Traffic signal processing method, device, electronic device and storage medium

Abstract

This disclosure provides a traffic signal processing method, relating to the field of artificial intelligence technology, and particularly to the fields of autonomous driving technology and intelligent transportation technology. The specific implementation scheme is as follows: Based on the saturation of multiple phases corresponding to traffic lights, a phase to be processed is determined from among the multiple phases, wherein the saturation of the phase is determined based on the duration of a first signal corresponding to the phase; Based on at least one constraint condition, a first parameter to be processed is adjusted to reduce a target fusion value, obtaining an adjusted target fusion value, wherein the target fusion value is determined based on the first parameter to be processed, and the at least one constraint condition includes a first constraint condition that the first parameter to be processed is greater than or equal to the saturation of the phase to be processed; Based on the duration of the first signal corresponding to the adjusted target fusion value, the signal corresponding to the phase to be processed is controlled. This disclosure also provides a traffic signal processing device, electronic device, and storage medium.

Description

Technical Field

[0001] This disclosure relates to the field of artificial intelligence technology, and more particularly to the fields of autonomous driving technology and intelligent transportation technology. More specifically, this disclosure provides a traffic signal processing method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the development of artificial intelligence technology, the control methods for traffic lights are constantly increasing. Traffic lights can include green lights and red lights, among others. Summary of the Invention

[0003] This disclosure provides a traffic signal processing method, apparatus, device, and storage medium.

[0004] According to one aspect of this disclosure, a traffic signal processing method is provided, the method comprising: determining a phase to be processed among a plurality of phases based on the saturation of each of the plurality of phases corresponding to a traffic light, wherein the saturation of the phase is determined based on a first signal duration corresponding to the phase; adjusting a first parameter to be processed according to at least one constraint condition to reduce a target fusion value, thereby obtaining an adjusted target fusion value, wherein the target fusion value is determined based on the first parameter to be processed, the at least one constraint condition including a first constraint condition including the first parameter to be processed being greater than or equal to the saturation of the phase to be processed; and controlling a signal corresponding to the phase to be processed according to the first signal duration corresponding to the adjusted target fusion value.

[0005] According to another aspect of this disclosure, a traffic signal processing apparatus is provided, the apparatus comprising: a determining module, configured to determine a phase to be processed among a plurality of phases based on the saturation of each of the plurality of phases corresponding to a traffic light, wherein the saturation of the phase is determined based on a first signal duration corresponding to the phase; an adjusting module, configured to adjust a first parameter to be processed according to at least one constraint condition to reduce a target fusion value, thereby obtaining an adjusted target fusion value, wherein the target fusion value is determined based on the first parameter to be processed, and the at least one constraint condition includes a first constraint condition that includes the first parameter to be processed being greater than or equal to the saturation of the phase to be processed; and a controlling module, configured to control a signal corresponding to the phase to be processed based on the first signal duration corresponding to the adjusted target fusion value.

[0006] According to another aspect of this disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform a method provided according to this disclosure.

[0007] According to another aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions for causing a computer to perform the methods provided according to this disclosure.

[0008] According to another aspect of this disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the method provided according to this disclosure.

[0009] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0010] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0011] Figure 1 This is an exemplary system architecture diagram of a traffic signal processing method and apparatus applicable according to an embodiment of the present disclosure;

[0012] Figure 2 This is a schematic flowchart of a traffic signal processing method according to an embodiment of the present disclosure;

[0013] Figures 3A to 3D This is a schematic diagram of multiple stages of a signal cycle according to an embodiment of the present disclosure;

[0014] Figure 3E This is a schematic diagram of a signal period according to an embodiment of the present disclosure;

[0015] Figure 4 This is a block diagram of a traffic signal processing apparatus according to an embodiment of the present disclosure; and

[0016] Figure 5 This is a block diagram of an electronic device to which a traffic signal processing method can be applied, according to an embodiment of the present disclosure. Detailed Implementation

[0017] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0018] In the field of traffic signal control, traffic signal schemes can be optimized to improve traffic efficiency and safety. Optimization can include optimizing signal cycle time and green light ratio. The green light ratio is the proportion of a green light signal within the signal cycle. Optimizing the green light ratio aims to balance the saturation in all directions, allocating more green light time to directions with higher traffic demand. For cycle time optimization, the Webster model or its optimized version can be used. However, the Webster model is primarily suitable for scenarios with unsaturated traffic flow and is less adaptable to scenarios with saturated traffic flow.

[0019] In some embodiments, the optimization objective of the Webster model can be to minimize vehicle delay. For example, a simplified Webster model can be implemented as follows:

[0020] (Formula 1)

[0021] C0 is the optimal cycle length. L is the total loss time. Y is the traffic flow ratio at the road intersection.

[0022] As shown in Formula 1, when traffic flow is oversaturated, Y will approach 1 infinitely, resulting in a very large C0. That is, the optimized cycle is unreasonable.

