Self-adaptive traffic signal lamp regulation and control method based on individual-level data

Abstract

The invention discloses a self-adaptive traffic signal lamp regulation and control method based on individual-level data, and belongs to the technical field of traffic control. In order to realize the fine control of the intersection, the method comprises the following steps: collecting the state information of vehicles, the state information of slow traffic individuals and the state information of traffic lights; constructing the minimum sum of the delay time of the vehicles and the slow traffic individuals as an optimization objective function; constructing a traffic signal structure constraint condition; constructing mutual constraint conditions between the vehicles; constructing mutual constraint conditions of travel individual tracks and traffic signals; forming a self-adaptive traffic signal lamp regulation and control model based on individual tracks; and solving the obtained self-adaptive traffic signal lamp regulation and control model based on the individual trajectory, optimizing a traffic signal timing scheme and a phase sequence of the intersection, optimizing traffic signals of the current period and a plurality of subsequent periods each time, and ensuring that each travel individual can leave the intersection within an optimized duration range. According to the invention, optimal comprehensive benefits of motor vehicles passing through the intersection and slow traffic are realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of traffic control, and in particular relates to an adaptive traffic signal light control method based on individual-level data. Background Art

[0002] Traffic signal control at intersections is the key to ensuring traffic safety and improving travel efficiency. The hardware facilities and control strategies of signal control systems have been developing, and currently three main control strategies have been formed: timing control, induction control, and adaptive control. Timing traffic signal control is based on historical traffic flow data, dividing a day into multiple time periods, assuming that traffic flow does not change much within a time period, and using the same set of signal timing schemes; induction control is based on detectors installed near intersections, real-time detection of vehicle arrival, and the use of green light extension, phase switching and other control methods. Compared with static timing control schemes, it can better adapt to random fluctuations in traffic flow; adaptive control is also a dynamic signal control strategy, relying on real-time detector data, predicting future short-term traffic flow conditions, and then combining the overall benefits of traffic flow in all directions, using a certain optimization model to optimize the signal timing scheme.

[0003] The detectors that adaptive control relies on are generally coils, radars, cameras and other devices fixed on the roads near the intersection to detect traffic flow and other data. The detection range of such equipment is limited and the maintenance cost of the equipment is high. With the development of technologies such as autonomous driving and vehicle-road-cloud integration and the construction of new equipment, continuous data at the level of individual travel trajectories can be collected in real time through vehicle-side OBU (On Board Unit) equipment, road-side RSU (Roadside Unit) facilities, V2I (Vehicle to Infrastructure) communication technology, etc., to achieve wider coverage and higher refinement of detection information. In addition, the vehicle-road-cloud environment provides more immediate communication capabilities and more powerful computing capabilities, which is of great significance to the innovation of adaptive signal optimization technology.

[0004] The method of adjusting the signal scheme based on the efficiency index of the signal intersection obtained through the individual vehicle data in the intelligent network environment can obtain the efficiency index such as the cumulative travel time of the vehicle corresponding to each signal phase based on the continuous position information data of the individual vehicles obtained in real time in the intelligent network environment. This index can reflect the congestion degree of the traffic flow corresponding to each signal phase, so it is used as the standard for phase extension or switching to adjust the traffic signal timing scheme in real time. This type of method is relatively simple and easy to implement, but the control strategy only relies on the index to make a simple adjustment to the green light time of the current phase, and does not comprehensively optimize the release time of each phase from the perspective of the overall traffic flow of the intersection, so it is difficult to achieve the optimal control effect.

[0005] The method of real-time rolling optimization of intersection signal control schemes based on dynamic programming and individual vehicle data acquired through intelligent network environment can complete the data of all individual vehicles that are about to arrive at the intersection through certain prediction and estimation methods based on the collected individual continuous position information data of some networked vehicles. Based on the dynamic programming method, the signal cycle is divided in time to search for the optimal duration scheme for each stage. Since the arrival schedule of each vehicle is known, the collective benefit indicators such as queuing and delay can be obtained by accumulating the individual vehicle indicators, and the individual vehicle indicators are calculated by whether the light is green. In this way, the signal scheme with the best benefit indicators such as delay and queuing can be optimized. The signal timing scheme of several cycles is optimized each time, and real-time rolling updates are made according to certain time intervals or trigger conditions. This type of method can comprehensively optimize the signal phase and sequence scheme from the perspective of the overall traffic flow of the intersection, but the indicator calculation model of individual vehicles has been greatly simplified, making it difficult to characterize the mutual interference between individual vehicles, and rarely considering the traffic benefits of slow traffic individuals such as pedestrians. Summary of the invention

