WO2020133453A1 - 一种控制交通信号灯的方法及装置 - Google Patents

一种控制交通信号灯的方法及装置 Download PDF

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Publication number
WO2020133453A1
WO2020133453A1 PCT/CN2018/125727 CN2018125727W WO2020133453A1 WO 2020133453 A1 WO2020133453 A1 WO 2020133453A1 CN 2018125727 W CN2018125727 W CN 2018125727W WO 2020133453 A1 WO2020133453 A1 WO 2020133453A1
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WIPO (PCT)
Prior art keywords
vehicle
target
road
level
target vehicle
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PCT/CN2018/125727
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English (en)
French (fr)
Inventor
石磊
张宇
林伟
冯威
刘晓彤
Original Assignee
驭势科技（北京）有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Application filed by 驭势科技（北京）有限公司 filed Critical 驭势科技（北京）有限公司
Priority to EP18944470.6A priority Critical patent/EP3905217A4/en
Priority to PCT/CN2018/125727 priority patent/WO2020133453A1/zh
Priority to US17/419,639 priority patent/US11302186B2/en
Priority to CN201910007978.3A priority patent/CN109598952B/zh
Publication of WO2020133453A1 publication Critical patent/WO2020133453A1/zh

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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/07—Controlling traffic signals
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/07—Controlling traffic signals
    • G08G1/087—Override of traffic control, e.g. by signal transmitted by an emergency vehicle
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • G06V20/584—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of vehicle lights or traffic lights
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/015—Detecting movement of traffic to be counted or controlled with provision for distinguishing between two or more types of vehicles, e.g. between motor-cars and cycles
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/095—Traffic lights
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/08—Detecting or categorising vehicles

Definitions

  • the invention relates to the field of intelligent driving, in particular to the field of V2X in the field of intelligent driving.
  • traffic control is very important, such as setting traffic lights on the road.
  • traffic lights are red, the vehicle stops.
  • a red light is not necessary. Therefore, a method of intelligently controlling traffic lights is very important and has important practicality.
  • the purpose of the present application is to provide a method for intelligently controlling traffic lights, which can intelligently control traffic lights according to specific situations at specific times. Thereby, traffic flow is controlled more reasonably, and people’s travel is more efficient.
  • An aspect of the present application provides an apparatus for controlling a traffic signal light, including at least one storage device, the storage device including a set of instructions; and at least one processor in communication with the at least one storage device, wherein, when executing the When grouping instructions, the at least one processor: acquires the vehicle class of the target vehicle on the first road, the vehicle class is determined by the type of the target vehicle and the purpose of travel; according to the vehicle class of the target vehicle To perform the target operation.
  • Another aspect of the present application provides a method of controlling a traffic signal lamp, the method comprising: a receiving device acquiring a vehicle class of a target vehicle on a first road, the vehicle class being determined by the type of the target vehicle and the purpose of travel ; According to the vehicle class of the target vehicle, the receiving device performs the target operation.
  • the computer program product includes instructions that cause the computing device to: obtain the vehicle class of the target vehicle on the first road, the vehicle class being determined by the type of the target vehicle and the purpose of travel; based on the target Vehicle level of the vehicle to perform the target operation.
  • FIG. 1 shows an application scenario diagram for controlling traffic lights according to some embodiments of the present application
  • FIG. 2 shows an exemplary data processing device according to some embodiments of the present application on which a method for controlling traffic lights can be implemented;
  • FIG. 3 is a block diagram of an exemplary vehicle with autonomous driving capabilities according to some embodiments of the present disclosure
  • FIG. 4 shows a flowchart of a method for controlling traffic lights according to some embodiments of the present application.
  • An aspect of the present application provides a device for controlling traffic lights.
  • the device may communicate with a vehicle (such as an autonomous driving vehicle) passing through traffic lights to obtain the vehicle class of the vehicle, and then decide whether to turn on the green light for the vehicle according to the vehicle class of the target vehicle. For example, when the vehicle is an on-duty fire truck, its vehicle level overrides any surrounding traffic conditions, so the device automatically turns on the green light for the fire truck.
  • a vehicle such as an autonomous driving vehicle
  • the communication between the device and the vehicle can be applied in a 4G or lower network environment.
  • the invention in this application has high requirements on network delay and data transmission speed, it is more suitable for 5G network environment.
  • the data transmission rate of 4G is on the order of 100Mbps
  • the delay is 30-50ms
  • the maximum number of connections per square kilometer is on the order of 10,000
  • the mobility is about 350KM/h
  • the transmission rate of 5G is on the order of 10Gbps
  • the delay is 1ms
  • the maximum number of connections per square kilometer is on the order of millions
  • the mobility is about 500km/h.
  • 5G has higher transmission rates, shorter delays, more connections per square kilometer, and higher speed tolerance.
  • Another advantage of 5G is the change of transmission path.
  • the device can be directly transmitted between devices without passing through the base station. Therefore, although the present invention is also applicable to the 4G environment, running in the 5G environment will result in better technical performance and reflect higher commercial value.
  • autonomous vehicle may refer to an environment that can perceive its environment and automatically perceive, judge, and then make an external environment without human input (or, driver, pilot, etc.) and/or intervention Decision making vehicle.
  • autonomous vehicle and “vehicle” can be used interchangeably.
  • autonomous driving may refer to the ability to make intelligent judgments on the surrounding environment and navigate without input by anyone (eg, driver, pilot, etc.).
  • the flowchart used in the present disclosure shows the operations implemented by the system according to some embodiments in the present disclosure. It should be clearly understood that the operations of the flowchart can be implemented out of order. Instead, the operations can be performed in reverse order or simultaneously. In addition, one or more other operations can be added to the flowchart. One or more operations can be removed from the flowchart.
  • the positioning technology used in this disclosure may be based on Global Positioning System (GPS), Global Navigation Satellite System (GLONASS), Compass Navigation System (COMPASS), Galileo Positioning System, Quasi-Zenith Satellite System (QZSS), Wireless Fidelity (WiFi) Positioning technology, etc., or any combination thereof.
  • GPS Global Positioning System
  • GLONASS Global Navigation Satellite System
  • COMPASS Compass Navigation System
  • Galileo Positioning System Galileo Positioning System
  • QZSS Quasi-Zenith Satellite System
  • WiFi Wireless Fidelity
  • An aspect of the present disclosure relates to a method of controlling traffic lights and a device employing the method.
  • the method may include: the receiving device first obtains the vehicle class of the target vehicle, and then determines whether to give the vehicle a green light at the traffic light according to the vehicle class.
  • This system automatically executes this method, on the one hand, it improves the traffic efficiency of the traffic flow at the intersection, and on the other hand, it also takes into account the smoothness of the special vehicle passing through the intersection.
  • FIG. 1 shows an application scenario diagram for controlling traffic lights according to some embodiments of the present application.
  • the road 130 is a north-south direction
  • the road 140 is an east-west direction.
  • Each road may include multiple lanes, for example, the north-south road 130 may include a straight lane 131 and a left-turn lane 132.
  • the road 130 intersects the road 140, and the intersection is the intersection 150.
  • the intersection 150 has four traffic lights A, B, C, and D. Among them, the A light controls the traffic flow of the road 130 from south to north, the B light controls the traffic flow of the road 130 from north to south, the C light controls the traffic flow of the road 140 from west to east, and the D light controls the traffic flow of the road 140 from east to west.
  • the center of the intersection is marked with a point O.
  • the position of point O is related to the position of the traffic lights at the intersection.
  • the center of the position of all traffic lights at the intersection may be point O.
  • the vehicle 120 travels on the road 130. Ahead of the intersection 150.
  • the vehicle 120 may be any vehicle legally traveling on the road 130.
  • the vehicle 120 may be a motor vehicle or a non-motor vehicle.
  • the vehicle 120 may include any one of fire trucks, ambulances, police cars, private cars, buses, taxis, trucks, motorcycles, electric vehicles, bicycles, and balancing vehicles.
  • the travel of the vehicle 120 is restricted by the traffic signal A corresponding to the intersection 150.
  • the corresponding traffic signal A is a red light
  • the vehicle 120 needs to stop traveling; when the corresponding traffic signal A is a green light, the vehicle 120 can go forward.
  • traffic signal lights at intersections are taken as examples. It should be understood that the technical solution disclosed in the present application is not only applicable to intersections, but also applicable to traffic signal lights at various intersections such as three-forked intersections, T-shaped intersections, five-forked intersections and roundabouts. When the type of intersection changes, the technical solution disclosed in this application can be adapted to change without requiring creative efforts by those skilled in the art.
  • the target area 110 may be determined according to the position of the traffic lights at the intersection.
  • the target area facilitates execution of the method for controlling traffic signals disclosed in this application, as described in detail below.
  • the vehicle 120 When the vehicle 120 travels on the road 130 in the north-south direction, it is restricted by the traffic light A in the north-south direction. More specifically, when the vehicle 120 travels to the straight lane 131 on the road 130 in the north-south direction, it is restricted by the straight-forward or left-turn traffic signal in the north-south direction signal A.