[0023] In other embodiments, when phase saturation is too high, the period can be increased to reduce saturation. For example, saturation can be determined using the following formula:

[0024] (Formula 2)

[0025] Q m S represents the flow rate at phase m. m Let G be the saturation flow rate at phase m. m Let C be the green light duration for phase m, and C be the period duration. In this case, the optimization objective could be to fuzzily reduce the saturation. However, determining the saturation requires using the period duration, which may require multiple iterations to obtain the optimized result, resulting in low optimization efficiency.

[0026] Therefore, in order to efficiently optimize traffic light schemes in both saturated and unsaturated traffic flow scenarios, this disclosure provides a traffic signal processing method, which will be described below.

[0027] Figure 1 This is a schematic diagram of an exemplary system architecture for applying traffic signal processing methods and apparatus according to an embodiment of this disclosure. It should be noted that... Figure 1The examples shown are merely examples of system architectures that can be applied to the embodiments of this disclosure, in order to help those skilled in the art understand the technical content of this disclosure, but do not mean that the embodiments of this disclosure cannot be used in other devices, systems, environments or scenarios.

[0028] like Figure 1 As shown, the system architecture 100 according to this embodiment may include sensors 1101, 1102, and 1103, a network 120, and a server 130. The network 120 serves as a medium for providing a communication link between the sensors 1101, 1102, and 1103 and the server 130. The network 120 may include various connection types, such as wired and / or wireless communication links, etc.

[0029] Sensors 1101, 1102, and 1103 can interact with server 130 via network 120 to receive or send messages, etc.

[0030] Sensors 1101, 1102, and 1103 can be functional components integrated on vehicle 110, such as infrared sensors, ultrasonic sensors, millimeter-wave radar, information acquisition devices, etc. Sensors 1101, 1102, and 1103 can be used to collect status data of obstacles around vehicle 110 and surrounding road data.

[0031] Vehicle 110 can communicate with Road Side Unit (RSU) 140, receiving information from or sending information to the Road Side Unit. The Road Side Unit 140 can, for example, be deployed on a traffic light to adjust the duration or frequency of the traffic light.

[0032] Server 130 can be set at a remote location that can establish communication with the vehicle terminal. It can be implemented as a distributed server cluster consisting of multiple servers or as a single server.

[0033] Server 130 can be a server that provides various services. Applications such as map applications and data processing applications can be installed on server 130. Taking server 130 running a data processing application as an example: it receives obstacle status data and road data transmitted from sensors 1101, 1102, and 1103 via network 120, and can process one or more of the obstacle status data and road data.

[0034] It should be noted that the traffic signal processing method provided in this embodiment can generally be executed by the server 130. Correspondingly, the traffic signal processing device provided in this embodiment can also be located in the server 130. However, it is not limited to this. The traffic signal processing method provided in this embodiment can also generally be executed by the roadside unit 140. Correspondingly, the traffic signal processing device provided in this embodiment can also be located in the roadside unit 140.

[0035] Understandable. Figure 1 The number of sensors, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of sensors, networks, and servers can be included.

[0036] It is understood that the system architecture of this disclosure has been described above, and the methods of this disclosure will be described below. It is also understood that the sequence numbers of each operation in the following methods are only for descriptive purposes and should not be considered as indicating the execution order of the operations. Unless explicitly stated otherwise, the method does not need to be executed in the exact order shown.

[0037] Figure 2 This is a flowchart of a traffic signal processing method according to an embodiment of the present disclosure.

[0038] like Figure 2 As shown, the method 200 may include operations S210 to S230.

[0039] In operation S210, the phase to be processed among the multiple phases is determined based on the saturation of each of the multiple phases corresponding to the traffic lights.

[0040] In this embodiment of the disclosure, the phase can be the direction of flow. For example, at an intersection corresponding to a traffic light, west to east can be considered as one phase. East to west can also be considered as one phase.

[0041] In this embodiment of the disclosure, the saturation of the phase is determined based on the duration of a first signal corresponding to the phase. For example, the first signal may be a green light signal. Upon receiving the green light signal, the green light can be turned on.

[0042] In this embodiment of the disclosure, the phase to be processed can be any one of multiple phases. For example, the phase to be processed can be the phase with the highest saturation or the phase with the lowest saturation.

[0043] In operation S220, the first parameter to be processed is adjusted according to at least one constraint to reduce the target fusion value, thereby obtaining the adjusted target fusion value.

[0044] In this embodiment of the disclosure, the target fusion value can be determined based on a first parameter to be processed. For example, the first parameter to be processed can be used as the target fusion value.

[0045] In embodiments of this disclosure, at least one constraint includes a first constraint. The first constraint includes a first parameter to be processed being greater than or equal to the saturation of the phase to be processed. For example, the first parameter to be processed may also be a saturation level. The first parameter to be processed is adjusted such that it continuously decreases while remaining greater than or equal to the saturation of the phase to be processed.

[0046] In operation S230, the signal corresponding to the phase to be processed is controlled according to the duration of the first signal corresponding to the adjusted target fusion value.

