A method for calibrating bus priority demand time windows across intersections

Abstract

This invention discloses a method for calibrating the time window of bus priority demand across intersections, comprising the following steps: virtualizing bus stops and signalized intersections as computing nodes; constructing probability distribution calculation models for bus arrival and departure from nodes based on the travel time of buses between adjacent nodes, signal timing delays within signalized intersection nodes, and station dwell time characteristics within bus stop nodes; effectively transmitting upstream bus information across intersections through a lookup table of bus route entry directions at signalized intersections, obtaining the arrival probability distribution of buses at signalized intersections and its maximum distribution segment; dynamically updating the active vehicle request table for bus request phases, and adjusting the demand time window of bus request phases in a timely manner based on the earliest maximum arrival probability distribution segment in the table, providing strong data support for bus signal priority control strategies.

Description

Technical Field

[0001] This invention belongs to the technical field of bus arrival prediction and bus request phase demand time window calibration in traffic engineering, and in particular, a method for calibrating bus priority demand time windows across intersections. Background Technology

[0002] With breakthroughs in traffic sensing technology and the rapid development of intelligent urban transportation, urban public transportation is becoming increasingly large-scale, and bus signal priority control is becoming increasingly sophisticated. The operating environment of buses is complex, easily affected by factors such as platform dwell time, signal timing delays, and traffic interference on road sections. It is difficult to predict the time distribution of buses' arrival at the stop line of signalized intersections simply and accurately, resulting in a lack of effective time windows to support bus request phase demand in bus signal priority control decisions. The difficulty of prediction increases significantly when buses cross intersections.

[0003] Currently, the industry mainly uses methods such as historical travel time data prediction and distance-speed formula calculation to predict bus arrival distribution. These methods do not consider the two key factors affecting the stable operation of buses: bus stops and signal delays. They also lack cross-intersection prediction methods, have slow response to real-time conditions, and the prediction results have deviations of minutes, which greatly reduces the effectiveness of subsequent bus signal priority control strategies.

[0004] Therefore, constructing a practical, precise, and real-time prediction model for bus arrival distribution based on key influencing factors, and designing a calibration method for the time window of bus request phase release demand, has significant socio-economic impacts on improving the effectiveness of bus signal priority control strategies and enhancing the level of urban public transport services. Summary of the Invention

[0005] The purpose of this invention is to address the current situation where bus arrival prediction results are too coarse, and to provide a method for calibrating the time window of bus priority demand across intersections. The method virtualizes bus stops and signalized intersections as computing nodes, constructs a calculation model for the probability distribution of bus arrival and departure nodes, calculates the arrival probability distribution of buses at signalized intersections and statistically analyzes its maximum distribution segment, thereby achieving a practical, precise and real-time calibration of the time window of bus priority demand across intersections.

[0006] The technical solution to achieve the purpose of this invention is: a method for calibrating the time window of bus priority demand across intersections, the method comprising the following steps:

[0007] Step 1: Construct a probability distribution calculation model for bus arrival and departure nodes: Virtualize bus stops and signalized intersections as nodes. Based on the travel time of buses between adjacent nodes, construct a probability distribution calculation model for bus arrival at nodes. Based on the signal timing delay within signalized intersection nodes and the dwell time within bus stop nodes, construct a probability distribution calculation model for bus departure at nodes.

[0008] Step 2: Calculate the arrival probability distribution of buses at the signalized intersection and statistically analyze its maximum distribution segment: Establish a lookup table containing all nodes between the upstream and current signalized intersections according to the direction of the bus priority route at the signalized intersection; obtain the departure probability distribution information of buses within a specific minimum time period at adjacent upstream signalized intersections, and calculate the arrival and departure probability distribution of buses for each node in the lookup table one by one using the method in Step 1; statistically analyze the maximum arrival probability distribution segment of buses at the current signalized intersection.

[0009] Step 3, Define the release demand time window for bus request phases at signalized intersections: Based on the mapping relationship between buses and request phases, establish an active vehicle request table for bus request phases at the current signalized intersection; based on the segmentation of the maximum arrival probability distribution of the earliest bus in the active vehicle request table, define the release demand time window for bus request phases.