  • the vehicle 120 (for example, an autonomous driving vehicle) or its carrying equipment (for example, an automatic driving control device, a mobile phone client) can interact with the receiving device 160, and the receiving device 160 can control the transformation of the signal lights A, B, C, and D Or, interact with the signal light control device, and then indirectly control the signal lights A, B, C, and D by issuing instructions to the signal light control device, thereby affecting the restriction of the traffic lights at the intersection on the vehicle 120.
  • the vehicle 120 may issue a request to the receiving device 160 to change the traffic signal, and when the request is passed, the restriction of the traffic signal on the vehicle 120 changes.
  • the method and device for controlling traffic lights refer to the description of FIG. 3.
  • the device 160 may be installed on any of the traffic lights A, B, C, and D, or may be independently installed at intersections or other locations, as long as the device controlling the traffic lights can interact with the vehicle 120 and the traffic lights.
  • the interaction can be achieved through near field communication, wireless network, mobile network (such as 3G, 4G, 5G).
  • FIG. 2 shows an exemplary data processing device according to some embodiments of the present application on which a method of controlling traffic lights can be implemented.
  • the data processing device 200 may serve as the receiving device 160 for performing the method for controlling traffic lights disclosed in this application.
  • the data processing device 200 may be used to execute the process 400.
  • the data processing device 200 may include a COM port 250 connected to a network connected thereto to facilitate data communication.
  • the data processing device 200 may also include a processor 220 in the form of one or more processors for executing computer instructions.
  • Computer instructions may include, for example, routines, programs, objects, components, data structures, processes, modules, and functions that perform specific functions described herein.
  • the processor 220 may receive a request from the vehicle 120, the request being to change the traffic signal light to a green light.
  • the processor 220 may determine the vehicle class of the vehicle 120, which is determined by the type of the vehicle 120 and the purpose of travel; and determine whether to pass the request according to the vehicle class.
  • the processor 220 may include one or more hardware processors, such as a microcontroller, microprocessor, reduced instruction set computer (RISC), application specific integrated circuit (ASIC), application-specific instruction-set Processor (ASIP), central processing unit (CPU), graphics processing unit (GPU), physical processing unit (PPU), microcontroller unit, digital signal processor (DSP), field programmable gate array (FPGA), advanced RISC machine (ARM), programmable logic device (PLD), any circuit or processor capable of performing one or more functions, etc., or any combination thereof.
  • RISC reduced instruction set computer
  • ASIC application specific integrated circuit
  • ASIP application-specific instruction-set Processor
  • CPU central processing unit
  • GPU graphics processing unit
  • PPU physical processing unit
  • DSP digital signal processor
  • FPGA field programmable gate array
  • ARM advanced RISC machine
  • PLD programmable logic device
  • Exemplary data processing device 200 may include an internal communication bus 210, program storage, and different forms of data storage (eg, magnetic disk 270, read only memory (ROM) 230, or random access memory (RAM) 240) for processing by a computer And/or various data files sent. Exemplary data processing device 200 may also include program instructions stored in ROM 230, RAM 240, and/or other types of non-transitory storage media to be executed by processor 220. The method and/or process of the present application may be implemented as program instructions.
  • the data processing device 200 also includes an I/O component 260 that supports input/output between the computer and other components (eg, user interface elements). The data processing device 200 can also receive programming and data through network communication.
  • the data processing device 200 in this application may further include multiple processors. Therefore, the operations and/or method steps disclosed in the present application may be performed by one processor as described in the present disclosure, or may be performed by multiple processors.
  • the processors execute jointly. For example, if the processor 220 of the data processing device 200 executes steps A and B in this application, it should be understood that steps A and B may also be executed jointly or separately by two different processors in information processing (for example, The first processor performs step A, the second processor performs step B, or the first and second processors perform steps A and B together.
  • FIG. 3 is a block diagram of an exemplary vehicle with autonomous driving capabilities according to some embodiments of the present disclosure.
  • the vehicle 120 shown in FIG. 1 may be the vehicle 300 or other vehicles with or without an automatic driving function.
  • the vehicle 300 with automatic driving capability may include a control module, multiple sensors, a communication module, a memory, a command module, and a controller area network (CAN) and an actuator.
  • CAN controller area network
  • the actuator may include, but is not limited to, drive execution of an accelerator, an engine, a braking system, and a steering system (including steering of tires and/or operation of turn signals).
  • the plurality of sensors may include various internal and external sensors that provide data to the vehicle 300.
  • the plurality of sensors may include vehicle component sensors and environment sensors.
  • the vehicle component sensor is connected to the actuator of the vehicle 300, and can detect the operating state and parameters of various components of the actuator.
  • the environmental sensor allows the vehicle to understand and potentially respond to its environment in order to assist the autonomous vehicle 300 in navigation, path planning, and to ensure the safety of passengers and people or property in the surrounding environment.
  • the environmental sensor can also be used to identify, track and predict the movement of objects, such as pedestrians and other vehicles.
  • the environment sensor may include a position sensor and an external object sensor.
  • the position sensor may include a GPS receiver, an accelerometer, and/or a gyroscope, a receiver.
  • the position sensor may sense and/or determine more than one geographic location and orientation of the autonomous vehicle 300. For example, determine the latitude, longitude and altitude of the vehicle.
  • the external object sensor can detect objects outside the vehicle, such as other vehicles, obstacles in the road, traffic signals, signs, trees, etc.
  • External object sensors may include laser sensors, radar, cameras, sonar, and/or other detection devices.
  • the communication module may be configured as a module for interactive communication between the autonomous vehicle and the external environment.
  • the communication module can help the control module to communicate wirelessly with external objects.
  • the communication module may include an antenna and a power amplifier circuit.
  • the control module may process information and/or data related to vehicle driving (for example, automatic driving).
  • the control module may be configured to drive the vehicle autonomously.
  • the control module may output multiple control signals. Multiple control signals may be configured to be received by one or more electronic control units (ECUs) to control the driving of the vehicle.
  • the control module may determine the reference path and one or more candidate paths based on the environmental information of the vehicle.
  • control module may include one or more central processors (eg, single-core processors or multi-core processors).
  • the control module may include a central processing unit (CPU), application-specific integrated circuit (ASIC), application-specific instruction-set processor (ASIP), graphics Processing unit (graphics, processing unit, GPU), physical processing unit (physics, processing unit, PPU), digital signal processor (DSP), field programmable gate array (field programmable gate array, FPGA), programmable logic Device (programmable logic, device, PLD), controller, microcontroller unit, reduced instruction-set computer (RISC), microprocessor (microprocessor), etc., or any combination thereof.
  • the control module can also perform wireless communication with the external object through the communication module.
  • the control module may interact with the receiving device 160 to inform the vehicle class of the autonomous vehicle and/or issue a limited request for traffic lights, and so on.
  • the command module receives the information from the control module and converts it into a command to drive the actuator to the Controller Area Network (Controller Area Network) CAN bus.
  • the control module sends the driving strategy (acceleration, deceleration, turning, etc.) of the autonomous vehicle 200 to the instruction module, and the instruction module receives the driving strategy and converts it into a driving instruction for the actuator (for throttle, braking Drive instructions for the mechanism and steering mechanism).
  • the instruction module then sends the instruction to the execution mechanism via the CAN bus.
  • the execution of the instruction by the actuator is detected by the vehicle component sensor and fed back to the control module, thereby completing the closed-loop control and driving of the automatic driving vehicle 300.
  • FIG. 4 shows a flowchart of a method for controlling traffic lights according to some embodiments of the present application.
  • the process 400 may be implemented as a set of instructions in a non-transitory storage medium in the data processing device 200 (eg, the receiving device 160).
  • the data processing device 200 (receiving device 160) can execute the set of instructions and can execute the steps in the process 400 accordingly to control the traffic lights.
  • the data processing apparatus 200 may acquire the vehicle level of the target vehicle 120 on the first road.
  • the first road may be a road in a certain direction, for example, a road 130 in a north-south direction or a road 140 in an east-west direction, or may refer to a specific lane in a road in a certain direction, for example, a straight lane 131 or a left-turn lane 132.
  • the vehicle level is determined by the type of the target vehicle 120 and the purpose of travel.
  • Types of transportation include fire trucks, ambulances, police cars, private cars, buses, taxis, trucks, etc.
  • the purpose of travel may include emergency rescue, transportation of patients, police (hunting down fugitives), travel, commuting, public transportation, and transportation of goods.
  • fire-fighting vehicles for emergency rescue and disaster relief ambulances for transporting patients, and police vehicles for pursuing fugitives have higher ranks; vehicles without transportation for urgent transportation purposes have lower ranks, for example, private cars for commuting, ordinary cargo Side truck.
  • the determination of the type of vehicle, the purpose of travel, and the vehicle class described above are only schematic, and the determination of the vehicle class may change according to specific circumstances.
  • the vehicle level of the vehicle may be determined by factors other than the type of vehicle and the purpose of travel, such as time. For example, a private car that gets off work at 5 pm and a private car that gets off work at two in the morning can have different vehicle ratings.
  • the target vehicle 120 can actively send its own vehicle level directly to the data processing device 200 (reception device 160).
