Vehicle passing guiding method, computer equipment and storage medium

Abstract

The invention discloses a vehicle passing guiding method, computer equipment and a storage medium, and the method comprises the steps: calling a recognizer to collect the vehicle type data of a vehicle when the vehicle is driven into a certain toll island, recognizing the type of the vehicle in the length dimension according to the vehicle type data, calling a track according to the type to move a passing device to a specified passing position, and carrying out the recognition of the type of the vehicle. Controlling the passing device to execute a prompt operation to guide the vehicle to move towards the passing device, detecting the length of the vehicle and a processing position when the vehicle stops moving in the toll island, calling the track to control the passing device to move towards the vehicle when the processing position is not adjacent to the passing position, and calling the track to control the passing device to move towards the vehicle when the processing position is adjacent to the passing position. And calling the passing device to execute passing operation on the vehicle according to the length so as to enable the vehicle to pass, and performing adaptive adjustment between the vehicle and the passing device, thereby improving the interaction smoothness between the user on the vehicle and the passing device, improving the passing efficiency of the vehicle, reducing the frequency of manual access, and greatly reducing the cost.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of intelligent transportation technology, and in particular to a vehicle traffic guidance method, a computer device and a storage medium. Background Art

[0002] At present, highway toll stations usually adopt ETC (Electronic Toll Collection), manual and mixed traffic modes. On this basis, toll stations currently install some intelligent equipment at relevant locations to allow users to operate and enable vehicles to pass by themselves.

[0003] However, the installation locations of these intelligent devices are fixed, which limits the interaction between users and the intelligent devices. When some vehicles fail to pass through by themselves, manual intervention is required, resulting in low efficiency and high cost. Summary of the invention

[0004] The present invention provides a vehicle traffic guiding method, a computer device and a storage medium, which are used to improve the efficiency of vehicle traffic and reduce the cost.

[0005] In a first aspect, an embodiment of the present invention provides a vehicle traffic guidance method, which is applied to a toll station on a highway, wherein the toll station has a plurality of toll islands, an identifier is provided at the entrance of each of the toll islands, a track is provided on each channel, and a passer is provided in the track, comprising:

[0006] When a vehicle enters a toll island, calling the identifier to collect vehicle model data of the vehicle;

[0007] Identifying the type of the vehicle in the dimension of length according to the vehicle model data;

[0008] Calling the track according to the type to move the passer to a designated pass position;

[0009] Controlling the pass device to perform a prompting operation to guide the vehicle to move toward the pass device;

[0010] detecting the length of the vehicle and the processing position when the vehicle stops moving in the toll island;

[0011] When the processing position and the passing position are not adjacent, calling the track to control the passer to move toward the vehicle;

[0012] When the processing position is adjacent to the passing position, the passing device is called to perform a passing operation on the vehicle according to the length to allow the vehicle to pass.

[0013] In a second aspect, an embodiment of the present invention further provides a vehicle traffic guiding device, which is applied to a toll station on a highway, wherein the toll station has a plurality of toll islands, an identifier is provided at the entrance of each of the toll islands, a track is provided on each channel, and a passer is provided in the track, including:

[0014] A vehicle model data collection module, used for calling the identifier to collect the vehicle model data of the vehicle when the vehicle enters a certain toll island;

[0015] A vehicle type identification module, used to identify the type of the vehicle in the dimension of length according to the vehicle type data;

[0016] A track moving module, used for calling the track according to the type to move the passer to a designated passing position;

[0017] A pass device execution module, used for controlling the pass device to execute a prompt operation to guide the vehicle to move toward the pass device;

[0018] a processing position detection module, for detecting the length of the vehicle and the processing position when the vehicle stops moving in the toll island;

[0019] A position non-adjacent module, used for calling the track to control the passer to move toward the vehicle when the processing position and the pass position are not adjacent;

[0020] The position adjacent module is used to call the passer to perform a passing operation on the vehicle according to the length to allow the vehicle to pass when the processing position is adjacent to the passing position.

