the time period;

[0014] S3: If the theoretical time value of a vehicle arriving at the downstream intersection is within the period, the theoretical time value of the vehicle arriving at the downstream intersection is phase-positioned; otherwise, the theoretical time value of the vehicle arriving at the downstream intersection is ignored.

[0015] If the theoretical time for the vehicle to arrive at the downstream intersection after phase positioning is within the green light phase interval of the cycle, then the statistics of vehicles arriving with a green light in the green light phase interval of the cycle are increased by 1; otherwise, the statistics of vehicles arriving with a red light in the red light phase interval of the cycle are increased by 1;

[0016] S5 repeats steps S2 to S4 to complete the determination of the theoretical value sequence of the time for all vehicles in the lane to arrive at the downstream intersection, and further obtains the green light time arrival rate, the number of vehicles arriving in the green light phase interval, and the number of vehicles arriving in the red light phase interval for the cycle;

[0017] S6 is based on the green light arrival rate, the number of vehicles arriving in the green light phase interval, and the number of vehicles arriving in the red light phase interval, through the formula Get the green light phase arrival ratio PAOG ;

[0018] S7 obtains the arrival proportion P of the green light phase AOG , and through the formula obtains the evaluation index R of the signal control phase of the upstream intersection p .

[0019] [[ID=1,3]]Preferably, step S1 includes:

[0020] S11 obtains the time series of the vehicles in the single lane Lane-id passing through the stop line of the downstream intersection in cycle i according to the bayonet data of the upstream intersection and satisfies where m is the total number of vehicles passing through in lane Lane-id in cycle i;

[0021] S12 performs license plate matching on the corresponding vehicles in the time series of the vehicles in the single lane Lane-id passing through the stop line of the downstream intersection in cycle i to obtain the time series of the vehicles in the single lane Lane-id passing through the stop line of the upstream intersection in cycle i and further obtains the theoretical time series of the vehicles in the single lane Lane-id arriving at the downstream intersection in cycle i and satisfies

[0022] S13 obtains the theoretical arrival time of the leading vehicle in the single lane Lane-id at the downstream intersection in cycle i based on the theoretical time series of the vehicles in the single lane Lane-id arriving at the downstream intersection in cycle i and the theoretical arrival time of the following vehicle j (1 < j < M) in the single lane Lane-id at the downstream intersection in cycle i where, is the time when the leading vehicle passes through the upstream stop line, t ff is the free flow time;

[0023] S14 obtains the theoretical arrival time of the leading vehicle in the single lane Lane-id at the downstream intersection in cycle i + 1 based on formulas (3) and (4)

[0024] S15 obtains the theoretical value series t of the arrival times of all vehicles in the single lane Lane-id at the downstream intersection within the time period (t A , t B ) that requires phase positioning A1 , t A2 , …, t AM ; M is the time period (t A , t B) The total number of vehicles arriving at the downstream intersection within a single lane Lane-id.

[0025] Preferably, steps S2 to S4 specifically include:

[0026] Set the green light phase interval of cycle i to reach the vehicle and vehicles arriving during the red light phase interval The initial values ​​of are 0;

[0027] If the theoretical time for the jth vehicle to arrive at the downstream intersection is t Aj In the time period (t A ,t B ) cycle If t Aj Perform phase positioning; otherwise, ignore this t Aj ;

[0028] If the t after phase positioning is performed Aj In the time period (t A ,t B ) cycle Green light phase interval Within the green light phase interval Green light arrives at the vehicle The statistical value of the red light is increased by 1; otherwise, the red light of the red light phase interval of the cycle reaches the vehicle The statistic value of is increased by 1.

[0029] Preferably, step S5 specifically includes:

[0030] If the time period (t A ,t B If the value of the vehicle sequence number j of the single lane Lane-id arriving at the downstream intersection is less than the value of M, then j is increased by 1, and steps S2 to S4 are repeated until the judgment of the theoretical value sequence of the time for all vehicles in the lane to arrive at the downstream intersection is completed; otherwise, the time period (t A ,t B ) cycle The green light time arrival rate, the number of vehicles arriving during the green light phase interval, and the number of vehicles arriving during the red light phase interval.