[0010] Furthermore, the virtualization of bus stops and signalized intersections into nodes in step 1 refers to virtualizing bus stops and signalized intersections into nodes that are easy to model and calculate. Data structures expressing node types and the distribution characteristics of bus arrivals and departures are constructed in each node. Among them, the node types are divided into three types: invalid, bus stop, and signalized intersection.

[0011] Furthermore, the probability distribution calculation model for bus arrival at nodes based on the travel time of buses between adjacent nodes, as described in step 1, is as follows:

[0012] (1) If the previous node N i-1 There are Q buses in the time domain [0, t] up If the probability of leaving is greater than 0 at a time in memory, then the q-th bus b... q In [0, t up Leaving N i-1 And reach N i The probability distribution is calculated as follows:

[0013] Bus vehicle b q In t j Always leave N i-1 probability Fluctuations depending on travel time Pass to N iThe arrival time range is distributed in probability decomposition coefficients satisfy Then because t j Bus schedule b q Leaving N i-1 ,exist Time reaches N i The probability is:

[0014]

[0015] Where Q>0, q∈[1,Q], j∈[0,t] up ];

[0016] For [0, t] up [Inner bus vehicle b] q Leaving N i-1 If the above probability decomposition is performed for all times when the probability is greater than 0, then t i At that time, bus b q Arrival at N i The probability is:

[0017]

[0018] Among them, t j and

[0019] (2) If the current time t0 is at node N i-1 With N i If there are Q buses, then the number of buses between time points t0 is b. q Arrival at N i The probability distribution is calculated as follows:

[0020] Bus vehicle b q Fluctuations depending on travel time Pass to N i Arrival distributed in probability decomposition coefficients satisfy Then due to the bus vehicles b between nodes q Running, in Time reaches N i The probability is:

[0021]

[0022] Furthermore, in step 1, a probability distribution calculation model for bus departure from the intersection is constructed based on the signal timing delay within the signalized intersection node and the station dwell time within the bus stop node, as detailed below:

[0023] 1) Let N i Let b be the current signalized intersection node. If Q buses arrive at this node, then bus b... q In [0, t up The signal timing delay affects the distance from node N. i The probability distribution is calculated as follows:

[0024] Bus vehicle b q In t j The probability of arriving at the stop line at the right time is Then the probability of it leaving the parking line The effects of the bus request phase release attribute in the current signal timing include:

[0025] (d)t j At any given time, if the bus requests a phase that is not green (i.e., not a green light), then...

[0026] (e)t j At any given moment, if the bus requests a green light (phase indicating release) and it is in the first second, then...

[0027]

[0028] in, This indicates the duration of the red light before the bus requests the green light to proceed;

[0029] (f)t j At any given moment, if the bus request phase is of the release attribute and is not in the first second, then...

[0030] 2) Let N i Let b be a bus stop node, and let Q buses arrive at it. q In [0, t up The departure time of node N is affected by fluctuations in the stationing time. i The probability distribution is calculated as follows:

[0031] Bus vehicle b q In t j Time reaches N i Arrival probability Station stay time fluctuation Leave the distribution in probability decomposition coefficients satisfy Then t j Bus schedule b q Arrival at platform node N i , and The probability of leaving at any given moment is:

[0032]

[0033] For [0, t] up [On the bus b] q Arrival at N i If the above probability decomposition is performed for all times when the probability is greater than 0, then t l At that time, bus b q Leaving N i The probability is:

[0034]

[0035] Among them, t j And t k =t l .

[0036] Furthermore, in step 2, a lookup table is established based on the direction of the bus priority route at the signalized intersection, containing all nodes between the upstream and the current signalized intersection, as detailed below:

[0037] Let W be the number of directions of the bus priority lane entrance at the signalized intersection, where K is the lookup table for direction w. w w = 1, 2, ..., W;

[0038] Using the upstream signalized intersection in direction w as the boundary, add node indices in the order of the upstream signalized intersection, all bus stops within the boundary, and the current signalized intersection, resulting in:

[0039] K w ={N1, ..., N n},

[0040] Where n is the total number of indices, N1 is the upstream signal intersection node, and N n N1 represents the current signalized intersection node, and the rest are all bus stop nodes within the boundary; N1 belongs to the calculation scope of the upstream signalized intersection and is the initial node of the current signalized intersection calculation scope, requiring no update; N2~N n This falls under the current scope of signalized intersection calculations and needs to be updated.

