Intelligent driving module instant leasing system and method based on distributed shared docking station

Abstract

The invention relates to an intelligent driving module instant leasing system and method based on a distributed shared dock, and the system comprises an intelligent driving module which is an integrated physical unit, and the interior of the intelligent driving module comprises a laser radar, a camera, a millimeter wave radar, and a GNSS / IMU integrated navigation system; the shared docking station comprises a storage unit, a mechanical arm unit, a charging unit and a control unit, the storage unit is used for storing the multiple intelligent driving modules, and the mechanical arm unit carries a visual system and a customized clamp and is used for accurately grabbing and mounting / dismounting the modules; the charging unit is used for performing wireless or wired charging on the modules stored in the docking station, and the control unit is used for receiving a cloud instruction and controlling the mechanical arm to complete automatic operation. The method greatly reduces the first use cost of the user, is expected to accelerate the popularization of the automatic driving technology, and solves the problem that the vehicle hardware of the user is solidified and cannot enjoy the continuous technology upgrade.

Description

Technical Field

[0001] This invention relates to the field of autonomous driving technology, and in particular to an instant rental system and method for intelligent driving modules based on a distributed shared docking station. Background Technology

[0002] With the development of autonomous driving technology, its high cost has become a major obstacle to its widespread adoption. Currently, solutions fall into two categories: Pre-installed mass production: Selling the autonomous driving system as part of the whole vehicle is costly, and technological iterations will cause the vehicle to depreciate rapidly.

[0003] Aftermarket retrofitting: Permanently installing autonomous driving systems on specific fleets (such as logistics trucks), resulting in low equipment utilization and a long investment payback period.

[0004] Existing sharing economy models (such as shared bicycles and shared power banks) have successfully separated the right to use high-value items from ownership, greatly lowering the barrier to entry for users. However, applying this model to the field of large-scale, sophisticated, and high-value autonomous driving hardware still faces many technical bottlenecks.

[0005] In the prior art, Chinese patent (application number: 202510587614.2, publication number: CN 120494386A) discloses a shared ride system and method for driverless vehicles, including obtaining user-inputted ride price, starting point, and destination point information to generate ride request information; matching the nearest available vehicle to the starting point based on the ride request information and generating a dispatch instruction; after receiving the dispatch instruction, the vehicle moves to the starting point, and after confirming the user's identity through biometrics, the user is transported to the destination point; after the vehicle reaches the destination point, a potential ride demand parking spot is allocated to the vehicle based on historical ride data, and the vehicle is moved to the potential ride demand parking spot. The intelligent driving module in this solution is non-removable, fixed to the vehicle, and has a low utilization rate. Summary of the Invention

[0006] In view of the above problems, the present invention provides an instant rental system and method for intelligent driving modules based on distributed shared docking stations, which not only greatly reduces the initial cost for users and is expected to accelerate the popularization of autonomous driving technology, but also solves the problem of users' vehicles having fixed hardware and being unable to enjoy continuous technology upgrades.

[0007] To achieve the above and other related objectives, the present invention provides the following technical solution: A smart driving module instant rental system based on a distributed shared docking station, the system comprising: The intelligent driving module is an integrated physical unit. The internal components of the intelligent driving module include a lidar, a camera, a millimeter-wave radar, a GNSS / IMU integrated navigation system, a main control computing unit, a vehicle control unit, a battery module, and a 4G / 5G communication module. The external components of the intelligent driving module are designed with standardized mechanical quick-release interfaces and electrical communication interfaces. The shared docking station includes a storage unit, a robotic arm unit, a charging unit, and a control unit. The storage unit is used to store multiple intelligent driving modules. The robotic arm unit is equipped with a vision system and customized grippers for precise grasping and installation / removal of modules. The charging unit is used to wirelessly or wired charge the modules stored in the docking station. The control unit is used to receive cloud commands and control the robotic arm to complete automated operations. The vehicle-side adapter includes a mechanical locking mechanism that matches the intelligent driving module and a universal vehicle bus interface for physical and electrical connection with the intelligent driving module; A cloud service platform is connected to the shared docking station for monitoring and management.

[0008] Furthermore, the cloud service platform includes a user APP backend unit, which is used to process user registration, reservation, payment, and unlocking requests.

