A method and system for estimating bus travel time considering traffic light constraints

Abstract

This invention proposes a method and system for estimating bus travel time considering traffic light constraints, belonging to the field of intelligent transportation technology. The method includes: determining the number of vehicles queuing at the downstream intersection and the travel time of the target bus through the road segment when the lane is not constrained by traffic lights; establishing a model of the number of vehicles queuing when the lane is constrained by traffic lights; predicting the state of the traffic lights at the moment the target bus reaches the end of the queue; calculating the signal delay time of the target bus when constrained by traffic lights based on the state of the traffic lights and the number of vehicles queuing; stopping the estimation when the fluctuation range of the predicted values ​​does not exceed a preset threshold, thus determining the final travel time of the target bus through the road segment under both traffic light and signal light constraints. Based on this method, a bus travel time estimation system considering traffic light constraints is also proposed. This invention improves the accuracy of bus scheduling, optimizes signal priority strategies, and enhances the reliability of passenger information services.

Description

Technical Field

[0001] This invention belongs to the field of intelligent transportation technology, and specifically relates to a method and system for estimating the travel time of public transport vehicles considering traffic light constraints. Background Technology

[0002] As a core component of urban public transportation, the efficiency of buses directly impacts passenger travel experience and the overall operational efficiency of the urban transportation network. However, buses often experience delays when passing through intersections due to factors such as queuing vehicles ahead and traffic light control. Traditional models are typically based on static assumptions, ignoring the dynamic changes in real-time traffic conditions, and often struggle to accurately predict transit times, leading to significant discrepancies between predicted and actual travel times.

[0003] Chinese patent application No. 201711159975.9, entitled "A Method for Calculating Intersection Delay Time," discloses a method that calculates the average travel time of a road segment based on the actual time required for each vehicle to enter and leave the segment within a certain period using electronic traffic enforcement checkpoints. The difference between this average and the theoretical travel time of the segment is the segment delay time. The average of the delay times of four road segments is the intersection delay time. This delay time not only reflects the dynamic characteristics of vehicles passing through the intersection but also serves as a basis for optimizing intersection signal timing parameters. It is used to establish an optimization model and objective function, with an appropriate cycle length, to allow the traffic capacity to slightly exceed the traffic demand while minimizing the total delay time for all vehicles passing through the intersection. However, this invention derives the delay by comparing the theoretical and actual travel times. It does not consider traffic light constraints, resulting in a lag in response to dynamic traffic conditions and poor adaptability to complex scenarios, making it difficult to accurately predict travel time. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes a method and system for estimating bus travel time considering traffic light constraints. This improves the accuracy of bus dispatching, optimizes signal priority strategies, and enhances the reliability of passenger information services.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A method for estimating bus travel time considering traffic light constraints includes the following steps:

[0007] Based on the GNSS data of the target bus, determine the number of vehicles queuing at the downstream intersection when the lane is not constrained by traffic lights and the travel time of the target bus through the road segment;

[0008] The system sets the travel time required for a target bus to reach the end of the queue when the lane is constrained by traffic lights; obtains the effective traffic light duration allocated to the lane when the lane is constrained by traffic lights; determines the number of complete signal cycles and the remaining time using the travel time required for the target bus to reach the end of the queue and the effective traffic light duration; calculates the number of vehicles in the queue when the lane is constrained by traffic lights using the number of complete signal cycles and the remaining time; predicts the state of the traffic lights at the moment the target bus reaches the end of the queue based on the discrete signal state of the traffic lights at the intersection downstream of the time the target bus's GNSS data is obtained; and calculates the signal delay time of the target bus when it is constrained by traffic lights based on the predicted state of the traffic lights at the moment the target bus reaches the end of the queue and the number of vehicles in the queue.

[0009] The estimation stops when the predicted travel time of the target bus on the route does not exceed a preset threshold for multiple consecutive predictions. The travel time of the target bus on the route under the two conditions of no traffic light constraint and traffic light constraint are determined respectively.

[0010] The present invention also proposes a bus travel time estimation system considering traffic light constraints, including a first calculation module, a second calculation module and a time determination module;

[0011] The first calculation module is used to determine the number of vehicles queuing at the downstream intersection and the travel time of the target bus through the road segment when the lane is not constrained by traffic lights, based on the GNSS data of the target bus.

[0012] The second calculation module is used to set the travel time required for a target bus to reach the end of the queue when the lane is constrained by traffic lights; obtain the effective traffic light duration allocated to the lane when the lane is constrained by traffic lights; determine the number of complete signal cycles and the remaining time using the travel time required for the target bus to reach the end of the queue and the effective traffic light duration; calculate the number of vehicles in the queue when the lane is constrained by traffic lights using the number of complete signal cycles and the remaining time; predict the state of the traffic lights at the moment the target bus reaches the end of the queue based on the discrete signal state of the traffic lights at the intersection downstream of the time the target bus's GNSS data is obtained; and calculate the signal delay time of the target bus when it is constrained by traffic lights based on the predicted state of the traffic lights at the moment the target bus reaches the end of the queue and the number of vehicles in the queue.