  • the target vehicle 120 may send the vehicle level information one or more times to the data processing device 200 (reception device 160). Accordingly, the data processing device 200 can receive one or more vehicle level information sent by the target vehicle 120. For example, in the case where it is ensured that the data processing device 200 (receiving device 160) successfully receives, the target vehicle 120 sends vehicle level information to the data processing device 200 (receiving device 160) only once. In some special cases, the target vehicle 120 may also send multiple vehicle level information to the data processing device 200 (reception device 160).
  • the target vehicle 120 may again send the data processing device 200 (receiving device) 160) Send vehicle level.
  • the data processing device 200 may obtain the vehicle rank of the target vehicle 120 in the following manner:
  • the data processing device 200 may first receive a request from the target vehicle 120, the request being to change the traffic signal light to a green light.
  • the request from the vehicle can be a request from the vehicle itself (for example, the autonomous vehicle 120), or it can be a device carried by the vehicle (for example, the control module of the autonomous car 120 or the mobile phone customer of the passenger on the autonomous car 120 End).
  • the vehicle 120 may send one or more requests to the data processing device 200 (reception device 160). Accordingly, the data processing device 200 (receiving device 160) can receive one or more requests issued by the vehicle. Generally, the data processing device 200 receives only one request from the vehicle. In some special cases, the data processing device 20 may receive multiple requests from the vehicle. For example, when the vehicle level of the vehicle changes, the data processing device 200 may receive the request from the target vehicle again.
  • the data processing device 200 may receive the request issued by the target vehicle within the target area.
  • the target area is the area L1 and/or L2 within the preset range of the traffic signal at the intersection, for example, the area within 20 meters of the traffic signal at the intersection. Since the position of the traffic signal in the intersection is close to the center (point O) of the intersection, the target area may also be an area within the preset range of point O.
  • the data processing device 200 may determine the vehicle class of the target vehicle 120.
  • the data processing device 200 may determine multiple dimensions including the type of vehicle and the purpose of travel, and then establish a model containing the multiple dimensions and determine the vehicle class of the vehicle based on this.
  • the data processing model may set the vehicle class of the fire truck and the ambulance transporting patients to the maximum vehicle class, for example, eleven; the police car of the fugitive hunter is set to a larger vehicle class, for example Level 10: The private car's vehicle class that is off duty at normal times is set to a smaller vehicle class, such as class four.
  • the data processing apparatus 200 may perform a target operation according to the vehicle class of the target vehicle.
  • the target operation in step 420 may include: the data processing device 200 (receiving device 160) determines whether the vehicle level of the target vehicle is less than a first threshold; when the vehicle level of the target vehicle 120 When it is not less than the first threshold, it indicates that the corresponding traffic signal light will turn on the green light.
  • the first threshold may be a preset level of traffic lights.
  • Said instructing the corresponding traffic signal to turn on the green light includes setting the corresponding traffic signal in the direction of travel of the target vehicle to be a green light, and may also include setting other conflicting traffic lights to be red lights.
  • the A signal light corresponding to the lane of the target vehicle 120 in FIG. 1 may be set to a green light.
  • the other conflicting traffic lights may be traffic lights that would prevent the target vehicle 120 from passing the intersection 150.
  • the turn-on time may be the length of time the vehicle 120 drives through traffic lights (or intersections), or a predetermined length of time.
  • the first threshold is less than the maximum vehicle level and greater than the minimum vehicle level.
  • the first threshold may be nine levels.
  • the vehicle ranks of fire fighting vehicles (vehicle grade 11), ambulances transporting patients (vehicle grade 11), and police vehicles chasing fugitives (vehicle grade 10) If they are not less than (or greater than or equal to) the first threshold, the data processing device 200 may instruct the corresponding traffic signal to turn on the green light.
  • the target operation in step 420 may further include: when the vehicle level of the target vehicle 120 is not less than the first threshold, determining whether the vehicle level of the target vehicle is greater than the target area The maximum value of the vehicle class of all vehicles on the second road (such as the road 140 in FIG. 1); when the vehicle class of the target vehicle is greater than the maximum value of the vehicle class of all vehicles on the second road in the target area, The data processing device 200 (receiving device 160) instructs the corresponding traffic signal to turn on the green light; when the vehicle level of the target vehicle is less than the maximum value of the vehicle level of all vehicles on the second road in the target area, the data processing device 200 ( The receiving device 160) does not set any traffic lights for the target vehicle.
  • the data processing device 200 instructs the corresponding traffic signal A to turn on the green light, and at the same time, other roads are closed by other signal lights B, C, and D, so that the police car 120 can smoothly pass the intersection 150.
  • the data processing device 200 (receiving device 160) will give priority to the firetruck road with a higher vehicle rank instead of The traffic lights 120 will be given higher priority and the traffic light settings will be changed. Therefore, the data processing device 200 (receiving device 160) will instruct the corresponding traffic light A to turn on the red light.
  • the corresponding traffic lights referenced when the target vehicle 120 is traveling in the target area are different from the traffic lights referenced when the vehicle on the second road is traveling. That is, the target vehicle and the vehicle on the second road cannot travel at the same time.
  • the first road and the second road may be different roads or different lanes of the same road.
  • the first road is a road 130 in a north-south direction
  • the second road is a road 140 in an east-west direction.
  • the first road is a straight lane 131
  • the second road is a left-turn lane 132.
  • the target operation in step 420 may further include: the data processing device 200 (receiving device 160) determines whether the vehicle level of the target vehicle is less than a first threshold; when the vehicle level of the target vehicle When it is less than the first threshold, it is determined whether the target vehicle is greater than the road level of the second road; when the target vehicle is greater than the road level of the second road, the data processing device 200 (reception device 160) instructs The corresponding traffic signal light turns on the green light; when the target vehicle is a road level no greater than the second road, the traffic signal light is instructed to work according to the predetermined settings.
  • the road level of the road is determined by the number and vehicle levels of all vehicles on the road (for example, the second road) in the target area.
  • the road grade during the commuting peak period is higher than the road grade at the time point outside the peak period.
  • the higher the vehicle level of all vehicles on the road (eg, the second road) in the target area the higher the road level. For example, when there are on-duty fire trucks and ambulances on the road, the road grade of the corresponding road section will be upgraded.
  • the data processing device 200 may determine multiple dimensions including the number of vehicles and the vehicle class of the vehicle, and then build a model containing the multiple dimensions and determine the road class of the road accordingly.
  • the target vehicle 120 shown in FIG. 1 is a private car returning home from get off work.
  • the vehicle level is four levels, which is less than the first threshold of nine levels.
  • the data processing device 200 (reception device 160) will say that the traffic light A is set to green, and set the traffic lights of other intersections Set to red.
  • the data processing device 200 instructs the current traffic light to operate according to the predetermined settings, that is, whether it is a red light or a red light, and whether it is a green light or a green light.
  • the target operation in step 420 may further include: when the vehicle level of the target vehicle is less than the first threshold, determining whether the target vehicle is greater than all of the second roads in the target area The maximum value of the vehicle grade of the vehicle; when the target vehicle is greater than the maximum value of the vehicle grade of all vehicles on the second road in the target area, determine whether the target vehicle is greater than the road grade of the second road.
  • the data processing device 200 can determine whether the vehicle level of the target vehicle is greater than the road of the second road Before classifying, first determine whether the vehicle class of the target vehicle is greater than the maximum value of the vehicle class of all vehicles on the second road in the target area. When the target vehicle is not greater than the maximum value of the vehicle class of all vehicles on the second road in the target area, the data processing device 200 may determine that the target vehicle is necessarily not greater than the road class of the second road.
  • the target operation in step 420 may further include: the data processing device 200 performs speed guidance on the target vehicle.
  • the data processing device 200 (receiving device 160) instructs the corresponding traffic signal A to perform a traffic light change before or at the same time, according to the distance and speed of the target vehicle 120 at the same intersection 150, according to the established strategy
  • the vehicle speed guidance for the target vehicle 120 is made.
  • the established strategy is to let the fire trucks arrive at the scene of the fire as soon as possible.
  • the time for the fire truck to reach the intersection at 150 o'clock must be slightly longer than this time, so its maximum speed and acceleration are limited.
  • the data processing device 200 acquires the vehicle class of the firetruck and determines that the corresponding traffic signal A should be instructed to turn on the green light, it also instructs the firetruck to speed up to the traffic conditions of the road 130 and the intersection 150. Maximum speed.
  • the data processing device 200 determines that the corresponding traffic signal A should be instructed to turn on green, but because the private car is not in an emergency, the established strategy may be Inform private cars to drive through the intersection at a constant speed.
  • the data processing device 200 will notify the private car to drive at a constant speed, and only when the private car sets a predetermined distance away from the intersection, only the traffic light A turns green.
  • the data processing device 200 determines that the private car will not change the existing rhythm of the traffic lights
  • the data processing device 200 will estimate the time when the private car arrives at the intersection.
  • the traffic light status of the traffic light A at the time it indicates whether the private car should drive at a constant speed, accelerate or decelerate.
  • the target operation in step 420 may further include: acquiring the driving route of the target vehicle, and notifying the next traffic light on the driving route by microwave, wireless communication, etc. of the vehicle level of the target vehicle And the estimated time of arrival, so that the next traffic light can be planned in advance (turn on the green light or not, time, duration, etc.).