[0047] In this embodiment of the disclosure, the saturation of the phase is determined by a first signal duration corresponding to the phase. The first parameter to be processed can also be a saturation value. This saturation corresponds to a first signal duration. The target fusion value is determined based on the first processing duration and also corresponds to a first signal duration.

[0048] In this embodiment of the disclosure, the duration of the first signal corresponding to the phase to be processed can be determined based on the duration of the first signal corresponding to the adjusted target fusion value. For example, after receiving the first signal, a signal light corresponding to the first signal can be illuminated within the duration of the first signal. This signal light can be, for example, a green light.

[0049] Through the embodiments of this disclosure, the target fusion value is reduced based on the saturation and constraints of the phase, and the first parameter to be processed is made greater than or equal to the original saturation of the phase. This allows for an appropriate increase in saturation without causing excessive traffic flow in the phase, thus helping to improve traffic efficiency and reduce green light loss time.

[0050] As can be understood, the method of this disclosure has been described above, and the application scenarios of this disclosure will be described below.

[0051] Figures 3A to 3D This is a schematic diagram of multiple stages of a signal cycle according to an embodiment of the present disclosure.

[0052] like Figure 3A As shown, the first stage s31 of the signal cycle can correspond to two phases. These two phases are the first phase and the second phase. The first phase corresponds to vehicles traveling straight from west to east. The second phase corresponds to vehicles traveling straight from east to west.

[0053] like Figure 3BAs shown, the second stage s32 of the signal cycle can correspond to four phases. These four phases can correspond to: a vehicle turning left from east to west, a vehicle turning right from east to west, a vehicle turning left from west to east, and a vehicle turning right from west to east. The second stage can occur after the first stage.

[0054] like Figure 3C As shown, the third stage s33 of the signal cycle can correspond to two phases. These two phases can include the third phase and the fourth phase. The third phase corresponds to vehicles traveling straight from north to south. The fourth phase corresponds to vehicles traveling straight from south to north. The third stage can occur after the second stage.

[0055] like Figure 3D As shown, the fourth stage s34 of the signal cycle can correspond to four phases. These four phases can respectively correspond to: a vehicle turning left from north to south, a vehicle turning right from north to south, a vehicle turning left from south to north, and a vehicle turning right from south to north. The fourth stage can occur after the third stage. This can be understood as... Figures 3A to 3D As shown, a phase of a signal cycle can include multiple phases.

[0056] Figure 3E This is a schematic diagram of a signal cycle according to an embodiment of the present disclosure.

[0057] like Figure 3E As shown, the green light duration of a signal cycle is 150 seconds. A signal cycle can also correspond to a lost time period. The lost time period can include the yellow light duration and the signal transition time. The signal transition time can be the duration required to switch between different traffic lights. This signal cycle can be the signal cycle of the traffic lights at a road intersection. In the first stage s31, the green light duration is 31 seconds, with a lost time period of 3 seconds. In the second stage s32, the green light duration is 30 seconds, with a lost time period of 6 seconds. In the third stage s33, the green light duration is 26 seconds, with a lost time period of 3 seconds. In the fourth stage s34, the green light duration is 63 seconds, with a lost time period of 7 seconds.

[0058] As can be understood, the application scenarios of this disclosure have been explained above, and the phase to be processed in this disclosure will be further explained below.

[0059] In some embodiments, in some implementations of the above operation S210, the saturation of the phase to be processed is the largest among a plurality of phases with the highest saturation. For example, if the first phase has the highest saturation, the first phase can be used as the phase to be processed.

[0060] In some embodiments, the phase to be processed corresponds to the duration of the first signal to be processed and the duration of the processing period. For example, the duration of the first signal of the phase to be processed can be used as the duration of the first signal to be processed. The duration of the signal period corresponding to the phase to be processed can be used as the duration of the processing period.

[0061] In some embodiments, the saturation of the phase to be processed is determined based on the flow data corresponding to the phase to be processed and the first signal to be processed ratio. The first signal to be processed ratio is the ratio of the duration of the first signal to be processed to the duration of the processing cycle. The first signal to be processed ratio can be determined by using the duration of the first signal to be processed as the numerator and the duration of the processing cycle as the denominator.

[0062] For example, the saturation of the phase to be processed can be determined using the following formula:

[0063] (Formula 3)

[0064] Phase i can be the first phase mentioned above, or it can be the phase to be processed. Let i be the saturation of phase i. The flow rate data for phase i (e.g., the flow rate ratio). Let be the duration of the first signal in phase i. Let C be the duration of the period.

[0065] In some embodiments, the first constraint may include: a first parameter to be processed is greater than or equal to the saturation of the phase to be processed. For example, the first constraint may be implemented as follows:

[0066] (Formula 4)

[0067] z can be the first parameter to be processed.