[0013] The time determination module is used to stop estimating when the fluctuation range of the predicted travel time of the target bus on the road segment does not exceed a preset threshold for multiple consecutive predictions, and to determine the travel time of the target bus on the road segment under the two conditions of no traffic light constraint and traffic light constraint respectively.

[0014] The effects described in the invention are merely those of the embodiments, and not all the effects of the invention. One of the above technical solutions has the following advantages or beneficial effects:

[0015] This invention proposes a method and system for estimating the travel time of public transport vehicles considering traffic light constraints, belonging to the field of intelligent transportation technology. The method includes the following steps: determining the number of vehicles queuing at the downstream intersection and the travel time of the target bus through the road segment when the lane is not constrained by traffic lights, based on the GNSS data of the target bus; setting the travel time required for the target bus to reach the end of the queue when the lane is constrained by traffic lights; obtaining the effective traffic light duration allocated to the lane when the lane is constrained by traffic lights; determining the number of complete signal cycles and the remaining time using the travel time required for the target bus to reach the end of the queue and the effective traffic light duration; calculating the number of vehicles queuing when the lane is constrained by traffic lights using the number of complete signal cycles and the remaining time; predicting the state of the traffic lights at the downstream intersection when the target bus reaches the end of the queue based on the discrete signal states of the traffic lights at the time the GNSS data of the target bus is obtained; calculating the signal delay time when the target bus is constrained by traffic lights based on the predicted state of the traffic lights and the number of vehicles queuing at the time the target bus reaches the end of the queue; stopping the estimation when the fluctuation range of the predicted travel time of the target bus through the road segment does not exceed a preset threshold, and determining the final travel time of the target bus through the road segment under both the unconstrained and constrained traffic light conditions. Based on a method for estimating bus travel time considering traffic light constraints, a system for estimating bus travel time considering traffic light constraints is also proposed. This invention uses modular design to perform multi-factor coupled modeling of traffic flow dynamics, signal control strategies, and vehicle behavior, achieving refined prediction of the entire process from vehicle approach to intersection passage. This provides a high-precision and highly adaptable theoretical framework for bus priority signal timing, dynamic scheduling optimization, and real-time passenger information services.

[0016] This invention decomposes the overall travel time into two parts: the travel time before entering the queue and the intersection signal delay. This simplifies the complexity of multi-factor coupling. Each module focuses on a single objective, making it easy to optimize and verify individually. This helps improve the accuracy and practicality of bus travel time prediction.

[0017] This invention obtains the real-time travel time of buses before they enter the queue and predicts their arrival time at the end of the queue. It can then send green light extension requests or phase switching instructions to the traffic signal control center to create a priority passage window for buses. Attached Figure Description

[0018] Figure 1 This is a flowchart of a method for estimating the travel time of public buses considering traffic light constraints, as proposed in Embodiment 1 of the present invention.

[0019] Figure 2 This is a schematic diagram of a bus travel time estimation system considering traffic light constraints proposed in Embodiment 2 of the present invention. Detailed Implementation

[0020] To clearly illustrate the technical features of this solution, the invention will be described in detail below through specific embodiments and in conjunction with the accompanying drawings. The following disclosure provides many different embodiments or examples for implementing different structures of the invention. To simplify the disclosure, components and arrangements of specific examples are described below. Furthermore, reference numerals and / or letters may be repeated in different examples. This repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed. It should be noted that the components illustrated in the drawings are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and processes are omitted to avoid unnecessarily limiting the invention.

[0021] Example 1

[0022] Embodiment 1 of this invention proposes a method for estimating the travel time of public transport vehicles considering traffic light constraints, including constructing a model of the number of vehicles in queue, calculating the travel time and the number of vehicles in queue, determining the phase state of the traffic light and calculating the remaining time of that phase, calculating the signal delay at intersections, and calculating the travel time of road segments.

[0023] Figure 1 This is a flowchart of a method for estimating the travel time of public buses considering traffic light constraints, as proposed in Embodiment 1 of the present invention.

[0024] In step S100, GNSS data of the target bus is acquired.

[0025] This application utilizes deployed vehicle-mounted terminals to collect GNSS data information from vehicles. The vehicle's GNSS data information is collected every... Uploads data every second, and the main application and stored data fields include the following:

[0026] <Route ID, Vehicle ID, Time, Longitude, Latitude, Speed>.

[0027] While acquiring the GNSS data of the target bus, the number of vehicles queuing at the signalized intersection downstream of the bus lane is simultaneously obtained through the traffic monitoring system. The vehicle GNSS data acquisition time is represented as .

[0028] In step S110, it is determined whether the lane where the target bus is located is constrained by traffic lights. This application calculates the number of vehicles queuing at the downstream intersection in two cases. If it is not constrained by traffic lights, step S120 is executed; otherwise, step S140 is executed.

[0029] In step S120, when not constrained by traffic lights, vehicles in this lane can continuously pass through the intersection without signal cycle restrictions. At this time, the number of vehicles queuing at the downstream intersection of the lane... .