[0031] As can be seen from the technical solutions provided by the embodiments of the present invention described above, the present invention provides a method for evaluating the control effects of urban arterial traffic signals based on the single-vehicle theory. This method utilizes acquired checkpoint data to derive a theoretical sequence of arrival times for all vehicles on a single lane at a downstream intersection within a certain time period requiring phase positioning. This method further derives a green light phase arrival ratio and an upstream intersection signal control phase evaluation index. The evaluation method provided by the present invention has the following beneficial effects:

[0032] The advantages of bicycle identification data in calculating the average travel time of bicycles are utilized, and the mechanism of calculating the travel time reliability index using checkpoint data is explained;

[0033] A more practical calculation model for the Platoon Ratio indicator based on single-vehicle recognition data is proposed. The theoretical arrival time of vehicles at the intersection stop line is derived using the vehicle matching characteristics of single-vehicle recognition data. This new model has practical guiding significance.

[0034] A TAD trunk coordination evaluation index based on single-vehicle identification data was proposed, which improved the PCD index and calculation method proposed in the existing technology for evaluating the coordinated control effect of trunk lines, improved its limitations in domestic application, and has more practical guiding significance in China.

[0035] Additional aspects and advantages of the present invention will be set forth in part in the following description, will become apparent from the following description, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1 A processing flow chart of a method for evaluating the control effect of urban arterial traffic signals based on the bicycle theory provided by the present invention;

[0038] Figure 2 A processing flow chart of a preferred embodiment of a method for evaluating the control effect of urban arterial traffic signals based on the bicycle theory provided by the present invention;

[0039] Figure 3 A 2-cycle TAD diagram was drawn for the Beijing Road-Jinning Street East Entrance Lane in Yinchuan City using the evaluation method for urban arterial traffic signal control effects based on the bicycle theory provided by the present invention;

[0040] Figure 4 A morning rush hour TAD diagram was drawn for the Beijing Road-Jinning Street East Entrance Lane in Yinchuan City using the urban arterial traffic signal control effect evaluation method based on the bicycle theory provided by the present invention;

[0041] Figure 5 It is a high-quality PCD diagram in an evaluation method of the prior art;

[0042] Figure 6This is a low-quality PCD diagram in an evaluation method of the prior art. DETAILED DESCRIPTION

[0043] The embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limiting the present invention.

[0044] It will be understood by those skilled in the art that, unless expressly stated otherwise, the singular forms "a", "an", "said" and "the" used herein may also include the plural forms. It should be further understood that the term "comprising" used in the description of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, "connected" or "coupled" as used herein may include wireless connections or couplings. The term "and / or" used herein includes any unit and all combinations of one or more associated listed items.

[0045] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art in the art to which the present invention pertains. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art and, unless defined as such herein, will not be interpreted in an idealized or overly formal sense.

[0046] To facilitate understanding of the embodiments of the present invention, several specific embodiments will be further explained below with reference to the accompanying drawings, and each embodiment does not constitute a limitation on the embodiments of the present invention.

[0047] The present invention provides a method for evaluating the coordinated effect of urban arterial traffic signal control based on the theoretical arrival time of a single vehicle, which is used to evaluate the efficiency of the arterial line. In the arterial coordination evaluation, a common method for evaluating the efficiency of the arterial line is to calculate the green light arrival rate, which characterizes the proportion of vehicles arriving during the green light phase. It is believed that the higher the green light arrival rate, the better the arterial operation. However, under an oversaturated state, a fleet with a high green light arrival rate cannot guarantee optimal signal control. Christopher M. Day and others from Purdue University used high-precision vehicle passing data collected by a front detector located 120 meters in front of the stop line, combined with the status of intersection signal lights, to propose the PCD evaluation index to answer these questions.