[0068] It is understood that the method for determining the saturation of the phase to be processed has been explained above. Therefore, in this embodiment, the first constraint is implemented as follows: the difference between the first product and the second product is greater than or equal to a first preset value, where the first product is the product of the first parameter to be processed and the duration of the first signal to be processed, and the second product is the product of the flow data and the duration of the processing cycle. The first product can be used as the minuend, and the second product can be used as the subtrahend. The first preset value can, for example, be 0. For example, combining Formula 3 and Formula 4, the first constraint can also be implemented as follows:

[0069] (Formula 5)

[0070] It can be the first product. It can be the second product.

[0071] In some embodiments of operation S220 described above, the first parameter to be processed can be used as the target fusion value. The first parameter to be processed, the duration of the first signal to be processed, and the duration of the processing period can be adjusted to reduce the target fusion value. For example, the target fusion value can be reduced based on the following formula:

[0072] (Formula 6)

[0073] In this embodiment, the adjusted target fusion value can be the minimum target fusion value obtained after at least one adjustment of the first parameter to be processed. In this embodiment, the phase to be processed is the phase with the highest saturation. The adjusted target fusion value is the minimum target fusion value after adjustment, which can reduce the saturation of the phase with the highest saturation, thereby increasing the saturation of other phases and improving overall road traffic efficiency.

[0074] It is understood that the method of this disclosure has been described above in conjunction with the first constraint condition. However, this disclosure is not limited thereto, and at least one constraint condition may also include a second constraint condition, which will be explained below.

[0075] In some embodiments, the second constraint includes a first parameter to be processed being greater than or equal to the desired saturation of the phase to be processed. The desired saturation can be greater than the saturation of the phase to be processed. For example, the desired saturation... For example, it could be 1.0. As another example, the second constraint could be implemented as:

[0076] (Formula 7)

[0077] Therefore, based on Formulas 5 and 7, Formula 6 can be solved to obtain the adjusted target fusion value, as well as the corresponding first signal duration and signal cycle duration. Based on the first signal duration and signal cycle duration corresponding to the adjusted target fusion value, the duration of the green light corresponding to the phase to be processed can be controlled. Through the embodiments of this disclosure, the saturation of the phase to be processed can be made closer to the desired saturation, and the green light loss time can be reduced. When the target fusion value is reduced, the saturation of the phase to be processed is maximized, and the saturation of the phase to be processed cannot reach the desired saturation, the traffic efficiency corresponding to the phase to be processed can be improved while reserving more margin for other phases, providing favorable conditions for improving the traffic efficiency of other phases.

[0078] It is understood that the above description uses the first parameter to be processed as the target fusion value as an example to illustrate this disclosure. However, this disclosure is not limited to this, as will be explained below.

[0079] In some embodiments, the target fusion value may be obtained based on a first processing parameter and a processing period duration. For example, the target fusion value may be obtained based on a first processing parameter and a processed processing period duration. The processed processing period duration is obtained by processing the processing period duration using the first processing parameter. For example, the target fusion value may be reduced based on the following formula:

[0080] (Formula 8)

[0081] α can be a first processing parameter. For example, α can be 0.001. Through the embodiments of this disclosure, by processing the processing parameter to be processed for the cycle duration, the primary and secondary objectives can be distinguished. For example, adjusting the first processing parameter z can be the primary objective, while adjusting the cycle duration C can be the secondary objective. As described above, when the primary objective is achieved, the cycle duration can be further reduced, resulting in less lost time and further improving traffic efficiency.

[0082] It is understood that the method of this disclosure has been described above in conjunction with the first and second constraints. However, this disclosure is not limited thereto, and at least one constraint may also include a third constraint, which will be explained below.

[0083] In some embodiments, the third constraint includes: the second parameter to be processed is greater than or equal to the saturation of the phase to be processed. For example, the third constraint can be implemented as follows:

[0084] (Formula Nine)

[0085] z a This can be the second parameter to be processed. It is understood that the method for determining the saturation of the phase to be processed has been explained above. Therefore, in this embodiment, the third constraint can be implemented as follows: the difference between the third product and the fourth product is greater than or equal to the second preset value, where the third product is the product between the second parameter to be processed and the duration of the first signal to be processed, and the fourth product is the product between the flow data and the preset period duration. The third product can be used as the minuend, and the fourth product can be used as the subtrahend. The second preset value can, for example, be 0. For example, combining Formula 3 and Formula 8, the third constraint can also be implemented as follows:

[0086] (Formula 10)

[0087] It can be the third product. It can be the fourth product. You can preset the cycle duration.

[0088] In this embodiment of the disclosure, the target fusion value can also be determined based on the first parameter to be processed and the second parameter to be processed. For example, the target fusion value can also be determined based on the first parameter to be processed and the processed second parameter to be processed.

