Driving method, device, electronic device and computer-readable medium

Abstract

This application discloses a driving method, device, electronic device, and computer-readable medium, relating to the field of computer technology. A specific embodiment includes triggering a driving process in response to detecting that the distance from a pathfinder device reaches a preset distance, obtaining road condition information returned by the pathfinder device; parsing the road condition information to obtain corresponding obstacle types and obstacle location information; planning a driving path based on the obstacle type and obstacle location information; determining a driving state based on the road condition information and the preset distance, and then driving in the driving state based on the driving path. This can improve driving efficiency and ensure driving safety.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a driving method, device, electronic device, and computer-readable medium. Background Art

[0002] At present, when logistics unmanned vehicles are driving on the road, the detection range of the sensors on the vehicle is limited, resulting in the inability to perceive the road conditions ahead in a timely manner. This causes the logistics unmanned vehicles to set a very slow driving speed to prevent accidents, resulting in low delivery efficiency. Summary of the Invention

[0003] In view of this, the embodiments of the present application provide a driving method, device, electronic device and computer-readable medium, which can solve the problem that the existing logistics unmanned vehicles have a very slow driving speed set to prevent accidents, resulting in low delivery efficiency.

[0004] To achieve the above objectives, according to one aspect of an embodiment of the present application, a driving method is provided, comprising:

[0005] In response to detecting that the distance from the pathfinder device reaches a preset distance, triggering a driving process and obtaining road condition information returned by the pathfinder device;

[0006] Analyze road condition information to obtain corresponding obstacle type and obstacle location information;

[0007] Plan driving paths based on obstacle types and location information;

[0008] The driving state is determined based on the road condition information and the preset distance, and the vehicle then drives in the driving state based on the driving path.

[0009] Optionally, after determining the driving state, the method further includes:

[0010] The driving path and driving status are sent to the pathfinder device so that the pathfinder device updates the road condition information based on the driving path and driving status and returns the updated information.

[0011] Optionally, parsing the road condition information to obtain corresponding obstacle type and obstacle location information includes:

[0012] Input road condition information into the classification model to output the corresponding obstacles and obstacle types;

[0013] Call the positioning program to determine the corresponding obstacle position information based on the output obstacles.

[0014] Optionally, a driving path is planned based on obstacle type and obstacle location information, including:

[0015] Obstacle type and location information are input into the path planning model to output a driving path.

[0016] Optionally, determining the driving state based on road condition information and a preset distance includes:

[0017] Obtain traffic information from road condition information;

[0018] determining a current driving speed, and then determining a time taken to travel a preset distance based on the driving speed and the preset distance;

[0019] Determine driving status based on traffic information and time.

[0020] Optionally, the driving status is determined based on traffic information and time, including:

[0021] Determine the color of the traffic light corresponding to the traffic information and the remaining time corresponding to the color;

[0022] Determine driving speed based on color, remaining time, and time.

[0023] Optionally, after driving in the driving state based on the driving path, the method further includes:

[0024] In response to detecting an obstacle, the obstacle avoidance process is triggered to execute a corresponding obstacle avoidance program based on the obstacle and perform corresponding obstacle avoidance actions.

[0025] In addition, the present application also provides a driving device, comprising:

[0026] an acquiring unit configured to trigger a driving process and acquire road condition information returned by the pathfinder device in response to detecting that the distance to the pathfinder device reaches a preset distance;

[0027] a parsing unit configured to parse the road condition information to obtain corresponding obstacle type and obstacle position information;

[0028] a path planning unit configured to plan a driving path according to obstacle type and obstacle position information;

[0029] The driving unit is configured to determine a driving state according to road condition information and a preset distance, and then drive in the driving state based on a driving path.

[0030] Optionally, the driving unit is further configured to:

[0031] The driving path and driving status are sent to the pathfinder device so that the pathfinder device updates the road condition information based on the driving path and driving status and returns the updated information.

[0032] Optionally, the parsing unit is further configured to:

[0033] Input road condition information into the classification model to output the corresponding obstacles and obstacle types;

[0034] Call the positioning program to determine the corresponding obstacle position information based on the output obstacles.