[0009] Furthermore, the cloud service platform includes an inventory and scheduling management unit, which is used to monitor the health status and inventory quantity of the shared docking station and perform intelligent allocation.

[0010] Furthermore, the cloud service platform includes a remote monitoring and assistance unit, which provides data support and a remote manual takeover interface.

[0011] Furthermore, the remote service platform includes a billing unit, which generates a bill based on usage duration and mileage.

[0012] Furthermore, the intelligent driving module quickly calibrates the extrinsic parameters of the sensors through short-distance driving and data fusion algorithms.

[0013] Furthermore, the process of quickly calibrating the sensor's extrinsic parameters through short-distance driving and data fusion algorithms includes: M1. When the vehicle travels a short distance, it acquires real-time positioning data based on the vehicle's GNSS / IMU integrated navigation system, real-time point cloud data of the road based on the vehicle's lidar, real-time image data of the road based on the vehicle's camera, and real-time distance data between the vehicle and obstacles based on the vehicle's millimeter-wave radar. M2. Based on the point cloud data of the road, the image data of the road, and the distance data between vehicles and obstacles, a multi-sensor data fusion function G is constructed. , Where x is the point cloud data of the road, y is the image data of the road, z is the distance data between the vehicle and the obstacle, f is the feature function of the road point cloud, g is the feature function of the road image, h is the feature function of the distance between the vehicle and the obstacle, and α, β and γ are weighting coefficients. The data from multiple sensors are fused to obtain the fused multi-sensor data information. M3. Based on the fused multi-sensor data and the vehicle positioning data, a matching model between vehicle positioning and multi-sensor data is constructed, and the extrinsic parameters of the sensors are optimized to obtain the optimized extrinsic parameter data.

[0014] Furthermore, the method of quickly calibrating the sensor's extrinsic parameters through short-distance driving and data fusion algorithms also includes: M4. Based on the optimized sensor extrinsic data, evaluate whether the sensor extrinsic parameters have converged. If they have converged, the sensor extrinsic parameter calibration is completed; otherwise, return to step M3.

[0015] Furthermore, the construction of the vehicle positioning and multi-sensor data matching model involves optimizing the initial extrinsic parameter estimation of each sensor in the current vehicle positioning based on the residual of the multi-sensor fusion data before and after vehicle positioning, thereby obtaining the optimized sensor extrinsic parameter data information.

[0016] To achieve the above and other related objectives, the present invention also provides a method for applying to any of the claims of the intelligent driving module instant rental system based on a distributed shared docking station, the method comprising: Users can reserve the intelligent driving module at a nearby shared docking station through the app; Users drive their vehicles into designated parking spaces at the shared docking station; The APP sends a command, and the robotic arm of the shared docking station automatically installs the intelligent driving module onto the vehicle adapter; The intelligent driving module performs a power-on self-test and initiates a self-calibration process; Once calibration is successful, the user's vehicle acquires autonomous driving capabilities, and the system begins billing. The user drives to a shared docking station near their destination; The robotic arm automatically disassembles the intelligent driving module and returns it to the warehouse via the app, ending the billing process.

[0017] The present invention has the following positive effects: This invention transforms autonomous driving from "selling hardware" to "providing services," greatly reducing the initial cost for users and potentially accelerating the popularization of autonomous driving technology. Furthermore, a single intelligent driving module can serve countless vehicles, with a utilization rate far exceeding that of fixed installations, creating greater economic value. Users do not need to bear the risk of hardware depreciation and can always enjoy the latest version of autonomous driving services, achieving "always new and exciting." Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the system framework of the present invention; Figure 2 This is a flowchart illustrating the short-distance driving and data fusion algorithm of the present invention; Figure 3 This is a schematic diagram of the method flow of the present invention. Detailed Implementation