[0041] Furthermore, the specific minimum time period mentioned in step 2 refers to the minimum time period from time t0 of the current signalized intersection to the time period containing all bus request phases in the scheme, and each bus request phase appears twice.

[0042] Furthermore, the step 2, which involves statistically analyzing the maximum arrival probability distribution segments of buses at the current signalized intersection, is detailed below:

[0043] The arrival probability distribution information of buses at the last node in the lookup table for each approach direction of the current signalized intersection is merged to generate the arrival probability distribution information of buses at the current signalized intersection, namely:

[0044] Time domain [t0, t up On the current signalized intersection N i There are Q buses with an arrival probability greater than 0, and bus b... q Arrival probability

[0045] Bus vehicle b q At the current signalized intersection N i [t0, t] up If there are K consecutive arrival time periods, then the number of buses b is... q At the current signalized intersection N i [t0, t] up The sum of arrival probabilities for time period k′ with the largest arrival probability distribution on the [database] is:

[0046]

[0047] in, Let k be the kth consecutive arrival distribution period, k∈[1,K].

[0048] Furthermore, in step 3, based on the mapping relationship between buses and requested phases, an active bus request phase request table is established for the current signalized intersection, as detailed below:

[0049] Set the current signalized intersection N i The bus requests the number of phases M in the time domain [t0, t1]. up On the [database], there are Q buses with an arrival probability greater than 0.

[0050] Then the bus requests phase Active vehicle request form Expressed as:

[0051]

[0052] Where, {q1, ..., q Q′} all represent bus request phases The active bus request vehicle number has a value that belongs to [1, Q]. Indicates the qth Q′ A bus requests a vehicle, m∈[1,M].

[0053] Furthermore, in step 3, the time window for determining the release requirement of a bus request phase is segmented based on the maximum arrival probability distribution of the earliest bus in the active vehicle request table, as detailed below:

[0054] Make bus request phase Active vehicle request form Active bus request vehicle b q The end time of the corresponding maximum arrival probability distribution period In {q1, ..., q Q′ The smallest in}, that is

[0055]

[0056] in, for Active bus request vehicle b q′ The corresponding maximum arrival probability distribution time interval ends when q and q′ both belong to {q1, ..., q}. Q′};

[0057] Then bus b q Request phase for bus Priority target buses;

[0058] Bus request phase The end time of the release demand time window is taken as the end time of the period with the highest arrival probability distribution of priority target buses, that is...

[0059] Bus request phase The value of the release demand time window Δt is:

[0060]

[0061] in, Weighted duration for the maximum arrival probability distribution of priority target buses For the start time of the consecutive arrival probability distribution period, and Within the same consecutive arrival probability distribution period, the weighting coefficient ω∈[0,1], Δt is the duration of the green light request for the bus to proceed. h Manually configure time window constraint values;

[0062] That is, the bus request phase The range of the release demand time window is

[0063] Compared with the prior art, the significant advantages of this invention are:

[0064] (1) Based on the characteristics between and within the bus stop and signalized intersection nodes, construct a calculation model for the probability distribution of bus arrival and departure, fully retain key element information, and ensure more precise subsequent predictions.

[0065] (2) By constructing a node retrieval table for the direction of bus routes at signalized intersections, the transmission of upstream bus vehicle information across intersections can be effectively realized. The method is simple and practical.

[0066] (3) By updating information such as bus location, station time, and timing scheme in seconds, the bus arrival distribution is calculated in real time, the active vehicle request table of the bus request phase is dynamically updated, and the demand time window of the bus request phase is adjusted in a timely manner based on the earliest maximum arrival probability distribution segment in the table, so as to provide strong data support for the bus signal priority control strategy.