[0048] The PCD metric has advantages in evaluating the operating conditions of arterial roads. However, Purdue University's PCD research used vehicle arrival information detected 120 meters before the stop line as the time a vehicle arrives at an intersection and expressed this time in relation to the current traffic light status. However, this approach has three problems:

[0049] (1) Since the front detector used is still some distance away from the stop line, the traffic light status at the intersection has changed when the vehicle actually reaches the stop line and is about to leave the stop line. This causes the relationship between the time when the vehicle actually reaches the stop line and the traffic light status shown in the PCD diagram to be inaccurate;

[0050] (2) Purdue University only studies straight-moving coordination and treats all vehicles detected by the front detector as straight-moving vehicles. However, in reality, there are often left-turning and right-turning vehicles at an intersection. Displaying these vehicles in the PCD diagram will cause inaccurate display of vehicles in the coordinated direction. In other words, the original detector cannot identify the true coordinated direction vehicles.

[0051] (3) The PCD diagram is aimed at straight-through coordination, and actually studies unsaturated flow. When the queue length reaches the front detector and occupies the front detector, the subsequent vehicles cannot detect the vehicle arrival time defined by the PCD. In other words, the original PCD lacks discussion of saturated flow.

[0052] In order to solve these problems and enrich the evaluation indicators of coordinated operation of trunk lines, based on the concept of PCD indicator and the shortcomings of PCD indicator, and combined with the characteristics of a large number of single-vehicle identification data currently available in China, this patent will discuss the use of checkpoint data as an evaluation indicator similar to PCD indicator for measuring trunk line coordination, namely the theoretical arrival-time diagram (TAD).

[0053] See also Figure 1The present invention provides a method for evaluating the control effect of urban trunk traffic signals based on the bicycle theory, comprising the following steps:

[0054] S1 obtains the theoretical time sequence of all vehicles on a single lane arriving at the downstream intersection within a certain time period requiring phase positioning based on the checkpoint data of the upstream intersection;

[0055] S2 sets the initial values ​​of vehicles arriving at the green light phase interval and the red light phase interval in a certain period, and determines the theoretical value sequence of the time for all vehicles in the single lane to arrive at the downstream intersection within the time period;

[0056] S3: If the theoretical time value of a vehicle arriving at the downstream intersection is within the period, the theoretical time value of the vehicle arriving at the downstream intersection is phase-positioned; otherwise, the theoretical time value of the vehicle arriving at the downstream intersection is ignored.

[0057] If the theoretical time for the vehicle to arrive at the downstream intersection after phase positioning is within the green light phase interval of the cycle, then the statistics of vehicles arriving with a green light in the green light phase interval of the cycle are increased by 1; otherwise, the statistics of vehicles arriving with a red light in the red light phase interval of the cycle are increased by 1;

[0058] S5 repeats steps S2 to S4 to complete the determination of the theoretical value sequence of the time for all vehicles in the lane to arrive at the downstream intersection, and further obtains the green light time arrival rate, the number of vehicles arriving in the green light phase interval, and the number of vehicles arriving in the red light phase interval for the cycle;

[0059] S6 is based on the green light arrival rate, the number of vehicles arriving in the green light phase interval, and the number of vehicles arriving in the red light phase interval, through the formula Get the green light phase arrival ratio P AOG ;

[0060] S7 is based on the green light phase arrival ratio P AOG , through the formula Get the upstream intersection signal control phase evaluation index R p .

[0061] In the evaluation of arterial roads, Platoon Ratio is an important indicator for evaluating intersection signal control phases. It uses the ratio of vehicles arriving during a green light phase interval at an intersection to measure whether the intersection timing is reasonable. In many cases, Platoon Ratio has a significant impact on delays and queue lengths. Smaglik et al. p ) is defined as follows:

[0062]

[0063] Where:

[0064] P AOG —Ratio of vehicles arriving at green light phase;

[0065] C—cycle duration;

[0066] g—Green light phase duration.

