WO2020020298A1 - 车辆无人驾驶控制方法及装置 - Google Patents

车辆无人驾驶控制方法及装置 Download PDF

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Publication number
WO2020020298A1
WO2020020298A1 PCT/CN2019/097740 CN2019097740W WO2020020298A1 WO 2020020298 A1 WO2020020298 A1 WO 2020020298A1 CN 2019097740 W CN2019097740 W CN 2019097740W WO 2020020298 A1 WO2020020298 A1 WO 2020020298A1
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Prior art keywords
vehicle
running speed
driving
information
speed information
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PCT/CN2019/097740
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English (en)
French (fr)
Inventor
杭春锋
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比亚迪股份有限公司
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Publication of WO2020020298A1 publication Critical patent/WO2020020298A1/zh

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
    • G05D1/0274—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means using mapping information stored in a memory device
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/025—Services making use of location information using location based information parameters
    • H04W4/027—Services making use of location information using location based information parameters using movement velocity, acceleration information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]

Definitions

  • the present disclosure relates to the technical field of vehicles, and in particular, to a method and device for controlling unmanned vehicles.
  • the existing unmanned driving methods of rail transit are ATP (Automatic Train Protection), ATO (Automatic Train Operation), and ATS (Automatic Train Supervisio) ),
  • the ATO subsystem is a device that controls the automatic operation of the train, including on-board equipment and ground equipment.
  • the ATO subsystem can realize the automatic driving of the train, the automatic adjustment of the speed, and the train under the protection of the ATP system. Door control, etc.
  • the traditional signal control system is based on the operating mode of the subway to meet the needs of the large capacity of the subway, and the technical solution architecture mainly follows foreign technology. It requires the equipment of the ground, vehicles, and railsides to control the driving of the vehicle, which is costly. , It is not applicable to new rail transit methods such as straddle monorail and light urban rail transit. And the ground equipment, in-vehicle equipment and central equipment are linked to realize driving, but the equipment is numerous and valuable, and the vehicle is in a passive position. The efficient and stable work of the vehicle-ground communication system is required to ensure the information transmission of the signal control system. The equipment is complex, Construction is difficult.
  • the present disclosure aims to solve at least one of the technical problems in the above-mentioned technologies.
  • the first object of the present disclosure is to propose a method for controlling an unmanned vehicle.
  • the vehicle itself can judge the driving-related information and make corresponding actions, without the need to construct complex track equipment, and at the same time reduce the central control equipment.
  • the number of vehicles not only reduces costs, but also improves the efficiency of vehicle operation and maintenance management.
  • a second object of the present disclosure is to propose a vehicle driverless control device.
  • a third object of the present disclosure is to propose an in-vehicle electronic device.
  • a fourth object of the present disclosure is to propose a vehicle.
  • an embodiment of the first aspect of the present disclosure provides a method for controlling an unmanned vehicle, including the following steps: collecting a video image in front of the vehicle; performing image recognition processing on the video image to obtain the video image Map data; acquiring geographic location information of the vehicle; determining, based on the map data of the video image, pre-stored three-dimensional map data of the vehicle driving route and the geographic location information, the vehicle on the vehicle driving route Vehicle position information; obtaining the vehicle position information of the vehicle on the vehicle driving line according to the correspondence relationship between the vehicle position information of the vehicle on the vehicle driving line and the pre-stored vehicle position information and driving control parameters Corresponding driving control parameters; acquiring running speed information of the vehicle; and controlling the vehicle to drive on the vehicle driving line according to the running speed information and the driving control parameter.
  • the vehicle driverless control method of the embodiment of the present disclosure firstly collect a video image in front of the vehicle, and perform image recognition processing on the video image to obtain map data of the video image, and then obtain geographic location information of the vehicle, and according to the video image's Map data, pre-stored three-dimensional map data of vehicle driving routes, and geographic location information, determine the vehicle position information of the vehicle on the vehicle driving route, and then according to the vehicle position information of the vehicle on the vehicle driving route and the vehicle position information stored in advance
  • Correspondence with driving control parameters obtain driving control parameters corresponding to the vehicle position information of the vehicle on the vehicle driving route, finally obtain the vehicle's running speed information, and control the vehicle on the vehicle driving route according to the operating speed information and driving control parameters On the road.
  • the vehicle itself can judge the driving-related information and make corresponding actions, without the need to build complex track equipment, and at the same time reduce the number of central control equipment, which not only reduces costs, but also improves the efficiency of vehicle operation and maintenance management.
  • an embodiment of the second aspect of the present disclosure provides a vehicle driverless control device, including: an acquisition module for acquiring a video image in front of the vehicle; and an identification module for performing image recognition on the video image Processing to obtain the map data of the video image; a first obtaining module for obtaining the geographic location information of the vehicle; a determining module for obtaining a three-dimensional map of the driving route of the vehicle according to the map data of the video image Data and the geographic location information to determine vehicle location information of the vehicle on the vehicle driving route; a second acquisition module, configured to, according to the vehicle location information of the vehicle on the vehicle driving route and a pre-stored Correspondence between vehicle position information and driving control parameters, to obtain driving control parameters corresponding to the vehicle position information of the vehicle on the vehicle driving route; a third acquisition module, configured to acquire running speed information of the vehicle; control A module for controlling an office based on the running speed information and the driving control parameters The vehicle is traveling on the traveling route of the vehicle.
  • the video image in front of the vehicle is collected by the acquisition module, and the video image is subjected to image recognition processing by the recognition module to obtain map data of the video image, and the vehicle is acquired by the first acquisition module.
  • the determining module determines the vehicle location information of the vehicle on the vehicle driving route according to the map data of the video image, the pre-stored three-dimensional map data of the vehicle driving route and the geographical location information
  • the second acquiring module Correspondence between the vehicle position information on the vehicle driving route and the pre-stored vehicle position information and driving control parameters to obtain driving control parameters corresponding to the vehicle position information of the vehicle on the vehicle driving route, and then obtain the vehicle's Running speed information, so that the control module controls the vehicle to run on the vehicle driving line according to the running speed information and driving control parameters.
  • an embodiment of the third aspect of the present disclosure provides a vehicle-mounted electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor.
  • the processor The program is executed to implement the vehicle driverless control method according to the embodiment of the first aspect of the present disclosure.
  • the vehicle-mounted electronic equipment can execute a computer program stored in a memory through a processor, and the vehicle can judge driving related information and make corresponding actions, without the need to construct complicated track equipment, and at the same time reduce the center control equipment.
  • the number of vehicles not only reduces costs, but also improves the efficiency of vehicle operation and maintenance management.
  • an embodiment of the fourth aspect of the present disclosure provides a vehicle including: a vehicle unmanned control device of an embodiment of the second aspect of the present disclosure.
  • the vehicle of the embodiment of the present disclosure enables the vehicle itself to determine driving-related information and make corresponding actions by using the vehicle unmanned driving control device, without the need to construct complicated track equipment, and at the same time reducing the number of central control equipment. Reduced costs and improved vehicle operation and maintenance management efficiency.
  • FIG. 1 is a flowchart of a vehicle driverless control method according to an embodiment of the present disclosure
  • FIG. 2 is a schematic diagram of a position-speed control curve of a vehicle according to a specific embodiment of the present disclosure
  • FIG. 3 is a schematic block diagram of a vehicle driverless control device according to an embodiment of the present disclosure.
  • FIG. 4 is a schematic block diagram of a vehicle-mounted electronic device according to an embodiment of the present disclosure.
  • FIG. 5 is a schematic block diagram of a vehicle according to an embodiment of the present disclosure.