[0035] Optionally, the path planning unit is further configured to:

[0036] Obstacle type and location information are input into the path planning model to output a driving path.

[0037] Optionally, the driving unit is further configured to:

[0038] Obtain traffic information from road condition information;

[0039] determining a current driving speed, and then determining a time taken to travel a preset distance based on the driving speed and the preset distance;

[0040] Determine driving status based on traffic information and time.

[0041] Optionally, the driving unit is further configured to:

[0042] Determine the color of the traffic light corresponding to the traffic information and the remaining time corresponding to the color;

[0043] Determine driving speed based on color, remaining time, and time.

[0044] Optionally, the driving device further includes an obstacle avoidance unit configured to:

[0045] In response to detecting an obstacle, the obstacle avoidance process is triggered to execute a corresponding obstacle avoidance program based on the obstacle and perform corresponding obstacle avoidance actions.

[0046] In addition, the present application also provides a driving electronic device, including: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by one or more processors, the one or more processors implement the driving method as described above.

[0047] In addition, the present application also provides a computer-readable medium on which a computer program is stored, and when the program is executed by a processor, the driving method as described above is implemented.

[0048] One embodiment of the above invention has the following advantages or beneficial effects: In response to detecting that the distance from a pathfinder device reaches a preset distance, the present application triggers a driving process and obtains road condition information returned by the pathfinder device; analyzes the road condition information to obtain corresponding obstacle types and obstacle location information; plans a driving path based on the obstacle type and obstacle location information; determines the driving state based on the road condition information and the preset distance, and then drives in the driving state based on the driving path. This improves driving efficiency and ensures driving safety.

[0049] The further effects of the above-mentioned non-conventional optional manner will be described below in conjunction with specific embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The accompanying drawings are provided to facilitate a better understanding of the present application and do not constitute an undue limitation on the present application.

[0051] Figure 1 is a schematic diagram of the main process of a driving method provided according to an embodiment of the present application;

[0052] Figure 2 is a schematic diagram of the main process of a driving method provided according to an embodiment of the present application;

[0053] Figure 3 This is a schematic diagram of an application scenario of a driving method provided according to an embodiment of the present application;

[0054] Figure 4 is a schematic diagram of the main units of a driving device according to an embodiment of the present application;

[0055] Figure 5 is an exemplary system architecture diagram to which embodiments of the present application may be applied;

[0056] Figure 6 It is a structural diagram of a computer system of a terminal device or server suitable for implementing an embodiment of the present application. DETAILED DESCRIPTION

[0057] The following describes exemplary embodiments of the present application in conjunction with the accompanying drawings, including various details of the embodiments of the present application to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those skilled in the art that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description. The acquisition, storage, use, processing, etc. of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0058] Figure 1 is a schematic diagram of the main process of the driving method provided according to an embodiment of the present application, such as Figure 1 As shown, the driving method includes:

[0059] Step S101: In response to detecting that the distance from the pathfinder device reaches a preset distance, a driving process is triggered to obtain road condition information returned by the pathfinder device.

[0060] In this embodiment, the execution entity of the driving method (for example, a server, specifically a server connected to an unmanned vehicle, such as a server connected to a logistics unmanned vehicle) can detect the distance from the pathfinder device via a wired or wireless connection. When the execution entity detects that the distance between the current location and the pathfinder device reaches a preset distance, for example, 5 meters, the driving process is triggered and driving along the preset route is initiated. Specifically, the embodiments of the present application can be applied to unmanned autonomous driving scenarios as well as manned driving scenarios. After the driving process is triggered, the execution entity can obtain road condition information returned by the pathfinder device ahead. Specifically, the road condition information can be road condition information at the location of the pathfinder device, and can include road sign and marking information, traffic light information, school information, construction information, congestion information, and roadblock information. The embodiments of the present application do not specifically limit the content of the road condition information returned by the pathfinder device. The pathfinder device can include various sensors installed on a small unmanned pathfinder vehicle. It is understood that the road condition information returned by the pathfinder device can be an image, and the embodiments of the present application do not specifically limit the format of the road condition information returned by the pathfinder device.