[0089] In some embodiments, in other implementations of operation S220 described above, adjusting the first parameter to be processed to reduce the target fusion value according to at least one constraint includes: adjusting the first parameter to be processed and the second parameter to be processed for at least one iteration based on at least one constraint to reduce the target fusion value. For example, the target fusion value can be reduced based on the following formula:

[0090] (Formula Eleven)

[0091] It can be a second processing parameter. For example, it could be 0.001. Through embodiments of this disclosure, by processing the second parameter to be processed using processing parameters, primary and secondary objectives can be distinguished. For example, adjusting z can be the primary objective, while adjusting z... a Adjusting the processing cycle duration can be a secondary objective. As mentioned above, during the adjustment of the processing cycle duration, the processing cycle duration can be shorter than the preset minimum cycle duration. In this case, the saturation of the phase to be processed may still differ significantly from the desired saturation. Setting a secondary objective can ensure that a better first signal duration is obtained, thereby effectively improving traffic efficiency.

[0092] In this embodiment of the disclosure, adjusting the first and second parameters to be processed for at least one iteration based on at least one constraint further includes: in response to determining that the processing cycle duration in the previous iteration of the target iteration is greater than or equal to a preset cycle duration, adjusting the first parameter to be processed, the second parameter to be processed, the duration of the first signal to be processed, and the processing cycle duration in the previous iteration based on the first and second constraints to obtain the second parameter to be processed and the duration of the first signal to be processed in the target iteration. For example, the processing cycle duration in the target iteration may be less than the preset cycle duration. The processing cycle duration in the previous iteration of the target iteration may be greater than or equal to the preset cycle duration. The preset cycle duration may be a preset minimum cycle duration. When the processing cycle duration is greater than or equal to the preset cycle duration, the first parameter to be processed, the second parameter to be processed, the duration of the first signal to be processed, and the processing cycle duration can be adjusted based on the constraints of Formulas 5 and 7 above.

[0093] In this embodiment of the disclosure, adjusting the first and second parameters to be processed for at least one iteration based on at least one constraint includes: in response to determining that the processing period duration of a target iteration in at least one iteration is less than a preset period duration, adjusting the second parameter to be processed and the duration of the first signal to be processed for the target iteration according to a third constraint, thereby obtaining the second parameter to be processed and the duration of the first signal to be processed in subsequent iterations of the target iteration. For example, when the processing period duration is less than the preset period duration, the preset period duration can be used as the signal period duration to adjust the second parameter to be processed and the duration of the first signal to be processed.

[0094] It is understood that the above description uses the example of determining the target fusion value based on the second parameter to be processed or the processing period duration to illustrate this disclosure. However, this disclosure is not limited to this; the target fusion value can be determined based on the first parameter to be processed, the second parameter to be processed, and the processing period duration, as will be explained below.

[0095] In this embodiment of the disclosure, the target fusion value can be determined based on a first parameter to be processed, a processed second parameter to be processed, and a processed processing period duration. For example, the target fusion value can be reduced using the following formula:

[0096] (Formula 12)

[0097] Formula 12 can serve as the optimization objective. This objective includes a primary objective and two secondary objectives. Next, based on the first to third constraints, the target fusion value can be reduced. After adjusting one or more of the first parameter to be processed, the duration of the first signal to be processed, the duration of the processing cycle, and the second parameter to be processed at least once, the minimum target fusion value obtained is taken as the adjusted target fusion value. For example, using Formula 12 as the optimization objective, Formula 5 as the first constraint, Formula 7 as the second constraint, and Formula 10 as the third constraint, the adjusted target fusion value can be obtained by solving the problem using a solver. The solver can be, for example, various solvers such as the Sloving Constraint Integer Programs (SCIP) solver.

[0098] It is understood that the above description is based on the first to third constraints. However, the disclosure is not limited thereto, and at least one constraint may include other constraints, which will be explained below.

[0099] In embodiments of this disclosure, at least one constraint may further include a fourth constraint. The fourth constraint may include: the signal period duration can be the sum of the first signal duration across multiple stages and the loss duration across multiple stages. For example, the fourth constraint may be implemented as follows:

[0100] (Formula Thirteen)

[0101] G s,j L can be the duration of the first signal in the j-th stage. s,j This can be the loss duration for the j-th stage. For example... Figures 3A to 3E As shown, j can be 4. The signal period duration can be the sum of the first signal duration of the four stages and the loss duration of the four stages.

[0102] In embodiments of this disclosure, at least one constraint may further include a fifth constraint. The fifth constraint may include: the sum of the first signal duration to be processed and the processing loss duration for the phase to be processed is the sum of the first signal duration and the loss duration corresponding to the phase to be processed across multiple stages. For example, the fifth constraint may be implemented as follows:

[0103] (Formula Fourteen)

[0104] G s,ij L can be the duration of the first signal corresponding to phase i in the j-th stage. s,ij G can be the loss duration corresponding to phase i in the j-th stage. i This can be the duration of the first signal to be processed. L i This can be set to the duration of pending loss processing. For example... Figures 3A to 3E As shown, if the first phase from west to east is the phase to be processed, the duration of the signal to be processed corresponding to the first phase is the duration of the first signal in the first stage, and the duration of the loss to be processed corresponding to the first phase is the duration of the loss in the first stage.