  • FIG. 1 is a flowchart of a vehicle driverless control method according to an embodiment of the present disclosure.
  • the vehicle may be a vehicle for rail transit, for example, a vehicle for a straddle-type monorail, a vehicle for light urban rail transit, and the like.
  • a vehicle driverless control method includes the following steps:
  • a video image in front of the vehicle may be collected by a camera, and the camera may be a high-performance camera, for example, a dedicated high-definition video camera. It should be noted that the camera can be installed in front of the front of the vehicle in order to collect video images in front of the vehicle.
  • image enhancement processing can include contrast enhancement, spatial filtering, noise cancellation, image smoothing, and image sharpening.
  • the method before collecting a video image in front of the vehicle, may further include generating a three-dimensional map of the driving route of the vehicle and storing the three-dimensional map data, and generating and storing the correspondence between the vehicle position information and the driving control parameters according to the three-dimensional map data. .
  • the driving control parameters described in this embodiment may include a position-speed control curve of the vehicle, where the position-speed control curve may include vehicle speed information, vehicle acceleration information, and vehicle Deceleration information.
  • the position-speed control curve may include vehicle speed information, vehicle acceleration information, and vehicle Deceleration information.
  • the particularity of rail transit is that the vehicle runs on a fixed line, and the vehicle's operation control parameters on the line, the environment of the line, and the location of surrounding buildings are relatively stable. Therefore, before capturing video images in front of the vehicle (for example, after the construction of the line is completed), a high-definition video camera combined with radar ranging technology can be used to draw a three-dimensional map of the line and store it in the vehicle controller.
  • the three-dimensional map data is used to generate the correspondence between vehicle position information and driving control parameters, and store it in the on-board controller so that it can be called in subsequent methods.
  • a database may be newly created in the vehicle-mounted controller, and the correspondence relationship between the vehicle position information and the driving control parameters is stored in the database to facilitate the maintenance of the correspondence relationship.
  • S2 Perform image recognition processing on the video image to obtain map data of the video image.
  • the video image described in this embodiment is composed of many frames, and each frame will record corresponding position features, where the position features may include external things and relative positions (with radar ranging) And other information. Therefore, map data of video images can be obtained by analyzing the corresponding position features of each frame.
  • the construction of rail transit can control the vehicle to run on a fixed line multiple times before the formal operation of the rail transit, collect video images in front of the vehicle, and Perform image recognition processing to obtain the map data of the video image, and combine the pre-stored map data of the current location to repeatedly train the map data of the obtained video image to improve the recognition accuracy, that is, to improve the recognition of the map data in the video image. Accuracy.
  • GPS Global Positioning System
  • other positioning technology may be used to obtain the geographic position information of the vehicle, which is not limited herein.
  • S4. Determine the vehicle position information of the vehicle on the vehicle driving line according to the map data of the video image, the pre-stored three-dimensional map data of the vehicle driving line, and the geographical position information.
  • the pre-stored three-dimensional map data and geographic location information of the vehicle driving route can be calibrated according to actual conditions.
  • the running speed information of the vehicle may be obtained through a speed measurement radar electronic device or a vehicle speed sensor. It should be noted that the speed measurement radar electronic device described in this embodiment may be installed in front of the front of the vehicle in order to obtain the running speed information of the vehicle.
  • a high-definition video camera installed on the front of the vehicle head may first collect a video image of the front of the vehicle, and perform image recognition processing on the video image to obtain map data of the video image. Then, the vehicle can obtain the current geographical location information of the vehicle through the built-in GPS, and call out the pre-stored three-dimensional map data of the vehicle driving route from its own on-board controller. Then, the vehicle compares the map data of the video image with the pre-stored three-dimensional map data of the vehicle driving route, and combines the current geographic location information of the vehicle obtained through GPS to determine the vehicle on the vehicle driving route. (For example, the vehicle is currently driving on the A bridge). Thereby, it is possible to accurately locate the current position information of the vehicle.
  • the vehicle After determining the vehicle position information of the vehicle on the vehicle driving route, the vehicle can call the corresponding relationship between the pre-stored vehicle position information and the driving control parameters from its own on-board controller, and according to the determined vehicle position information and the corresponding relationship To obtain driving control parameters corresponding to the determined vehicle position information. Finally, the vehicle obtains the running speed information of the vehicle through the above-mentioned speed measuring radar electronic device, and controls the vehicle to drive on the vehicle driving line according to the running speed information and the driving control parameter.
  • the method before controlling the vehicle to drive on the vehicle driving route according to the running speed information and driving control parameters, the method may further include performing image recognition processing on the video image to obtain the running speed information of the vehicle in front of the vehicle.
  • Controlling the vehicle on the vehicle driving route according to the running speed information and driving control parameters may include calculating the safe running speed information of the vehicle according to the running speed information of the vehicle and the running speed information of the vehicle in front, and according to the safe running speed of the vehicle Information and driving control parameters to control the vehicle on the vehicle driving route.
  • a video camera for example, a video image with an image collection distance exceeding 500 meters
  • the video image can be Image recognition processing
  • the change in the vehicle image on the XY axis of the picture taken by the camera can be compared by skipping the frame, and the vehicle on the XY axis of the picture taken by the camera is combined with the running speed ratio of the own vehicle
  • the change of the image intelligently recognizes the speed information of the vehicle ahead, such as acceleration, uniform speed, deceleration, and parking status.
  • the vehicle can accurately calculate the safe running speed information of the vehicle such as its safe running speed and safety protection distance according to its own running speed information and the running speed information of the vehicle in front, and according to the above obtained corresponding to its current position information
  • the driving control parameters and its own safe running speed information control itself to drive on the vehicle's driving route (that is, to achieve automatic vehicle control).
  • the relative speed and safe distance between the vehicle and the preceding vehicle can be used to calculate the permitted driving speed and safe distance of the vehicle. If the vehicle and the preceding vehicle are both traveling at the same speed, the maximum travel of the vehicle is The speed must not exceed this speed, and to ensure that once the front vehicle has an emergency brake or is in a stopped state, the vehicle cannot crash due to inertial driving after braking.
  • This driving distance multiplied by a preset coefficient can be set to be adjacent Safety distance between cars. The preset coefficients can be calibrated according to the actual situation.
  • a thermal imaging camera can be arranged side by side with the front of the vehicle facing outwards.
  • video images of the front of the vehicle can still be collected without obstacles, the safety distance is controlled, and the safety of driving around the clock is ensured.
  • the method before controlling the vehicle to drive on the vehicle driving route according to the running speed information and driving control parameters, the method may further include performing image recognition processing on the video image to determine that the vehicle is about to enter the station, and Decelerating the vehicle and performing image recognition processing on the video image acquired again to obtain distance information between the vehicle and a stop sign located in front of the vehicle.
  • Controlling the vehicle on the vehicle driving route according to the running speed information and driving control parameters may include calculating acceleration information of the vehicle according to the running speed information and distance information, and controlling the vehicle on the vehicle according to the vehicle acceleration information and driving control parameters. Driving on a driving route.
  • a video camera in front of the vehicle can be used to collect a real-time video image of the front of the vehicle and perform image recognition processing on the video image. If it is identified that the vehicle is about to enter the station, The vehicle can control itself to start deceleration, and continue to perform image recognition processing on the currently collected video images to obtain the distance information between the vehicle and the stop sign located in front of the vehicle.
  • the stop sign can be three pieces, and the entrance , One in the center of the station and one in front of the station.
  • the labels can be 1,2,3, and installed in positions that will not be blocked by passengers.