[0019] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0020] Example 1: As Figure 1 As shown, an instant rental system for intelligent driving modules based on a distributed shared docking station is disclosed. The system includes: The intelligent driving module is an integrated physical unit. The internal components of the intelligent driving module include a lidar, a camera, a millimeter-wave radar, a GNSS / IMU integrated navigation system, a main control computing unit, a vehicle control unit, a battery module, and a 4G / 5G communication module. The external components of the intelligent driving module are designed with standardized mechanical quick-release interfaces and electrical communication interfaces. The shared docking station includes a storage unit, a robotic arm unit, a charging unit, and a control unit. The storage unit is used to store multiple intelligent driving modules. The robotic arm unit is equipped with a vision system and customized grippers for precise grasping and installation / removal of modules. The charging unit is used to wirelessly or wired charge the modules stored in the docking station. The control unit is used to receive cloud commands and control the robotic arm to complete automated operations. The vehicle-side adapter includes a mechanical locking mechanism that matches the intelligent driving module and a universal vehicle bus interface for physical and electrical connection with the intelligent driving module; A cloud service platform is connected to the shared docking station for monitoring and management.

[0021] In this embodiment, the cloud service platform includes a user APP backend unit, which is used to process user registration, reservation, payment and unlocking requests.

[0022] In this embodiment, the cloud service platform includes an inventory and scheduling management unit, which is used to monitor the health status and inventory quantity of the shared docking station and perform intelligent allocation.

[0023] In this embodiment, the cloud service platform includes a remote monitoring and assistance unit, which provides data support and a remote manual takeover interface.

[0024] In this embodiment, the remote service platform includes a billing unit, which is used to generate bills based on usage duration and mileage.

[0025] In this embodiment, the intelligent driving module quickly completes the calibration of sensor extrinsic parameters through short-distance driving and data fusion algorithms.

[0026] In this embodiment, as Figure 2 As shown, the process of quickly calibrating the sensor's extrinsic parameters through short-distance driving and data fusion algorithms includes: M1. When the vehicle travels a short distance, it acquires real-time positioning data based on the vehicle's GNSS / IMU integrated navigation system, real-time point cloud data of the road based on the vehicle's lidar, real-time image data of the road based on the vehicle's camera, and real-time distance data between the vehicle and obstacles based on the vehicle's millimeter-wave radar. M2. Based on the point cloud data of the road, the image data of the road, and the distance data between vehicles and obstacles, a multi-sensor data fusion function G is constructed. , Where x is the point cloud data of the road, y is the image data of the road, z is the distance data between the vehicle and the obstacle, f is the feature function of the road point cloud, g is the feature function of the road image, h is the feature function of the distance between the vehicle and the obstacle, and α, β and γ are weighting coefficients. The data from multiple sensors are fused to obtain the fused multi-sensor data information. M3. Based on the fused multi-sensor data and the vehicle positioning data, a matching model between vehicle positioning and multi-sensor data is constructed, and the extrinsic parameters of the sensors are optimized to obtain the optimized extrinsic parameter data.

[0027] In this embodiment, the step of quickly calibrating the sensor's extrinsic parameters through short-distance driving and data fusion algorithms further includes: M4. Based on the optimized sensor extrinsic data, evaluate whether the sensor extrinsic parameters have converged. If they have converged, the sensor extrinsic parameter calibration is completed; otherwise, return to step M3.

[0028] In this embodiment, the construction of the matching model between vehicle positioning and multi-sensor data involves optimizing the initial extrinsic parameter estimation of each sensor in the current vehicle positioning based on the residual of the multi-sensor fusion data before and after vehicle positioning, thereby obtaining the optimized sensor extrinsic parameter data information.

[0029] Example 2: Based on the intelligent driving module instant rental system based on a distributed shared docking station in Example 1, the present invention will be further explained and described below.

[0030] like Figure 1 As shown, an instant rental system for intelligent driving modules based on a distributed shared docking station is disclosed. The system includes: The intelligent driving module is an integrated physical unit. The internal components of the intelligent driving module include a lidar, a camera, a millimeter-wave radar, a GNSS / IMU integrated navigation system, a main control computing unit, a vehicle control unit, a battery module, and a 4G / 5G communication module. The external components of the intelligent driving module are designed with standardized mechanical quick-release interfaces and electrical communication interfaces. The shared docking station includes a storage unit, a robotic arm unit, a charging unit, and a control unit. The storage unit is used to store multiple intelligent driving modules. The robotic arm unit is equipped with a vision system and customized grippers for precise grasping and installation / removal of modules. The charging unit is used to wirelessly or wired charge the modules stored in the docking station. The control unit is used to receive cloud commands and control the robotic arm to complete automated operations. The vehicle-side adapter includes a mechanical locking mechanism that matches the intelligent driving module and a universal vehicle bus interface for physical and electrical connection with the intelligent driving module; A cloud service platform is connected to the shared docking station for monitoring and management.