[0030] In step S130, if there are no traffic lights and the number of vehicles queuing at the intersection entrance is 0, the required travel time is the travel time for the bus to pass through the section of road. The travel time of the target bus through the road segment. for:

[0031] ;

[0032] in, The distance between the target bus and the downstream intersection node; The average speed of the target bus before it enters the queue;

[0033] When there is only one GNSS data point in a road segment, the speed field in the GNSS data is used as the average speed of the target bus before it enters the queue. ;

[0034] Included in the road segment When there are GNSS data points, among which, ,but:

[0035] ;

[0036] in, Indicates the first GNSS data point and the second GNSS data point. Road network distance between GNSS data points Indicates the first GNSS data point and the second GNSS data point. The time interval between GNSS data points.

[0037] In step S140, a model of the number of vehicles queuing when the lane is constrained by traffic lights is constructed.

[0038] Set the travel time required for a target bus to reach the end of the queue when the lane is constrained by traffic lights; obtain the effective traffic light duration allocated to the lane when the lane is constrained by traffic lights; determine the number of complete signal cycles and the remaining time using the travel time required for the target bus to reach the end of the queue and the effective traffic light duration; calculate the number of vehicles in the queue when the lane is constrained by traffic lights using the number of complete signal cycles and the remaining time.

[0039] The effective signal light duration allocated to each lane is obtained through the traffic signal control system; the green light duration is... seconds, red light duration is seconds, yellow light duration is Seconds, the complete cycle duration Represented as:

[0040] ;

[0041] Let the arrival rate of the bus lane be... and saturation flow rate The bus is expected to arrive at the end of the queue at [time]. At this time, the number of vehicles queuing at the downstream intersection entrance lane corresponding to the bus lane is: The travel time required for the bus to reach the end of the queue Expressed as ;

[0042] in, The estimated arrival time of the target bus at the end of the queue; To obtain the time of the target bus's GNSS data;

[0043] The time period may contain multiple complete signal cycles or incomplete residual cycles. The number of complete cycles in the travel time required for the target bus to reach the end of the queue is represented as:

[0044] ;

[0045] in, The number of complete cycles;

[0046] The remaining time in the travel time required for the target bus to reach the end of the queue is expressed as:

[0047] ;

[0048] Residual Time This includes the remaining red light duration. The remaining yellow light duration is The remaining green light duration is ;

[0049] Total red light duration within the time period Total duration of yellow light Total green light duration They are:

[0050] ;

[0051] ;

[0052] ;

[0053] Therefore, the equation for the number of vehicles in the queue is expressed as:

[0054] ;

[0055] in, The vehicle arrival rate in the lane where the target bus is located; The saturation flow rate of the lane where the target bus is located;

[0056] In the formula, ; This represents the theoretical time required to clear all the queued vehicles. This indicates the total number of vehicles that need to be eliminated. This represents the net dissipation rate of the queue.

[0057] This application also includes using an iterative algorithm to solve for the travel time required for the target bus to reach the end of the queue when the lane is constrained by traffic lights, based on the bidirectional coupling relationship between the two-way coupling relationship between the target bus and the vehicles in the queue.

[0058] Assume the average length of each car is The deceleration distance of a bus before entering an intersection and queuing is: Travel time and Number of vehicles queuing at any given time There is a bidirectional coupling relationship, specifically manifested as follows:

[0059] ①、 The number of vehicles in the queue at future moments ;

[0060] ②、 Determine the effective distance that the bus needs to travel The effective distance that the bus needs to travel. Expressed as ;

[0061] ③、 Determined by vehicle kinematic constraints :

[0062] Buses at speed driving Distance, time Seconds, then decelerate to stop time Seconds; at this moment, Represented as:

[0063] ;

[0064] Solving by iterative algorithm and The process is as follows:

[0065] Establish the equation: ;

[0066] Combined into a single iterative function: ;

[0067] The iterative process is as follows:

[0068] ① Initialization: retrieve ,but:

[0069] ;

[0070] ;

[0071] ② Iterative process :

[0072] A. Splitting traffic light time periods: Based on ,statistics Total red light duration within the time period Total duration of yellow light Total green light duration ;

[0073] B. Update the number of vehicles in the queue. During the iteration process, if the calculated... Forced to be set To avoid negative numbers of vehicles in the queue;

[0074] ;

[0075] C. Correcting distance and arrival time: ;

[0076] D. Introduce judgment conditions to dynamically adjust deceleration distance. ;

[0077] like The bus needs to slow down and stop.

[0078] ;

[0079] like The vehicle does not need to slow down and can reach the stop line directly.

[0080]

[0081] E. Convergence Judgment

[0082] when and When the iteration terminates, the default is... , and The size can be determined according to the specific circumstances.

[0083] The above calculations can be used to determine the answer. as well as Number of vehicles queuing at intersections .

[0084] In step S150, the state of the traffic lights at the intersection downstream of the target bus is predicted based on the discrete signal states of the traffic lights at the time when the target bus arrives at the end of the queue.

[0085] The time to acquire GNSS data of the target bus The current phase color of the traffic light is indicated as follows: ;in Indicates the index of the current light color status. When the light is green, it indicates a green light. , indicates a yellow light; When the light is red, it indicates a red light.