  • the vehicle can calculate its own acceleration information according to its running speed information and the distance information, and control itself to drive on the vehicle's driving route based on its acceleration information and the aforementioned driving control parameters, so that the vehicle corresponds to the stop sign. Docking.
  • each time period is determined by the position where it is located.
  • acceleration * driving time + normal speed * driving time + negative acceleration * time each time period is determined by the position where it is located.
  • the vehicle When the vehicle recognizes the position where the deceleration starts (for example, when the vehicle recognizes that the vehicle is about to enter the station ahead), it will The instruction is transmitted to the braking system to start deceleration (that is, to control the vehicle to decelerate according to the above-mentioned driving control parameters (for example, the arrival time) and to calculate its own acceleration information) until it stops.
  • the braking system to start deceleration (that is, to control the vehicle to decelerate according to the above-mentioned driving control parameters (for example, the arrival time) and to calculate its own acceleration information) until it stops.
  • a short-range full-HD camera can also be installed on the front of the vehicle toward the side, and when the vehicle recognizes that the vehicle is about to enter the station, control the vehicle to start decelerating, and acquire images through the short-range full-HD camera.
  • the parking sign image within a preset range (for example, 50 meters) is accurately analyzed and calculated to calculate the parking position to accurately calculate the parking position through real-time image comparison so that the vehicle can be parked corresponding to the parking sign and further enhance the high vehicle The accuracy of pit stops.
  • the method before controlling the vehicle to drive on the vehicle driving route according to the running speed information and driving control parameters, the method may further include performing image recognition processing on the video image to obtain the route of the vehicle driving route in front of the vehicle. State information, and the vehicle's safe operating speed information is calculated based on the line state information. Controlling the vehicle on the vehicle's driving route according to the running speed information and the driving control parameters may include controlling the vehicle on the vehicle's driving route based on the safe running speed information and the driving control parameters.
  • At least one of a camera installed in front of the vehicle head and the above-mentioned short-range full-HD camera can collect a video image of the front of the vehicle and perform image recognition on the video image. Processing to obtain line status information (for example, a series of track condition information such as turning, climbing, downhill, frost, rain, snow, station signs, turnouts, etc.) of the vehicle driving route in front of the vehicle. Then the vehicle can calculate its own safe running speed information according to the line state information, and control itself to drive on the vehicle's driving line according to the safe running speed information and the aforementioned driving control parameters, that is, dynamically based on the line state information, Adjust the speed and brakes to ensure safe driving.
  • line status information for example, a series of track condition information such as turning, climbing, downhill, frost, rain, snow, station signs, turnouts, etc.
  • the method before controlling the vehicle to drive on the vehicle driving route according to the running speed information and the driving control parameters, the method may further include the vehicle position information, the running speed information, and the video image through the wireless communication module. Send to the monitoring center on the ground, and receive the dispatching instruction sent by the surveillance center, and adjust the running speed information according to the dispatching instruction.
  • controlling the vehicle to run on the vehicle driving route may include controlling the vehicle to run on the vehicle driving line according to the adjusted running speed information and driving control parameters, thereby completing train scheduling and driving tracking.
  • the wireless communication module described in this embodiment may include a 4G communication unit, a 3G communication unit, a digital transmission station communication unit, a spread spectrum microwave communication unit, and the like.
  • the vehicle driverless control method of the embodiment of the present disclosure firstly collect a video image in front of the vehicle, and perform image recognition processing on the video image to obtain map data of the video image, and then obtain the geographic location information of the vehicle, and according to The map data of the video image, the pre-stored three-dimensional map data of the vehicle driving route and the geographical location information determine the vehicle position information of the vehicle on the vehicle driving route, and then according to the vehicle position information and the pre-stored vehicle position information and driving control parameters The corresponding relationship is obtained, and the driving control parameters corresponding to the vehicle position information are obtained, and finally the vehicle running speed information is obtained, and the vehicle is driven on the vehicle driving line according to the running speed information and the driving control parameters.
  • the vehicle itself can judge the driving-related information and make corresponding actions, without the need to build complex track equipment, and at the same time reduce the number of central control equipment, which not only reduces costs, but also improves the efficiency of vehicle operation and maintenance management.
  • FIG. 3 is a schematic block diagram of a vehicle driverless control device according to an embodiment of the present disclosure.
  • the vehicle unmanned driving control device 1000 includes: an acquisition module 100, an identification module 200, a first acquisition module 300, a determination module 400, a second acquisition module 500, a third acquisition module 600, and Control module 700.
  • the acquisition module 100 is configured to acquire a video image in front of the vehicle.
  • the recognition module 200 is configured to perform image recognition processing on a video image to obtain map data of the video image.
  • the first obtaining module 300 is configured to obtain geographic location information of a vehicle.
  • the determining module 400 is configured to determine the vehicle position information of the vehicle on the vehicle driving line according to the map data of the video image, the pre-stored three-dimensional map data of the vehicle driving line, and the geographical position information.
  • the second obtaining module 500 is configured to obtain driving control parameters corresponding to the vehicle position information of the vehicle on the driving route of the vehicle according to the correspondence relationship between the vehicle position information of the vehicle on the vehicle driving route and the stored vehicle position information and driving control parameters. .
  • the third acquisition module 600 is configured to acquire running speed information of the vehicle.
  • the control module 700 is configured to control the vehicle to run on the vehicle driving line according to the running speed information and the driving control parameters.
  • the acquisition module 100 is further configured to generate a three-dimensional map of the driving route of the vehicle and store the three-dimensional map data before acquiring a video image in front of the vehicle.
  • the acquisition module 100 is further configured to generate and store a correspondence relationship between vehicle position information and driving control parameters according to the three-dimensional map data before acquiring a video image in front of the vehicle.
  • control module 700 is specifically configured to perform image recognition processing on the video image to obtain the running speed information of the vehicle in front of the vehicle, and according to the running speed information of the vehicle and the running speed information of the vehicle in front, The vehicle's safe operating speed information is calculated, and the vehicle is controlled to travel on the vehicle's driving route according to the vehicle's safe operating speed information and driving control parameters.
  • control module 700 is specifically configured to perform image recognition processing on a video image, determine that a vehicle is about to enter a station, perform deceleration processing on the vehicle, and perform image recognition processing on a newly acquired video image. Obtain the distance information between the vehicle and the stop sign located in front of the vehicle, then calculate the acceleration information of the vehicle according to the running speed information and distance information, and control the vehicle to drive on the vehicle's driving route according to the vehicle's acceleration information and driving control parameters. .
  • control module 700 is specifically configured to perform image recognition processing on a video image to obtain line state information of a driving route of a vehicle in front of the vehicle, and calculate and obtain safe vehicle speed information based on the line state information, And controlling the vehicle on the vehicle's driving route according to the safe running speed information and driving control parameters.
  • control module 700 is specifically configured to send vehicle position information, running speed information, and video images to a monitoring center on the ground through a wireless communication module, and receive a scheduling instruction sent by the monitoring center, according to the scheduling The instruction adjusts the running speed information, and controls the vehicle to run on the vehicle driving line according to the adjusted running speed information and driving control parameters.
  • the video image in front of the vehicle is collected by the acquisition module, and the video image is subjected to image recognition processing by the recognition module, to obtain map data of the video image, and obtained through the first
  • the module acquires the geographic location information of the vehicle, so that the determination module determines the vehicle location information of the vehicle on the vehicle traveling route based on the map data of the video image, the pre-stored three-dimensional map data of the vehicle traveling route, and the geographic location information.