[0006] The problem to be solved by the present invention is to achieve refined control of intersections and improve traffic efficiency, and an adaptive traffic signal light control method based on individual-level data is proposed.

[0007] To achieve the above object, the present invention is implemented through the following technical solutions: An adaptive traffic signal control method based on individual level data comprises the following steps: S1. Collect vehicle status information, slow-moving traffic status information, and traffic light status information; S2. Construct the optimization objective function by minimizing the sum of delay times of vehicles and slow-moving traffic individuals; S3. Construct traffic signal structure constraints; S4. Construct mutual constraints between vehicles; S5. Construct the mutual constraints between individual travel trajectories and traffic signals; S6. Based on steps S2-S5, an adaptive traffic light control model based on individual trajectories is formed; S7. Solve the adaptive traffic signal control model based on individual trajectories obtained in step S6, optimize the traffic signal timing plan and phase sequence at the intersection, optimize the traffic signals of the current cycle and the next few cycles each time, ensure that each traveling individual can leave the intersection within the optimized time range, and update the optimization results in real time.

[0008] Furthermore, the sum of the delay times of vehicles and slow-moving traffic individuals constructed in step S2 is the minimum min fThe expression for optimizing the objective function is: (1) in, is the vehicle number, It is the pedestrian's number. is the time when the vehicle leaves the stop line, It is the time when the last traffic signal turns green for pedestrians to cross the street.

[0009] Furthermore, step S3 constructs the traffic signal structure constraint condition as follows: The traffic signal adopts a double-loop control structure, which includes 8 motor vehicle phases and 6 pedestrian phases, of which 4 pedestrian phases are pedestrian secondary crossing phases and the motor vehicle phase In the The start time of the cycle is ,in Starting from 1, the maximum value of the cycle Determined based on intersection scope and expected speed; The motor vehicle phase is set to meet the minimum duration requirement, as shown in equations (2) to (3): (2) (3) in, The motor vehicle phase The next phase start time of The motor vehicle phase The minimum green time, The motor vehicle phase The green light interval time, The motor vehicle phase In the A variable that indicates whether a cycle is not skipped. If the value is 0, skip. If the value is 1, it will not be skipped; When the traffic signal reaches the barrier, the phase time of each motor vehicle ends at the same time, as shown in formula (4): (4) Furthermore, step S4 constructs the mutual constraints between vehicles as follows: Assume that vehicles leave during the green light period of any cycle, and each vehicle leaves the intersection in a certain cycle, as shown in equations (5) to (6): (5) (6) in, Indicates vehicle Is it in The variables of leaving the intersection in cycles, If the value is 0, then do not leave the intersection. If the value is 1, leave the intersection; When a vehicle passes through the widening section junction, for the lane upstream of the widening section junction, the traffic on the same lane leaves the widening section junction in sequence, and the departure time meets the saturated headway constraint, as shown in formula (7): (7) in, The vehicle is in the lane The sequence number on is the time when the vehicle leaves the junction of the widening section. It's a lane saturated headway; The time for the vehicle to leave the widening section junction is set to be greater than the time it takes to drive to the widening section junction without stopping at the current position, as shown in formula (8): (8) in, It is a vehicle The distance to the stop line at the current moment, is the distance from the widening section to the stop line. is the expected speed of the vehicle; For the lanes downstream of the widening section connection, the vehicles on the same lane leave the stop line in sequence and the departure time meets the saturated headway constraint, as shown in formula (9). The departure time of the vehicles downstream of the widening section connection is greater than the time of driving from the widening section connection to the stop line without stopping, as shown in formula (10). The departure time of the vehicles downstream of the widening section connection is greater than the time of driving from the current position to the stop line without stopping, as shown in formula (11): (9) (10) (11) Furthermore, step S5 constructs the mutual constraints between individual travel trajectories and traffic signals as follows: Set pedestrian phase Meet the minimum duration requirement, as shown in equations (12) to (13): (12) (13) in, Pedestrian phase The minimum green time, Pedestrian phase The green light interval time, Pedestrian phase In the A variable that indicates whether a cycle is not skipped. A value of 0 means it is skipped. A value of 1 means it is not skipped; Set the pedestrian flow direction for a single crossing. Leave during the green light period of any cycle, and each pedestrian is determined to leave the intersection in a certain cycle, as shown in equations (14) to (15): (14) (15) in, Indicates pedestrian Is it in The variables of leaving the intersection in cycles, A value of 0 means not leaving the intersection. A value of 1 means leaving the intersection; Assume that pedestrians cross the street twice, and the first pedestrian crossing time is during the green light period, as shown in formulas (16) to (17): (16) (17) in, It is the time it takes for pedestrians crossing the street twice to leave the first pedestrian crossing. Indicates pedestrian Is it in The variables of the first pedestrian crossing are left in cycles, A value of 0 means not leaving the first pedestrian crossing. A value of 1 means leaving the first pedestrian crossing; Assuming that pedestrians cross the street twice, the time for the second pedestrian crossing is greater than the sum of the time for leaving the first pedestrian crossing and the length of the first pedestrian crossing, as shown in formula (18): (18) in, A pedestrian crossing the street twice The corresponding duration of the first pedestrian crossing.