[0086] The remaining time for the current phase is Seconds, after The subsequent phase light color is The remaining phase time is Second;

[0087] The discrete signal states of traffic lights are represented as ordered pairs. The duration of a traffic light phase is represented as an array. ;

[0088] ① If ; The signal status of the traffic lights is represented as follows: ;

[0089] ② If Calculate the remaining time ;

[0090] Current light color status index Next light color state index Represented as: ;

[0091] Light color status index Next light color state index Represented as: ;

[0092] Calculate the time remainder when the remaining time is divided by the signal period. , ;

[0093] go through After seconds, the phase and remaining phase time of the traffic light are expressed as follows:

[0094] .

[0095] In step S160, the signal delay time when the target bus is constrained by the signal light is calculated based on the predicted state of the signal light and the number of vehicles in the queue at the time when the target bus arrives at the end of the queue.

[0096] exist At that moment, the signal status of the traffic light is The number of vehicles queuing at the intersection is ;

[0097] Assume the starting delay of the first car behind the stop line is... Furthermore, vehicles will not cross the intersection stop line during the yellow light period; the delay caused by traffic lights at intersections is defined as... , The calculation is as follows:

[0098] (1) If The number of vehicles queuing at the downstream intersection entrance lane is 0 at this time.

[0099] ① The current phase of the traffic light is yellow, and the remaining time of the yellow light is... ,

[0100] Control delay at this time Expressed as ;

[0101] ② The traffic light is currently in red, and the remaining red light time is... ,

[0102] Control delay at this time Expressed as

[0103] ③ When the current phase of the traffic light is green,

[0104] At this time, there were no vehicles queuing in front of the bus, and the delay was controlled. .

[0105] (2) If If the number of vehicles queuing at the downstream intersection entrance is not zero, the bus will experience queuing delays at the downstream intersection. Represented as:

[0106] ;

[0107] according to Intersection traffic light signal status ;Analyze according to different scenarios:

[0108] The traffic light is currently red.

[0109] Compare and the duration of the green light Size;

[0110] A. If This indicates that the bus cannot pass through the intersection within one green light duration. Therefore:

[0111] ;

[0112] Calculate control delay , ;

[0113] B. If This indicates that the bus can pass through the intersection within one green light duration; in this case, the delay is calculated and controlled. for: ;

[0114] ② The traffic light is yellow.

[0115] Compare and the duration of the green light Size;

[0116] A. If This indicates that the bus cannot pass through the intersection within one green light duration. Therefore:

[0117] ;

[0118] Calculate control delay , ;

[0119] B. If This indicates that buses can pass through the intersection within one green light duration, and delays are calculated and controlled. ,

[0120] ;

[0121] The traffic light is green;

[0122] judge and Size

[0123] A. If This means that buses cannot pass through the intersection within the remaining time of the current green light.

[0124] ;

[0125] Calculate control delay , ;

[0126] B. If This indicates that the bus can pass through the intersection within the remaining time of the current green light, at which point the control delay is calculated. ; .

[0127] In step S170, while collecting GNSS data, the travel time of bus routes is estimated simultaneously until continuous The fluctuation range of the predicted value shall not exceed the preset threshold. When the estimation process is stopped, the process is terminated. With threshold It can be set according to actual needs.

[0128] The travel time of the target bus through the road segment when not constrained by traffic lights is determined as follows:

[0129] ;

[0130] in, This indicates the travel time to finally pass through a road segment when not subject to traffic lights.

[0131] In step S180, while collecting GNSS data, the travel time of bus routes is estimated simultaneously until continuous The fluctuation range of the predicted value shall not exceed the preset threshold. When the estimation process is stopped, the process is terminated. With threshold It can be set according to actual needs.

[0132] Determine the final travel time of the target bus through the road segment when constrained by traffic lights, specifically:

[0133] ;

[0134] This indicates the travel time to finally pass through a road segment when constrained by traffic lights.

[0135] The present invention, in embodiment 1, proposes a method for estimating the travel time of buses that considers traffic light constraints. Through modular design, it performs multi-factor coupled modeling of traffic flow dynamics, signal control strategies, and vehicle behavior, and realizes refined prediction of the entire process from vehicle approach to crossing the intersection. This provides a high-precision and highly adaptable theoretical framework for bus priority signal timing, dynamic scheduling optimization, and real-time passenger information services.

[0136] The bus travel time estimation method considering traffic light constraints provided in Embodiment 1 of this application decomposes the overall travel time into two parts: the travel time before entering the queue and the intersection signal delay. This simplifies the complexity of multi-factor coupling, and each module focuses on a single objective, which is convenient for individual optimization and verification. This is beneficial to improving the accuracy and practicality of bus travel time prediction.

[0137] Example 2

[0138] Based on the bus travel time estimation method considering traffic light constraints proposed in Embodiment 1 of this invention, Embodiment 2 of this invention also proposes a bus travel time estimation system considering traffic light constraints. Figure 2 This is a schematic diagram of a bus travel time estimation system considering traffic light constraints proposed in Embodiment 2 of the present invention. The system includes: a first calculation module, a second calculation module, and a time determination module.