  • the second acquisition module The driving control parameters corresponding to the vehicle position information are obtained according to the correspondence between the vehicle position information and the pre-stored vehicle position information and the driving control parameters, and then the vehicle's running speed information is obtained through a third acquisition module, so that the control module is based on the running speed. Information and driving control parameters to control the vehicle on the vehicle driving route.
  • the vehicle itself can judge the driving-related information and make corresponding actions, without the need to build complex track equipment, and at the same time reduce the number of central control equipment, which not only reduces costs, but also improves the efficiency of vehicle operation and maintenance management.
  • the present disclosure also proposes a vehicle-mounted electronic device.
  • the vehicle-mounted electronic device 2000 includes a memory 10, a processor 20, and a computer stored on the memory 10 and operable on the processor 20.
  • the program 11 and the processor 20 execute the program 11 to implement the vehicle unmanned control method provided by the above embodiment of the present disclosure.
  • the vehicle-mounted electronic equipment can execute a computer program stored in a memory through a processor, and the vehicle can judge driving related information and make corresponding actions, without the need to construct complicated track equipment, and at the same time reduce the center control equipment.
  • the number of vehicles not only reduces costs, but also improves the efficiency of vehicle operation and maintenance management.
  • the present disclosure also proposes a vehicle.
  • the vehicle 10000 includes the vehicle unmanned control device 1000 described above.
  • the vehicle of the embodiment of the present disclosure enables the vehicle itself to determine driving-related information and make corresponding actions by using the vehicle unmanned driving control device, without the need to construct complicated track equipment, and at the same time reducing the number of central control equipment. Reduced costs and improved vehicle operation and maintenance management efficiency.
  • first and second are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as “first” and “second” may explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "a plurality” is at least two, for example, two, three, etc., unless it is specifically and specifically defined otherwise.
  • Any process or method description in a flowchart or otherwise described herein can be understood as representing a module, fragment, or portion of code that includes one or more executable instructions for implementing steps of a custom logic function or process
  • the scope of the preferred embodiments of the present disclosure includes additional implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order according to the functions involved, which It is understood by those skilled in the art to which the embodiments of the present disclosure belong.
  • Logic or steps represented in a flowchart or otherwise described herein, for example, a sequenced list of executable instructions that can be considered to implement a logical function, can be embodied in any computer-readable medium for use in Instruction execution systems, devices, or devices (such as computer-based systems, systems that include processors, or other systems that can take instructions from and execute instructions), or combine these instruction execution systems, devices, or devices While using.
  • a "computer-readable medium” may be any device that can contain, store, communicate, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device.
  • computer-readable media include the following: electrical connections (electronic devices) with one or more wirings, portable computer disk cartridges (magnetic devices), random access memory (RAM), Read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disk read-only memory (CDROM).