[0010] Furthermore, the input of the adaptive traffic light control model based on individual trajectories in step S6 includes the following parameters: Static parameters include travel speed, queue density, saturation flow rate, widening section length, and pedestrian or non-vehicle crossing time; Real-time vehicle detection information includes distance to the stop line, lane, and turn; Real-time pedestrian and non-vehicle detection information is the direction of crossing; traffic signal related information includes phase sequence scheme, minimum phase duration, green light interval, and real-time operation status; Status information of vehicles and slow-moving traffic entities, and traffic light status information; The output of the adaptive traffic light control model based on individual-level data includes the phase sequence and duration plan of several signal cycles starting from the current cycle.

[0011] Beneficial effects of the present invention: The adaptive traffic light control method based on individual-level data described in the present invention models individual vehicles at the trajectory level to describe the relationship between signal and vehicle efficiency indicators, and solves the problem that traditional optimization models are difficult to describe in situations such as inaccurate delays in formula calculations caused by uneven distribution of traffic flow arrivals, and reduction in saturated flow rate when the green light duration is long when short lanes exist.

[0012] The adaptive traffic signal control method based on individual-level data described in the present invention aims at the problem that pedestrians and other slow-moving traffic, especially the continuity of secondary crossing, are less considered in the signal optimization model. The pedestrian / non-vehicle trajectory level modeling is performed to describe their discontinuous passage delays in situations such as secondary crossing. The pedestrian / non-vehicle trajectory level modeling is added to the above-mentioned vehicle optimization model to construct an adaptive signal optimization model for intersections with the optimal comprehensive benefits of vehicles and slow-moving traffic, thereby achieving the optimal comprehensive benefits of vehicles and slow-moving traffic passing through the intersection. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A flowchart of an adaptive traffic signal light control method based on individual-level data according to the present invention; Figure 2 This is a schematic diagram of the double-loop control structure of a traffic signal of the present invention; Figure 3 It is a schematic diagram of the vehicle-related constraints of the present invention. DETAILED DESCRIPTION

[0014] In order to make the purpose, technical solution and advantages of the present invention more clear, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention, that is, the specific embodiments described are only part of the embodiments of the present invention, rather than all of the specific embodiments. The components of the specific embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations, and the present invention can also have other embodiments.