[0105] It is understood that in some other embodiments, turning may also be permitted simultaneously in the second phase. Therefore, the second phase may also include a first signal duration corresponding to the phase to be processed. In this case, the first signal duration to be processed can be the green light duration in the first phase and the green light duration in the second phase. The loss duration to be processed can be the loss duration in the first phase and the loss duration in the second phase.

[0106] It is understood that the optimization objective of this disclosure has been explained above in conjunction with Formulas 6, 8, 11, and 12. In the embodiments of this disclosure, the above-mentioned optimization objective can be obtained from the following initial objective:

[0107] (Formula Fourteen)

[0108] Initial objectives may include: optimizing the saturation D of each phase to approach the desired saturation De, thus minimizing the green light loss time. Additionally, initial objectives may include: maximizing the saturation D. max Minimum. For example, if the desired saturation cannot be achieved, the initial objective also includes the maximum saturation D. max Minimum.

[0109] As can be understood, the above text has explained how to obtain the adjusted target fusion value. The following will explain some methods for controlling the signal corresponding to the phase to be processed.

[0110] In some embodiments of operation S230, controlling the signal corresponding to the phase to be processed based on the first signal duration corresponding to the adjusted target fusion value includes controlling the signal corresponding to the phase to be processed based on the first signal duration and the signal period duration corresponding to the adjusted target fusion value. For example, by using formula 12 as the optimization objective, formula 5 as the first constraint, formula 7 as the second constraint, and formula 10 as the third constraint, and solving the problem using a solver, the adjusted target fusion value can be obtained. The first signal duration and the signal period duration corresponding to the adjusted target fusion value can be used to control the signal corresponding to the phase to be processed.

[0111] It is understood that the method of this disclosure has been described above, and the apparatus of this disclosure will be described below.

[0112] Figure 4 This is a block diagram of a traffic signal processing apparatus according to an embodiment of the present disclosure.

[0113] like Figure 4 As shown, the device 400 may include a determining module 410, an adjusting module 420, and a controlling module 430.

[0114] The determination module 410 is used to determine the phase to be processed among multiple phases based on the saturation of each of the multiple phases corresponding to the traffic lights.

[0115] In this embodiment of the disclosure, the saturation of the phase is determined based on the duration of a first signal corresponding to the phase.

[0116] The adjustment module 420 is used to adjust the first parameter to be processed according to at least one constraint condition to reduce the target fusion value and obtain the adjusted target fusion value.

[0117] In this embodiment of the disclosure, the target fusion value is determined based on a first parameter to be processed, and at least one constraint condition includes a first constraint condition, which includes the first parameter to be processed being greater than or equal to the saturation of the phase to be processed.

[0118] The control module 430 is used to control the signal corresponding to the phase to be processed according to the duration of the first signal corresponding to the adjusted target fusion value.

[0119] In some embodiments, the phase to be processed corresponds to the duration of a first signal to be processed and the duration of a processing cycle. The saturation of the phase to be processed is determined based on the ratio of the flow data corresponding to the phase to be processed to the first signal to be processed, where the first signal to be processed ratio is the ratio of the duration of the first signal to the duration of the processing cycle. A first constraint is implemented as follows: the difference between a first product and a second product is greater than or equal to a first preset value, where the first product is the product between the first parameter to be processed and the duration of the first signal to be processed, and the second product is the product between the flow data and the duration of the processing cycle. At least one constraint further includes a second constraint, which includes the first parameter to be processed being greater than or equal to the desired saturation of the phase to be processed.

[0120] In some embodiments, the adjustment module includes: a first adjustment submodule, configured to adjust a first parameter to be processed, a first signal duration to be processed, and a processing cycle duration according to at least one constraint.

[0121] In some embodiments, at least one constraint further includes a third constraint, the third constraint including: the second parameter to be processed is greater than or equal to the saturation of the phase to be processed, and the target fusion value is determined based on the first parameter to be processed and the second parameter to be processed. The adjustment module includes: a second adjustment submodule, configured to adjust the first parameter to be processed and the second parameter to be processed for at least one iteration based on at least one constraint, so as to reduce the target fusion value.

[0122] In some embodiments, the third constraint is implemented as follows: the difference between the third product and the fourth product is greater than or equal to the second preset value, the third product is the product between the second parameter to be processed and the duration of the first signal to be processed, and the fourth product is the product between the traffic data and the preset period duration.

[0123] In some embodiments, the second adjustment submodule is further configured to: in response to determining that the processing period duration of the target iteration cycle in at least one iteration cycle is less than a preset period duration, adjust the second processing parameter and the first processing signal duration of the target iteration cycle according to a third constraint condition to obtain the second processing parameter and the first processing signal duration of the target iteration cycle in subsequent iteration cycles.