  • the computer-readable medium may even be paper or other suitable medium on which the program can be printed, for example, by optically scanning the paper or other medium, followed by editing, interpretation, or other suitable means if necessary Process to obtain the program electronically and then store it in computer memory.
  • portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof.
  • multiple steps or methods may be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system.
  • Discrete logic circuits with logic gates for implementing logic functions on data signals Logic circuits, ASICs with suitable combinational logic gate circuits, programmable gate arrays (PGA), field programmable gate arrays (FPGA), etc.
  • each functional unit in each embodiment of the present disclosure may be integrated into one processing module, or each unit may exist separately physically, or two or more units may be integrated into one module.
  • the above integrated modules may be implemented in the form of hardware or software functional modules. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.
  • the aforementioned storage medium may be a read-only memory, a magnetic disk, or an optical disk.

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Abstract

本公开公开了一种车辆无人驾驶控制方法和车辆无人驾驶控制装置，该方法包括：采集车辆前方的视频图像以得到视频图像的地图数据；获取车辆的地理位置信息；根据视频图像的地图数据、预先存储的车辆行驶线路的立体地图数据和地理位置信息，确定车辆在车辆行驶线路上的车辆位置信息；根据车辆位置信息和预先存储的车辆位置信息与行车控制参数的对应关系，获取相应的行车控制参数；获取车辆的运行速度信息；根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。由此，车辆自身可以判断跟行驶相关的信息并做出相应的动作，无需建设复杂的轨道设备，同时可减少中心控制设备的数量，既降低了成本，又提升了车辆运维管理的效率。

Description

车辆无人驾驶控制方法及装置
相关申请的交叉引用
本公开要求比亚迪股份有限公司于2018年07月26日提交的、发明名称为“车辆无人驾驶控制方法及装置”的、中国专利申请号为“201810835657.8”的优先权。
技术领域
本公开涉及车辆技术领域，特别涉及一种车辆无人驾驶控制方法及装置。
背景技术
现有的轨道交通的无人驾驶方式是通过信号系统的ATP(Automatic Train Protection，列车自动保护系统)、ATO(Automatic Train Operatio，列车自动运行装置)、以及ATS(Automatic Train Supervisio，列车自动监控系统)组成，ATO子系统是控制列车自动运行的设备，包含车载设备和地面设备，ATO子系统可在ATP系统的保护下，根据ATS系统的指令实现列车运行的自动驾驶、速度的自动调整和列车车门控制等。
然而，传统的信号控制系统是基于地铁的运营模式，以满足地铁的大运量需求，且技术方案架构主要沿袭国外技术，需要地面、车辆、轨旁的设备配合进行车辆的行驶控制，成本高昂，对于跨座式单轨以及轻型城市轨道交通等新型轨道交通方式不适用。并且地面设备、车载设备以及中心设备三者之间的联动实现驾驶，但是设备繁多、贵重，车辆处于被动地位，需要车地通信系统的高效稳定的工作确保信号控制系统的信息传递，设备复杂、建设困难。
发明内容
本公开旨在至少在一定程度上解决上述技术中的技术问题之一。
为此，本公开的第一个目的在于提出一种车辆无人驾驶控制方法，车辆自身可以判断跟行驶相关的信息并做出相应的动作，无需建设复杂的轨道设备，同时可减少中心控制设备的数量，既降低了成本，又提升了车辆运维管理的效率。
本公开的第二个目的在于提出一种车辆无人驾驶控制装置。
本公开的第三个目的在于提出一种车载电子设备。
本公开的第四个目的在于提出一种车辆。
为达到上述目的，本公开第一方面实施例提出了一种车辆无人驾驶控制方法，包括以 下步骤：采集车辆前方的视频图像；对所述视频图像进行图像识别处理，得到所述视频图像的地图数据；获取所述车辆的地理位置信息；根据所述视频图像的地图数据、预先存储的车辆行驶线路的立体地图数据和所述地理位置信息，确定所述车辆在所述车辆行驶线路上的车辆位置信息；根据所述车辆在所述车辆行驶线路上的车辆位置信息和预先存储的车辆位置信息与行车控制参数的对应关系，获取与所述车辆在所述车辆行驶线路上的车辆位置信息对应的行车控制参数；获取所述车辆的运行速度信息；根据所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶。
根据本公开实施例的车辆无人驾驶控制方法，首先采集车辆前方的视频图像，并对视频图像进行图像识别处理以得到视频图像的地图数据，然后获取车辆的地理位置信息，并根据视频图像的地图数据、预先存储的车辆行驶线路的立体地图数据和地理位置信息，确定车辆在车辆行驶线路上的车辆位置信息，再然后根据车辆在车辆行驶线路上的车辆位置信息和预先存储的车辆位置信息与行车控制参数的对应关系，获取与车辆在车辆行驶线路上的车辆位置信息对应的行车控制参数，最后获取车辆的运行速度信息，并根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。由此，车辆自身可以判断跟行驶相关的信息并做出相应的动作，无需建设复杂的轨道设备，同时可减少中心控制设备的数量，既降低了成本，又提升了车辆运维管理的效率。
为达到上述目的，本公开第二方面实施例提出了一种车辆无人驾驶控制装置，包括：采集模块，用于采集车辆前方的视频图像；识别模块，用于对所述视频图像进行图像识别处理，得到所述视频图像的地图数据；第一获取模块，用于获取所述车辆的地理位置信息；确定模块，用于根据所述视频图像的地图数据、预先存储的车辆行驶线路的立体地图数据和所述地理位置信息，确定所述车辆在所述车辆行驶线路上的车辆位置信息；第二获取模块，用于根据所述车辆在所述车辆行驶线路上的车辆位置信息和预先存储的车辆位置信息与行车控制参数的对应关系，获取与所述车辆在所述车辆行驶线路上的车辆位置信息对应的行车控制参数；第三获取模块，用于获取所述车辆的运行速度信息；控制模块，用于根据所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶。
根据本公开实施例的车辆无人驾驶控制装置，通过采集模块采集车辆前方的视频图像，并通过识别模块对视频图像进行图像识别处理，得到视频图像的地图数据，以及通过第一获取模块获取车辆的地理位置信息，以使确定模块根据视频图像的地图数据、预先存储的车辆行驶线路的立体地图数据和地理位置信息，确定车辆在车辆行驶线路上的车辆位置信息，第二获取模块根据车辆在车辆行驶线路上的车辆位置信息和预先存储的车辆位置信息与行车控制参数的对应关系，获取与车辆在车辆行驶线路上的车辆位置信息对应的行车控制参数，而后通过第三获取模块获取车辆的运行速度信息，以使控制模块根据运行速 度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。由此，车辆自身可以判断跟行驶相关的信息并做出相应的动作，无需建设复杂的轨道设备，同时可减少中心控制设备的数量，既降低了成本，又提升了车辆运维管理的效率。
为达到上述目的，本公开第三方面实施例提出了一种车载电子设备，包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，所述处理器执行所述程序，以实现如本公开第一方面实施例所述的车辆无人驾驶控制方法。
本公开实施例的车载电子设备，通过处理器执行存储在存储器上的计算机程序，车辆自身可以判断跟行驶相关的信息并做出相应的动作，无需建设复杂的轨道设备，同时可减少中心控制设备的数量，既降低了成本，又提升了车辆运维管理的效率。
为达到上述目的，本公开第四方面实施例提出了一种车辆包括：本公开第二方面实施例的车辆无人驾驶控制装置。
本公开实施例的车辆，通过上述车辆无人驾驶控制装置，使车辆自身可以判断跟行驶相关的信息并做出相应的动作，无需建设复杂的轨道设备，同时可减少中心控制设备的数量，既降低了成本，又提升了车辆运维管理的效率。
本公开附加的方面和优点将在下面的描述中部分给出，部分将从下面的描述中变得明显，或通过本公开的实践了解到。
附图说明