[0067] In addition, Smaglik, Bullock and Sharma affirmed the advantages of evaluating the operation effect of trunk lines based on the definition of vehicle arrival type (AT) in the American HCM manual, and proposed a method based on R p AT definition method, through R p The different value ranges of represent six types of arrival, and then the quality of signal control is evaluated, see Table 1.

[0068] Table 1 Based on R p Vehicle arrival type determination table

[0069]

[0070] The Platoon Ratio evaluates individual road segments rather than the entire route. It is a transformation of the proportion of vehicles arriving during the green light period. The introduction of the cycle duration C and the green light phase duration g allows the Platoon Ratio to measure the rationality of the relationship between the cycle duration and the green light phase duration.

[0071] Based on the premise that bicycle recognition detectors are currently being widely used in China, how to use the available detector data to calculate the Platoon Ratio is the core of the present invention.

[0072] Smaglik et al. based on a front detector that can obtain high-precision data and combined with the intersection timing scheme to calculate R p , the time when the vehicle reaches the front detector is regarded as the actual time when the vehicle arrives at the intersection, and the phase information of the intersection at that time is used to determine whether the vehicle arrives at the green light phase or the red light phase. However, because the detector is located in the front, there is still some distance from the intersection. When the vehicle reaches the stop line, the phase information of the intersection may have changed. Therefore, the P calculated by the front detector is AOG There is a certain deviation from the actual traffic operation situation, which is also a problem that needs to be solved.

[0073] According to the definition of Platoon Ratio in formula (2), we need to know the quantity P AOG, C and g, namely the vehicle green light phase arrival rate, cycle length and green light phase duration. Checkpoint data is a stop line detector that records the moment when the vehicle passes the stop line, but this moment is not always the moment when the vehicle actually arrives at the intersection. How to use the checkpoint data to deduce the moment when the vehicle actually arrives at the intersection is a problem that needs to be solved; when the signal-controlled intersection is evaluated online, the intersection's signal control timing information cycle length C and green light phase duration g can be directly obtained. Therefore, the key to calculating Platoon Ratio is to determine the green light phase arrival ratio P AOG .

[0074] The calculation method of the green light phase arrival ratio is:

[0075]

[0076] Therefore, from formula (1), if we want to calculate the green light phase arrival ratio P of a certain cycle, AOG , it is necessary to determine the position of the vehicle's arrival time in the cycle. The checkpoint data only records the moment when the vehicle passes the stop line, and does not record the status of the signal light when the vehicle arrives at the intersection. These vehicles may arrive directly at the intersection and pass the stop line during the green light phase of the intersection. At this time, the checkpoint data records the actual arrival time of the vehicle; the vehicle may also arrive during the green light phase of the intersection, but because the queue in front has not been cleared, the vehicle needs to enter the queue and wait. At this time, the actual arrival time of the vehicle cannot be determined by the checkpoint data; in addition, vehicles arriving during the red light phase need to queue behind the stop line, and the time when these queued vehicles enter the queue cannot be determined. The checkpoint data records the actual time when the vehicle arrives at the stop line, and when calculating P AOG We need to know the theoretical time when the vehicle arrives at the stop line, and determine the number of vehicles arriving during the green light phase and the red light phase respectively by the position of the signal cycle at which the vehicle theoretically arrives at the stop line.

[0077] When there are left turns and straight ahead phases at an intersection, the original model by J. Smaglik E. et al. fails to distinguish between different vehicle turns and simply uses the vehicle's arrival time at the detector at 120 meters. Consequently, the calculated results do not distinguish between different left turns and straight ahead phases. Therefore, a method is needed to convert the time it takes for the front detector to detect a vehicle into the theoretical value of the vehicle reaching the stop line and to distinguish between left-turning and straight ahead vehicles, thereby enabling the calculation of the Platoon Ratio for a single lane.