[0015] Therefore, the following detailed description of the specific embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents the selected specific embodiments of the present invention. Based on the specific embodiments of the present invention, all other specific embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0016] In order to further understand the content, features and effects of the present invention, the following specific implementation methods are given as examples, and the attached Figure 1 -Attached Figure 3 The detailed instructions are as follows:

[0017] Embodiment 1: An adaptive traffic signal control method based on individual level data comprises the following steps: S1. Collect vehicle status information, slow-moving traffic status information, and traffic light status information; S2. Construct the optimization objective function by minimizing the sum of delay times of vehicles and slow-moving traffic individuals; Furthermore, the sum of the delay times of vehicles and slow-moving traffic individuals constructed in step S2 is the minimum min f The expression for optimizing the objective function is: (1) in, is the vehicle number, It is the pedestrian's number. is the time when the vehicle leaves the stop line, It is the time when the last traffic signal turns green for pedestrians to cross the street.

[0018] S3. Construct traffic signal structure constraints; Furthermore, step S3 constructs the traffic signal structure constraint condition as follows: The traffic signal adopts a double-loop control structure, which includes 8 motor vehicle phases and 6 pedestrian phases, of which 4 pedestrian phases are pedestrian secondary crossing phases and the motor vehicle phase In the The start time of the cycle is ,in Starting from 1, the maximum value of the cycle Determined based on intersection scope and expected speed; The motor vehicle phase is set to meet the minimum duration requirement, as shown in equations (2) to (3): (2) (3) in, The motor vehicle phase The next phase start time of The motor vehicle phase The minimum green time, The motor vehicle phase The green light interval time, The motor vehicle phase In the A variable that indicates whether a cycle is not skipped. If the value is 0, skip. If the value is 1, it will not be skipped; When the traffic signal reaches the barrier, the phase time of each motor vehicle ends at the same time, as shown in formula (4): (4) S4. Construct mutual constraints between vehicles; Furthermore, step S4 constructs the mutual constraints between vehicles as follows: Assume that vehicles leave during the green light period of any cycle, and each vehicle leaves the intersection in a certain cycle, as shown in equations (5) to (6): (5) (6) in, Indicates vehicle Is it in The variables of leaving the intersection in cycles, If the value is 0, then do not leave the intersection. If the value is 1, leave the intersection; When a vehicle passes through the widening section junction, for the lane upstream of the widening section junction, the traffic on the same lane leaves the widening section junction in sequence, and the departure time meets the saturated headway constraint, as shown in formula (7): (7) in, The vehicle is in the lane The sequence number on is the time when the vehicle leaves the junction of the widening section. It's a lane saturated headway; The time for the vehicle to leave the widening section junction is set to be greater than the time it takes to drive to the widening section junction without stopping at the current position, as shown in formula (8): (8) in, It is a vehicle The distance to the stop line at the current moment, is the distance from the widening section to the stop line. is the expected speed of the vehicle; For the lanes downstream of the widening section connection, the vehicles on the same lane leave the stop line in sequence and the departure time meets the saturated headway constraint, as shown in formula (9). The departure time of the vehicles downstream of the widening section connection is greater than the time of driving from the widening section connection to the stop line without stopping, as shown in formula (10). The departure time of the vehicles downstream of the widening section connection is greater than the time of driving from the current position to the stop line without stopping, as shown in formula (11): (9) (10) (11) S5. Construct the mutual constraints between individual travel trajectories and traffic signals; Furthermore, step S5 constructs the mutual constraints between individual travel trajectories and traffic signals as follows: Set pedestrian phase Meet the minimum duration requirement, as shown in equations (12) to (13): (12) (13) in, Pedestrian phase The minimum green time, Pedestrian phase The green light interval time, Pedestrian phase In the A variable that indicates whether a cycle is not skipped. A value of 0 means it is skipped. A value of 1 means it is not skipped; Set the pedestrian flow direction for a single crossing. Leave during the green light period of any cycle, and each pedestrian is determined to leave the intersection in a certain cycle, as shown in equations (14) to (15): (14) (15) in, Indicates pedestrian Is it in The variables of leaving the intersection in cycles, A value of 0 means not leaving the intersection. A value of 1 means leaving the intersection; Assume that pedestrians cross the street twice, and the first pedestrian crossing time is during the green light period, as shown in formulas (16) to (17): (16) (17) in, It is the time it takes for pedestrians crossing the street twice to leave the first pedestrian crossing. Indicates pedestrian Is it in The variables of the first pedestrian crossing are left in cycles, A value of 0 means not leaving the first pedestrian crossing. A value of 1 means leaving the first pedestrian crossing; Assuming that pedestrians cross the street twice, the time for the second pedestrian crossing is greater than the sum of the time for leaving the first pedestrian crossing and the length of the first pedestrian crossing, as shown in formula (18): (18) in, A pedestrian crossing the street twice The corresponding duration of the first pedestrian crossing.