[0139] The first calculation module is used to determine the number of vehicles queuing at the downstream intersection and the travel time of the target bus through the road segment when the lane is not constrained by traffic lights, based on the GNSS data of the target bus.

[0140] The second calculation module is used to set the travel time required for a target bus to reach the end of the queue when the lane is constrained by traffic lights; obtain the effective traffic light duration allocated to the lane when the lane is constrained by traffic lights; determine the number of complete signal cycles and the remaining time using the travel time required for the target bus to reach the end of the queue and the effective traffic light duration; calculate the number of vehicles in the queue when the lane is constrained by traffic lights using the number of complete signal cycles and the remaining time; predict the state of the traffic lights at the time the target bus will reach the end of the queue based on the discrete signal state of the traffic lights at the intersection downstream of the time the target bus's GNSS data is obtained; and calculate the signal delay time of the target bus when it is constrained by traffic lights based on the predicted state of the traffic lights at the time the target bus will reach the end of the queue and the number of vehicles in the queue.

[0141] The time determination module is used to stop estimating when the fluctuation range of the predicted travel time of the target bus on the road segment does not exceed a preset threshold for multiple consecutive predictions. It determines the final travel time of the target bus through the road segment under the two conditions of no traffic light constraint and traffic light constraint.

[0142] The detailed process executed by the first calculation module includes:

[0143] Based on the GNSS data of the target bus, the number of vehicles queuing at the intersection downstream of the lane when the target bus is not constrained by traffic lights and the specific travel time of the target bus through the road segment are determined as follows:

[0144] When the lane is not constrained by traffic lights, the number of vehicles queuing at the intersection downstream of the lane. ;

[0145] The travel time of the target bus through the route for:

[0146] ;

[0147] in, The distance between the target bus and the downstream intersection node; The average speed of the target bus before it enters the queue;

[0148] When there is only one GNSS data point in a road segment, the speed field in the GNSS data is used as the average speed of the target bus before it enters the queue. ;

[0149] Included in the road segment When there are GNSS data points, among which, ,but:

[0150] ;

[0151] in, Indicates the first GNSS data point and the second GNSS data point. Road network distance between GNSS data points Indicates the first GNSS data point and the second GNSS data point. The time interval between GNSS data points.

[0152] The detailed process executed by the second calculation module includes:

[0153] When a lane is constrained by traffic lights, the effective traffic light duration allocated to that lane is:

[0154] ;

[0155] in, Indicates the duration of the red light; Indicates the duration of the green light; Indicates the duration of the yellow light;

[0156] Assume the travel time required for the target bus to reach the end of the queue. ;

[0157] in, The estimated arrival time of the target bus at the end of the queue; To obtain the time of the target bus's GNSS data;

[0158] The number of complete cycles in the travel time required for the target bus to reach the end of the queue is expressed as:

[0159] ;

[0160] in, The number of complete cycles;

[0161] The remaining time in the travel time required for the target bus to reach the end of the queue is expressed as:

[0162] ;

[0163] Residual Time This includes the remaining red light duration. The remaining yellow light duration is The remaining green light duration is ;

[0164] Total red light duration within the time period Total duration of yellow light Total green light duration They are:

[0165] ;

[0166] ;

[0167] ;

[0168] Therefore, the equation for the number of vehicles in the queue is expressed as:

[0169] ;

[0170] in, The vehicle arrival rate in the lane where the target bus is located; The saturation flow rate of the lane where the target bus is located;

[0171] In the formula, ; This represents the theoretical time required to clear all the queued vehicles. This indicates the total number of vehicles that need to be eliminated. This represents the net dissipation rate of the queue.

[0172] The method further includes: using an iterative algorithm to solve for the travel time required for the target bus to reach the end of the queue when the lane is constrained by traffic lights, based on the bidirectional coupling relationship between the target bus and the vehicles in the queue;

[0173] Assume the average length of each car is The deceleration distance of a bus before entering an intersection and queuing is: ;

[0174] The number of vehicles in the queue at future moments ;

[0175] Determine the effective distance that the bus needs to travel ; ;

[0176] Buses at speed driving Distance, time Seconds, then decelerate to stop time Seconds; at this moment, Represented as:

[0177] ;

[0178] Solving by iterative algorithm and The process is as follows:

[0179] Establish the equation: ;

[0180] Combined into a single iterative function: ;

[0181] The iterative process is as follows:

[0182] Initialization: Get ,but:

[0183] ;

[0184] ;

[0185] Iterative process :

[0186] Splitting traffic light time periods: Based on ,statistics Total red light duration within the time period Total duration of yellow light Total green light duration ;

[0187] Update the number of vehicles in the queue. During the iteration process, if the calculated... Forced to be set To avoid negative numbers of vehicles in the queue;

[0188] ;

[0189] Corrected distance and arrival time: ;

[0190] Introduce judgment conditions to dynamically adjust deceleration distance ;

[0191] like The bus needs to slow down and stop.

