A control method, system and medium for automatically opening and closing doors at unmanned vehicle stations

Abstract

The present invention relates to a control method, system, and medium for automatically opening and closing doors of unmanned vehicle stations. The method comprises the following steps: U1. When a vehicle stops at a station, the vehicle obtains internal and external image data information based on an onboard camera, obtains external point cloud data information based on an onboard laser radar, and obtains pedal gravity data information based on an onboard retractable inductive gravity pedal; U2. Based on the internal and external image data information and the external point cloud data information, a feature extraction and classification algorithm is used to output the number of passengers getting on and off the vehicle at the station; U3. Based on the number of passengers getting on and off the vehicle at the station and the pedal gravity data information, a greedy algorithm is used to output vehicle door opening signal data information and vehicle door closing signal data information. The present invention not only eliminates the need for manual intervention and saves labor costs, but also automatically opens and closes doors at the station according to the number of passengers, making it more user-friendly and improving the passengers' riding experience.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned vehicles, and in particular to a control method, system and medium for automatically opening and closing doors at an unmanned vehicle station. Background Art

[0002] With the development of scientific and technological innovation, not only can the management of environment and resources be improved, but also the quality of social services and the quality of society can be improved, which will contribute to social harmony and stability. Unmanned vehicles have gradually become a part of our daily lives, not only providing convenience, but also enabling a higher level of economic, living and social development.

[0003] Currently, driverless minibuses and other public transportation vehicles have the problem of manually closing the doors after they automatically open at a stop, and manually restarting the vehicle's automatic driving to start leaving the station. This operation makes it impossible for the driverless vehicles to complete the entire automatic driving operation process without human intervention. Summary of the Invention

[0004] In view of the above problems, the present invention provides a control method, system and medium for automatically opening and closing doors of unmanned vehicle stations. Not only does it require no human intervention and save labor costs, but it also automatically opens and closes doors at the station according to the number of passengers, which is more humane and improves the passengers' riding experience.

[0005] In order to achieve the above-mentioned and other related purposes, the present invention provides the following technical solutions:

[0006] A method for controlling automatic opening and closing of doors at an unmanned vehicle station, the method comprising:

[0007] U1. The vehicle stops at a station and acquires interior and exterior image data using the onboard camera, exterior point cloud data using the onboard lidar, and pedal gravity data using the onboard retractable gravity-sensing pedal.

[0008] U2. Based on the vehicle's internal and external image data and the vehicle's external point cloud data, a feature extraction and classification algorithm is used to output the number of passengers getting on and off the bus within the station;

[0009] U3. Based on the number of passengers getting on and off the vehicle at the station and the pedal gravity data information, a greedy algorithm is used to output the vehicle door opening signal data information and the vehicle door closing signal data information.

[0010] Furthermore, in step U3, the greedy algorithm includes:

[0011] U31. The number of passengers getting on and off the station and the pedal gravity data information are classified separately, and the number of passengers getting on the station and the corresponding pedal gravity data information, the number of passengers getting off the station and the corresponding pedal gravity data information;

[0012] U32. Establish a first relationship function Q based on the number of passengers boarding the bus at the station and the corresponding pedal gravity data information.

[0013] Q=a1m 2 +b1m+c1, where m is the number of passengers boarding at each moment in the station, Q is the pedal gravity data corresponding to boarding, a1 is a constant parameter, b1 is a constant parameter, and c1 is a constant parameter;

[0014] U33. According to the number of passengers getting off the station and the corresponding pedal gravity data information, establish a second relationship function J,

[0015] J=a2n 2 +b2n+c2, where n is the number of passengers getting off at each moment in the station, J is the pedal gravity data corresponding to getting off, a2 is a constant parameter, b2 is a constant parameter, and c2 is a constant parameter;

[0016] U34. Based on the first relationship function Q and the second relationship function J, construct a weight analysis function E, E = αmin{Q} + βmin{J}, where α is the weight value corresponding to the first relationship function, β is the weight value corresponding to the second relationship function, min{Q} is the minimum value of the first relationship, and min{J} is the minimum value of the second relationship.

[0017] Furthermore, the sum of the weight value α corresponding to the first relationship function and the weight value β corresponding to the second relationship is 1.

[0018] Furthermore, the weight value α corresponding to the first relationship function has a value range of (0, 1), and the weight value β corresponding to the second relationship has a value range of (0, 1).