[0067] The present invention will now be described in further detail with reference to the accompanying drawings. Attached Figure Description

[0068] Figure 1 This is a flowchart illustrating the method for calibrating the time window of bus priority demand across intersections according to the present invention.

[0069] Figure 2 This is a schematic diagram of the arrival and departure distribution of buses during operation in one embodiment.

[0070] Figure 3 This is a schematic diagram illustrating the probability distribution characteristics of buses and nodes, as well as departure and arrival between nodes, in one embodiment.

[0071] Figure 4 This is a schematic diagram illustrating the probability distribution characteristics of arrivals and departures within a signalized intersection node in one embodiment.

[0072] Figure 5 This is a schematic diagram illustrating the probability distribution characteristics of arrivals and departures within a bus stop node in one embodiment.

[0073] Figure 6 This is a schematic representation of the transmission and retrieval of bus operation information nodes across intersections in one embodiment.

[0074] Figure 7 This is a schematic diagram of the bus request phase demand time window in one embodiment. Detailed Implementation

[0075] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0076] In one embodiment, a method for calibrating a cross-intersection bus priority demand time window is provided, the method comprising the following steps:

[0077] Step 1: Construct a probability distribution calculation model for bus arrival and departure nodes: Virtualize bus stops and signalized intersections as nodes. Based on the travel time of buses between adjacent nodes, construct a probability distribution calculation model for bus arrival at nodes. Based on the signal timing delay within signalized intersection nodes and the dwell time within bus stop nodes, construct a probability distribution calculation model for bus departure at nodes.

[0078] Here, the virtualization of bus stops and signalized intersections into nodes refers to the virtualization of bus stops and signalized intersections into nodes that are easy to model and calculate. Each node contains a data structure that expresses the node type and the distribution characteristics of bus arrivals and departures. The node types are divided into three types: invalid, bus stop, and signalized intersection.

[0079] Here, the probability distribution calculation model for bus arrival at nodes is constructed based on the travel time of buses between adjacent nodes, as detailed below:

[0080] (1) If the previous node N i-1 There are Q buses in the time domain [0, t] up If the probability of leaving is greater than 0 at a time in memory, then the q-th bus b... q In [0, t up Leaving N i-1 And reach N i The probability distribution is calculated as follows:

[0081] Bus vehicle b q In t j Always leave N i-1 probability Fluctuations depending on travel time Pass to N i The arrival time range is distributed in probability decomposition coefficients satisfy Then because t j Bus schedule b q Leaving N i-1 ,exist Time reaches N i The probability is:

[0082]

[0083] Where Q>0, q∈[1,Q], j∈[0,t] up ];

[0084] For [0, t]up [Inner bus vehicle b] q Leaving N i-1 If the above probability decomposition is performed for all times when the probability is greater than 0, then t l At that time, bus b q Arrival at N i The probability is:

[0085]

[0086] Among them, t j and

[0087] (2) If the current time t0 is at node N i-1 With N i If there are Q buses, then the number of buses between time points t0 is b. q Arrival at N i The probability distribution is calculated as follows:

[0088] Bus vehicle b q Fluctuations depending on travel time Pass to N i Arrival distributed in probability decomposition coefficients satisfy Then due to the bus vehicles b between nodes q Running, in Time reaches N i The probability is:

[0089]

[0090] Here, a probability distribution calculation model for buses leaving the intersection is constructed based on the signal timing delay within the signalized intersection node and the station dwell time within the bus stop node, as detailed below:

[0091] 1) Let N i Let b be the current signalized intersection node. If Q buses arrive at this node, then bus b... q In [0, t up The signal timing delay affects the distance from node N. i The probability distribution is calculated as follows:

[0092] Bus vehicle b q In t j The probability of arriving at the stop line at the right time is Then the probability of it leaving the parking line The effects of the bus request phase release attribute in the current signal timing include:

[0093] (g)tj At any given time, if the bus requests a phase that is not green (i.e., not a green light), then...

[0094] (h)t j At any given moment, if the bus requests a green light (phase indicating release) and it is in the first second, then...