[0021] In a third aspect, an embodiment of the present invention further provides a computer device, including:

[0022] one or more processors;

[0023] A storage device for storing one or more programs;

[0024] When the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle traffic guidance method provided in the first aspect of the present invention.

[0025] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the vehicle traffic guidance method provided in the first aspect of the present invention.

[0026] In a fifth aspect, an embodiment of the present invention further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the vehicle traffic guidance method provided in the first aspect of the present invention.

[0027] In this embodiment, a toll station applied to a highway has multiple toll islands in the toll station. An identifier is provided at the entrance of each toll island, and a track is provided on each channel. A passer is provided in the track. When a vehicle enters a toll island, the identifier is called to collect vehicle model data of the vehicle, and the type of the vehicle is identified in the dimension of length according to the vehicle model data. The track is called according to the type to move the passer to a designated pass position, and the passer is controlled to perform a prompt operation to guide the vehicle to move toward the passer, detect the length of the vehicle and the processing position when it stops moving in the toll island, and between the processing position and the pass position When the processing position and the passing position are not adjacent, the track is called to control the passer to move toward the vehicle. When the processing position and the passing position are adjacent, the passer is called to perform a passing operation on the vehicle according to the length to allow the vehicle to pass. The track, identifier and passer are arranged on the toll island. The track can be driven to control the passer to approach the vehicle according to the type of vehicle divided by length, and the passer can also be controlled to guide the vehicle to approach it, realizing two-way running, making adaptive adjustment between the vehicle and the passer, improving the smoothness of the interaction between the user on the vehicle and the passer, improving the vehicle's passing efficiency, reducing the frequency of manual access, and greatly reducing costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A flow chart of a vehicle traffic guidance method provided in Embodiment 1 of the present invention;

[0029] Figure 2 A schematic diagram of a charging island design provided in the first embodiment of the present invention;

[0030] Figure 3 A structural block diagram of a vehicle traffic guidance device provided in Embodiment 2 of the present invention;

[0031] Figure 4 A schematic diagram of the structure of a computer device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0033] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can cover sequential implementations other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0034] Embodiment 1

[0035] See also Figure 1 , shows a flow chart of a vehicle traffic guidance method provided by Embodiment 1 of the present invention, the method can be executed by a vehicle traffic guidance device, the vehicle traffic guidance device can be implemented in the form of hardware and / or software, and the vehicle traffic guidance device can be configured in a computer device. Figure 1 As shown, the method includes:

[0036] Step 101: When a vehicle enters a toll island, a recognizer is called to collect vehicle model data.

[0037] In this embodiment, a toll station applied to a highway has multiple toll islands. An identifier is provided at the entrance of each toll island. When a vehicle enters the range of the identifier, the identifier collects the vehicle model data. Tracks are provided on each channel, and passes are provided on the tracks.

[0038] Applicable to highway toll stations, which can be expressways, national highways, cross-sea bridges, mountain tunnels, internal roads in industrial parks, certain scenic spots, etc.

[0039] A toll island is a specific area on a highway where tolls are collected or other traffic management operations are performed. There are usually one or more toll booths on the toll island, which are used to house a variety of vehicle detection equipment to ensure smooth and safe traffic and effectively manage the collection of tolls.

[0040] In the specific implementation, Figure 2As shown, the passer arranges a robot 203, a display 204, a barrier machine 205, and a license plate recognizer 206 in sequence. The distance between the robot 203 and the barrier machine 205 is 4 meters, and the minimum distance between the barrier machine 205 and the license plate recognizer 206 is 1 meter. A global camera 202 is arranged above the track 207, and the recognizer 201 is arranged at the entrance of the toll island. One track is arranged for one toll island. The order and distance of the arrangement of each device can more accurately identify and judge the incoming vehicles and speed up the passage efficiency.

[0041] Robot 203: An intelligent device with automated charging function, which can interact with users on the vehicle to complete charging operations and other tasks. For example, the entrance is a self-service card issuing robot and the exit is a self-service payment robot. Robot 203 is connected to the display 204, barrier machine 205 and license plate reader 206 through retractable wires, where the retractable wires are used to send control signals and power supply.