本公开上述的或附加的方面和优点从下面结合附图对实施例的描述中将变得明显和容易理解，其中：
图1是根据本公开一个实施例的车辆无人驾驶控制方法的流程图；
图2是根据本公开一个具体实施例的车辆的位置-速度的控制曲线示意图；
图3是根据本公开一个实施例的车辆无人驾驶控制装置的方框示意图；
图4是根据本公开一个实施例的车载电子设备的方框示意图；以及
图5是根据本公开一个实施例的车辆的方框示意图。
具体实施方式
下面详细描述本公开的实施例，所述实施例的示例在附图中示出，其中自始至终相同或类似的标号表示相同或类似的元件或具有相同或类似功能的元件。下面通过参考附图描述的实施例是示例性的，旨在用于解释本公开，而不能理解为对本公开的限制。
下面结合附图来描述本公开实施例的车辆无人驾驶控制方法及装置。
图1是根据本公开一个实施例的车辆无人驾驶控制方法的流程图。在本公开的实施例 中，车辆可为轨道交通的车辆，例如，跨座式单轨所用的车辆、轻型城市轨道交通所用的车辆等。
如图1所示，本公开实施例的车辆无人驾驶控制方法，包括以下步骤：
S1，采集车辆前方的视频图像。
在本公开的实施例中，可通过摄像机采集车辆前方的视频图像，且该摄像机可为高性能摄像机，例如，专用高清视频摄像机。应说明的是，该摄像机可安装在车辆的车头前方，以便于采集车辆前方的视频图像。
另外，鉴于图像在采集和传输时，色彩信息容易受到光源颜色和方向等多种因素的影响。为了避免这种色彩偏移，摄像机在采集到车辆前方的视频图像后，可首先对该视频图像进行图像增强处理，可包括对比度增强、空域滤波、噪声消除、图像平滑和图像锐化等。
作为一个实施例，在采集车辆前方的视频图像之前，还可包括生成车辆行驶线路的立体地图，并存储立体地图数据，以及根据立体地图数据，生成并存储车辆位置信息与行车控制参数的对应关系。
需要说明的是，该实施例中所描述的行车控制参数可包括车辆的位置-速度的控制曲线，其中，该位置-速度的控制曲线中可包含车辆的行驶速度信息、车辆的加速度信息和车辆的减速度信息。例如，如图2所示，当车辆行驶到A处的位置时，该车辆可控制自身以初始速度V1和加速度△V1行驶；当车辆行驶到B处的位置时，该车辆可控制自身以运行速度V2行驶。
具体而言，轨道交通的特殊性为车辆行驶在固定的线路上，线路上车辆运行控制参数、线路的环境以及周围建筑的位置相对稳定。因此，在采集车辆前方的视频图像之前(例如，在线路建设完成后)，可先通过高清视频摄像机结合雷达测距技术绘制线路立体地图，并将其存储在车载控制器中，而后可根据该立体地图数据，生成车辆位置信息与行车控制参数的对应关系，并将其存储在车载控制器，以便在后续的方法中调用。
另外，在本公开的其他实施例中，还可在车载控制器中新建一个数据库，将上述的车辆位置信息与行车控制参数的对应关系保存在该数据库中，以方便对该对应关系的维护。
S2，对视频图像进行图像识别处理，得到视频图像的地图数据。
需要说明的是，该实施例中所描述的视频图像是由许多的帧组成的，且每幅帧都会记录相应的位置特征，其中，位置特征可包含外界事物、相对位置(配合雷达测距)等信息。因此，可通过对每幅帧都会记录相应的位置特征进行分析，得到视频图像的地图数据。
另外，轨道交通(例如，轻轨、跨座式单轨)的建设方可在该轨道交通正式运营之前，通过控制车辆在固定的线路上多次运行，采集该车辆前方的视频图像，并对视频图像进行图像识别处理，得到视频图像的地图数据，以及结合预先存储的当前位置的地图数据，对 得到视频图像的地图数据进行反复的训练，以提升识别精确度，即提升识别视频图像中地图数据的精确度。
S3，获取车辆的地理位置信息。
在本公开的实施例中，可采用GPS(Global Positioning System，全球定位系统)或其它定位技术获取车辆的地理位置信息，在此不做限定。
S4，根据视频图像的地图数据、预先存储的车辆行驶线路的立体地图数据和地理位置信息，确定车辆在车辆行驶线路上的车辆位置信息。其中，预先存储的车辆行驶线路的立体地图数据和地理位置信息可根据实际情况进行标定。
S5，根据车辆在车辆行驶线路上的车辆位置信息和预先存储的车辆位置信息与行车控制参数的对应关系，获取与车辆在车辆行驶线路上的车辆位置信息对应的行车控制参数。其中，预先存储的车辆位置信息可根据实际情况进行标定。
S6，获取车辆的运行速度信息。
在本公开的实施例中，可通过测速雷达电子设备或车速传感器获取车辆的运行速度信息。应说明的是，该实施例中所描述的测速雷达电子设备可安装在车辆的车头前方，以便于获取车辆的运行速度信息。
S7，根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。
具体地，在上述固定的线路上运行的车辆，可先通过安装在车辆车头前方上的高清视频摄像机采集车辆前方的视频图像，并对该视频图像进行图像识别处理以得到视频图像的地图数据。然后该车辆可通过内置的GPS获取车辆当前所处的地理位置信息，并从自身的车载控制器中调出预先存储的车辆行驶线路的立体地图数据。再然后该车辆将该视频图像的地图数据，与预先存储的车辆行驶线路的立体地图数据进行实时比对，并结合通过GPS获取的车辆当前所处的地理位置信息，确定车辆在车辆行驶线路上的车辆位置信息(例如，车辆当前正行驶在A大桥上)。由此，可以精确定位车辆当前所处的位置信息。
车辆在确定自身在车辆行驶线路上的车辆位置信息后，可从自身的车载控制器中调出预先存储的车辆位置信息与行车控制参数的对应关系，并根据确定的车辆位置信息和该对应关系，获取与该确定的车辆位置信息对应的行车控制参数。最后，该车辆通过上述的测速雷达电子设备获取车辆的运行速度信息，并根据运行速度信息和该行车控制参数，控制车辆在车辆行驶线路上行驶。
作为一个实施例，根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶之前，还可包括对视频图像进行图像识别处理，得到位于车辆前方的前方车辆的运行速度信息。根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶，可包括根据车辆的运行速度信息和前方车辆的运行速度信息，计算得到车辆的安全运行速度信息， 并根据车辆的安全运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。
具体而言，车辆在固定的线路上运行的过程中，可通过装在车头前方的摄像机，采集车辆前方的视频图像(例如，图像采集距离超500米的视频图像)，并对该视频图像进行图像识别处理，如果识别出前方有车辆，则可通过跳帧比对上述摄像机拍摄的图片XY轴上的车辆图像的变化，以及结合本车的运行速度比对该摄像机拍摄图片XY轴上的车辆图像的变化，智能识别前方车辆加速、匀速、减速和停车状态等前方车辆的运行速度信息。
然后该车辆可根据自身的运行速度信息和前方车辆的运行速度信息，精准计算出自身的安全行车速度、安全保护距离等车辆的安全运行速度信息，并根据上述获取的与自身当前位置信息对应的行车控制参数，和自身的安全运行速度信息，控制自身在车辆行驶线路上行驶(即，实现车辆自动运行控制)。例如，可通过该车辆与前车之间的相对位置及速度，计算该车辆允许的行车速度以及安全的距离，其中，如果该车辆与前车均以相同的速度行驶，则该车辆的最大行驶速度不能超过此速度，并且确保一旦前车发生紧急制动或处在停止状态时，该车辆制动后由于惯性行驶的不能发生碰撞，此行驶距离乘以预设的系数可设定为相邻车车之间的安全距离。其中，预设的系数可根据实际情况进行标定。
在本公开的其他实施例中，车辆的车头外朝前方可并列配置一台热成像摄像机，大雾天气仍可无障碍采集车辆前方的视频图像，控制安全车距，确保全天候行车安全，从而完成全自动无人驾驶。
另外，在本公开的一个实施例中，根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶之前，还可包括对视频图像进行图像识别处理，确定出车辆前方即将进站，并对车辆进行减速处理，以及对重新获取的视频图像进行图像识别处理，得到车辆与位于车辆前方的停车牌之间的距离信息。根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶，可包括根据运行速度信息和距离信息，计算得到车辆的加速度信息，并根据车辆的加速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。
具体而言，车辆在固定的线路上运行的过程中，可通过装在车头前方的摄像机实时采集车辆前方的视频图像，并对该视频图像进行图像识别处理，如果识别出车辆前方即将进站，该车辆则可控制自身开始减速，并继续对当前采集的视频图像进行图像识别处理，以得到车辆与位于车辆前方的停车牌之间的距离信息，其中，停车牌可为三块，进站口，车站中央、出站前方各安装一块，标号可为1,2,3，且安装在不会被乘客遮挡的位置。然后该车辆可根据自身的运行速度信息和该距离信息，计算得到自身的加速度信息，并根据自身的加速度信息和上述的行车控制参数，控制自身在车辆行驶线路上行驶，以使车辆对应停车牌进行停靠。
需要说明的是，上述的固定的线路上可存储多个站点，车辆在固定的线路上运行的过 程中，需要严格控制通过两个相邻的站点之间的区间的时间，其中，两个相邻的站点之间的区间的长度＝加速度*行驶时间+正常速度*行驶时间+负加速度*时间，每个时间段都是由所处的位置决定，当车辆识别到开始加速行驶的位置点时，将指令发给车载的牵引系统开始加速行驶，达到设定速度值时，正常行驶，当车辆识别到开始减速的位置点时(例如，当车辆识别出车辆前方即将进站时)，将控制指令传给制动系统开始减速(即，根据上述的行车控制参数(例如，到站时间)和计算得到自身的加速度信息控制车辆进行减速行驶)，直到停止。
在本公开的其他实施例中，还可在车辆的车头朝向侧前方安装短程全高清相机，并在车辆识别出车辆前方即将进站时，控制车辆开始减速，并通过该短程全高清相机图像采集预设范围(例如，50米)内的停车牌图像，精准分析处理，计算停车位置，以通过实时图像比对，精准计算停车位置，以使车辆可以对应停车牌进行停靠，并进一步提升高车辆进站停靠的精准度。