[0095]

[0096] in, This indicates the duration of the red light before the bus requests the green light to proceed;

[0097] (i)t j At any given moment, if the bus request phase is of the release attribute and is not in the first second, then...

[0098] 2) Let N i Let b be a bus stop node, and let Q buses arrive at it. q In [0, t up The departure time of node N is affected by fluctuations in the stationing time. i The probability distribution is calculated as follows:

[0099] Bus vehicle b q In t j Time reaches N i Arrival probability Station stay time fluctuation Leave the distribution in probability decomposition coefficients satisfy Then t j Bus schedule b q Arrival at platform node N i , and The probability of leaving at any given moment is:

[0100]

[0101] For [0, t] up [On the bus b] q Arrival at N i If the above probability decomposition is performed for all times when the probability is greater than 0, then t l At that time, bus b q Leaving N i The probability is:

[0102]

[0103] Among them, t j And t k =t l .

[0104] Step 2: Calculate the arrival probability distribution of buses at the signalized intersection and statistically analyze its maximum distribution segment: Establish a lookup table containing all nodes between the upstream and current signalized intersections according to the direction of the bus priority route at the signalized intersection; obtain the departure probability distribution information of buses within a specific minimum time period at adjacent upstream signalized intersections, and calculate the arrival and departure probability distribution of buses for each node in the lookup table one by one using the method in Step 1; statistically analyze the maximum arrival probability distribution segment of buses at the current signalized intersection.

[0105] Here, the establishment of a lookup table containing all nodes between the upstream and current signalized intersections, based on the direction of the bus priority route at the signalized intersection, is as follows:

[0106] Let W be the number of directions of the bus priority lane entrance at the signalized intersection, where K is the lookup table for direction w. w w = 1, 2, ..., W;

[0107] Using the upstream signalized intersection in direction w as the boundary, add node indices in the order of the upstream signalized intersection, all bus stops within the boundary, and the current signalized intersection, resulting in:

[0108] K w ={N1, ..., N n},

[0109] Where n is the total number of indices, N1 is the upstream signal intersection node, and N n N1 represents the current signalized intersection node, and the rest are all bus stop nodes within the boundary; N1 belongs to the calculation scope of the upstream signalized intersection and is the initial node of the current signalized intersection calculation scope, requiring no update; N2~N n This falls under the current scope of signalized intersection calculations and needs to be updated.

[0110] Here, the specific minimum time period refers to the minimum time period from time t0 at the current signalized intersection until it includes all bus request phases in the plan, and each bus request phase appears twice.

[0111] Here, the segmentation of the maximum arrival probability distribution of buses at the current signalized intersection is as follows:

[0112] The arrival probability distribution information of buses at the last node in the lookup table for each approach direction of the current signalized intersection is merged to generate the arrival probability distribution information of buses at the current signalized intersection, namely:

[0113] Time domain [t0, t up On the current signalized intersection N iThere are Q buses with an arrival probability greater than 0, and bus b... q Arrival probability

[0114] Bus vehicle b q At the current signalized intersection N i [t0, t] up If there are K consecutive arrival time periods, then the number of buses b is... q At the current signalized intersection N i [t0, t] up The sum of arrival probabilities for time period k′ with the largest arrival probability distribution on the [database] is:

[0115]

[0116] in, Let k be the kth consecutive arrival distribution period, k∈[1,K].

[0117] Step 3, Define the release demand time window for bus request phases at signalized intersections: Based on the mapping relationship between buses and request phases, establish an active vehicle request table for bus request phases at the current signalized intersection; based on the segmentation of the maximum arrival probability distribution of the earliest bus in the active vehicle request table, define the release demand time window for bus request phases.

[0118] Here, based on the mapping relationship between buses and requested phases, an active bus request phase request table is established for the current signalized intersection, as detailed below:

[0119] Set the current signalized intersection N i The bus requests the number of phases M in the time domain [t0, t1]. up On the [database], there are Q buses with an arrival probability greater than 0.

[0120] Then the bus requests phase Active vehicle request form Expressed as:

[0121]

[0122] Where, {q1, ..., q Q′} all represent bus request phases The active bus request vehicle number has a value that belongs to [1, Q]. Indicates the qth Q′ A bus requests a vehicle, m∈[1,M].