[0078] Using the matching characteristics of bayonet data, the lane information and time information of vehicles passing through the upstream stop line when passing through the downstream single-lane stop line can be found. For the cycle i of the single lane Lane-id, according to the time sequence of vehicles passing through the stop line, the time when the vehicle passes through the stop line is recorded as and there is where m is the total number of vehicles passing through the lane Lane-id in cycle i. Correspondingly, through vehicle license plate matching, the time series of the corresponding vehicle passing through the upstream intersection stop line can be obtained: Record the theoretical time series of these vehicles arriving at the downstream intersection as: and there must be Taking cycle i as the starting calculation cycle, for the leading vehicle, the theoretical time to reach the downstream intersection is the time when the leading vehicle passes through the upstream stop line plus the free flow time:

[0079]

[0080] For the vehicles behind the leading vehicle, The size relationship between them is uncertain, and it cannot be simply determined that the theoretical arrival time of the j-th (1 < j < M) vehicle is This cannot ensure that the theoretical arrival time of the following vehicle is later than that of the previous vehicle. Since a certain headway needs to be maintained between vehicles, the theoretical arrival times of two consecutive vehicles cannot be equal either. Therefore, the theoretical arrival time of the j-th (1 < j < M) vehicle is calculated by the following formula

[0081] interval:

[0082]

[0083] For cycle i + 1, in order to ensure that the theoretical arrival time of the leading vehicle is greater than the theoretical arrival time of the trailing vehicle in cycle i, another

[0084]

[0085] The calculation method of the remaining vehicles in cycle i + 1 is the same as that of the remaining vehicles in cycle i except for the leading vehicle.

[0086] In a preferred embodiment provided by the present invention, obtaining the theoretical value sequence of the time when all vehicles in a certain single lane reach the downstream intersection within a certain time period that requires phase positioning specifically includes:

[0087] S11 Obtain the time series of vehicles in the single lane Lane-id passing through the downstream intersection stop line in cycle i according to the bayonet data of the upstream intersection and satisfy In the formula, m is the total number of vehicles passing through the lane Lane-id in cycle i;

[0088] S12 matches the vehicles corresponding to the time series of the vehicles in the single lane Lane-id passing through the stop line of the downstream intersection in cycle i, and obtains the time series of the vehicles in the single lane Lane-id passing through the stop line of the upstream intersection in cycle i Furthermore, obtain the theoretical time series of the vehicles in the single lane Lane-id arriving at the downstream intersection in cycle i and satisfy

[0089] S13 is based on the theoretical time series of the vehicles in the single lane Lane-id arriving at the downstream intersection in cycle i Obtain the theoretical time when the leading vehicle in the single lane Lane-id arrives at the downstream intersection in cycle i and the theoretical time when the following vehicle j (1 < j < M) in the single lane Lane-id arrives at the downstream intersection in cycle i In the formula, is the time when the leading vehicle passes through the upstream stop line, t ff is the free flow time;

[0090] S14 is based on formulas (3) and (4) to obtain the theoretical time when the leading vehicle in the single lane Lane-id arrives at the downstream intersection in cycle i + 1

[0091] S15 is based on formulas (3), (4) and (5) to obtain the time period (t A , t B ) during which phase positioning is required, and the theoretical time value series t of all vehicles in the single lane Lane-id arriving at the downstream intersection A1 , t A2 , …, t AM ; M is the total number of vehicles in the single lane Lane-id arriving at the downstream intersection during the time period (t A , t B ).