此外，在本公开的一个实施例中，根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶之前，还可包括对视频图像进行图像识别处理，得到车辆前方的车辆行驶线路的线路状态信息，并根据线路状态信息，计算得到车辆的安全运行速度信息。根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶，可包括根据安全运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。
具体而言，车辆在固定的线路上运行的过程中，可通过装在车头前方的摄像机和上述的短程全高清相机中的至少一个，采集车辆前方的视频图像，并对该视频图像进行图像识别处理，以得到车辆前方的车辆行驶线路的线路状态信息(例如，转弯、爬坡、下坡、冰霜雨雪、车站指示牌、道岔等一系列轨道状况信息)。然后该车辆可根据该线路状态信息，计算得到自身的安全运行速度信息，以及根据该安全运行速度信息和上述的行车控制参数，控制自身在车辆行驶线路上行驶，即，根据线路状态信息，动态调整车速和刹车，确保行车安全。
此外，在本公开的另一个实施例中，根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶之前，还可包括将车辆位置信息、运行速度信息和视频图像，通过无线通信模块发送至地面上的监控中心，并接收监控中心发送的调度指令，根据调度指令对运行速度信息进行调节。根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶，可包括根据调节后的运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶，从而完成列车调度与行车追踪。应说明的是，该实施例中所描述的无线通信模块可包括4G通信单元、3G通信单元、数传电台通信单元和扩频微波通信单元等。
综上，根据本公开实施例的车辆无人驾驶控制方法，首先采集车辆前方的视频图像， 并对视频图像进行图像识别处理以得到视频图像的地图数据，然后获取车辆的地理位置信息，并根据视频图像的地图数据、预先存储的车辆行驶线路的立体地图数据和地理位置信息，确定车辆在车辆行驶线路上的车辆位置信息，再然后根据车辆位置信息和预先存储的车辆位置信息与行车控制参数的对应关系，获取与车辆位置信息对应的行车控制参数，最后获取车辆的运行速度信息，并根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。由此，车辆自身可以判断跟行驶相关的信息并做出相应的动作，无需建设复杂的轨道设备，同时可减少中心控制设备的数量，既降低了成本，又提升了车辆运维管理的效率。
图3是根据本公开一个实施例的车辆无人驾驶控制装置的方框示意图。
如图3所示，本公开实施例的车辆无人驾驶控制装置1000包括：采集模块100、识别模块200、第一获取模块300、确定模块400、第二获取模块500、第三获取模块600和控制模块700。
其中，采集模块100用于采集车辆前方的视频图像。
识别模块200用于对视频图像进行图像识别处理，得到视频图像的地图数据。
第一获取模块300用于获取车辆的地理位置信息。
确定模块400用于根据视频图像的地图数据、预先存储的车辆行驶线路的立体地图数据和地理位置信息，确定车辆在车辆行驶线路上的车辆位置信息。
第二获取模块500用于根据车辆在车辆行驶线路上的车辆位置信息和预先存储的车辆位置信息与行车控制参数的对应关系，获取与车辆在车辆行驶线路上的车辆位置信息对应的行车控制参数。
第三获取模块600用于获取车辆的运行速度信息。
控制模块700用于根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。
在本公开的一个实施例中，采集模块100还用于在采集车辆前方的视频图像之前，生成车辆行驶线路的立体地图，并存储立体地图数据。
在本公开的一个实施例中，采集模块100还用于在采集车辆前方的视频图像之前，根据立体地图数据，生成并存储车辆位置信息与行车控制参数的对应关系。
在本公开的一个实施例中，控制模块700具体用于对视频图像进行图像识别处理，得到位于车辆前方的前方车辆的运行速度信息，并根据车辆的运行速度信息和前方车辆的运行速度信息，计算得到车辆的安全运行速度信息，以及根据车辆的安全运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。
在本公开的一个实施例中，控制模块700具体用于对视频图像进行图像识别处理，确 定出车辆前方即将进站，并对车辆进行减速处理，以及对重新获取的视频图像进行图像识别处理，得到车辆与位于车辆前方的停车牌之间的距离信息，然后根据运行速度信息和距离信息，计算得到车辆的加速度信息，并根据车辆的加速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。
在本公开的一个实施例中，控制模块700具体用于对视频图像进行图像识别处理，得到车辆前方的车辆行驶线路的线路状态信息，并根据线路状态信息，计算得到车辆的安全运行速度信息，以及根据安全运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。
在本公开的一个实施例中，控制模块700具体用于将车辆位置信息、运行速度信息和视频图像，通过无线通信模块发送至地面上的监控中心，并接收监控中心发送的调度指令，根据调度指令对运行速度信息进行调节，以及根据调节后的运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。
需要说明的是，本公开实施例的车辆无人驾驶控制装置中未披露的细节，请参照本公开实施例的车辆无人驾驶控制方法中所披露的细节，具体这里不再赘述。
综上，根据本公开实施例的车辆无人驾驶控制装置，通过采集模块采集车辆前方的视频图像，并通过识别模块对视频图像进行图像识别处理，得到视频图像的地图数据，以及通过第一获取模块获取车辆的地理位置信息，以使确定模块根据视频图像的地图数据、预先存储的车辆行驶线路的立体地图数据和地理位置信息，确定车辆在车辆行驶线路上的车辆位置信息，第二获取模块根据车辆位置信息和预先存储的车辆位置信息与行车控制参数的对应关系，获取与车辆位置信息对应的行车控制参数，而后通过第三获取模块获取车辆的运行速度信息，以使控制模块根据运行速度信息和行车控制参数，控制车辆在车辆行驶线路上行驶。由此，车辆自身可以判断跟行驶相关的信息并做出相应的动作，无需建设复杂的轨道设备，同时可减少中心控制设备的数量，既降低了成本，又提升了车辆运维管理的效率。
为了实现上述实施例，本公开还提出一种车载电子设备，如图4所示，该车载电子设备2000包括存储器10、处理器20及存储在存储器10上并可在处理器20上运行的计算机程序11，处理器20执行程序11，以实现本公开上述实施例提出的车辆无人驾驶控制方法。
本公开实施例的车载电子设备，通过处理器执行存储在存储器上的计算机程序，车辆自身可以判断跟行驶相关的信息并做出相应的动作，无需建设复杂的轨道设备，同时可减少中心控制设备的数量，既降低了成本，又提升了车辆运维管理的效率。
为了实现上述实施例，本公开还提出一种车辆，如图5所示，该车辆10000包括上述车辆无人驾驶控制装置1000。
本公开实施例的车辆，通过上述车辆无人驾驶控制装置，使车辆自身可以判断跟行驶相关的信息并做出相应的动作，无需建设复杂的轨道设备，同时可减少中心控制设备的数量，既降低了成本，又提升了车辆运维管理的效率。
在本说明书的描述中，参考术语“一个实施例”、“一些实施例”、“示例”、“具体示例”、或“一些示例”等的描述意指结合该实施例或示例描述的具体特征、结构、材料或者特点包含于本公开的至少一个实施例或示例中。在本说明书中，对上述术语的示意性表述不必须针对的是相同的实施例或示例。而且，描述的具体特征、结构、材料或者特点可以在任一个或多个实施例或示例中以合适的方式结合。此外，在不相互矛盾的情况下，本领域的技术人员可以将本说明书中描述的不同实施例或示例以及不同实施例或示例的特征进行结合和组合。
此外，术语“第一”、“第二”仅用于描述目的，而不能理解为指示或暗示相对重要性或者隐含指明所指示的技术特征的数量。由此，限定有“第一”、“第二”的特征可以明示或者隐含地包括至少一个该特征。在本公开的描述中，“多个”的含义是至少两个，例如两个，三个等，除非另有明确具体的限定。
流程图中或在此以其他方式描述的任何过程或方法描述可以被理解为，表示包括一个或更多个用于实现定制逻辑功能或过程的步骤的可执行指令的代码的模块、片段或部分，并且本公开的优选实施方式的范围包括另外的实现，其中可以不按所示出或讨论的顺序，包括根据所涉及的功能按基本同时的方式或按相反的顺序，来执行功能，这应被本公开的实施例所属技术领域的技术人员所理解。
在流程图中表示或在此以其他方式描述的逻辑或步骤，例如，可以被认为是用于实现逻辑功能的可执行指令的定序列表，可以具体实现在任何计算机可读介质中，以供指令执行系统、装置或设备(如基于计算机的系统、包括处理器的系统或其他可以从指令执行系统、装置或设备取指令并执行指令的系统)使用，或结合这些指令执行系统、装置或设备而使用。就本说明书而言，"计算机可读介质"可以是任何可以包含、存储、通信、传播或传输程序以供指令执行系统、装置或设备或结合这些指令执行系统、装置或设备而使用的装置。计算机可读介质的更具体的示例(非穷尽性列表)包括以下：具有一个或多个布线的电连接部(电子装置)，便携式计算机盘盒(磁装置)，随机存取存储器(RAM)，只读存储器(ROM)，可擦除可编辑只读存储器(EPROM或闪速存储器)，光纤装置，以及便携式光盘只读存储器(CDROM)。另外，计算机可读介质甚至可以是可在其上打印程序的纸或其他合适的介质，因为可以例如通过对纸或其他介质进行光学扫描，接着进行编辑、解译或必要时以其他合适方式进行处理来以电子方式获得程序，然后将其存储在计算机存储器中。