[0123] Here, the time window for determining the release requirement of a bus request phase is specifically defined based on the segmentation of the maximum arrival probability distribution of the earliest bus in the active vehicle request table:

[0124] Make bus request phase Active vehicle request form Active bus request vehicle b q The end time of the corresponding maximum arrival probability distribution period In {q1, ..., q Q′ The smallest in}, that is

[0125]

[0126] in, for Active bus request vehicle b q′ The corresponding maximum arrival probability distribution time interval ends when q and q′ both belong to {q1, ..., q}. Q′};

[0127] Then bus b q Request phase for bus Priority target buses;

[0128] Bus request phase The end time of the release demand time window is taken as the end time of the period with the highest arrival probability distribution of priority target buses, that is...

[0129] Bus request phase The value of the release demand time window Δt is:

[0130]

[0131] in, Weighted duration for the maximum arrival probability distribution of priority target buses For the start time of the consecutive arrival probability distribution period, and Within the same consecutive arrival probability distribution period, the weighting coefficient ω∈[0,1], Δt is the duration of the green light request for the bus to proceed. h Manually configure time window constraint values;

[0132] That is, the bus request phase The range of the release demand time window is

[0133] As a specific example, the invention will be further verified and illustrated in one embodiment.

[0134] In this embodiment, a bus (b) is approaching 600 meters west of signalized intersection R1. Between the two locations are signalized intersection R3, a bus stop, and signalized intersection R2. The arrival and departure times of the bus are as follows: Figure 2 As shown.

[0135] Bus stops and signalized intersections are used as calculation nodes.

[0136] The probability distribution characteristics of bus departures and arrivals between nodes and between nodes, such as... Figure 3 As shown. The bus that leaves at time l1 is propagated to times a1 to a4 as the travel time of the route fluctuates, and the probability is decomposed accordingly. Similarly, it can be obtained The probability decomposition can take the form of a uniform distribution, a Poisson distribution, or other distributions. Here, we take the uniform distribution as an example, then we have: This example uses consecutive departures from l1 to l3. Even if departures are not consecutive, a similar probability decomposition can be performed and the results summed again to obtain the node arrival probability distribution. Of course, the range of travel time fluctuations for each road segment can also be flexibly adjusted.

[0137] The probability distribution characteristics of arrivals and departures within the signalized intersection nodes, such as... Figure 4 As shown. The bus arrives at time a1 when the light is green, and the arrival probability is passed to time l1, resulting in... The bus arrives at a red light between times a2 and a4, and the arrival probability is passed to time a5 when the bus requests the green light to be released again. Similarly, we can obtain... This example illustrates the transition of arrival probabilities from times a2 to a4 to time a5. Alternatively, a simple rule can be set to transition to {a5, a6, ..., a...}. n Of course, to ensure the effect, the value of n should not be too large.

[0138] The probability distribution characteristics of arrivals and departures within bus stop nodes, such as... Figure 5 As shown. The bus arriving at time a1 is affected by the fluctuation in its stop time, which propagates to times l1-l4, and the probability is decomposed accordingly. Similarly, it can be obtained The probability decomposition can take the form of a uniform distribution, a Poisson distribution, or other distributions. Here, we take the uniform distribution as an example, then we have: This explanation uses the example of consecutive arrivals from a1 to a3. If the arrivals are not consecutive, a similar probability decomposition can be performed and the results summed again to obtain the node departure probability distribution. Similarly, the range of station time fluctuations can be flexibly adjusted.

[0139] For signalized intersections R1 and R2, construct lookup tables respectively, such as... Figure 6 As shown, taking the lookup table of R2 as an example, it includes {N1, N2, N3}, representing the arrival probability distribution of bus b. This probability distribution is transmitted to N2 based on the travel time fluctuations between the bus and N2, and further transmitted to N3 via the stop time fluctuations within N2 and the travel time fluctuations between N2 and N3. Similarly, the lookup table of R1 will also complete the departure probability distribution of bus b in N1, transmitting it to N2 based on the travel time fluctuations between N1 and N2. In other words, by using the node lookup tables of the two signalized intersections, the transmission of bus information across intersections can be completed.