[0042] Identifier 201: It can usually be a recognition device such as a camera, a laser radar, an infrared sensor, a license plate recognition system OCR (Optical Character Recognition) and the like, which is used to automatically recognize the type of vehicle, for example, to distinguish different types of vehicles such as cars, buses, trucks, etc.

[0043] Display 204: A device for displaying information such as the amount of fees to be paid, so that users on the vehicle can understand the amount of fees to be paid.

[0044] Barrier machine 205: A device used to control the passage of vehicles, which can automatically raise or lower the barrier to open or close the passage.

[0045] License plate reader 206: installed at the rear of the toll island and used to photograph and recognize vehicle license plates.

[0046] Global camera 202: A camera device installed on the ceiling that is specifically used to capture and identify vehicle location information. Through image acquisition and analysis technology, it monitors the specific location and status of vehicles in a specific area in real time, providing key location data basis for the subsequent adaptive adjustment of toll-related equipment.

[0047] Track 207: It has a built-in motor and controller. A platform is arranged above track 207. The passer is installed on the platform of track 207. The length of track 207 is 20 meters. The platform can move up to 15 meters. According to the instructions issued by robot 203, it drives the other passers to slide. The fastest moving speed of the platform on track 207 can reach 2 meters / second.

[0048] In this embodiment, when a vehicle enters a toll island, the identifier identifies the vehicle and the collected vehicle type data is fed back to the pass for subsequent operations.

[0049] Step 102: Identify the vehicle type in the length dimension based on the vehicle model data.

[0050] In this embodiment, the identifier collects vehicle type data of the incoming vehicle, and the type of the incoming vehicle can be determined in the dimension of length based on the collected vehicle type data.

[0051] In this embodiment, the vehicle type data includes vehicle height, vehicle length, load value and other data, and the type of vehicle is determined based on the vehicle height in the length dimension.

[0052] Judging the vehicle type based on its length requires the entire vehicle to pass through the identifier, which will increase processing time and reduce efficiency. Judging the vehicle type based on its load value requires the installation of a vehicle load device to measure the weight of the incoming vehicle. This device needs to be installed in a specific area for accurate measurement, which will also increase processing time.

[0053] In a specific implementation, the vehicle height value is compared with a preset standard value. If the vehicle height value is less than or equal to the standard value, the type of the vehicle is determined to be a first model. The first model generally includes small and medium-sized vehicles such as sedans, SUVs (Sport Utility Vehicles), and vans.

[0054] If the vehicle height value is greater than the standard value, the type of the vehicle is determined to be the second type, which generally includes large vehicles such as trucks and construction vehicles.

[0055] Wherein, the length of the vehicle in the first model is less than the length of the vehicle in the second model.

[0056] Step 103: Call the track according to the type to move the passer to the designated pass position.

[0057] In this embodiment, according to the type of vehicle, the passer receives the type of vehicle to generate corresponding control instructions to drive the track to perform different operations, and the passer on the track slides to the designated pass position under the platform. The designated pass position refers to the position set according to different vehicle models, which can accurately and quickly identify the vehicle and perform the pass operation.

[0058] In this embodiment, the license plate recognizer is initially placed at the end of the island and does not move with other passers-by. When the robot cannot receive the license plate information collected by the license plate recognizer, the robot issues a control command to drive the license plate display to slide to a position 1 meter away from the barrier machine, thereby identifying the vehicle license plate.

[0059] If the type of vehicle is the first model, the passer will generate a first control instruction, and the first control instruction will be sent to the track through the industrial computer inside the robot, driving the track to move the passer to the designated passage position in the middle of the toll island.

[0060] The middle part of the toll island refers to half the distance between the entrance and exit of the toll island. The first type of vehicle is shorter in length and the time to identify its model is short. Therefore, it actively approaches the vehicle through the track to shorten its transaction time and achieve rapid passage. When it is at the peak of vehicle traffic, each time the first type of vehicle is identified, the position of the passer on the track is maintained to speed up the identification and passage of the next vehicle.