[0061] Step S102: parse the road condition information to obtain the corresponding obstacle type and obstacle position information.

[0062] Specifically, the road condition information is parsed to obtain the corresponding obstacle type and obstacle location information, including: inputting the road condition information into a classification model to output the corresponding obstacle and obstacle type; calling a positioning program to determine the corresponding obstacle location information based on the output obstacle.

[0063] The execution entity can call upon a trained classification model, such as a KNN model, and input road condition information into the KNN model to obtain one or more information categories corresponding to the road condition information, such as one or more of signal light information, road marking information, roadblock information, school information, construction information, and congestion information. The execution entity can then determine the obstacle type corresponding to each information category. For example, if the information category is school information, the corresponding obstacle can be predicted to be a student passing through the intersection after school, and the obstacle type is human. If the information category is roadblock information, the corresponding obstacle can be predicted to be a roadblock warning post, and the obstacle type is inanimate. Once the execution entity has determined the obstacle and obstacle type corresponding to the road condition information, it can call upon a positioning program to accurately locate the obstacle and output the corresponding obstacle location information, such as the obstacle's latitude and longitude coordinates, so that the unmanned logistics vehicle can accurately avoid the obstacle upon reaching it and ensure safe driving.

[0064] Step S103: planning a driving path based on obstacle type and obstacle location information.

[0065] Specifically, planning a driving path according to obstacle type and obstacle position information includes: inputting the obstacle type and obstacle position information into a path planning model to output a driving path.

[0066] The execution entity can call on a pre-trained path planning model, taking obstacle type and location information as input, to calculate and output the optimal driving path that can circumvent the obstacles. The execution entity can replace the pre-set delivery route of the logistics unmanned vehicle with the output optimal driving path and use it as the current real-time driving path.

[0067] Step S104 : determining a driving state based on the road condition information and the preset distance, and then driving in the driving state based on the driving path.

[0068] Specifically, after determining the driving state, the driving method further includes:

[0069] The driving path and driving status are sent to the pathfinder device so that the pathfinder device updates the road condition information based on the driving path and driving status and returns the updated information.

[0070] Taking logistics unmanned vehicles and small pathfinder unmanned vehicles as examples, the pathfinder device is set on the small pathfinder unmanned vehicle, and the logistics unmanned vehicle follows the small pathfinder unmanned vehicle. The execution entity is communicated with the logistics unmanned vehicle. After the execution entity re-plans the driving path according to the road condition information returned by the pathfinder device and determines the driving status according to the road condition information and the distance from the pathfinder device, it can return the re-planned driving path and determined driving status to the pathfinder device, so that the unmanned vehicle where the pathfinder device is located (such as a small pathfinder unmanned vehicle) can adjust the driving path and driving status of the unmanned vehicle where the pathfinder device is located according to the re-planned driving path and driving status returned by the execution entity, thereby avoiding obstacles on the road corresponding to the driving path and adjusting the driving status of the unmanned vehicle where the pathfinder device is located (such as a small pathfinder unmanned vehicle) to comply with traffic rules. After receiving the re-planned driving path and the driving status of the logistics unmanned vehicle, the pathfinder device can drive into the re-planned driving path and drive in the same driving status as the logistics unmanned vehicle. The driving status may include the driving speed and driving direction of the logistics unmanned vehicle, etc. Then, the pathfinder device can return the detected road condition information on the re-planned driving path to the logistics unmanned vehicle in real time, thereby ensuring the safe driving of the logistics unmanned vehicle on the re-planned driving path.

[0071] Specifically, the driving state is determined based on the road condition information and the preset distance, including: obtaining traffic information in the road condition information; determining the current driving speed, and then determining the time taken to travel the preset distance based on the driving speed and the preset distance; and determining the driving state based on the traffic information and time.

[0072] Specifically, the driving state is determined according to the traffic information and time, including: determining the color of the traffic light corresponding to the traffic information and the remaining time corresponding to the color; and determining the driving speed according to the color, the remaining time and the time.