[0092] The above calculation rules ensure that the calculated theoretical arrival time of the vehicle is consistent with the time magnitude relationship of the vehicle passing through the stop line in this lane. For a determined time period (t A , t B ), find the theoretical arrival time series t of all vehicles arriving at the downstream lane Lane-id within the time period A1 , t A2 , …, t AM ​According to the timing information of the signal light intersection, the number of vehicles arriving in each cycle is counted. The number of vehicles arriving in the green light phase interval and the number of vehicles arriving in the red light phase interval in a cycle can be used to calculate the green light time arrival rate of a single lane in a cycle. For a certain lane, let the time period (t A ,t B ) There are a total of M vehicles theoretically arriving at the downstream intersection lane Lane-id, and assuming the cycle In the period (t A ,t B ), in the calculation cycle When the green light phase arrival rate is high, the time period (t A ,t B ) in the cycle middle.

[0093] Figure 2 The process shown is the optimal calculation process for the single-cycle single-lane green light phase interval arrival rate based on the above calculation rules. The main steps are as follows:

[0094] (1) Input the time period (t A ,t B ) Theoretical value of vehicle arrival time t A1 ,t A2 ,…,t AM ;

[0095] (2) Set the green light phase interval of cycle i to reach the vehicle and vehicles arriving during the red light phase interval The initial values ​​of are 0, and the judgment starts from the first value (i.e. the first vehicle);

[0096] (3) If the theoretical time t of the jth vehicle arriving at the downstream intersection needs to be determined Aj In the time period (t A ,t B ) cycle If t Aj Perform phase positioning; otherwise, ignore this t Aj ;

[0097] (4) If the t Aj In the time period (t A ,t B ) cycle Green light phase interval Within the green light phase interval Green light arrives at the vehicle The statistical value of the red light is increased by 1; otherwise, the red light of the red light phase interval of the cycle reaches the vehicle The statistical value of is increased by 1;

[0098] (5) If the time period (t A ,t B ) If the value of the vehicle sequence number j arriving at the downstream intersection in the single lane Lane-id is less than the value of M, then j is increased by 1, that is, the next theoretical arrival time t is located. A(j+1) Repeat steps (2) to (4) until (t A ,t B ) After all vehicles in the time period have been judged once, the cycle ends;

[0099] (6) Calculate the green light arrival rate and output the green light arrival rate, the number of vehicles arriving in the green light phase interval, and the number of vehicles arriving in the red light phase interval in cycle i.

[0100] After calculating the vehicle arrival rate for the green light phase according to the above method, the Platoon Ratio value for a single cycle and single lane is calculated by combining it with the calculation formula of the Platoon Ratio. The arrival type of the vehicle in the lane can then be obtained by consulting the manual, and the signal timing scheme can be evaluated. However, in general, the signal timing of the intersection is fixed in time periods. In this case, if the Platoon Ratio value or vehicle arrival type for a time period and lane is to be calculated, the fixed timing period can be divided into several consecutive red light phase intervals and green light phase intervals. The calculated theoretical number of vehicles arriving in the fixed timing period is then located in these phase intervals. The number of vehicles located in the red light phase interval and the green light phase interval is then counted respectively. The Platoon Ratio of the fixed timing period is then calculated using equations (2) to (1), and the rationality of the corresponding signal control operation effect is evaluated.

[0101] Combined with the above calculation of the theoretical vehicle arrival time, the required TAD diagram can be made. The horizontal axis of the TAD diagram represents the time of day, and the vertical axis represents the cycle time. The vehicles detected by the checkpoint data are expressed in the form of PCD, and it is necessary to accurately estimate the time when the vehicle theoretically arrives at the stop line. Because the checkpoint records the information of vehicles passing the stop line during the green light period, but vehicles arriving during the red light phase need to queue and wait for the green light to come on before passing through the intersection, or vehicles arriving during the green light phase need to wait for the intersection queue to clear before passing through the intersection. At this time, the checkpoint system cannot record the theoretical arrival time of these vehicles at the intersection, so it is crucial to accurately estimate the theoretical arrival time of the vehicle at the stop line.