[0061] If the vehicle type is the second model, the passer will generate a second control instruction, and the second control instruction will be sent to the track through the industrial computer inside the robot, driving the track to move the passer to the designated passage position at the end of the toll island.

[0062] The tail end of the toll island refers to the area near the toll island exit. The second-type vehicle is relatively long. Driving the track to move the passer to the tail end of the toll island can leave a longer identification distance for the second-type vehicle, thereby realizing the ability to identify its vehicle type and reduce manual intervention. When it is at the peak of vehicle traffic, each time the second-type vehicle is identified, the passer on the track will be returned to its original position to speed up the identification and passage of the next vehicle.

[0063] Step 104: Control the pass device to perform a prompting operation to guide the vehicle to move toward the pass device.

[0064] In this embodiment, the cloud server receives information that the vehicle has entered the island, generates a control instruction and sends it to the pass device to control the pass device to perform prompt operations in two dimensions of sound and light to guide the vehicle to move toward the pass device.

[0065] In this embodiment, the cloud server receives the data of vehicle traffic, generates a third control instruction when the vehicle enters the toll island, and sends the third control instruction to the passer. The robot in the passer has a built-in light box and a speaker to play the specified audio data and start the lights in the specified mode to guide the vehicle to move toward the passer. The audio data is the words that the vehicle can drive to the vicinity of the robot in the passer, and the lights are flashing to attract the attention of the vehicle personnel.

[0066] A cloud server refers to a virtual server deployed in a cloud computing environment. It is usually deployed in multiple data centers and geographical locations to provide high availability and redundant backup to ensure the continuous availability of services. The cloud server receives data collected by the identifier and passcode to determine whether a vehicle has passed by, and can generate corresponding instructions to send to the passcode.

[0067] Step 105: Detect the length of the vehicle and the processing position when the vehicle stops moving in the toll island.

[0068] In this embodiment, when a vehicle enters the island, the length of the vehicle and the position of the vehicle parked in the toll island are detected so that the track can be driven to run according to the parking position of the vehicle, and the pass device on the track can be adapted to the position of the vehicle to complete the vehicle passage operation.

[0069] In this embodiment, the length of the vehicle and the processing position when it stops moving on the toll island are obtained through a global camera. The global camera is arranged above the track and installed on the top of the toll booth in the toll island to facilitate accurate identification of the vehicle's parking position.

[0070] In one embodiment of the present invention, step 105 may include the following steps:

[0071] Step 1051: Call the global camera to collect multiple frames of raw image data from the toll island.

[0072] In this embodiment, a global camera is used to collect multiple frames of original image data of a vehicle traveling on a toll island, so as to perform statistical analysis on the collected multiple frames of original image data.

[0073] Step 1052: Preprocess multiple frames of original image data to obtain candidate image data.

[0074] Preprocessing refers to a series of simple and basic operations on raw data before more complex data analysis or processing. In the field of image processing, preprocessing is to improve image quality, reduce noise, highlight specific features, or simplify image representation so that subsequent steps (such as feature extraction, classification, or recognition) can be performed more effectively.

[0075] In this embodiment, the process of performing preprocessing on the multiple frames of raw image data may include at least one of smoothing, binarization, edge detection, denoising, and improving the contrast of the effective area.

[0076] Among them, the denoising operation can use median filtering or Gaussian filtering to eliminate noise points and artifacts in multiple frames of original images, thereby reducing interference in subsequent processing steps.

[0077] Improving the contrast of the effective area can be achieved through histogram equalization or contrast enhancement methods to enhance the brightness and color contrast of important areas in multiple frames of original images, making the multiple frames of original images clearer and easier to analyze. These preprocessing steps can effectively optimize the multiple frames of original image data and generate candidate image data with more information and quality, which is helpful for subsequent analysis and application.

[0078] Step 1053 : when traversing multiple frames of candidate image data in sequence, matching feature points between two adjacent frames of candidate image data, and splicing two adjacent frames of candidate image data based on the feature points.