  • the target vehicle may be any vehicle or vehicles driving on the first road.
  • the data processing device 200 may separately determine the vehicle ranks of the plurality of vehicles, and then process the request of the vehicle with the largest vehicle rank.
  • the number of second roads may be one or more than two (marked as sub-second roads).
  • the second road may include two sub-second roads, respectively a left turn lane 132 and an east-west road 140.
  • the data processing device may comprehensively consider the road grades of the two sub-second roads to determine the road grade of the second road.
  • the data processing device 200 may use the weighted average, maximum value, etc. of the road levels of the two sub-second roads as the road levels of the second road.
  • the process 400 may further include: when the target vehicle enters the target area, determining that the traffic signal light is a red light. That is, before the data processing device 200 receives the request of the target vehicle, the data processing device 200 can determine in advance the state where the vehicle enters the traffic signal of the target area. For example, the data processing device 200 may determine in advance the state where the vehicle enters the traffic signal of the target area through information such as the vehicle position, speed, and destination address sent by the target vehicle. When it is predicted that the state of the target vehicle passing through the traffic lights is a green light, the data processing device 200 does not accept the request sent by the vehicle.
  • the process 400 may further include: when the traffic signal referenced when the target vehicle travels in the target area is a red light or a green light for a continuous duration greater than a second threshold, the traffic signal referenced when the target vehicle travels in the target area Change to green or red light.
  • the second threshold is the continuous length of time that the traffic lights remain red or green. This is because, under certain special circumstances, the vehicles on a certain road are always very large or small due to their vehicle grades. As a result, the traffic lights referenced by the vehicles while driving continue to be green or red, which will destroy the traffic. order.
  • the traffic signal light referenced by a vehicle on a certain road is a red light or a green light for a continuous duration greater than a second threshold
  • the traffic referenced by the target vehicle in the target area when driving The signal light turns green or red.
  • the traffic volume in the target area L2 is always much larger than the traffic volume in the target area L1.
  • the data processing device 200 sets the red light time of the traffic lights A, B to a second threshold, such as 2 minutes.
  • the data processing device 200 (reception device 160) can also set the green light time of the traffic lights A and B, for example, 40 seconds.
  • the second threshold may be determined according to actual traffic conditions at the intersection, or may be manually set according to experience.
  • one aspect of the present disclosure relates to a method of controlling traffic lights and a traffic signal system employing this method.
  • the method may include: the receiving device first obtains the vehicle class of the target vehicle, and then determines whether to give the vehicle a green light at the traffic light according to the vehicle class.
  • This system automatically executes this method, on the one hand, it improves the traffic efficiency of the traffic flow at the intersection, and on the other hand, it also takes into account the smoothness of the special vehicle passing through the intersection.
  • a number expressing the quantity or nature used to describe and claim certain embodiments of the present application should be understood as modified in some cases by the terms “about”, “approximately”, or “substantially.” For example, unless stated otherwise, "about”, “approximately”, or “substantially” may represent a ⁇ 20% change in the value it describes. Therefore, in some embodiments, the numerical parameters listed in the written description and the appended claims are approximate values, which may vary depending on the desired properties sought by the particular embodiment. In some embodiments, the numerical parameter should be interpreted according to the number of significant digits reported and by applying ordinary rounding techniques. Although some embodiments that illustrate the present application list a wide range of numerical ranges and parameters are approximate values, specific examples list the most accurate numerical values possible.