[0019] Furthermore, preset thresholds c1 and c2 are set and 0<c1<c2. If the value of the weight analysis function E is less than the preset threshold c1, the door is opened; if the value of the weight analysis function E is between c1 and c2, the door is closed.

[0020] Furthermore, if the value of the weight analysis function E is greater than c2, the vehicle reaches the expected number of passengers and enters the next station.

[0021] Furthermore, in step U2, the feature extraction and classification algorithm includes:

[0022] U21. The vehicle interior and exterior image data information and the vehicle exterior point cloud data information are subjected to culling and noise reduction processing, and the processed image data information and point cloud data information are output;

[0023] U22. Based on the processed image data information, image feature extraction is performed and feature data information is output. Based on the processed point cloud data information, feature vector extraction is performed and point cloud feature data information is output.

[0024] U23. Perform identification, classification and statistics based on the feature data information and the point cloud feature data information, and output information on the number of passengers getting on and off the bus at the station.

[0025] In order to achieve the above-mentioned and other related purposes, the present invention also provides a control system for automatically opening and closing doors at an unmanned vehicle station, the system comprising:

[0026] An autonomous driving controller, used to control the vehicle's autonomous driving and process vehicle status data information;

[0027] A body control module, connected to the automatic driving controller, for driving the vehicle and opening and closing doors;

[0028] A human-machine interface, connected to the automatic driving controller, for receiving vehicle status data information and displaying vehicle status;

[0029] The PCU module is connected to the automatic driving controller and is used to control the start or stop of the retractable gravity-sensing pedal and receive pedal gravity data information.

[0030] Furthermore, the system also includes a voice prompt module and an early warning module for reminding and warning passengers when getting on and off the bus.

[0031] In order to achieve the above-mentioned and other related purposes, the present invention also provides a computer-readable storage medium, which stores a computer program programmed or configured to execute any one of the control methods for automatically opening and closing doors at unmanned vehicle stations.

[0032] The present invention has the following positive effects:

[0033] 1. The present invention adopts a greedy algorithm to analyze and process the number of passengers getting on and off the bus at the station and the pedal gravity data information, thereby obtaining the vehicle door opening and closing signal data information. It can not only meet the needs of most passengers, but also does not require manual intervention, saving labor costs.

[0034] 2. The present invention transmits the vehicle door opening and closing data information to the body control module through the automatic driving controller. At the same time, the PCU module controls the retractable gravity-sensing pedal to open or close, which is more humane and improves the passengers' riding experience.

[0035] 3. The present invention realizes automatic opening and closing of vehicle doors through a vehicle-mounted camera, a vehicle-mounted laser radar and a vehicle-mounted retractable gravity-sensing pedal, which is convenient for operation and promotion and has good industrial prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 Schematic diagram of the process of the present invention;

[0037] Figure 2 This is a flow chart of the greedy algorithm of the present invention. DETAILED DESCRIPTION

[0038] The following description of exemplary embodiments of the present disclosure is made in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding. These details should be considered as merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0039] Example 1: Figure 1 As shown, a method for controlling automatic opening and closing of doors at an unmanned vehicle station, the method comprising:

[0040] U1. The vehicle stops at a station and acquires interior and exterior image data using the onboard camera, exterior point cloud data using the onboard lidar, and pedal gravity data using the onboard retractable gravity-sensing pedal.

[0041] U2. Based on the vehicle's internal and external image data and the vehicle's external point cloud data, a feature extraction and classification algorithm is used to output the number of passengers getting on and off the bus within the station;

[0042] U3. Based on the number of passengers getting on and off the vehicle at the station and the pedal gravity data information, a greedy algorithm is used to output the vehicle door opening signal data information and the vehicle door closing signal data information.

[0043] In this embodiment, if Figure 2 As shown, in step U3, the greedy algorithm includes:

[0044] U31. The number of passengers getting on and off the station and the pedal gravity data information are classified separately, and the number of passengers getting on the station and the corresponding pedal gravity data information, the number of passengers getting off the station and the corresponding pedal gravity data information;

[0045] U32. Establish a first relationship function Q based on the number of passengers boarding the bus at the station and the corresponding pedal gravity data information.