[0079] In this embodiment, when traversing multiple frames of candidate image data in chronological order, feature point matching is performed on two adjacent frames of candidate image data. This step uses feature point detection and descriptor matching technology in computer vision (such as SIFT (Scale-Invariant Feature Transform)) to find the common key feature points between the two frames. By using geometric transformations (such as homography transformations) or feature point-based registration algorithms, these feature points are mapped to the same coordinate system, thereby achieving splicing of two adjacent frames of candidate image data. This process can effectively and seamlessly integrate the information between consecutive frames, providing a basis for subsequent motion analysis, target tracking or scene reconstruction.

[0080] Step 1054: when it is detected that the vehicle is complete in the candidate image data, stop stitching two adjacent frames of candidate image data, and output the stitched candidate image data as target image data.

[0081] In this embodiment, a target detection algorithm (such as Faster R-CNN (Faster Region-Based Convolutional Neural Network)) is used to detect the vehicle position and bounding box in each frame, and the integrity of the vehicle is verified by the overlap, motion consistency, and shape and size consistency of the bounding box. When the vehicle is detected to be complete, the splicing of two adjacent frames of candidate image data is stopped, and the spliced ​​candidate image data is output as the final target image data. When the detected vehicle is incomplete, the splicing of two adjacent frames of candidate image data continues.

[0082] Step 1055: Detect the length of the vehicle in the target image data.

[0083] In this embodiment, the length of the vehicle is usually obtained by first using a target detection algorithm (such as Faster R-CNN) to detect the position of the vehicle's bounding box, and then calculating the length of the bounding box in the actual scene based on camera parameters or known scene size information. This is achieved through geometric reasoning or a conversion relationship from pixels to actual sizes.

[0084] In the specific implementation, the conversion ratio of the global camera for the toll island calibration is queried, the length of the vehicle in pixels is counted in the target image data, and the length of the vehicle in pixels is multiplied by the conversion ratio to obtain the actual length of the vehicle.

[0085] In the case of offline calibration, the conversion ratio refers to the mapping relationship between the global camera pixels and the actual distance, which is determined by the camera internal parameters and distortion parameters. In the toll island global camera, by detecting the pixel length of the vehicle and multiplying it by the conversion ratio, the length of the vehicle in the actual scene can be accurately measured without direct physical measurement, which improves efficiency and accuracy.

[0086] Step 1056: When it is detected in the multiple frames of target image data that the vehicle has stopped moving, the processing position of the vehicle at the toll island is identified based on the target image data.

[0087] In this embodiment, multiple frames of target image data are analyzed to detect whether the vehicle is moving or stopped. If the vehicle stops moving, its position information in the target image data can be further analyzed. For the location of the toll island, it can be identified and located through predefined areas or markers at the toll station, thereby determining whether the vehicle is parked at the designated processing location. This process combines motion detection and area recognition technology to achieve accurate positioning and recognition of the vehicle's parking position at the toll island.

[0088] Step 106: When the processing position and the passing position are not adjacent, call the track control passer to move toward the vehicle.

[0089] In this embodiment, if the processing position where the vehicle stops is not adjacent to the passing position, the passer issues a command to drive the platform on the track to operate so that the passer on the track is adjacent to the vehicle.

[0090] Non-adjacent means that the distance between the driver of the vehicle and the robot in the pass is not within a certain range, which is considered non-adjacent. If non-adjacent, the track is driven to control the pass to move toward the vehicle, realizing adaptive driver position, which is a more intelligent process.

[0091] Step 107: When the processing position is adjacent to the passing position, the passing device is called to perform a passing operation on the vehicle according to the length to allow the vehicle to pass.

[0092] In this embodiment, if the processing position where the vehicle stops is adjacent to the passing position, the pass device performs a passing operation on the vehicle according to the detected length of the vehicle to allow the vehicle to pass.