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Abstract

一种控制交通信号灯的方法和采用此方法的交通信号灯系统。方法包括：接收装置首先获取目标交通工具的车辆等级（410），然后根据车辆等级决定是否给车辆在交通灯处开绿灯（420）。由于对网络时延和数据的传输速度要求较高，因此虽然披露的技术可以应用在4G网络环境，但是更适合5G网络环境。

Description

一种控制交通信号灯的方法及装置 技术领域
本发明涉及智能驾驶领域，尤其涉及智能驾驶领域中的V2X领域。
背景技术
随着人类社会发展的进步，汽车已经成为人类出行的重要工具。在给人类生活带来便利的同时，由汽车引发的交通堵塞也给人们带来了困扰。
所以交通管控是十分重要的，例如道路上设置交通信号灯。当交通信号灯为红灯时，车辆停止前行。但是某些情况下，比如，道路附近没有其他行驶车辆，红灯是没有必要的。因此一种智能控制交通信号灯的方法是十分重要的，且具有很重要的实用性。
发明内容
本申请的目的在于提供一种智能控制交通信号灯的方法，该方法可以根据特定时刻的特定情况智能的控制交通信号灯。从而更加合理地控制交通流，使人们的出行更加高效。
本申请一方面提供一种控制交通信号灯的装置，包括至少一个存储设备，所述存储设备包括一组指令；以及与所述至少一个存储设备通信的至少一个处理器，其中，当执行所述一组指令时，所述至少一个处理器：获取第一道路上的目标交通工具的车辆等级，所述车辆等级由所述目标交通工具的类型和出行目的确定；根据所述目标交通工具的车辆等级，执行目标操作。
本申请另一方面提供一种控制交通信号灯的方法，所述方法包括：接收装置获取第一道路上的目标交通工具的车辆等级，所述车辆等级由所述目标交通工具的类型和出行目的确定；根据所述目标交通工具的车辆等级，所述接收装置执行目标操作。
本申请另一方面提供一种包括计算机程序产品的非暂时性计算机可读介质。所述计算机程序产品包括一些指令，所述指令使计算设备：获取第一道路上的目标交通工具的车辆等级，所述车辆等级由所述目标交通工具的类型和出行目的确定；根据所述目标交通工具的车辆等级，执行目标操作。
本申请中另外的特征将部分地在下面的描述中阐述。通过该阐述，使以下附图和实施例叙述的内容对本领域普通技术人员来说变得显而易见。本申请中的发明点可以通过实践或使用下面讨论的详细示例中阐述的方法、手段及其组合来得到充分阐释。
附图说明
以下附图详细描述了本申请中披露的示例性实施例。其中相同的附图标记在附图的若干视图中表示类似的结构。本领域的一般技术人员将理解这些实施例是非限制性的、示例性的实施例，附图仅用于说明和描述的目的，并不旨在限制本公开的范围，其他方式的实施例也可能同样的完成本申请中的发明意图。应当理解，附图未按比例绘制。其中：
图1示出了根据本申请的一些实施例所示的控制交通信号灯的应用场景图；
图2示出了根据本申请的一些实施例所示的可以在其上实现控制交通信号灯的方法的示例性数据处理设备；
图3是根据本公开的一些实施例的具有自主驾驶能力的示例性车辆的框图；
图4示出了根据本申请的一些实施例所示的控制交通信号灯的方法的流程图。
具体实施方式
本申请的一个方面提供一种控制交通信号灯的装置。所述装置可以通经过交通信号灯的车辆(比如自动驾驶车辆)通讯，获取车辆的车辆等级，然后再根据所述目标交通工具的车辆等级，决定是否为该车辆开绿灯。比如，当该车辆为一辆出勤的救火车的时候，其车辆等级压倒任何周边交通状况，因此该装置自动为该救火车开绿灯。
本申请中该装置同该车辆的通讯可以在4G或者更低的网络环境得到应用。但是由于本申请中的发明对网络时延和数据的传输速度要求较高，更适合5G网络环境。4G的数据传输速率是100Mbps量级，时延是30-50ms，每平方千米的最大连接数1万量级，移动性350KM/h左右，而5G的传输速率是10Gbps量级，时延是1ms，每平方千米的最大连接数是百万量级，移动性是500km/h左右。5G具有更高的传输速率，更短的时延，更多的平方千米连接数，以及更高的速度容忍度。5G还有一个优势，就是传输路径的变化。设备和设备之间就可以直接进行传输，不需要再通过基站。因此，本 发明虽然也适用于4G环境，但是5G环境下运行会得到更好的技术表现，体现更高的商业价值。
以下描述提供了本申请的特定应用场景和要求，目的是使本领域技术人员能够制造和使用本申请中的内容。对于本领域技术人员来说，对所公开的实施例的各种局部修改是显而易见的，并且在不脱离本公开的精神和范围的情况下，可以将这里定义的一般原理应用于其他实施例和应用。因此，本公开不限于所示的实施例，而是与权利要求一致的最宽范围。
这里使用的术语仅用于描述特定示例实施例的目的，而不是限制性的。比如，除非上下文另有明确说明，这里所使用的，单数形式“一”，“一个”和“该”也可以包括复数形式。当在本说明书中使用时，术语“包括”、“包含”和/或“含有”意思是指所关联的整数，步骤、操作、元素和/或组件存在，但不排除一个或多个其他特征、整数、步骤、操作、元素、组件和/或组的存在或在该系统/方法中可以添加其他特征、整数、步骤、操作、元素、组件和/或。
在本公开中，术语“自动驾驶车辆”可以指能够感知其环境并且在没有人(例如，驾驶员，飞行员等)输入和/或干预的情况下对外界环境自动进行感知、判断并进而做出决策的车辆。术语“自动驾驶车辆”和“车辆”可以互换使用。术语“自动驾驶”可以指没有人(例如，驾驶员，飞行员等)输入的对周边环境进行智能判断并进行导航的能力。
考虑到以下描述，本公开的这些特征和其他特征、以及结构的相关元件的操作和功能、以及部件的组合和制造的经济性可以得到明显提高。参考附图，所有这些形成本公开的一部分。然而，应该清楚地理解，附图仅用于说明和描述的目的，并不旨在限制本公开的范围。
本公开中使用的流程图示出了根据本公开中的一些实施例的系统实现的操作。应该清楚地理解，流程图的操作可以不按顺序实现。相反，操作可以以反转顺序或同时实现。此外，可以向流程图添加一个或多个其他操作。可以从流程图中移除一个或多个操作。
本公开中使用的定位技术可以基于全球定位系统(GPS)，全球导航卫星系统(GLONASS)，罗盘导航系统(COMPASS)，伽利略定位系统，准天顶卫星系统(QZSS)，无线保真(WiFi)定位技术等，或其任何组合。一个或多个上述定位系统可以在本公开中互换使用。
本公开的一个方面涉及一种控制交通信号灯的方法和采用此方法的装置。具体地，该方法可以包括：接收装置首先获取目标交通工具的车辆等级，然后根据该车辆等级决定是否给车辆在交通灯处开绿灯。本系统为自动执行本方法，一方面提高了在路口车流的交通效率，另一方面还兼顾了特殊车辆在通过所述路口的顺畅度。
图1示出了根据本申请的一些实施例所示的控制交通信号灯的应用场景图。
在图1，道路130中为南北走向，道路140为东西走向。每个道路可以包括多个车道，例如，南北方向的道路130可以包括直行车道131和左转弯车道132。道路130与道路140相交，交叉点为十字路口150。十字路口150有四个红绿灯A、B、C、D。其中A灯控制道路130从南到北的车流，B灯控制道路130从北到南的车流，C灯控制道路140从西到东的车流，D灯控制道路140从东到西的车流。十字路口的中心为点标记为O。点O的位置同该十字路口的交通信号灯的位置相关，例如该十字路口所有交通信号灯的位置中心可以为点O。交通工具120行驶在道路130上。前方是十字路口150。所述交通工具120可以是合法行驶在道路130上的任何车辆。比如交通工具120可以是机动车也可以是非机动车。比如，交通工具120可以包括消防车、救护车、警车、私家车、公交车、出租车、货车、摩托车、电动车、自行车、平衡车等车辆中的任何一种。
当交通工具120行驶到路口150时，交通工具120的行驶受到该路口150相应的交通信号灯A的制约。当该相应的交通信号灯A为红灯时，交通工具120需要停止前行；当相应的交通信号灯A为绿灯时，交通工具120可以前行。
为了便于叙述本申请，在本申请以下的描述中，均以十字路口的交通信号灯为例。应当可以理解的是，本申请披露的技术方案不仅适用于十字路口，还适用于三岔口、丁字路口、五岔口、环岛等多种路口的交通信号灯。当路口的类型发生变化时，本申请披露的技术方案可以适应性的变化，而不需要本领域的技术人员付出创造性的努力。
可以根据十字路口的交通信号灯位置确定目标区域110。所述目标区域便于执行本申请公开的控制交通信号的方法，详见下文描述。
交通工具120行驶到南北方向的道路130上时，其受到南北方向的交通信号灯A的制约。更具体地，交通工具120行驶到南北方向的道路130上直行车道131时，其受到南北方向信号灯A的直行或者左转交通信号灯的制约。
交通工具120(例如，自动驾驶车辆)或其承载的设备(例如，自动驾驶控制设备、手机客户端)可以同接收装置160进行交互，接收装置160可以控制信号灯A、 B、C、D的变换，或者同信号灯控制装置相交互，然后通过向信号灯控制装置发出指令来间接控制信号灯A、B、C、D，从而影响该十字路口的交通信号灯对交通工具120的制约。例如，交通工具120可以向接收装置160发出改变交通信号灯的请求，当所述请求被通过时，所述交通信号灯对交通工具120的制约改变。具体，控制交通信号灯的方法和装置参见图3的描述。
所述装置160可以安装在任何一个交通信号灯A、B、C、D上，也可以独立的安装在十字路口或其他位置，只要控制交通信号灯的装置可以同交通工具120和交通信号灯交互。所述交互可以通过近场通信、无线网、移动网络(如3G、4G、5G)实现。