[0124] In some embodiments, the second adjustment submodule is further configured to: in response to determining that the processing cycle duration of the previous iteration cycle of the target iteration cycle is greater than or equal to a preset cycle duration, adjust the first processing parameter, the second processing parameter, the first processing signal duration and the processing cycle duration of the previous iteration cycle according to the first constraint condition and the second constraint condition, so as to obtain the second processing parameter and the first processing signal duration of the target iteration cycle.

[0125] In some embodiments, the target fusion value is determined based on a first parameter to be processed, a second parameter to be processed, and a processing period duration.

[0126] In some embodiments, the target fusion value is determined based on a first processing parameter, a processed second processing parameter, and a processed processing cycle duration. The processed processing cycle duration is obtained by processing the processing cycle duration using the first processing parameter, and the processed second processing parameter is obtained by processing the second processing parameter using the second processing parameter.

[0127] In some embodiments, the saturation of the phase to be processed is the largest among multiple saturations of multiple phases.

[0128] In some embodiments, the adjusted target fusion value is the minimum target fusion value obtained after at least one adjustment of the first parameter to be processed.

[0129] In some embodiments, the control module is further configured to: control the signal corresponding to the phase to be processed based on the first signal duration and the signal period duration corresponding to the adjusted target fusion value.

[0130] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0131] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0132] In some embodiments, an electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor. The memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method provided according to this disclosure (e.g., method 200 described above).

[0133] In some embodiments, a non-transitory computer-readable storage medium stores computer instructions for causing a computer to perform a method provided in accordance with this disclosure (e.g., method 200 described above).

[0134] In some embodiments, a computer program product includes a computer program that, when executed by a processor, implements a method provided according to this disclosure (e.g., method 200 described above). The following will be combined with... Figure 5 Further explanation is needed.

[0135] Figure 5 A schematic block diagram of an example electronic device 500 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0136] like Figure 5 As shown, device 500 includes a computing unit 501, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 502 or a computer program loaded from storage unit 508 into random access memory (RAM) 503. RAM 503 may also store various programs and data required for the operation of device 500. The computing unit 501, ROM 502, and RAM 503 are interconnected via bus 504. Input / output (I / O) interface 505 is also connected to bus 504.

[0137] Multiple components in device 500 are connected to I / O interface 505, including: input unit 506, such as keyboard, mouse, etc.; output unit 507, such as various types of monitors, speakers, etc.; storage unit 508, such as disk, optical disk, etc.; and communication unit 509, such as network card, modem, wireless transceiver, etc. Communication unit 509 allows device 500 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0138] The computing unit 501 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above, such as traffic signal processing methods. For example, in some embodiments, the traffic signal processing method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on device 500 via ROM 502 and / or communication unit 509. When the computer program is loaded into RAM 503 and executed by the computing unit 501, one or more steps of the traffic signal processing method described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to perform traffic signal processing methods by any other suitable means (e.g., by means of firmware).

[0139] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard parts (ASSPs), systems-on-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0140] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0141] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory, read-only memory, erasable programmable read-only memory (EPROM) or flash memory, optical fiber, compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0142] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a cathode ray tube (CRT) monitor or a liquid crystal display (LCD)); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0143] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0144] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other.

[0145] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0146] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A traffic signal processing method, comprising: Based on the saturation of each of the multiple phases corresponding to the traffic lights, a phase to be processed is determined among the multiple phases. The saturation of the phase is determined based on the duration of the first signal corresponding to the phase. The phase to be processed corresponds to the duration of the first signal to be processed and the duration of the processing cycle. The saturation of the phase to be processed is determined based on the ratio of the flow data corresponding to the phase to be processed and the first signal to be processed. The first signal to be processed ratio is the ratio of the duration of the first signal to the duration of the processing cycle. According to at least one constraint, the first parameter to be processed is adjusted to reduce the target fusion value, thereby obtaining the adjusted target fusion value. The target fusion value is determined based on the first parameter to be processed. At least one constraint includes a first constraint, which includes the first parameter to be processed being greater than or equal to the saturation of the phase to be processed. The first constraint is implemented as follows: the difference between a first product and a second product is greater than or equal to a first preset value. The first product is the product between the first parameter to be processed and the duration of the first signal to be processed, and the second product is the product between the traffic data and the duration of the processing cycle. The signal corresponding to the phase to be processed is controlled based on the first signal duration corresponding to the adjusted target fusion value.

2. The method according to claim 1, wherein, At least one of the constraints further includes a second constraint, the second constraint including the first parameter to be processed being greater than or equal to the desired saturation of the phase to be processed.

3. The method according to claim 2, wherein, The step of adjusting the first parameter to be processed according to at least one constraint includes: The first parameter to be processed, the duration of the first signal to be processed, and the duration of the processing cycle are adjusted according to at least one of the constraints.