[0093] Adjacent means that the distance between the driver of the vehicle and the robot in the pass is within a certain range, and they are judged to be adjacent. If the positions are adjacent, the vehicle can be operated to pass.

[0094] In one embodiment of the present invention, the robot receives the license plate information collected by the license plate recognizer from the passing vehicles, and calculates the toll generated by the vehicle on the road according to the license plate information and the length of the vehicle. The cloud server also receives the license plate information and toll, sends a fourth instruction to the display to display the license plate information and toll, and sends a fifth instruction to the robot to guide the user of the vehicle on how much toll he needs to pay. When the user completes the payment, the robot drives the barrier machine to lift up to allow the vehicle to pass.

[0095] In the embodiment of the present invention, a toll station applied to a highway has multiple toll islands in the toll station, an identifier is provided at the entrance of each toll island, a track is provided on each channel, a passer is provided in the track, when a vehicle enters a toll island, the identifier is called to collect vehicle model data of the vehicle, the vehicle type is identified in the dimension of length according to the vehicle model data, the track is called to move the passer to a designated pass position according to the type, the passer is controlled to perform a prompt operation to guide the vehicle to move toward the passer, the length of the vehicle and the processing position when the vehicle stops moving in the toll island are detected, and the processing position and the pass position are compared. When the two positions are not adjacent, the track is called to control the passer to move toward the vehicle. When the processing position and the pass position are adjacent, the passer is called to perform a pass operation on the vehicle based on the length to allow the vehicle to pass. The track, identifier and passer are arranged on the toll island. The track can be driven to control the passer to approach the vehicle according to the type of vehicle divided by length, and the passer can also be controlled to guide the vehicle to approach it, realizing two-way travel, making adaptive adjustments between the vehicle and the passer, improving the smoothness of the interaction between the user on the vehicle and the passer, improving the vehicle's passage efficiency, reducing the frequency of manual access, and greatly reducing costs.

[0096] Embodiment 2

[0097] Figure 3 The schematic diagram of the structure of a vehicle traffic guiding device provided in the second embodiment of the present invention is applied to a toll station on a highway. The toll station has a plurality of toll islands. An identifier is provided at the entrance of each toll island. A track is provided on each channel. A pass device is provided in the track. Figure 3 As shown, the device comprises:

[0098] The vehicle model data collection module 301 is used to call the identifier to collect the vehicle model data when the vehicle enters a certain toll island;

[0099] A vehicle type identification module 302, used to identify the type of the vehicle in the dimension of length according to the vehicle type data;

[0100] A track moving module 303, used to call the track according to the type to move the passer to a specified passing position;

[0101] A passer execution module 304, used to control the passer to execute a prompt operation to guide the vehicle to move toward the passer;

[0102] a processing position detection module 305, for detecting the length of the vehicle and the processing position when the vehicle stops moving in the toll island;

[0103] A position non-adjacent module 306 is used to call the track to control the passer to move toward the vehicle when the processing position and the pass position are not adjacent;

[0104] The position adjacent module 307 is used to call the passer to perform a passing operation on the vehicle according to the length to allow the vehicle to pass when the processing position is adjacent to the passing position.

[0105] In one embodiment of the present invention, the vehicle type data includes a vehicle height value, and the vehicle type identification module 302 includes:

[0106] A vehicle height comparison module, used for comparing the vehicle height value with a preset standard value;

[0107] a first model determination module, configured to determine that the type of the vehicle is a first model if the vehicle height value is less than or equal to the standard value;

[0108] a second model determination module, configured to determine that the type of the vehicle is a second model if the vehicle height value is greater than the standard value;

[0109] Wherein, the length of the vehicle in the first model is smaller than the length of the vehicle in the second model.

[0110] In one embodiment of the present invention, the track movement module 303 includes:

[0111] A first control instruction generating module, configured to generate a first control instruction if the type is a first model;

[0112] A first control instruction sending module, used for sending the first control instruction to the track to move the passer to a designated passing position in the middle of the toll island;

[0113] A second control instruction generating module, configured to generate a second control instruction if the type is a second model;

[0114] The second control instruction sending module is used to send the second control instruction to the track to move the passer to the designated passing position at the tail of the toll island.