[0140] Bus request phase at signalized intersection R1 Corresponding active vehicle table Currently, there are two active vehicles, b1 and b2, such as Figure 7 As shown. The end time of the maximum arrival distribution segment b1 is earlier than that of b2, then the phase... The end point of the demand time window is the end point of the maximum arrival distribution segment b1. The value of the time window is taken as the weighted value and phase of the maximum arrival distribution segment b1. The minimum value in the constraints of green light duration and manually configured time window.

[0141] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention without departing from its spirit and scope should be included within the protection scope of the present invention.

Claims

1. A method for calibrating the time window of bus priority demand across intersections, characterized in that, The method includes the following steps: Step 1: Construct a probability distribution calculation model for bus arrival and departure nodes: Virtualize bus stops and signalized intersections as nodes. Based on the travel time of buses between adjacent nodes, construct a probability distribution calculation model for bus arrival at nodes. Based on the signal timing delay within signalized intersection nodes and the dwell time within bus stop nodes, construct a probability distribution calculation model for bus departure at nodes. Step 2: Calculate the arrival probability distribution of buses at the signalized intersection and statistically analyze its maximum distribution segment: Establish a lookup table containing all nodes between the upstream and current signalized intersections according to the direction of the bus priority route at the signalized intersection; obtain the departure probability distribution information of buses within a specific minimum time period at adjacent upstream signalized intersections, and calculate the arrival and departure probability distribution of buses for each node in the lookup table one by one using the method in Step 1; statistically analyze the maximum arrival probability distribution segment of buses at the current signalized intersection. Step 3, Define the release time window for bus request phases at signalized intersections: Based on the mapping relationship between buses and request phases, establish an active vehicle request table for bus request phases at the current signalized intersection; based on the segmentation of the maximum arrival probability distribution of the earliest bus in the active vehicle request table, define the release time window for bus request phases. The probability distribution calculation model for bus arrival at nodes, based on the travel time between adjacent nodes, described in step 1, is as follows: (1) If the previous node Above A bus in the time domain If the memory exits at a time with a probability greater than 0, then the first... bus exist leave And arrive The probability distribution is calculated as follows: Buses exist Leave at any time probability Fluctuations depending on travel time Transmitted to The arrival time range is distributed in probability decomposition coefficients satisfy Therefore, Bus schedule leave ,exist Time arrives The probability is: in, , , ; right Inner public transport vehicles leave If the above probability decomposition is performed for all moments with a probability greater than 0, then... At any time, buses arrive The probability is: in, and , ; (2) If the current The time is located at the node and There are A bus, then Buses between time points arrive The probability distribution is calculated as follows: Buses Fluctuations depending on travel time Transmitted to Arrival distributed in probability decomposition coefficients satisfy Then, due to the buses between nodes Running, in Time arrives The probability is: Step 1 involves constructing a probability distribution calculation model for buses leaving the intersection based on signal timing delays within the signalized intersection node and station dwell time within the bus stop node, as detailed below: 1) Order This is the current signalized intersection node, which has... If a bus arrives, then the bus... exist Affected by signal timing delay, it leaves the node The probability distribution is calculated as follows: Buses exist The probability of arriving at the stop line at the right time is The probability of it leaving the parking line is... The effects of the bus request phase release attribute in the current signal timing include: (a) At any given time, if the bus requests a phase that is not green (i.e., not a green light), then... ; (b) At any given moment, if the bus requests a green light (phase indicating release) and it is in the first second, then... in,[ The red light duration indicates the time a bus needs to wait for the green light to be turned on before requesting the green light to proceed. (c) At any given moment, if the bus request phase is of the release attribute and is not in the first second, then... ; 2) Order It is a bus stop node, on which there is If a bus arrives, then the bus... exist The departure node is affected by fluctuations in stationing time. The probability distribution is calculated as follows: Buses exist Time arrives Arrival probability Station stay time fluctuates , leaving the distribution in probability decomposition coefficients satisfy ,but Bus schedule Arrival at platform node , and The probability of leaving at any given moment is: right boarding the bus arrive If the above probability decomposition is performed for all moments with a probability greater than 0, then... At any time, buses leave The probability is: in, and .