4. The method according to claim 2, wherein, At least one of the constraints further includes a third constraint, the third constraint including: the second parameter to be processed is greater than or equal to the saturation of the phase to be processed, and the target fusion value is determined based on the first parameter to be processed and the second parameter to be processed; The step of adjusting the first parameter to be processed according to at least one constraint to reduce the target fusion value includes: Based on at least one of the constraints, the first parameter to be processed and the second parameter to be processed are adjusted for at least one iteration to reduce the target fusion value.

5. The method according to claim 4, wherein, The third constraint is implemented as follows: the difference between the third product and the fourth product is greater than or equal to the second preset value. The third product is the product between the second parameter to be processed and the duration of the first signal to be processed, and the fourth product is the product between the traffic data and the preset period duration.

6. The method according to claim 4, wherein, The step of adjusting the first parameter to be processed and the second parameter to be processed for at least one iteration based on at least one of the constraints includes: In response to determining that the processing period duration of the target iteration cycle in at least one of the iteration cycles is less than a preset period duration, the second processing parameter and the first processing signal duration of the target iteration cycle are adjusted according to the third constraint condition to obtain the second processing parameter and the first processing signal duration of the subsequent iteration cycle of the target iteration cycle.

7. The method according to claim 6, wherein, The step of adjusting the first parameter to be processed and the second parameter to be processed for at least one iteration based on at least one of the constraints further includes: In response to determining that the processing cycle duration of the previous iteration of the target iteration is greater than or equal to a preset cycle duration, the first processing parameter, the second processing parameter, the first processing signal duration, and the processing cycle duration of the previous iteration are adjusted according to the first constraint and the second constraint to obtain the second processing parameter and the first processing signal duration of the target iteration.

8. The method according to claim 4, wherein, The target fusion value is determined based on the first parameter to be processed, the second parameter to be processed, and the processing period duration.

9. The method according to claim 4, wherein, The target fusion value is determined based on at least one of the processed second parameter to be processed and the processed processing cycle duration, as well as the first parameter to be processed. The processed processing cycle duration is obtained by processing the processing cycle duration using the first processing parameter, and the processed second parameter to be processed is obtained by processing the second parameter to be processed using the second processing parameter.

10. The method according to claim 1, wherein, The saturation of the phase to be processed is the largest among the multiple saturations of the multiple phases.

11. The method according to claim 1, wherein, The adjusted target fusion value is the minimum target fusion value obtained after at least one adjustment of the first parameter to be processed.

12. The method according to claim 1, wherein, The step of controlling the signal corresponding to the phase to be processed based on the first signal duration corresponding to the adjusted target fusion value includes: The signal corresponding to the phase to be processed is controlled based on the first signal duration and the signal period duration corresponding to the adjusted target fusion value.

13. A traffic signal processing device, comprising: The determination module is used to determine the phase to be processed among multiple phases based on the saturation of each phase corresponding to the traffic light. The saturation of the phase is determined based on the duration of the first signal corresponding to the phase. The phase to be processed corresponds to the duration of the first signal to be processed and the duration of the processing cycle. The saturation of the phase to be processed is determined based on the ratio of the flow data corresponding to the phase to be processed and the first signal to be processed. The first signal to be processed ratio is the ratio of the duration of the first signal to the duration of the processing cycle. An adjustment module is used to adjust a first parameter to be processed according to at least one constraint condition to reduce the target fusion value and obtain an adjusted target fusion value. The target fusion value is determined based on the first parameter to be processed. At least one constraint condition includes a first constraint condition, which includes the first parameter to be processed being greater than or equal to the saturation of the phase to be processed. The first constraint condition is implemented as follows: the difference between a first product and a second product is greater than or equal to a first preset value. The first product is the product between the first parameter to be processed and the duration of the first signal to be processed, and the second product is the product between the traffic data and the duration of the processing cycle. The control module is used to control the signal corresponding to the phase to be processed according to the first signal duration corresponding to the adjusted target fusion value.

14. The apparatus according to claim 13, wherein, At least one of the constraints further includes a second constraint, the second constraint including the first parameter to be processed being greater than or equal to the desired saturation of the phase to be processed.

15. The apparatus according to claim 13, wherein, The adjustment module includes: The first adjustment submodule is used to adjust the first parameter to be processed, the duration of the first signal to be processed, and the duration of the processing period according to at least one of the constraints.

16. The apparatus according to claim 14, wherein, At least one of the constraints further includes a third constraint, the third constraint including: the second parameter to be processed is greater than or equal to the saturation of the phase to be processed, and the target fusion value is determined based on the first parameter to be processed and the second parameter to be processed; The adjustment module includes: The second adjustment submodule is used to adjust the first parameter to be processed and the second parameter to be processed for at least one iteration based on at least one of the constraints, so as to reduce the target fusion value.

17. The apparatus according to claim 16, wherein, The third constraint is implemented as follows: the difference between the third product and the fourth product is greater than or equal to the second preset value. The third product is the product between the second parameter to be processed and the duration of the first signal to be processed, and the fourth product is the product between the traffic data and the preset period duration.

18. An electronic device comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 12.

19. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 1 to 12.

20. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 1 to 12.

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