应当理解，本公开的各部分可以用硬件、软件、固件或它们的组合来实现。在上述实 施方式中，多个步骤或方法可以用存储在存储器中且由合适的指令执行系统执行的软件或固件来实现。如，如果用硬件来实现和在另一实施方式中一样，可用本领域公知的下列技术中的任一项或他们的组合来实现：具有用于对数据信号实现逻辑功能的逻辑门电路的离散逻辑电路，具有合适的组合逻辑门电路的专用集成电路，可编程门阵列(PGA)，现场可编程门阵列(FPGA)等。
本技术领域的普通技术人员可以理解实现上述实施例方法携带的全部或部分步骤是可以通过程序来指令相关的硬件完成，的程序可以存储于一种计算机可读存储介质中，该程序在执行时，包括方法实施例的步骤之一或其组合。
此外，在本公开各个实施例中的各功能单元可以集成在一个处理模块中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个模块中。上述集成的模块既可以采用硬件的形式实现，也可以采用软件功能模块的形式实现。集成的模块如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。
上述提到的存储介质可以是只读存储器，磁盘或光盘等。尽管上面已经示出和描述了本公开的实施例，可以理解的是，上述实施例是示例性的，不能理解为对本公开的限制，本领域的普通技术人员在本公开的范围内可以对上述实施例进行变化、修改、替换和变型。

Claims (14)

  1. 一种车辆无人驾驶控制方法，其特征在于，包括以下步骤：
    采集车辆前方的视频图像；
    对所述视频图像进行图像识别处理，得到所述视频图像的地图数据；
    获取所述车辆的地理位置信息；
    根据所述视频图像的地图数据、预先存储的车辆行驶线路的立体地图数据和所述地理位置信息，确定所述车辆在所述车辆行驶线路上的车辆位置信息；
    根据所述车辆在所述车辆行驶线路上的车辆位置信息和预先存储的车辆位置信息与行车控制参数的对应关系，获取与所述车辆在所述车辆行驶线路上的车辆位置信息对应的行车控制参数；
    获取所述车辆的运行速度信息；
    根据所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶。
  2. 根据权利要求1所述的车辆无人驾驶控制方法，其特征在于，所述采集车辆前方的视频图像之前，还包括：
    生成所述车辆行驶线路的立体地图，并存储所述立体地图数据；
    根据所述立体地图数据，生成并存储所述车辆位置信息与行车控制参数的对应关系。
  3. 根据权利要求1或2所述的车辆无人驾驶控制方法，其特征在于，所述根据所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶之前，还包括：
    对所述视频图像进行图像识别处理，得到位于所述车辆前方的前方车辆的运行速度信息；
    所述根据所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶，包括：
    根据所述车辆的运行速度信息和所述前方车辆的运行速度信息，计算得到所述车辆的安全运行速度信息；
    根据所述车辆的安全运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶。
  4. 根据权利要求1-3任一项所述的车辆无人驾驶控制方法，其特征在于，所述根据所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶之前，还包括：
    对所述视频图像进行图像识别处理，确定出所述车辆前方即将进站；
    对所述车辆进行减速处理；
    对重新获取的所述视频图像进行图像识别处理，得到所述车辆与位于所述车辆前方的停车牌之间的距离信息；
    所述根据所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶，包括：
    根据所述运行速度信息和所述距离信息，计算得到所述车辆的加速度信息；
    根据所述车辆的加速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶。
  5. 根据权利要求1-4任一项所述的车辆无人驾驶控制方法，其特征在于，所述根据所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶之前，还包括：
    对所述视频图像进行图像识别处理，得到所述车辆前方的所述车辆行驶线路的线路状态信息；
    根据所述线路状态信息，计算得到所述车辆的安全运行速度信息；
    所述根据所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶，包括：
    根据所述安全运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶。
  6. 根据权利要求1-5任一项所述的车辆无人驾驶控制方法，其特征在于，所述根据所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶之前，还包括：
    将所述车辆位置信息、所述运行速度信息和所述视频图像，通过无线通信模块发送至地面上的监控中心；
    接收所述监控中心发送的调度指令，根据所述调度指令对所述运行速度信息进行调节；
    所述根据所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶，包括：
    根据调节后的所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶。
  7. 一种车辆无人驾驶控制装置，其特征在于，包括：
    采集模块，用于采集车辆前方的视频图像；
    识别模块，用于对所述视频图像进行图像识别处理，得到所述视频图像的地图数据；
    第一获取模块，用于获取所述车辆的地理位置信息；
    确定模块，用于根据所述视频图像的地图数据、预先存储的车辆行驶线路的立体地图数据和所述地理位置信息，确定所述车辆在所述车辆行驶线路上的车辆位置信息；
    第二获取模块，用于根据所述车辆在所述车辆行驶线路上的车辆位置信息和预先存储的车辆位置信息与行车控制参数的对应关系，获取与所述车辆在所述车辆行驶线路上的车辆位置信息对应的行车控制参数；
    第三获取模块，用于获取所述车辆的运行速度信息；
    控制模块，用于根据所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶。
  8. 根据权利要求7所述的车辆无人驾驶控制装置，其特征在于，所述采集模块，还用于：
    在采集车辆前方的视频图像之前，生成所述车辆行驶线路的立体地图，并存储所述立体地图数据；
    根据所述立体地图数据，生成并存储所述车辆位置信息与行车控制参数的对应关系。
  9. 根据权利要求7或8所述的车辆无人驾驶控制装置，所述控制模块，具体用于：
    对所述视频图像进行图像识别处理，得到位于所述车辆前方的前方车辆的运行速度信息；
    根据所述车辆的运行速度信息和所述前方车辆的运行速度信息，计算得到所述车辆的安全运行速度信息；
    根据所述车辆的安全运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶。
  10. 根据权利要求7-9任一项所述的车辆无人驾驶控制装置，所述控制模块，具体用于：
    对所述视频图像进行图像识别处理，确定出所述车辆前方即将进站；
    对所述车辆进行减速处理；
    对重新获取的所述视频图像进行图像识别处理，得到所述车辆与位于所述车辆前方的停车牌之间的距离信息；
    根据所述运行速度信息和所述距离信息，计算得到所述车辆的加速度信息；
    根据所述车辆的加速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶。
  11. 根据权利要求7-10任一项所述的车辆无人驾驶控制装置，所述控制模块，具体用于：
    对所述视频图像进行图像识别处理，得到所述车辆前方的所述车辆行驶线路的线路状 态信息；
    根据所述线路状态信息，计算得到所述车辆的安全运行速度信息；
    根据所述安全运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶。
  12. 根据权利要求7-11任一项所述的车辆无人驾驶控制装置，所述控制模块，具体用于：
    将所述车辆位置信息、所述运行速度信息和所述视频图像，通过无线通信模块发送至地面上的监控中心；
    接收所述监控中心发送的调度指令，根据所述调度指令对所述运行速度信息进行调节；
    根据调节后的所述运行速度信息和所述行车控制参数，控制所述车辆在所述车辆行驶线路上行驶。
  13. 一种车载电子设备，其特征在于，包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，所述处理器执行所述程序，以实现如权利要求1-6任一项所述的车辆无人驾驶控制方法。
  14. 一种车辆，其特征在于，其特征在于，包括如权利要求7-12中任一项所述的车辆无人驾驶控制装置。
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