[0019] S6. Based on steps S2-S5, an adaptive traffic light control model based on individual trajectories is formed; Furthermore, the input of the adaptive traffic light control model based on individual trajectories in step S6 includes the following parameters: Static parameters include travel speed, queue density, saturation flow rate, widening section length, and pedestrian or non-vehicle crossing time; Real-time vehicle detection information includes distance to the stop line, lane, and turn; Real-time pedestrian and non-vehicle detection information is the direction of crossing; traffic signal related information includes phase sequence scheme, minimum phase duration, green light interval, and real-time operation status; Status information of vehicles and slow-moving traffic entities, and traffic light status information; The output of the adaptive traffic light control model based on individual-level data includes the phase sequence and duration plan of several signal cycles starting from the current cycle.

[0020] S7. Solve the adaptive traffic signal control model based on individual trajectories obtained in step S6, optimize the traffic signal timing plan and phase sequence at the intersection, optimize the traffic signals of the current cycle and the next few cycles each time, ensure that each traveling individual can leave the intersection within the optimized time range, and update the optimization results in real time.

[0021] Figure 2This is a schematic diagram of the dual-loop control structure of a traffic signal of the present invention. The horizontal axis represents time, which describes the time correlation relationship of each phase. It can be seen from the figure that after the p1 phase ends, the p2 phase comes, and the p1 phase and the p5 phase are turned on at the same time.

[0022] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0023] Although the present application has been described above with reference to specific embodiments, various modifications may be made thereto and parts thereof may be replaced with equivalents without departing from the scope of the present application. In particular, as long as there is no structural conflict, the various features in the specific embodiments disclosed in the present application may be used in combination with each other in any manner, and the fact that these combinations are not exhaustively described in this specification is only for the sake of omitting space and saving resources. Therefore, the present application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. An adaptive traffic light control method based on individual-level data, characterized in that: The steps include: S1. Collect vehicle status information, slow-moving traffic status information, and traffic light status information; S2. Construct the optimization objective function by minimizing the sum of delay times of vehicles and slow-moving traffic individuals; S3. Construct traffic signal structure constraints; S4. Construct mutual constraints between vehicles; S5. Construct the mutual constraints between individual travel trajectories and traffic signals; S6. Based on steps S2-S5, an adaptive traffic light control model based on individual trajectories is formed; S7. Solve the adaptive traffic signal control model based on individual trajectories obtained in step S6, optimize the traffic signal timing plan and phase sequence at the intersection, optimize the traffic signals of the current cycle and the next few cycles each time, ensure that each traveling individual can leave the intersection within the optimized time range, and update the optimization results in real time.

2. The method for adaptively controlling traffic lights based on individual-level data according to claim 1, characterized in that: The minimum sum of the delay times of vehicles and slow-moving traffic individuals constructed in step S2 is min f The expression for optimizing the objective function is: （1） in, is the vehicle number, It is the pedestrian's number. is the time when the vehicle leaves the stop line, It is the time when the last traffic signal turns green for pedestrians to cross the street.