2. The method for calibrating the time window of bus priority demand across intersections according to claim 1, characterized in that, The virtualization of bus stops and signalized intersections as nodes in step 1 refers to virtualizing bus stops and signalized intersections as nodes that are easy to model and calculate. Each node has a data structure that expresses the node type and the distribution characteristics of bus arrivals and departures. The node types are divided into three types: invalid, bus stop, and signalized intersection.

3. The method for calibrating the time window of bus priority demand across intersections according to claim 1, characterized in that, Step 2 involves establishing a lookup table containing all nodes between the upstream and current signalized intersections, based on the direction of the bus priority route at the intersection. The details are as follows: Set the number of bus priority lanes at signalized intersections to the number of directions of entry. , among which direction Search table , ; In direction Taking the upstream signalized intersection as the boundary, add node indices in the order of upstream signalized intersection, all bus stops within the boundary, and the current signalized intersection, resulting in: ， in, For the total number of indexes, For the upstream signal intersection node, The current signalized intersection node is represented by one node, while the rest are all bus stop nodes within the boundary. Belonging to the calculation scope of the upstream signalized intersection, it is the initial node of the current signalized intersection calculation scope and does not need to be updated; This falls under the current scope of signalized intersection calculations and needs to be updated.

4. The method for calibrating the time window of bus priority demand across intersections according to claim 1, characterized in that, The specific minimum time period mentioned in step 2 refers to the current signalized intersection from... The minimum time period from the start of the current time to the occurrence of all bus request phases in the plan, with each bus request phase appearing twice.

5. The method for calibrating the time window of bus priority demand across intersections according to claim 1, characterized in that, Step 2, which involves statistically analyzing the maximum arrival probability distribution segments of buses at the current signalized intersection, is as follows: The arrival probability distribution information of buses at the last node in the lookup table for each approach direction of the current signalized intersection is merged to generate the arrival probability distribution information of buses at the current signalized intersection, namely: Time Domain Above, current signalized intersection have The probability of arrival of any bus is greater than 0. Arrival probability , ; Buses At the current signalized intersection of Above If there are consecutive arrival periods, then the buses At the current signalized intersection of The time period with the largest arrival probability distribution is The probability and value of arrival during the specified time period: in, For the first A series of consecutive arrival distribution periods, .

6. The method for calibrating the time window of bus priority demand across intersections according to claim 1, characterized in that, Step 3 involves establishing an active bus request table for the current signalized intersection based on the mapping relationship between buses and requested phases, as detailed below: Set the current signal intersection Bus request phase number In the time domain Above, there is The probability of any of the buses arriving is greater than 0. Then the bus requests phase Active vehicle request form Expressed as: in, All indicate that the bus requested the phase. The active bus request vehicle number, the value belongs to , Indicates the first A bus requested a vehicle. .

7. The method for calibrating the time window of bus priority demand across intersections according to claim 6, characterized in that, Step 3, which involves segmenting the maximum arrival probability distribution of the earliest bus in the active vehicle request table and defining the release demand time window for the bus request phase, is as follows: Make bus request phase Active vehicle request form Active bus request vehicles The end time of the corresponding maximum arrival probability distribution period exist The smallest, that is in, for Active bus request vehicles The end time of the corresponding maximum arrival probability distribution period. and All belong to ; Then public buses Request phase for bus Priority target buses; Bus request phase The end time of the release demand time window is taken as the end time of the period with the highest arrival probability distribution of priority target buses, that is... ; Bus request phase The value of the release demand time window for: in, Weighted duration for the maximum arrival probability distribution of priority target buses , For the start time of the consecutive arrival probability distribution period, and Weighting coefficients within the same continuous arrival probability distribution period , Request the green light duration for the bus to proceed. Manually configure time window constraint values; That is, the bus request phase The range of the release demand time window is .

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