[0102] According to the estimation method of vehicle theoretical arrival time and the construction principle of TAD diagram, the required TAD diagram is made according to the example, such as Figure 3Shown is a TAD plot for a single cycle of the No. 2 east-west straight lane between Beijing Road and Jinning Street in Yinchuan. A complete cycle is divided into effective green light time and effective red light time. The horizontal axis represents the time of day, and the vertical axis represents the time of cycle. Black dots indicate the theoretical arrival time of a vehicle, both within the day and within the intersection's signal cycle. During the study cycle, vehicles arriving during the green phase far outnumbered those arriving during the red phase, indicating reasonable intersection timing.

[0103] Figure 4 A diagram of theoretical vehicle arrival times during the morning rush hour, 7:00-9:00 AM. It's easy to see from the diagram that during the morning rush hour, the vast majority of vehicles arrive during the green light phase, while only a small number arrive during the red light phase, forcing them to queue during the red light period. This demonstrates that the east-west straight-through direction of Beijing Road in Yinchuan has excellent arterial coordination, which is consistent with the Platoon Ratio evaluation results.

[0104] In summary, the present invention provides a method for evaluating the effectiveness of urban arterial traffic signal control based on the single-vehicle theory. This method utilizes acquired checkpoint data to derive a theoretical sequence of arrival times for all vehicles on a single lane at a downstream intersection within a specific time period requiring phase positioning. This method further derives the green light phase arrival ratio and an evaluation index for the upstream intersection signal control phase. The evaluation method provided by the present invention has the following beneficial effects:

[0105] Starting from a review of commonly used evaluation indicators at home and abroad and the detectors required to calculate these indicators, a comparison revealed that traffic detection data is currently underutilized in China. This led to an in-depth analysis of traffic detection data based on single-vehicle recognition. A calculation method for the Platoon Ratio indicator based on single-vehicle recognition data was proposed, enriching the intersection signal control operation effect evaluation system based on single-vehicle recognition data.

[0106] The advantages of bicycle identification data in calculating the average travel time of bicycles are utilized, and the mechanism of calculating the travel time reliability index using checkpoint data is explained;

[0107] Through the vehicle matching function of bicycle identification data, the method of calculating travel time reliability index is sorted out, and the calculation method of travel time reliability index such as buffer index using bicycle identification data is discussed;

[0108] A more practical calculation model for the Platoon Ratio indicator based on single-vehicle recognition data is proposed. The theoretical arrival time of vehicles at the intersection stop line is derived using the vehicle matching characteristics of single-vehicle recognition data. This new model has practical guiding significance.

[0109] In terms of trunk line coordination evaluation, taking into account factors such as queue length and signal timing, a TAD (Theoretical Arrival-time Diagram) model based on the theoretical arrival time of a single vehicle was established, and a TAD trunk line coordination evaluation index based on single vehicle identification data was proposed. This improves the PCD index and calculation method proposed in the existing technology for evaluating the coordinated control effect of trunk lines, improves its limitations in domestic application, and has more practical guiding significance in China.

[0110] Those skilled in the art will appreciate that the accompanying drawings are merely schematic diagrams of an embodiment, and the modules or processes in the accompanying drawings are not necessarily required to implement the present invention.

[0111] From the above description of the embodiments, it can be seen that those skilled in the art can clearly understand that the present invention can be implemented by means of software plus the necessary general-purpose hardware platform. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present invention or certain parts of the embodiments.

[0112] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the device or system embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For the relevant parts, refer to the partial description of the method embodiments. The device and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. A person of ordinary skill in the art can understand and implement it without making any creative efforts.