图2示出了根据本申请的一些实施例所示的可以在其上实现控制交通信号灯的方法的示例性数据处理设备。
数据处理设备200可以作为接收装置160，用于执行本申请所披露的控制交通信号灯的方法。例如，数据处理设备200可以用于执行流程400。
数据处理设备200可以包括连接到与其连接的网络的COM端口250，以便于数据通信。数据处理设备200还可以包括处理器220，处理器220以一个或多个处理器的形式，用于执行计算机指令。计算机指令可以包括例如执行本文描述的特定功能的例程，程序，对象，组件，数据结构，过程，模块和功能。例如，处理器220可以接收交通工具120发出的请求，所述请求为将交通信号灯变为绿灯。又例如，处理器220可以确定交通工具120的车辆等级，所述车辆等级由交通工具120的类型和出行目的确定；并根据所述车辆等级确定是否通过所述请求。
在一些实施例中，处理器220可以包括一个或多个硬件处理器，例如微控制器，微处理器，精简指令集计算机(RISC)，专用集成电路(ASIC)，特定于应用的指令-集处理器(ASIP)，中央处理单元(CPU)，图形处理单元(GPU)，物理处理单元(PPU)，微控制器单元，数字信号处理器(DSP)，现场可编程门阵列(FPGA)，高级RISC机器(ARM)，可编程逻辑器件(PLD)，能够执行一个或多个功能的任何电路或处理器等，或其任何组合。
示例性数据处理设备200可以包括内部通信总线210，程序存储和不同形式的数据存储(例如，磁盘270，只读存储器(ROM)230，或随机存取存储器(RAM)240)用于由计算机处理和/或发送的各种数据文件。示例性数据处理设备200还可以包括存储在ROM 230，RAM 240和/或将由处理器220执行的其他类型的非暂时性存储介质中的程序指令。本申请的方法和/或过程可以作为程序指令实现。数据处理设备200 还包括I/O组件260，支持计算机和其他组件(例如，用户界面元件)之间的输入/输出。数据处理设备200还可以通过网络通信接收编程和数据。
仅仅为了说明问题，在本申请中数据处理设备200中仅描述了一个处理器。然而，应当注意，本申请中数据处理设备200还可以包括多个处理器，因此，本申请中披露的操作和/或方法步骤可以如本公开所述的由一个处理器执行，也可以由多个处理器联合执行。例如，如果在本申请中数据处理设备200的处理器220执行步骤A和步骤B，则应该理解，步骤A和步骤B也可以由信息处理中的两个不同处理器联合或分开执行(例如，第一处理器执行步骤A，第二处理器执行步骤B，或者第一和第二处理器共同执行步骤A和B)。
图3是根据本公开的一些实施例的具有自主驾驶能力的示例性车辆的框图。图1所示的交通工具120可以是所述车辆300，也可以是其他有自动驾驶功能或者没有自动驾驶功能的车辆。例如，具有自动驾驶能力的车辆300可包括控制模块、多个传感器、通讯模块、存储器、指令模块、和控制器区域网络(CAN)以及执行机构。
所述执行机构可以包括，但不限于，油门、引擎、制动系统和转向系统(包括轮胎的转向和/或转向灯的操作)的驱动执行。
所述多个传感器可以包括向车辆300提供数据的各种内部和外部传感器。比如图3中所示，所述多个传感器可以包括车辆部件传感器和环境传感器。车辆部件传感器连接着车辆300的执行机构，可以检测到所述执行机构各个部件的运行状态和参数。
所述环境传感器允许车辆理解并潜在地响应其环境，以便帮助自动驾驶车辆300进行导航、路径规划以及保障乘客以及周围环境中的人或财产的安全。所述环境传感器还可用于识别，跟踪和预测物体的运动，例如行人和其他车辆。所述环境传感器可以包括位置传感器和外部对象传感器。
所述位置传感器可以包括GPS接收器、加速度计和/或陀螺仪，接收器。所述位置传感器可以感知和/或确定自动驾驶车辆300多地理位置和方位。例如，确定车辆的纬度，经度和高度。
所述外部对象传感器可以检测车辆外部的物体，例如其他车辆，道路中的障碍物，交通信号，标志，树木等。外部对象传感器可以包括激光传感器、雷达、照相机、声纳和/或其他检测装置。
所述通讯模块可以构造为自动驾驶汽车同外部环境交互通讯的模块。比如，通讯模块可以帮助控制模块同外界对象进行无线通讯。在一些实施例中，所述通讯模块 可以包括天线和功放电路。
所述控制模块接收所述多个传感器感知的信息后，可以处理与车辆驾驶(例如，自动驾驶)有关的信息和/或数据。在一些实施例中，控制模块可以配置成自主地驱动车辆。例如，控制模块可以输出多个控制信号。多个控制信号可以被配置为由一个或者多个电子控制模块(electronic control units，ECU)接收，以控制车辆的驱动。在一些实施例中，控制模块可基于车辆的环境信息确定参考路径和一个或多个候选路径。
在一些实施例中，控制模块可以包括一个或多个中央处理器(例如，单核处理器或多核处理器)。仅作为示例，控制模块可以包括中央处理单元(central processing unit，CPU)，专用集成电路(application-specific integrated circuit，ASIC)，专用指令集处理器(application-specific instruction-set processor，ASIP)，图形处理单元(graphics processing unit，GPU)，物理处理单元(physics processing unit，PPU)，数字信号处理器(digital signal processor，DSP)，场可编程门阵列(field programmable gate array，FPGA)，可编程逻辑器件(programmable logic device，PLD)，控制器，微控制器单元，精简指令集计算机(reduced instruction-set computer，RISC)，微处理器(microprocessor)等，或其任何组合。
控制模块还可以通过通讯模块同所述外界对象进行无线通讯。比如控制模块可以可以同接收装置160进行交互来告知自动驾驶车辆的车辆等级和/或发出红绿灯有限请求等等。
指令模块接收控制模块传来的信息，并将之转换成驱动执行机构的指令传给控制器区域网络(Controller Area Network)CAN总线。比如，控制模块向指令模块发送自动驾驶车辆200的行驶策略(加速、减速、转弯等等)，指令模块接收所述行驶策略，并将之转换成对执行机构的驱动指令(对油门、制动机构、转向机构的驱动指令)。同时，指令模块再将所述指令通过CAN总线下发到所述执行机构去。执行机构对所述指令的执行情况再由车辆部件传感器检测并反馈到控制模块，从而完成对自动驾驶车辆300到闭环控制和驱动。
图4示出了根据本申请的一些实施例所示的控制交通信号灯的方法的流程图。流程400可以实施为数据处理设备200(比如，接收装置160)中的非临时性存储介质中的一组指令。数据处理设备200(接收装置160)可以执行该一组指令并且可以相应地执行流程400中的步骤来控制交通信号灯。
以下呈现的所示流程400的操作，旨在是说明性的而非限制性的。在一些实 施例中，流程400在实现时可以添加一个或多个未描述的额外操作，和/或删减一个或多个此处所描述的操作。此外，图4中所示的和下文描述的操作的顺序并不对此加以限制。
在410中，数据处理设备200(接收装置160)可以获取第一道路上的目标交通工具120的车辆等级。
第一道路可以为某一方向上的道路，例如，南北方向的道路130或东西方向的道路140，也可以指某一方向上的道路中的具体车道，例如，直行车道131或左转弯车道132。
所述车辆等级由所述目标交通工具120的类型和出行目的确定。交通工具的类型包括消防车、救护车、警车、私家车、公交车、出租车、货车等。出行目的可以包括抢险救灾、运输病人、出警(追捕逃犯)、出游、上下班、公共运输、运输货物。一般而言，抢险救灾的消防车、运输病人的救护车、追捕逃犯的警车的车辆等级较高；没有紧迫性运输目的交通工具的车辆等级较低，例如，上下班的私家车、运输普通货物侧货车。应当理解的是，以上描述的交通工具的类型、出行目的及车辆等级的确定仅为示意性的，根据具体的情况车辆等级的确定会发生变化。比如，对于公交车，乘客的出行目的是不同的。此外，交通工具的车辆等级可以由除交通工具的类型和出行目的以外的因素确定，例如时间。比如，下午五点下班的私家车与凌晨两点下班的私家车的车辆等级可以是不同的。
目标交通工具120可以主动的将自己的车辆等级直接发送给数据处理设备200(接收装置160)。目标交通工具120可以发送一次或多次车辆等级信息给数据处理设备200(接收装置160)。相应地，数据处理设备200可以接收目标交通工具120发出的一次或多次车辆等级信息。比如，在保证数据处理设备200(接收装置160)成功接收的情况下，目标交通工具120仅发出一次车辆等级信息给数据处理设备200(接收装置160)。在某些特殊情况下，目标交通工具120也可能发出的多次车辆等级信息给数据处理设备200(接收装置160)。例如，数据处理设备200(接收装置160)没有成功接收到目标交通工具120点车辆等级的时候，或者目标交通工具120的车辆等级改变时，目标交通工具120可以再次向数据处理设备200(接收装置160)发送车辆等级。
或者，数据处理设备200(接收装置160)可以通过下述方式获得目标交通工具120的车辆等级：
(1)数据处理设备200(接收装置160)可以首先接收目标交通工具120 发出的请求，所述请求为将交通信号灯变为绿灯。
交通工具发出的请求可以是交通工具本身(例如，自动驾驶车辆120)发出的请求，也可以是交通工具承载的设备(例如，自动驾驶汽车120的控制模块或者自动驾驶汽车120上乘客的手机客户端)发出的请求。
交通工具120可以发送一次或多次请求给数据处理设备200(接收装置160)。相应地，数据处理设备200(接收装置160)可以接收交通工具发出的一次或多次请求。一般，数据处理设备200仅接收交通工具发出的一次请求。在某些特殊情况下，数据处理设备20可以接收交通工具发出的多次请求。例如，交通工具的车辆等级改变时，数据处理设备200可以再次接收所述目标交通工具发出的请求。
数据处理设备200可以接收目标区域内的目标交通工具发出的请求。在图1所示的情况下，所述目标区域为十字路口中交通信号灯预设范围内的区域L1和/或L2，例如，十字路口交通信号灯20米范围内的区域。由于十字路口中交通信号灯的位置同十字路口的中心(点O)接近，所述目标区域也可以是点O预设范围内的区域。