3. The method for adaptively controlling traffic lights based on individual-level data according to claim 2, characterized in that: Step S3 constructs the traffic signal structure constraints as follows: The traffic signal adopts a double-loop control structure, which includes 8 motor vehicle phases and 6 pedestrian phases, of which 4 pedestrian phases are pedestrian secondary crossing phases and the motor vehicle phase In the The start time of the cycle is ,in Starting from 1, the maximum value of the cycle Determined based on intersection scope and expected speed; The motor vehicle phase is set to meet the minimum duration requirement, as shown in equations (2) to (3): （2） （3） in, The motor vehicle phase The next phase start time of The motor vehicle phase The minimum green time, The motor vehicle phase The green light interval time, The motor vehicle phase In the A variable that indicates whether a cycle is not skipped. If the value is 0, skip. If the value is 1, it will not be skipped; When the traffic signal reaches the barrier, the phase time of each motor vehicle ends at the same time, as shown in formula (4): （4）。 4. The method for adaptively controlling traffic lights based on individual-level data according to claim 3, characterized in that: Step S4 constructs the mutual constraints between vehicles as follows: Assume that vehicles leave during the green light period of any cycle, and each vehicle leaves the intersection in a certain cycle, as shown in equations (5) to (6): （5） （6） in, Indicates vehicle Is it in The variables of leaving the intersection in cycles, If the value is 0, then do not leave the intersection. If the value is 1, leave the intersection; When a vehicle passes through the widening section junction, for the lane upstream of the widening section junction, the traffic on the same lane leaves the widening section junction in sequence, and the departure time meets the saturated headway constraint, as shown in formula (7): （7） in, The vehicle is in the lane The sequence number on is the time when the vehicle leaves the junction of the widening section. It's a lane saturated headway; The time for the vehicle to leave the widening section junction is set to be greater than the time it takes to drive to the widening section junction without stopping at the current position, as shown in formula (8): （8） in, It is a vehicle The distance to the stop line at the current moment, is the distance from the widening section to the stop line. is the expected speed of the vehicle; For the lanes downstream of the widening section connection, the vehicles on the same lane leave the stop line in sequence and the departure time meets the saturated headway constraint, as shown in formula (9). The departure time of the vehicles downstream of the widening section connection is greater than the time of driving from the widening section connection to the stop line without stopping, as shown in formula (10). The departure time of the vehicles downstream of the widening section connection is greater than the time of driving from the current position to the stop line without stopping, as shown in formula (11): （9） （10） （11）。 5. The method for adaptively controlling traffic lights based on individual-level data according to claim 4, characterized in that: Step S5 constructs the mutual constraints between individual travel trajectories and traffic signals as follows: Set pedestrian phase Meet the minimum duration requirement, as shown in equations (12) to (13): （12） （13） in, Pedestrian phase The minimum green time, Pedestrian phase The green light interval time, Pedestrian phase In the A variable that indicates whether a cycle is not skipped. A value of 0 means it is skipped. A value of 1 means it is not skipped; Set the pedestrian flow direction for a single crossing. Leave during the green light period of any cycle, and each pedestrian is determined to leave the intersection in a certain cycle, as shown in equations (14) to (15): （14） （15） in, Indicates pedestrian Is it in The variables of leaving the intersection in cycles, A value of 0 means not leaving the intersection. A value of 1 indicates leaving the intersection; Assume that pedestrians cross the street twice, and the first pedestrian crossing time is during the green light period, as shown in formulas (16) to (17): （16） （17） in, It is the time it takes for pedestrians crossing the street twice to leave the first pedestrian crossing. Indicates pedestrian Is it in The variables of the first pedestrian crossing are left in cycles, A value of 0 means not leaving the first pedestrian crossing. A value of 1 means leaving the first pedestrian crossing; Assuming that pedestrians cross the street twice, the time for the second pedestrian crossing is greater than the sum of the time for leaving the first pedestrian crossing and the length of the first pedestrian crossing, as shown in formula (18): （18） in, A pedestrian crossing the street twice The corresponding duration of the first pedestrian crossing.

6. The method for adaptively controlling traffic lights based on individual-level data according to claim 5, characterized in that: Step S6: The input of the adaptive traffic light control model based on individual trajectories includes the following parameters: Static parameters include travel speed, queue density, saturation flow rate, widening section length, and pedestrian or non-vehicle crossing time; Real-time vehicle detection information includes distance to the stop line, lane, and turn; Real-time pedestrian and non-vehicle detection information is the direction of crossing; traffic signal related information includes phase sequence scheme, minimum phase duration, green light interval, and real-time operation status; Status information of vehicles and slow-moving traffic entities, and traffic light status information; The output of the adaptive traffic light control model based on individual-level data includes the phase sequence and duration plan of several signal cycles starting from the current cycle.

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