[0115] In one embodiment of the present invention, it is characterized in that a global camera is arranged above the track, and the processing position detection module 305 includes:

[0116] A raw image data acquisition module, used for calling the global camera to collect multiple frames of raw image data from the toll island;

[0117] An original image data preprocessing module, used to perform preprocessing on multiple frames of the original image data to obtain candidate image data; the preprocessing includes at least one of denoising and improving the contrast of an effective area;

[0118] A feature point matching module, used for matching feature points of two adjacent frames of candidate image data when sequentially traversing multiple frames of candidate image data, and splicing two adjacent frames of candidate image data according to the feature points;

[0119] a target image data output module, configured to stop splicing two adjacent frames of the candidate image data and output the spliced ​​candidate image data as target image data when the vehicle is detected to be intact in the candidate image data;

[0120] A vehicle length detection module, used to detect the length of the vehicle in the target image data;

[0121] The target image data recognition module is used to identify the processing position of the vehicle parked on the toll island based on the target image data when it is detected in multiple frames of the target image data that the vehicle has stopped moving.

[0122] In one embodiment of the present invention, the vehicle length detection module includes:

[0123] A conversion ratio query module, used to query the conversion ratio of the global camera to the toll island calibration;

[0124] A length statistics module, used for counting the length of the vehicle in pixels in the target image data;

[0125] The actual length acquisition module is used to multiply the length of the vehicle in pixels by the conversion ratio to obtain the actual length of the vehicle.

[0126] In one embodiment of the present invention, the passer arranges a robot, a display, a barrier machine and a license plate reader in sequence.

[0127] In one embodiment of the present invention, the passer execution module 304 includes:

[0128] A third control instruction generating module, used to generate a third control instruction;

[0129] The third control instruction sending module is used to send the third control instruction to the robot to play the specified audio data and start the light of the specified mode to guide the vehicle to move towards the passer.

[0130] In one embodiment of the present invention, the location neighbor module 307 includes:

[0131] A license plate information receiving module, used to receive the license plate information collected by the license plate recognizer on the vehicle;

[0132] A toll calculation module, used for calculating the toll incurred by the vehicle on the highway according to the license plate information and the length;

[0133] A control instruction generating module, used for generating a fourth control instruction and a fifth control instruction according to the license plate information and the toll;

[0134] A fourth control instruction sending module, used for sending the fourth control instruction to the display to display the license plate information and the toll;

[0135] a fifth control instruction sending module, used for sending the fifth control instruction to the robot to guide the user in the vehicle to pay the toll;

[0136] a sixth control instruction generating module, configured to generate a sixth control instruction when the user in the vehicle completes paying the toll;

[0137] The sixth instruction sending module is used to send the sixth control instruction to the barrier machine to control the barrier machine to lift up and allow the vehicle to pass.

[0138] The vehicle traffic guidance device provided in the embodiment of the present invention can execute the vehicle traffic guidance method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the vehicle traffic guidance method.

[0139] Embodiment 3

[0140] See also Figure 4 , shows a schematic diagram of the structure of a computer device provided by an embodiment of the present invention. The computer device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, blade servers, mainframe computers, and other suitable computers. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0141] like Figure 4As shown, the computer device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the computer device 10 can also be stored. The processor 11, ROM 12 and RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0142] A number of components in the computer device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the computer device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0143] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the vehicle traffic guidance method.

[0144] In some embodiments, the vehicle traffic guidance method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the computer device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the vehicle traffic guidance method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the vehicle traffic guidance method in any other appropriate manner (e.g., by means of firmware).

[0145] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0146] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0147] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0148] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0149] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0150] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0151] Embodiment 4

[0152] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the vehicle traffic guidance method provided by any embodiment of the present invention is implemented.