(2)，数据处理设备200(接收装置160)可以确定所述目标交通工具120的车辆等级。
数据处理设备200(接收装置160)可以确定包括交通工具的类型和出行目的在内的多个维度，然后建立包含所述多个维度的模型并据此确定交通工具的车辆等级。
作为示例，数据处理模型可以将抢险救灾的消防车、运输病人的救护车的车辆等级设为最大车辆等级，例如十一级；将追捕逃犯的警车的车辆等级设为较大的车辆等级，例如十级；正常时间下班的私家车的车辆等级设为较小的车辆等级，例如四级。
在420中，数据处理设备200(接收装置160)可以根据所述目标交通工具的车辆等级，执行目标操作。
在一些实施例中，步骤420中所述目标操作可包括：数据处理设备200(接收装置160)判断所述目标交通工具的车辆等级是否小于第一阈值；当所述目标交通工具120的车辆等级不小于所述第一阈值时，指示对应的交通信号灯将绿灯开启。第一阈值可以为交通信号灯预设的等级。
所述指示对应的交通信号灯将绿灯开启包括将目标交通工具行驶方向上对应的交通信号灯设置为绿灯，也可以同时包括将相冲突的其他信号灯设置为红灯。比如可以将图1中对应于目标交通工具120车道的A信号灯设置为绿灯。所述相冲突的其他 信号灯可以为会妨碍目标交通工具120通过路口150的交通信号灯。比如图1中的B、C、D信号灯。如果不将这些信号灯都设置为红灯(或者先黄灯再红灯)，行驶在对应道路上的车辆在通过路口150的时候有可能妨碍目标交通工具120顺畅的通过路口150。所述开启时间可以是交通工具120驶过红绿灯(或者路口)的时间长度，或者是预定时间长度。
所述第一阈值小于最大车辆等级大于最小车辆等级。作为示例，第一阈值可以为九级。结合上文的示例，对于抢险救灾的消防车(车辆等级为十一级)、运输病人的救护车(车辆等级为十一级)、追捕逃犯的警车(车辆等级为十级)，其车辆等级均不小于(或者大于或者等于)第一阈值，数据处理设备200可以指示对应的交通信号灯将绿灯开启。
在一些实施例中，步骤420中所述目标操作可进一步包括：当所述目标交通工具120的车辆等级不小于所述第一阈值时，判断所述目标交通工具的车辆等级是否大于目标区域内第二道路(比如图1中的道路140)上所有交通工具的车辆等级的最大值；当所述目标交通工具的车辆等级大于目标区域内第二道路上所有交通工具的车辆等级的最大值，数据处理设备200(接收装置160)指示对应的交通信号灯将绿灯开启；当所述目标交通工具的车辆等级小于目标区域内第二道路上所有交通工具的车辆等级的最大值，数据处理设备200(接收装置160)不针对目标交通工具做任何有关红绿灯的设置。
比如，当一辆警车120在道路130上追捕犯人时，其车辆等级为十级，大于道路130上的第一阈值九级。在通过路口150直行之时，如果道路140上都是正常行驶的车辆，则道路140上没有等于或者超过九级的车辆。则数据处理设备200(接收装置160)指示对应的交通信号灯A将绿灯开启，同时通过其他信号灯B、C、D将其他道路都封闭，使得警车120能顺利通过路口150。然而，如果在通过路口150直行的时候，道路140恰巧有一辆十一级的救火车通过，则数据处理设备200(接收装置160)会优先给车辆等级更高的救火车道路优先权，而不会针对警车120给予更高的道路优先权而改变红绿灯的设置。因此数据处理设备200(接收装置160)会指示对应的交通信号灯A将红灯开启。
目标区域内所述目标交通工具120行驶时参考的对应交通信号灯与所述第二道路上的交通工具行驶时参考的交通信号灯不同。即，目标交通工具和第二道路上的交通工具不能同时行驶。
所述第一道路和所述第二道路可以为不同的道路或同一条道路的不同车道。比如，第一道路为南北方向的道路130，第二道路为东西方向的道路140。又例如，第一道路为直行车道131，第二道路为左转弯车道132。
在一些实施例中，步骤420中所述目标操作还可包括：数据处理设备200(接收装置160)判断所述目标交通工具的车辆等级是否小于第一阈值；当所述目标交通工具的车辆等级小于所述第一阈值时，判断所述目标交通工具是否大于第二道路的道路等级；当所述目标交通工具是大于第二道路的道路等级时，则数据处理设备200(接收装置160)指示对应的交通信号灯将绿灯开启；当所述目标交通工具是不大于第二道路的道路等级时，指示所述交通信号灯按照既定设置工作。
其中，道路(例如，第二道路)的道路等级由目标区域内该道路(例如，第二道路)上所有交通工具的数量和车辆等级确定。目标区域内道路(例如，第二道路)上所有交通工具的数量越大，道路等级越大。比如同一条道路，在上下班高峰时期的道路等级要高于高峰期之外的时间点道路等级。目标区域内道路(例如，第二道路)上所有交通工具的车辆等级越高，道路等级越大。比如，当道路上有执勤的救火车、救护车行驶的时候，相应的路段的道路等级会被提升。因为上述车辆的车辆等级是十一级，所以相应路段的等级会在上述车辆进过的时候被提升到十一级。数据处理设备200可以确定包括交通工具的数量和交通工具的车辆等级在内的多个维度，然后建立包含所述多个维度的模型并据此确定道路的道路等级。
比如，图1所示的目标交通工具120是一辆下班回家的私家车，车辆等级为四级，小于第一阈值九级。在晚上10点左右到达目标区域L1。由于晚上10点在目标区域L2上的车辆非常少，几乎没有，数据处理设备200将道路140的道路等级降为四以下，比如二级。接近路口150的时候，由于目标交通工具120的车辆等级高于第二道路140的道路等级，数据处理设备200(接收装置160)会讲交通灯A设定为绿色，而将其他路口的红绿灯设定为红色。但是如果目标交通工具120下班回家的时间是下午6点，此时正是下班的高峰期，目标区域L2中有为数较多的车流，以至于其当时的道路等级为5，高于目标交通工具120的四级车辆等级，则数据处理设备200(接收装置160)指示当前的红绿灯按照既定设置工作，也就是该是红灯还是红灯，该是绿灯还是绿灯。
在一些实施例中，步骤420中所述目标操作可进一步包括：当所述目标交通工具的车辆等级小于所述第一阈值时，判断所述目标交通工具是否大于目标区域内第二道路上所有交通工具的车辆等级的最大值；当所述目标交通工具大于目标区域内第二道 路上所有交通工具的车辆等级的最大值，判断所述目标交通工具是否大于第二道路的道路等级。
因为确定第二道路的道路等级的计算量大于确定第二道路上所有交通工具的车辆等级的最大值的计算量，数据处理设备200可以在判断目标交通工具的车辆等级是否大于第二道路的道路等级前，先判断目标交通工具的车辆等级是否大于目标区域内第二道路上所有交通工具的车辆等级的最大值。当所述目标交通工具不大于目标区域内第二道路上所有交通工具的车辆等级的最大值时，数据处理设备200可以判定所述目标交通工具必然不大于第二道路的道路等级。
在一些实施例中，步骤420中所述目标操作还可以包括：数据处理设备200对所述目标交通工具进行车速引导。比如，在图1所示的场景下，数据处理设备200(接收装置160)指示对应的交通信号灯A进行红绿灯变换之前或者同时，会根据目标交通工具120同路口150的距离和速度，按照既定策略作出对目标交通工具120的车速引导。比如对于执勤中的救火车，既定策略是让所述救火车尽快抵达火灾现场。但是，通过将红绿灯A、B、C、D清理路口交通需要一些时间，所以救火车到达路口150点时间一定要略长于这个时间，因此其最大的速度、加速度是有限制的。相应的，当数据处理设备200(接收装置160)获取所述救火车的车辆等级并判断应该指示对应的交通信号灯A开绿灯的时候，同时指示救火车提速到道路130和路口150的交通状况允许的最大速度。再比如，如果是晚上10点一辆私家车下班回家，数据处理设备200(接收装置160)判断应该指示对应的交通信号灯A开绿灯，但是因为私家车并不在紧急情况下，因此既定策略可以是通知私家车匀速行驶通过路口。相应的，数据处理设备200(接收装置160)会通知私家车匀速行驶，并在私家车离路口预先设定距离的时候只是交通信号灯A开绿灯。再比如，如果数据处理设备200(接收装置160)的判断是不会给私家车改变红绿灯已有的变换节奏，则数据处理设备200(接收装置160)会估算私家车到达路口时的时间，在对应到时候的交通灯A的红绿灯状态，相应的指示私家车应该匀速行驶、加速还是减速。
在一些实施例中，步骤420中所述目标操作还可以包括：获取目标交通工具的行车路线，并通过微波、无线通讯等手段通知行车路线上的下一个交通灯所述目标交通工具的车辆级别以及预估的到达时间，以便下一个交通灯提前做好相应的筹划(开启绿灯与否、时间、时长等等)。
应当理解的是，上述描述的第几个施例、可以分别作为独立的实施例实施， 也可以结合成一个实施例进行实施。
应当可以理解的是，目标交通工具可以是行驶在第一道路上的任意一辆或多辆交通工具。当目标交通工具为多辆交通工具时，数据处理设备200可以分别确定该多辆交通工具的车辆等级，然后处理车辆等级最大的交通工具的请求。
应当可以理解的时，数据处理设备200处理目标交通工具发出的请求时，第二道路的数量可以是一个或两个以上(标记为子第二道路)。例如，当第一道路为直行车道131时，第二道路可以包括两个子第二道路，分别为左转弯车道132和东西方向的道路140。当第二道路的数量为两个以上时，数据处理设备可以综合考虑所述两个子第二道路的道路等级，确定第二道路的道路等级。例如，数据处理设备200可以将所述两个子第二道路的道路等级的加权平均值、最大值等作为第二道路的道路等级。
流程400可以进一步包括：当所述目标交通工具进入目标区域时，确定所述交通信号灯为红灯。即在数据处理设备200接收目标交通工具的请求前，数据处理设备200可以事先判断该交通工具进入目标区域交通信号灯的状态。例如，数据处理设备200可以通过目标交通工具发送的车辆位置、速度、目的地址等信息事先判断该交通工具进入目标区域交通信号灯的状态。当预判目标交通工具通过交通信号灯的状态为绿灯时，数据处理设备200不接受交通工具发出的请求。