[0192] ;

[0193] like The vehicle does not need to slow down and can reach the stop line directly.

[0194]

[0195] Convergence judgment

[0196] when and When the iteration ends, the iteration is terminated.

[0197] Based on the discrete signal states of the traffic lights at the downstream intersection at the time the target bus's GNSS data is acquired, the state of the traffic lights at the moment the target bus arrives at the end of the queue is predicted. Specifically:

[0198] The time to acquire GNSS data of the target bus The current phase color of the traffic light is indicated as follows: ;in Indicates the index of the current light color status. When the light is green, it indicates a green light. , indicates a yellow light; When the light is red, it indicates a red light.

[0199] The remaining time for the current phase is Seconds, after The subsequent phase light color is The remaining phase time is Second;

[0200] The discrete signal states of traffic lights are represented as ordered pairs. The duration of a traffic light phase is represented as an array. ;

[0201] like ; The signal status of the traffic lights is represented as follows: ;

[0202] like Calculate the remaining time ;

[0203] Current light color status index Next light color state index Represented as: ;

[0204] Light color status index Next light color state index Represented as: ;

[0205] Calculate the time remainder when the remaining time is divided by the signal period. , ;

[0206] go through After seconds, the phase and remaining phase time of the traffic light are expressed as follows:

[0207] .

[0208] Based on the predicted arrival time of the target bus at the end of the queue, the traffic light status, and the number of vehicles in the queue, the signal delay time of the target bus under traffic light constraints is calculated as follows:

[0209] exist At that moment, the signal status of the traffic light is The number of vehicles queuing at the intersection is ;

[0210] Assume the starting delay of the first car behind the stop line is... Furthermore, vehicles will not cross the intersection stop line during the yellow light period; the delay caused by traffic lights at intersections is defined as... , The calculation is as follows:

[0211] like When the number of vehicles queuing at the downstream intersection approach lane is 0, and the current phase of the traffic light is yellow, the remaining time of the yellow light is... Controlling delays Expressed as When the current phase of the traffic light is red, the remaining red light time is... Controlling delays Expressed as Control delay when the current phase of the traffic light is green. ;

[0212] like If the number of vehicles queuing at the downstream intersection entrance is not zero, the bus will experience queuing delays at the downstream intersection. Represented as:

[0213] ;

[0214] according to Intersection traffic light signal status When the current phase of the traffic light is red, if This indicates that the bus cannot pass through the intersection within one green light duration. Therefore:

[0215] ;

[0216] Calculate control delay , ;

[0217] like This indicates that the bus can pass through the intersection within one green light duration; in this case, the delay is calculated and controlled. for: ;

[0218] When the traffic light is yellow, if This indicates that the bus cannot pass through the intersection within one green light duration. Therefore:

[0219] ;

[0220] Calculate control delay , ;

[0221] like This indicates that buses can pass through the intersection within one green light duration, and delays are calculated and controlled. ,

[0222] ;

[0223] When the traffic light is green; if This means that buses cannot pass through the intersection within the remaining time of the current green light.

[0224] ;

[0225] Calculate control delay , ;

[0226] like This indicates that the bus can pass through the intersection within the remaining time of the current green light, at which point the control delay is calculated. ; .

[0227] The detailed process of the time determination module includes:

[0228] The travel time of the target bus through the road segment when not constrained by traffic lights is determined as follows:

[0229] ;

[0230] in, This indicates the travel time to finally pass through a road segment when not subject to traffic lights.

[0231] Determine the final travel time of the target bus through the road segment when constrained by traffic lights, specifically:

[0232] ;

[0233] This indicates the travel time to finally pass through a road segment when constrained by traffic lights.

[0234] The bus travel time estimation system considering traffic light constraints provided in Embodiment 2 of this application uses modular design to perform multi-factor coupled modeling of traffic flow dynamics, signal control strategies and vehicle behavior, and realizes fine prediction of the entire process from vehicle approach to crossing the intersection. It provides a high-precision and highly adaptable theoretical framework for bus priority signal timing, dynamic scheduling optimization and real-time passenger information services.

[0235] The bus travel time estimation system provided in Embodiment 2 of this application, which considers traffic light constraints, decomposes the overall travel time into two parts: the travel time before entering the queue and the intersection signal delay. This simplifies the complexity of multi-factor coupling, and each module focuses on a single objective, which is convenient for individual optimization and verification. This is beneficial to improving the accuracy and practicality of bus travel time prediction.

[0236] The description of the relevant parts of the bus travel time estimation system considering traffic light constraints provided in Embodiment 2 of this application can be found in the detailed description of the corresponding parts of the bus travel time estimation method considering traffic light constraints provided in Embodiment 1 of this application, and will not be repeated here.

[0237] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that the elements inherent in a process, method, article, or apparatus that includes a list of elements are included. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. Additionally, portions of the technical solutions provided in the embodiments of this application that are consistent with the implementation principles of corresponding technical solutions in the prior art have not been described in detail to avoid excessive elaboration.