[0031] In this embodiment, as Figure 3 As shown, the present invention provides a method for applying to any of the claims of an intelligent driving module instant rental system based on a distributed shared docking station, the method comprising: Users can reserve the intelligent driving module at a nearby shared docking station through the app; Users drive their vehicles into designated parking spaces at the shared docking station; The APP sends a command, and the robotic arm of the shared docking station automatically installs the intelligent driving module onto the vehicle adapter; The intelligent driving module performs a power-on self-test and initiates a self-calibration process; Once calibration is successful, the user's vehicle acquires autonomous driving capabilities, and the system begins billing. The user drives to a shared docking station near their destination; The robotic arm automatically disassembles the intelligent driving module and returns it to the warehouse via the app, ending the billing process.

[0032] In this embodiment, the system includes four core components: intelligent driving module, shared docking station, vehicle adapter and cloud service platform.

[0033] The intelligent driving module is an integrated physical unit that internally includes a lidar, camera, millimeter-wave radar, GNSS / IMU integrated navigation system, main control computing unit, vehicle control unit, battery module, and 4G / 5G communication module. Externally, it features standardized mechanical quick-release interfaces and electrical communication interfaces. This module has a self-calibration function; after installation, it can quickly complete the calibration of sensors and external parameters through short-distance driving and data fusion algorithms.

[0034] The shared docking station is an automated facility deployed at key transportation nodes (such as service areas and parking lots). Its internal components include: Storage unit: Used to store multiple intelligent driving modules.

[0035] Robotic arm unit: Equipped with a vision system and customized grippers, it is used for precise gripping and installation / removal of modules.

[0036] Charging unit: Provides wireless or wired charging for modules stored in the dock.

[0037] Control unit: Receives instructions from the cloud and controls the robotic arm to complete automated operations.

[0038] The vehicle adapter is a low-cost hardware component pre-installed in the vehicle. It includes a mechanical locking mechanism that matches the autonomous driving module and a universal vehicle bus interface. This adapter ensures that vehicles of different brands and models can establish physical and electrical connections with standard autonomous driving modules.

[0039] The cloud service platform is the brain of the system, and its functions include: User App Backend: Handles user registration, appointment, payment, and unlocking requests.

[0040] Inventory and scheduling management: Monitor the health status and inventory quantity of all docking station modules and perform intelligent allocation.

[0041] Remote monitoring and assistance: Provides data support and remote manual takeover interface.

[0042] Billing system: Generates bills based on usage duration and mileage.

[0043] In this embodiment, the present invention also provides a computer-readable storage medium storing a computer program programmed or configured to perform any of the methods for instant rental of intelligent driving modules based on distributed shared docking stations.

[0044] Any references to memory, storage, database, or other media used in the embodiments provided in this application 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. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0045] In summary, this invention not only significantly reduces the initial cost for users and is expected to accelerate the popularization of autonomous driving technology, but also solves the problem of users' vehicles having fixed hardware and being unable to enjoy continuous technology upgrades.