流程400可以进一步包括：当目标区域内所述目标交通工具行驶时参考的交通信号灯为红灯或绿灯的连续时长大于第二阈值时，将目标区域内所述目标交通工具行驶时参考的交通信号灯变为绿灯或红灯。第二阈值为交通信号灯保持红灯或绿灯的连续时长。这是由于，在某些特殊的情形下，某一道路上的交通工具由于其车辆等级一直很大或很小，导致该交通工具行驶时参考的交通信号灯持续为绿灯或红灯，会破坏交通秩序。因此，当某一道路(例如第一道路)上的交通工具行驶时参考的交通信号灯为红灯或绿灯的连续时长大于第二阈值时，将目标区域内所述目标交通工具行驶时参考的交通信号灯变为绿灯或红灯。比如，当道路140为非常繁忙的主干道，而道路130为一个很小的支路的时候，目标区域L2中的车流量始终远远大于目标区域L1中的车流量。为了避免道路140在目标区域L2的道路等级长时间高于等待的车辆120的车辆等级，数据处理设备200(接收装置160)将交通灯A、B的红灯时间设定为第二阈值，比如2分钟。同理，数据处理设备200(接收装置160)也可以将交通灯A、B的绿灯时间做设定，比如40秒。所述第二阈值可以根据十字路口实际的交通情况确定，也可以根据经验人工设置。
综上所述，本公开的一个方面涉及一种控制交通信号灯的方法和采用此方法的交通信号灯系统。具体地，该方法可以包括：接收装置首先获取目标交通工具的车辆等级，然后根据该车辆等级决定是否给车辆在交通灯处开绿灯。本系统为自动执行本方法，一方面提高了在路口车流的交通效率，另一方面还兼顾了特殊车辆在通过所述路口的顺畅度。
在阅读本详细公开内容之后，本领域技术人员可以明白，前述详细公开内容可以仅以示例的方式呈现，并且可以不是限制性的。尽管这里没有明确说明，本领域技术人员可以理解本申请意图囊括对实施例的各种合理改变，改进和修改。这些改变，改进和修改旨在由本公开提出，并且在本公开的示例性实施例的精神和范围内。
此外，本申请中的某些术语已被用于描述本公开的实施例。例如，“一个实施例”，“实施例”和/或“一些实施例”意味着结合该实施例描述的特定特征，结构或特性可以包括在本公开的至少一个实施例中。因此，可以强调并且应当理解，在本说明书的各个部分中对“实施例”或“一个实施例”或“替代实施例”的两个或更多个引用不一定都指代相同的实施例。此外，特定特征，结构或特性可以在本公开的一个或多个实施例中适当地组合。
应当理解，在本公开的实施例的前述描述中，为了帮助理解一个特征，出于简化本公开的目的，本申请有时将各种特征组合在单个实施例、附图或其描述中。或者，本申请又是将各种特征分散在多个本发明的实施例中。然而，这并不是说这些特征的组合是必须的，本领域技术人员在阅读本申请的时候完全有可能将其中一部分特征提取出来作为单独的实施例来理解。也就是说，本申请中的实施例也可以理解为多个次级实施例的整合。而每个次级实施例的内容在于少于单个前述公开实施例的所有特征的时候也是成立的。
在一些实施方案中，表达用于描述和要求保护本申请的某些实施方案的数量或性质的数字应理解为在某些情况下通过术语“约”，“近似”或“基本上”修饰。例如，除非另有说明，否则“约”，“近似”或“基本上”可表示其描述的值的±20％变化。因此，在一些实施方案中，书面描述和所附权利要求书中列出的数值参数是近似值，其可以根据特定实施方案试图获得的所需性质而变化。在一些实施方案中，数值参数应根据报告的有效数字的数量并通过应用普通的舍入技术来解释。尽管阐述本申请的一些实施方案列出了广泛范围的数值范围和参数是近似值，但具体实施例中都列出了尽可能精确的数值。
本文引用的每个专利，专利申请，专利申请的出版物和其他材料，例如文章，书籍，说明书，出版物，文件，物品等，可以通过引用结合于此。用于所有目的的全部内容，除了与其相关的任何起诉文件历史，可能与本文件不一致或相冲突的任何相同的，或者任何可能对权利要求的最宽范围具有限制性影响的任何相同的起诉文件历史。现在或以后与本文件相关联。举例来说，如果在与任何所包含的材料相关联的术语的描述、定义和/或使用与本文档相关的术语、描述、定义和/或之间存在任何不一致或冲突时，使用本文件中的术语为准。
最后，应理解，本文公开的申请的实施方案是对本申请的实施方案的原理的说明。其他修改后的实施例也在本申请的范围内。因此，本申请披露的实施例仅仅作为示例而非限制。本领域技术人员可以根据本申请中的实施例采取替代配置来实现本申请中的发明。因此，本申请的实施例不限于申请中被精确地描述过的哪些实施例。

Claims (20)

  1. 一种控制交通信号灯的装置，包括：
    至少一个存储设备，所述存储设备包括一组指令；以及
    与所述至少一个存储设备通信的至少一个处理器，其中，当执行所述一组指令时，所述至少一个处理器：
    获取第一道路上的目标交通工具的车辆等级，所述车辆等级由所述目标交通工具的类型和出行目的确定；
    根据所述目标交通工具的车辆等级，执行目标操作。
  2. 如权利要求1所述的装置，其特征在于，为了执行所述目标操作，所述至少一个处理器：
    当所述目标交通工具进入目标区域时，确定所同目标交通工具对应的目标交通信号灯为红灯，所述目标区域为目标交通信号灯预设范围内的区域。
  3. 如权利要求1所述的装置，其中为了执行所述目标操作，所述至少一个处理器：
    判断所述目标交通工具的车辆等级不小于所述第一阈值，
    指示目标交通信号灯将绿灯开启。
  4. 如权利要求1所述的装置，其中，为了执行所述目标操作，所述至少一个处理器：
    判断所述目标交通工具的车辆等级不小于所述第一阈值，
    判断所述目标交通工具的车辆等级不小于目标区域内第二道路上所有交通工具的车辆等级的最大值；
    指示目标交通信号灯将绿灯开启，
    其中，目标区域内所述目标交通工具行驶时参考的交通信号灯与所述第二道路上的交通工具行驶时参考的交通信号灯不同，所述第一道路和所述第二道路为相交的道路或同一条道路的不同车道。
  5. 如权利要求1所述的装置，其中，所述目标操作包括：
    对所述目标交通工具进行车速引导，和
    将所述目标交通工具的车辆信息发送给目标交通工具行车路线上的下一个接收装置中的至少一个。
  6. 如权利要求1所述的装置，其中，为了执行所述目标操作，所述至少一个处理器：
    判断所述目标交通工具的车辆等级小于所述第一阈值；
    判断所述目标交通工具不小于第二道路的道路等级，所述道路等级由目标区域内第二道路上所有交通工具的数量和车辆等级确定；
    指示目标交通信号灯将绿灯开启，
    其中，目标区域内所述目标交通工具行驶时参考的交通信号灯与所述第二道路上的交通工具行驶时参考的交通信号灯不同，所述第一道路和所述第二道路为相交的道路或同一条道路的不同车道。
  7. 如权利要求6所述的装置，其中，为了判断所述目标交通工具不小于第二道路的道路等级，所述至少一个处理器：
    判断所述目标交通工具不小于目标区域内第二道路上所有交通工具的车辆等级的最大值；以及
    判断所述目标交通工具不小于第二道路的道路等级。
  8. 如权利要求7所述的装置，其中，
    所述目标区域内第二道路上所有交通工具的数量越大，所述道路等级越大；
    所述目标区域内第二道路上所有交通工具的车辆等级越高，所述道路等级越大。
  9. 如权利要求1所述的装置，其中，所述至少一个处理器进一步地：
    当所述目标交通工具的车辆等级改变时，再次接收所述目标交通工具发出的请求。
  10. 如权利要求1所述的装置，其中，所述至少一个处理器进一步地：
    当目标区域内所述目标交通工具行驶时参考的交通信号灯为红灯或绿灯的连续时长大于第二阈值时，所述接收装置改变目标区域内所述目标交通工具行驶时参考的交通信号灯的颜色。
  11. 一种控制交通信号灯的方法，其特征在于，所述方法包括：
    接收装置获取第一道路上的目标交通工具的车辆等级，所述车辆等级由所述目标交通工具的类型和出行目的确定；
    根据所述目标交通工具的车辆等级，所述接收装置执行目标操作。
  12. 如权利要求11所述的方法，其特征在于，所述目标操作包括：
    当所述目标交通工具进入目标区域时，确定所同目标交通工具对应的目标交通信号灯为红灯，所述目标区域为目标交通信号灯预设范围内的区域。
  13. 如权利要求11所述的方法，其特征在于，所述目标操作包括：
    判断所述目标交通工具的车辆等级不小于所述第一阈值，
    指示目标交通信号灯将绿灯开启。
  14. 如权利要求11所述的方法，其特征在于，所述目标操作包括：
    判断所述目标交通工具的车辆等级不小于所述第一阈值，
    判断所述目标交通工具的车辆等级不小于目标区域内第二道路上所有交通工具的车辆等级的最大值；
    指示目标交通信号灯将绿灯开启，
    其中，目标区域内所述目标交通工具行驶时参考的交通信号灯与所述第二道路上的交通工具行驶时参考的交通信号灯不同。
  15. 如权利要求11所述的方法，其特征在于，所述目标操作包括：
    对所述目标交通工具进行车速引导，和
    将所述目标交通工具的车辆信息发送给目标交通工具行车路线上的下一个接收装置中的至少一个。
  16. 如权利要求11所述的方法，其特征在于，所述目标操作包括：
    判断所述目标交通工具的车辆等级小于所述第一阈值；
    判断所述目标交通工具不小于第二道路的道路等级，所述道路等级由目标区域内第 二道路上所有交通工具的数量和车辆等级确定；
    指示目标交通信号灯将绿灯开启，
    其中，目标区域内所述目标交通工具行驶时参考的交通信号灯与所述第二道路上的交通工具行驶时参考的交通信号灯不同。
  17. 如权利要求16所述的方法，其特征在于，所述判断所述目标交通工具不小于第二道路的道路等级包括：
    判断所述目标交通工具不小于目标区域内第二道路上所有交通工具的车辆等级的最大值；以及
    判断所述目标交通工具不小于第二道路的道路等级。
  18. 如权利要求17所述的方法，其特征在于，
    所述目标区域内第二道路上所有交通工具的数量越大，所述道路等级越大；
    所述目标区域内第二道路上所有交通工具的车辆等级越高，所述道路等级越大。
  19. 如权利要求11所述的方法，其特征在于，所述方法进一步包括：
    当所述目标交通工具的车辆等级改变时，再次接收所述目标交通工具发出的请求。
  20. 如权利要求11所述的方法，其特征在于，所述方法进一步包括：
    当目标区域内所述目标交通工具行驶时参考的交通信号灯为红灯或绿灯的连续时长大于第二阈值时，所述接收装置改变目标区域内所述目标交通工具行驶时参考的交通信号灯的颜色。
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