[0046] Q=a1m 2 +b1m+c1, where m is the number of passengers boarding at each moment in the station, Q is the pedal gravity data corresponding to boarding, a1 is a constant parameter, b1 is a constant parameter, and c1 is a constant parameter;

[0047] U33. According to the number of passengers getting off the station and the corresponding pedal gravity data information, establish a second relationship function J,

[0048] J=a2n 2 +b2n+c2, where n is the number of passengers getting off at each moment in the station, J is the pedal gravity data corresponding to getting off, a2 is a constant parameter, b2 is a constant parameter, and c2 is a constant parameter;

[0049] U34. Based on the first relationship function Q and the second relationship function J, construct a weight analysis function E, E = αmin{Q} + βmin{J}, where α is the weight value corresponding to the first relationship function, β is the weight value corresponding to the second relationship function, min{Q} is the minimum value of the first relationship, and min{J} is the minimum value of the second relationship.

[0050] In this embodiment, the sum of the weight value α corresponding to the first relationship function and the weight value β corresponding to the second relationship is 1.

[0051] In this embodiment, the weight value α corresponding to the first relationship function has a value range of (0, 1), and the weight value β corresponding to the second relationship has a value range of (0, 1).

[0052] In this embodiment, preset thresholds c1 and c2 are set and 0<c1<c2. If the value of the weight analysis function E is less than the preset threshold c1, the door is opened; if the value of the weight analysis function E is between c1 and c2, the door is closed.

[0053] In this embodiment, if the value of the weight analysis function E is greater than c2, the vehicle has reached the expected number of passengers and enters the next station.

[0054] Example 2: Based on the control method for automatically opening and closing doors of an unmanned vehicle station in Example 1, the present invention is further described and illustrated below.

[0055] Any reference to memory, storage, database or other media used in the embodiments provided herein may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0056] In this embodiment, a method for controlling the automatic opening and closing of doors at an unmanned vehicle station is provided. In step U2, the feature extraction and classification algorithm includes:

[0057] U21. The vehicle interior and exterior image data information and the vehicle exterior point cloud data information are subjected to culling and noise reduction processing, and the processed image data information and point cloud data information are output;

[0058] U22. Based on the processed image data information, image feature extraction is performed and feature data information is output. Based on the processed point cloud data information, feature vector extraction is performed and point cloud feature data information is output.

[0059] U23. Perform identification, classification and statistics based on the feature data information and the point cloud feature data information, and output information on the number of passengers getting on and off the bus at the station.

[0060] In order to achieve the above-mentioned and other related purposes, the present invention also provides a control system for automatically opening and closing doors at an unmanned vehicle station, the system comprising:

[0061] An autonomous driving controller, used to control the vehicle's autonomous driving and process vehicle status data information;

[0062] A body control module, connected to the automatic driving controller, for driving the vehicle and opening and closing doors;

[0063] A human-machine interface, connected to the automatic driving controller, for receiving vehicle status data information and displaying vehicle status;

[0064] The PCU module is connected to the automatic driving controller and is used to control the start or stop of the retractable gravity-sensing pedal and receive pedal gravity data information.

[0065] In this embodiment, the system further includes a voice prompt module and an early warning module for reminding and warning passengers when getting on and off the bus.

[0066] When the autonomous vehicle is 50 meters from the next stop, the autonomous driving controller transmits this distance information to the human-machine interface (HMI) via the CAN line. The HMI then announces the impending arrival of the stop and urges passengers to hold on tight and prepare to exit. Upon arrival, the autonomous driving controller transmits the vehicle's arrival information to the HMI, BCM, and PCU. The HMI announces the arrival, the BCM automatically opens the vehicle door, and the PCU automatically deploys the step. During stops, the autonomous driving controller's perception module continuously uses internal and external cameras and an external LiDAR to detect passengers. It monitors for passengers within 1 meter of the door, standing passengers inside, and waving passengers within 10 meters of the vehicle. Based on these three scenarios, it determines whether any passengers need to get on or off. If the autonomous driving controller's perception module determines that no one is getting on or off under all three conditions, and the PCU detects that no one is on the step for 5 seconds using gravity sensing, the HMI determines that no passengers are getting on or off and announces that the door is about to close and asks passengers to hold on tight and be careful. The BCM then closes the door.

[0067] After the automatic driving controller detects that the door is closed, it starts to automatically drive out of the station, and the human-machine interface simultaneously broadcasts the next station information.

[0068] In order to achieve the above-mentioned and other related purposes, the present invention also provides a computer-readable storage medium, which stores a computer program programmed or configured to execute any one of the control methods for automatically opening and closing doors at unmanned vehicle stations.