[0153] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0154] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0155] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A vehicle traffic guidance method, characterized in that: The method is applied to a toll station on a highway, wherein the toll station has a plurality of toll islands, an identifier is provided at the entrance of each toll island, a track is provided on each channel, and a passer is provided in the track, and the method comprises: When a vehicle enters a toll island, calling the identifier to collect vehicle model data of the vehicle; Identifying the type of the vehicle in the dimension of length according to the vehicle model data; Calling the track according to the type to move the passer to a designated pass position; Controlling the pass device to perform a prompting operation to guide the vehicle to move toward the pass device; detecting the length of the vehicle and the processing position when the vehicle stops moving in the toll island; When the processing position and the passing position are not adjacent, calling the track to control the passer to move toward the vehicle; When the processing position is adjacent to the passing position, the passing device is called to perform a passing operation on the vehicle according to the length to allow the vehicle to pass.

2. The method according to claim 1, characterized in that The vehicle model data includes a vehicle height value, and the vehicle type identification based on the vehicle model data in the dimension of length includes: Comparing the vehicle height value with a preset standard value; If the vehicle height value is less than or equal to the standard value, determining the type of the vehicle is the first model; If the vehicle height value is greater than the standard value, determining that the type of the vehicle is a second model; Wherein, the length of the vehicle in the first model is smaller than the length of the vehicle in the second model.

3. The method according to claim 2, characterized in that The step of calling the track according to the type to move the passer to a designated pass position includes: If the type is the first model, generating a first control instruction; Sending the first control instruction to the track to move the passer to a designated pass position in the middle of the toll island; If the type is the second model, generating a second control instruction; The second control instruction is sent to the track to move the passer to a designated passing position at the tail end of the toll island.

4. The method according to any one of claims 1 to 3, characterized in that A global camera is arranged above the track, and the detection of the length of the vehicle and the processing position when the vehicle stops moving in the toll island includes: Calling the global camera to collect multiple frames of raw image data from the toll island; Performing preprocessing on the multiple frames of the original image data to obtain candidate image data; the preprocessing includes at least one of denoising and improving the contrast of the effective area; When traversing the plurality of frames of candidate image data in sequence, matching feature points of two adjacent frames of candidate image data, and splicing the two adjacent frames of candidate image data according to the feature points; When the vehicle is detected to be complete in the candidate image data, stop stitching two adjacent frames of the candidate image data and output the stitched candidate image data as target image data; detecting a length of the vehicle in the target image data; When it is detected in the plurality of frames of the target image data that the vehicle has stopped moving, a processing position where the vehicle is parked at the toll island is identified based on the target image data.

5. The method according to claim 4, characterized in that The detecting the length of the vehicle in the target image data comprises: Querying the conversion ratio of the global camera to the toll island calibration; Counting the length of the vehicle in pixels in the target image data; The actual length of the vehicle is obtained by multiplying the length of the vehicle in pixels by the conversion ratio.

6. The method according to any one of claims 1 to 4, characterized in that The passer arranges a robot, a display, a barrier machine and a license plate recognizer in sequence.

7. The method according to claim 6, characterized in that The controlling the pass device to perform a prompting operation to guide the vehicle to move toward the pass device includes: generating a third control instruction; The third control instruction is sent to the robot to play the specified audio data and start the light of the specified mode to guide the vehicle to move toward the passer.

8. The method according to claim 6, characterized in that The calling of the pass device to perform a passing operation on the vehicle according to the length so as to allow the vehicle to pass includes: Receiving license plate information collected from the vehicle by the license plate recognizer; Calculate the toll incurred by the vehicle on the highway according to the license plate information and the length; generating a fourth control instruction and a fifth control instruction according to the license plate information and the toll; sending the fourth control instruction to the display to display the license plate information and the toll; sending the fifth control instruction to the robot to guide the user in the vehicle to pay the toll; When the user in the vehicle completes paying the toll, generating a sixth control instruction; The sixth control instruction is sent to the barrier machine to control the barrier machine to lift up and allow the vehicle to pass.

9. A computer device, characterized in that: include: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle traffic guidance method as described in any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the vehicle traffic guidance method as described in any one of claims 1 to 8 is implemented.

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