[0046] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A smart driving module instant rental system based on a distributed sharing dock station, characterized in that, The system comprises: The intelligent driving module is an integrated physical unit, the inside of the intelligent driving module comprises a laser radar, a camera, a millimeter wave radar, a GNSS / IMU combined navigation system, a main control computing unit, a vehicle control unit, a battery module and a 4G / 5G communication module, and the outside of the intelligent driving module is designed with a standardized mechanical quick-release interface and an electrical communication interface; The sharing station comprises a storage unit, a mechanical arm unit, a charging unit and a control unit, the storage unit is used for storing a plurality of intelligent driving modules, the mechanical arm unit is provided with a vision system and a customized clamp and is used for accurately grabbing and installing / dismounting the modules, the charging unit is used for wirelessly or wiredly charging the modules stored in the station, and the control unit is used for receiving cloud instructions and controlling the mechanical arm to complete automatic operation; The vehicle-end adapter comprises a mechanical locking mechanism matched with the intelligent driving module and a general vehicle bus interface and is used for physically and electrically connecting with the intelligent driving module; The cloud service platform is in communication connection with the sharing station and is used for monitoring and managing the sharing station. 2.The instant renting system of intelligent driving module based on distributed sharing dock station according to claim 1, characterized in that: The cloud service platform comprises a user APP backend unit, which is used for processing user registration, reservation, payment and unlocking requests. 3.The instant renting system of intelligent driving module based on distributed sharing dock station according to claim 1, characterized in that: The cloud service platform comprises an inventory and scheduling management unit, which is used for monitoring the health status and inventory quantity of the sharing station and intelligently allocating. 4.The instant renting system of intelligent driving module based on distributed sharing dock station according to claim 1, characterized in that: The cloud service platform comprises a remote monitoring and assistance unit, which is used for providing data support and a remote manual takeover interface. 5.The instant renting system of intelligent driving module based on distributed sharing dock station according to claim 1, characterized in that: The remote service platform comprises a charging unit, which is used for generating a bill according to the use time length and mileage. 6.The instant renting system of intelligent driving module based on distributed sharing dock station according to claim 1, characterized in that: The intelligent driving module quickly completes the calibration of the external parameters of the sensors through short-distance driving and a data fusion algorithm. 7.The instant renting system of intelligent driving module based on distributed sharing dock station according to claim 6, characterized in that, The calibration of the external parameters of the sensors through short-distance driving and a data fusion algorithm comprises: M1. The vehicle drives for a short distance, real-time acquisition of the positioning data information of the vehicle based on the vehicle-mounted GNSS / IMU combined navigation system, real-time acquisition of the point cloud data information of the road based on the vehicle-mounted laser radar, real-time acquisition of the image data information of the road based on the vehicle-mounted camera and real-time acquisition of the distance data information of the vehicle and the obstacles based on the vehicle-mounted millimeter wave radar; M2. Construction of a multi-sensor data fusion function G based on the point cloud data information of the road, the image data information of the road and the distance data information of the vehicle and the obstacles, ， wherein x is the point cloud data information of the road, y is the image data information of the road, z is the distance data information of the vehicle and the obstacles, f is a characteristic value function of the road point cloud, g is a characteristic value function of the road image, h is a characteristic value function of the distance of the vehicle and the obstacles, and ɑ, β and γ are weight coefficients, the data of the multi-sensor is fused to obtain fused multi-sensor data information; M3. Based on the fused multi-sensor data information and the vehicle positioning data information, a matching model of vehicle positioning and multi-sensor data is constructed, the extrinsic parameters of the sensor are optimized, and the data information of the optimized extrinsic parameters of the sensor is obtained. 8.The instant renting system of intelligent driving module based on distributed sharing dock station according to claim 7, characterized in that, The calibration of the extrinsic parameters of the sensor through short-distance driving and data fusion algorithm further includes: M4. Based on the data information of the optimized extrinsic parameters of the sensor, it is evaluated whether the extrinsic parameters of the sensor converge, if the extrinsic parameters of the sensor converge, the calibration of the extrinsic parameters of the sensor is completed, and if the extrinsic parameters of the sensor do not converge, step M3 is returned. 9.The instant renting system of intelligent driving module based on distributed sharing dock station according to claim 7, characterized in that: The matching model of vehicle positioning and multi-sensor data is constructed by optimizing the initial extrinsic parameter estimation of each sensor of the current vehicle positioning according to the residual error of the multi-sensor fusion data before and after the vehicle positioning, and obtaining the data information of the optimized extrinsic parameters of the sensor.

10. A method applied to the intelligent driving module instant leasing system based on the distributed shared docking station according to any one of claims 1-9, characterized in that, The method comprises: The user makes an appointment for the intelligent driving module of the nearby shared dock station through the APP; The user drives the vehicle into the designated parking space of the shared dock station; The APP sends an instruction, and the mechanical arm of the shared dock station automatically installs the intelligent driving module on the vehicle adapter; The intelligent driving module is powered on for self-checking and starts the self-calibration process; After successful calibration, the user's vehicle obtains the automatic driving function, and the system starts charging; The user drives to the shared dock station near the destination; Through APP operation, the mechanical arm automatically disassembles the intelligent driving module, returns to the warehouse, and the charging ends.

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