[0238] While specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art can make other modifications or variations based on the above description. It is neither necessary nor possible to exhaustively describe all embodiments here. Various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for estimating the travel time of public transport vehicles considering traffic light constraints, characterized in that, Includes the following steps: Based on the GNSS data of the target bus, determine the number of vehicles queuing at the downstream intersection when the lane is not constrained by traffic lights and the travel time of the target bus through the road segment; Set the travel time required for a target bus to reach the end of the queue when the lane is restricted by traffic lights; Obtain the effective signal light duration allocated to a lane when the lane is constrained by traffic lights; The number of complete signal cycles and the remaining time are determined by using the travel time required for the target bus to reach the end of the queue and the effective signal light duration; the number of vehicles in the queue when the lane is constrained by the signal light is calculated using the number of complete signal cycles and the remaining time; the state of the signal light at the moment the target bus reaches the end of the queue is predicted based on the discrete signal state of the signal light at the intersection downstream of the time the GNSS data of the target bus is acquired; and the signal delay time when the target bus is constrained by the signal light is calculated based on the predicted state of the signal light at the moment the target bus reaches the end of the queue and the number of vehicles in the queue. The estimation stops when the predicted travel time of the target bus on the route does not exceed the preset threshold for multiple consecutive predictions. The travel time of the target bus on the route under the two conditions of no traffic light constraint and traffic light constraint is determined respectively. Based on the discrete signal states of the traffic lights at the downstream intersection at the time the target bus's GNSS data is acquired, the state of the traffic lights at the moment the target bus arrives at the end of the queue is predicted. Specifically: The time to acquire GNSS data of the target bus The current phase color of the traffic light is indicated as follows: ;in Indicates the index of the current light color status. When the light is green, it indicates a green light. , indicates a yellow light; When the light is red, it indicates a red light. To obtain the time of the target bus's GNSS data; The remaining time for the current phase is Seconds, after The subsequent phase light color is The remaining phase time is Second; The discrete signal states of traffic lights are represented as ordered pairs. The duration of a traffic light phase is represented as an array. ;in, Indicates the duration of the red light; Indicates the duration of the green light; Indicates the duration of the yellow light; like ; The signal status of the traffic lights is represented as follows: ; This indicates the travel time required for the target bus to reach the end of the queue; like Calculate the remaining time ; Current light color status index Next light color state index Expressed as: ; Light color status index Next light color state index Expressed as: ; Calculate the time remainder when the remaining time is divided by the signal period. , ; go through After seconds, the phase and remaining phase time of the traffic light are expressed as follows: ； Based on the predicted arrival time of the target bus at the end of the queue, the traffic light status, and the number of vehicles in the queue, the signal delay time of the target bus under traffic light constraints is calculated as follows: exist At that moment, the signal status of the traffic light is The number of vehicles queuing at the intersection is ; The estimated arrival time of the target bus at the end of the queue; The starting delay of the first car behind the stop line is Furthermore, vehicles will not cross the intersection stop line during the yellow light period; the delay caused by traffic lights at intersections is defined as... , The calculation is as follows: like When the number of vehicles queuing at the downstream intersection approach lane is 0, and the current phase of the traffic light is yellow, the remaining time of the yellow light is... Controlling delays Represented as When the current phase of the traffic light is red, the remaining red light time is... Controlling delays Represented as Control delay when the current phase of the traffic light is green. ; like If the number of vehicles queuing at the downstream intersection entrance is not zero, the bus will experience queuing delays at the downstream intersection. Expressed as: ; The saturation flow rate of the lane where the target bus is located; according to Intersection traffic light signal status When the current phase of the traffic light is red, if This indicates that the bus cannot pass through the intersection within one green light duration. Therefore: ； Calculate control delay , ; like This indicates that the bus can pass through the intersection within one green light duration; in this case, the delay is calculated and controlled. for: ; When the traffic light is yellow, if This indicates that the bus cannot pass through the intersection within one green light duration. Therefore: ； Calculate control delay , ; like This indicates that buses can pass through the intersection within one green light duration, and delays are calculated and controlled. , ； When the traffic light is green; if This means that buses cannot pass through the intersection within the remaining time of the current green light. ； Calculate control delay , ; like This indicates that the bus can pass through the intersection within the remaining time of the current green light, at which point the control delay is calculated. ; .

2. The method for estimating bus travel time considering traffic light constraints according to claim 1, characterized in that, The GNSS data of the target bus includes route ID, vehicle ID, time, longitude, latitude, and target bus speed.

3. The method for estimating bus travel time considering traffic light constraints according to claim 1, characterized in that, Based on the GNSS data of the target bus, the number of vehicles queuing at the intersection downstream of the lane when the target bus is not constrained by traffic lights and the specific travel time of the target bus through the road segment are determined as follows: When the lane is not constrained by traffic lights, the number of vehicles queuing at the intersection downstream of the lane. ; The travel time of the target bus through the section of road. for: ； in, The distance between the target bus and the downstream intersection node; The average speed of the target bus before it enters the queue; When there is only one GNSS data point in a road segment, the speed field in the GNSS data is used as the average speed of the target bus before it enters the queue. ; Included in the road segment When there are GNSS data points, among which, ,but: ； in, Indicates the first GNSS data point and the second GNSS data point. Road network distance between GNSS data points Indicates the first GNSS data point and the second GNSS data point. The time interval between GNSS data points.