[0069] In summary, the present invention not only does not require manual intervention and saves labor costs, but also automatically opens and closes doors at stations according to the number of passengers, which is more humane and improves the passengers' riding experience.

[0070] The above specific embodiments do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.

Claims

1. A method for controlling the automatic opening and closing of doors at an unmanned vehicle station, characterized in that: The method comprises: U1. The vehicle stops at a station and acquires interior and exterior image data using the onboard camera, exterior point cloud data using the onboard lidar, and pedal gravity data using the onboard retractable gravity-sensing pedal. U2. Based on the vehicle's internal and external image data and the vehicle's external point cloud data, a feature extraction and classification algorithm is used to output the number of passengers getting on and off the bus within the station; U3 according to the number of passengers getting on and off the station and the pedal gravity data information, using a greedy algorithm, output vehicle door opening signal data information and vehicle door closing signal data information; In step U3, the greedy algorithm includes: U31. The number of passengers getting on and off the station and the pedal gravity data information are classified separately, and the number of passengers getting on the station and the corresponding pedal gravity data information, the number of passengers getting off the station and the corresponding pedal gravity data information; U32. Establish a first relationship function Q based on the number of passengers boarding the bus at the station and the corresponding pedal gravity data information. Q=a1m 2 +b1m+c1, where m is the number of passengers boarding at each moment in the station, Q is the pedal gravity data corresponding to boarding, a1 is a constant parameter, b1 is a constant parameter, and c1 is a constant parameter; U33. According to the number of passengers getting off the station and the corresponding pedal gravity data information, establish a second relationship function J, J=a2n 2 +b2n+c2, where n is the number of passengers getting off at each moment in the station, J is the pedal gravity data corresponding to getting off, a2 is a constant parameter, b2 is a constant parameter, and c2 is a constant parameter; U34. Based on the first relationship function Q and the second relationship function J, construct a weight analysis function E, E = αmin{Q} + βmin{J}, where α is the weight value corresponding to the first relationship function, β is the weight value corresponding to the second relationship function, min{Q} is the minimum value of the first relationship, and min{J} is the minimum value of the second relationship; set preset thresholds c1 and c2 and 0﹤c1﹤c2, if the value of the weight analysis function E is less than the preset threshold c1, the door is opened, if the value of the weight analysis function E is between c1 and c2, the door is closed; if the value of the weight analysis function E is greater than c2, the vehicle reaches the expected number of passengers and the vehicle enters the next station.

2. The method for controlling automatic door opening and closing at an unmanned vehicle station according to claim 1, characterized in that: The sum of the weight value α corresponding to the first relationship function and the weight value β corresponding to the second relationship is 1.

3. The method for controlling automatic door opening and closing at an unmanned vehicle station according to claim 2, characterized in that: The weight value α corresponding to the first relationship function has a value range of (0, 1), and the weight value β corresponding to the second relationship has a value range of (0, 1).

4. The control method for automatic door opening and closing at an unmanned vehicle station according to claim 1, characterized in that: In step U2, the feature extraction and classification algorithm includes: U21. The vehicle interior and exterior image data information and the vehicle exterior point cloud data information are subjected to culling and noise reduction processing, and the processed image data information and point cloud data information are output; U22. Based on the processed image data information, image feature extraction is performed, and feature data information is output. Based on the processed point cloud data information, feature vector extraction is performed, and point cloud feature data information is output; U23. Perform identification, classification and statistics based on the feature data information and the point cloud feature data information, and output information on the number of passengers getting on and off the bus at the station.

5. A control system for automatic door opening and closing at an unmanned vehicle station, characterized in that: A method for controlling the automatic opening and closing of doors at an unmanned vehicle station according to any one of claims 1 to 4, the system comprising: an automatic driving controller for controlling the automatic driving of the vehicle and processing vehicle status data information; A body control module, connected to the automatic driving controller, for driving the vehicle and opening and closing doors; A human-machine interface, connected to the automatic driving controller, for receiving vehicle status data information and displaying vehicle status; The PCU module is connected to the automatic driving controller and is used to control the start or stop of the retractable gravity-sensing pedal and receive pedal gravity data information.

6. The control system for automatic door opening and closing at an unmanned vehicle station according to claim 5, characterized in that: The system also includes a voice prompt module and an early warning module for reminding and warning passengers when getting on and off the bus.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program that is programmed or configured to execute the control method for automatically opening and closing doors at an unmanned vehicle station as described in any one of claims 1 to 4.

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