[0113] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. An evaluation method for the control effect of urban arterial traffic signals based on the bicycle theory is characterized by: include: S1 obtains the theoretical time sequence of all vehicles on a single lane arriving at the downstream intersection within a certain time period requiring phase positioning based on the checkpoint data of the upstream intersection; S2 sets the initial values ​​of vehicles arriving at the green light phase interval and the red light phase interval in a certain period, and determines the theoretical value sequence of the time for all vehicles in the single lane to arrive at the downstream intersection within the time period; S3: If the theoretical time value of a vehicle arriving at the downstream intersection is within the period, the theoretical time value of the vehicle arriving at the downstream intersection is phase-positioned; otherwise, the theoretical time value of the vehicle arriving at the downstream intersection is ignored. If the theoretical time for the vehicle to arrive at the downstream intersection after phase positioning is within the green light phase interval of the cycle, then the statistics of vehicles arriving with a green light in the green light phase interval of the cycle are increased by 1; otherwise, the statistics of vehicles arriving with a red light in the red light phase interval of the cycle are increased by 1; S5 repeats steps S2 to S4 to complete the determination of the theoretical value sequence of the time for all vehicles in the lane to arrive at the downstream intersection, and further obtains the green light time arrival rate, the number of vehicles arriving in the green light phase interval, and the number of vehicles arriving in the red light phase interval for the cycle; S6 is based on the green light arrival rate, the number of vehicles arriving in the green light phase interval, and the number of vehicles arriving in the red light phase interval, through the formula Get the green light phase arrival ratio P AOG ; S7 is based on the green light phase arrival ratio P AOG , through the formula Get the upstream intersection signal control phase evaluation index R p .

2. The evaluation method according to claim 1, wherein: Step S1 includes: S11 obtains the time series of the vehicle with lane ID passing through the stop line of the downstream intersection in cycle i based on the checkpoint data of the upstream intersection and satisfy Where m is the total number of vehicles passing through lane Lane-id in cycle i; S12 is the time series of the vehicles of the single lane Lane-id passing the stop line of the downstream intersection in cycle i. The corresponding vehicle is matched with the license plate to obtain the time series of the vehicle with single lane Lane-id passing the upstream intersection stop line in cycle i Further obtain the theoretical time series of vehicles with single lane Lane-id arriving at the downstream intersection in cycle i and satisfy S13 Theoretical time series of vehicles on the single lane with Lane-id arriving at the downstream intersection in cycle i Obtain the theoretical time when the leading vehicle on the single lane with Lane-id arrives at the downstream intersection in cycle i And the theoretical time when the following vehicle j (1 < j < M) on the single lane with Lane-id arrives at the downstream intersection in cycle i In the formula is the time when the leading vehicle passes the upstream stop line, t ff is the free flow time S14 Based on formulas (3) and (4), the theoretical time for the first vehicle of single lane Lane-id to reach the downstream intersection in cycle i+1 is obtained: S15 obtains the time period (t A ,t B ) The theoretical time sequence t of all vehicles in a single lane Lane-id arriving at the downstream intersection A1 ,t A2 ,…,t AM ; M is the time period (t A ,t B ) The total number of vehicles arriving at the downstream intersection within a single lane Lane-id.

3. The evaluation method according to claim 2, wherein: Steps S2 to S4 specifically include: Set the green light phase interval of cycle i to reach the vehicle and vehicles arriving during the red light phase interval The initial values ​​of are 0; If the theoretical time for the jth vehicle to arrive at the downstream intersection is t Aj In the time period (t A ,t B ) cycle If t Aj Perform phase positioning; otherwise, ignore this t Aj ; If the t after phase positioning is performed Aj In the time period (t A ,t B ) cycle Green light phase interval Within the green light phase interval Green light arrives at the vehicle The statistical value of the red light is increased by 1; otherwise, the red light of the red light phase interval of the cycle reaches the vehicle The statistic value of is increased by 1.

4. The evaluation method according to claim 3, wherein: Step S5 specifically includes: If the time period (t A ,t B If the value of the vehicle sequence number j of the single lane Lane-id arriving at the downstream intersection is less than the value of M, then j is increased by 1, and steps S2 to S4 are repeated until the judgment of the theoretical value sequence of the time for all vehicles in the lane to arrive at the downstream intersection is completed; otherwise, the time period (t A ,t B ) cycle The green light time arrival rate, the number of vehicles arriving during the green light phase interval, and the number of vehicles arriving during the red light phase interval.

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