4. The method for estimating bus travel time considering traffic light constraints according to claim 1, characterized in that, Set the travel time required for a target bus to reach the end of the queue when the lane is restricted by traffic lights; Obtain the effective signal light duration allocated to the lane when the lane is constrained by the traffic light; determine the number of complete signal cycles and the remaining time using the travel time required for the target bus to reach the end of the queue and the effective signal light duration; calculate the number of vehicles in the queue when the lane is constrained by the traffic light using the number of complete signal cycles and the remaining time. When a lane is constrained by traffic lights, the effective traffic light duration allocated to that lane is: ； in, Indicates the duration of the red light; Indicates the duration of the green light; Indicates the duration of the yellow light; Travel time required for the target bus to reach the end of the queue ; in, The estimated arrival time of the target bus at the end of the queue; To obtain the time of the target bus's GNSS data; The number of complete cycles in the travel time required for the target bus to reach the end of the queue is expressed as: ； in, The number of complete cycles; The remaining time in the travel time required for the target bus to reach the end of the queue is expressed as: ； Residual Time This includes the remaining red light duration. The remaining yellow light duration is The remaining green light duration is ; Total red light duration within the time period Total duration of yellow light Total green light duration They are respectively: ； ； ； Therefore, the equation for the number of vehicles in the queue is expressed as: ； in, The vehicle arrival rate in the lane where the target bus is located; The saturation flow rate of the lane where the target bus is located; In the formula, ; This represents the theoretical time required to clear all the queued vehicles. This indicates the total number of vehicles that need to be eliminated. This represents the net dissipation rate of the queue.

5. The method for estimating bus travel time considering traffic light constraints according to claim 4, characterized in that, The method further includes: using an iterative algorithm to solve for the travel time required for the target bus to reach the end of the queue when the lane is constrained by traffic lights, based on the bidirectional coupling relationship between the target bus and the vehicles in the queue; The average length of each vehicle is The deceleration distance of a bus before entering an intersection and queuing is: ; The number of vehicles in the queue at future moments ; Determine the effective distance that the bus needs to travel ; ; Buses at speed driving Distance, time Seconds, then decelerate to stop time Seconds; at this moment, Expressed as: ； Solving by iterative algorithm and The process is as follows: Establish the equation: ; Combined into a single iterative function: ; The iterative process is as follows: Initialization: Get ,but: ； ； Iterative process : Splitting traffic light time periods: Based on ,statistics Total red light duration within the time period Total duration of yellow light Total green light duration ; Update the number of vehicles in the queue. During the iteration process, if the calculated... Forced to be set To avoid negative numbers of vehicles in the queue; ； Corrected distance and arrival time: ; Introduce judgment conditions to dynamically adjust deceleration distance ; like The bus needs to slow down and stop. ； like The vehicle does not need to slow down and can reach the stop line directly. Convergence judgment when and When the iteration ends, the iteration is terminated.

6. The method for estimating bus travel time considering traffic light constraints according to claim 3, characterized in that, The travel time of the target bus through the road segment when not constrained by traffic lights is determined as follows: ； in, This indicates the travel time to finally pass through a road segment when not subject to traffic lights.

7. The method for estimating bus travel time considering traffic light constraints according to claim 5, characterized in that, Determine the final travel time of the target bus through the road segment when constrained by traffic lights, specifically: ； This indicates the travel time to finally pass through a road segment when constrained by traffic lights.

8. A bus travel time estimation system considering traffic light constraints, used to execute the bus travel time estimation method considering traffic light constraints as described in any one of claims 1 to 7, characterized in that, It includes a first calculation module, a second calculation module, and a time determination module; The first calculation module is used to determine the number of vehicles queuing at the downstream intersection and the travel time of the target bus through the road segment when the lane is not constrained by traffic lights, based on the GNSS data of the target bus. The second calculation module is used to set the travel time required for the target bus to reach the end of the queue when the lane is constrained by traffic lights; Obtain the effective signal light duration allocated to a lane when the lane is constrained by traffic lights; The number of complete signal cycles and the remaining time are determined by using the travel time required for the target bus to reach the end of the queue and the effective signal light duration; the number of vehicles in the queue when the lane is constrained by the signal light is calculated using the number of complete signal cycles and the remaining time; the state of the signal light at the moment the target bus reaches the end of the queue is predicted based on the discrete signal state of the signal light at the intersection downstream of the time the GNSS data of the target bus is acquired; and the signal delay time when the target bus is constrained by the signal light is calculated based on the predicted state of the signal light at the moment the target bus reaches the end of the queue and the number of vehicles in the queue. The time determination module is used to stop estimating when the fluctuation range of the predicted travel time of the target bus on the road segment does not exceed a preset threshold for multiple consecutive times, and to determine the travel time of the target bus to finally pass through the road segment under the two conditions of no traffic light constraint and traffic light constraint respectively.

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