[0073] Taking an unmanned logistics vehicle and a small-sized pathfinder vehicle as an example, the pathfinder device is installed on the small-sized pathfinder vehicle, and the unmanned logistics vehicle follows the small pathfinder vehicle. The execution entity is in communication with the unmanned logistics vehicle. Traffic information can include road signs and markings, traffic lights, the remaining time for the traffic lights to change color, onboard navigation equipment, radio traffic broadcasts, and the vehicle information system's prompt tone for speeding. The traffic light sequence is: red, green, and yellow, with these three colors lighting up in sequence. The execution entity can determine the unmanned logistics vehicle's current driving speed and, based on the current driving speed and distance from the pathfinder device, calculate the time it will take to reach the location corresponding to the road condition information returned by the pathfinder device. Based on this time and the traffic light color and remaining time for the color change in the acquired traffic information, the execution entity can adjust the real-time driving status, that is, the real-time driving speed.

[0074] Specifically, the driving status is determined based on the traffic information and time, including: determining the color of the traffic light corresponding to the traffic information and the remaining time (e.g., 30 seconds) corresponding to the color (e.g., green); determining the driving speed (e.g., slowing down from 60 km / h to 40 km / h) based on the color (e.g., green), the remaining time (e.g., 30 seconds) and the time (i.e., the time taken to travel the preset distance between the driving and the pathfinder device, e.g., 1 minute).

[0075] For example, the current driving speed is 60 kilometers per hour, and the calculated time to reach the position corresponding to the road condition information returned by the pathfinder device is 1 minute (that is, the time used to travel the preset distance between the driving and the pathfinder device is 1 minute, and the embodiment of the present application does not specifically limit the time used). The color of the traffic light in the obtained traffic information is green, and the remaining color change time is 30 seconds, which means that it will turn yellow after 30 seconds. According to traffic rules, the traffic light turns yellow when the logistics unmanned vehicle reaches the position corresponding to the road condition information returned by the pathfinder device. Therefore, the logistics unmanned vehicle needs to change the driving state to deceleration before reaching the position corresponding to the road condition information returned by the pathfinder device, for example, the deceleration is 40 kilometers per hour. The embodiment of the present application does not specifically limit the deceleration rate by kilometers per hour, and it can be determined according to the surrounding traffic conditions obtained by the logistics unmanned vehicle.

[0076] This embodiment triggers the driving process in response to detecting that the distance from the pathfinder device reaches a preset distance, obtains road condition information returned by the pathfinder device, analyzes the road condition information to obtain corresponding obstacle types and obstacle locations, plans a driving path based on the obstacle types and locations, determines the driving state based on the road condition information and the preset distance, and then drives in the driving state based on the driving path. This can improve driving efficiency and ensure driving safety.

[0077] Figure 2 This is a schematic diagram of the main flow of a driving method provided according to an embodiment of the present application. Figure 2 As shown, the driving method includes:

[0078] Step S201: In response to detecting that the distance from the pathfinder device reaches a preset distance, a driving process is triggered to obtain road condition information returned by the pathfinder device.

[0079] For example, when an unmanned logistics vehicle and a small-scale pathfinder vehicle collaborate to deliver goods, the preset distance can be determined based on the detection range of the wireless communication modules installed on the unmanned logistics vehicle and the small-scale pathfinder vehicle. For example, the preset distance could be the maximum detection range of the wireless communication modules installed on the unmanned logistics vehicle and the small-scale pathfinder vehicle. This ensures that the unmanned logistics vehicle has maximum reaction time and ensures its safe operation.

[0080] Step S202: parse the road condition information to obtain the corresponding obstacle type and obstacle position information.

[0081] The road condition information may be the road condition information at the location of the pathfinder device, and may specifically include road sign and marking information, traffic light information, the duration of the traffic light color change, school information, construction information, congestion information and roadblock information, etc. The embodiment of the present application does not specifically limit the content of the road condition information returned by the pathfinder device.

[0082] Step S203: planning a driving path based on obstacle type and obstacle location information.

[0083] Specifically, the automatic driving unit on the logistics unmanned vehicle calculates the road condition information returned by the pathfinder device located on the small pathfinder unmanned vehicle, thereby calculating the precise driving path and driving status of the logistics unmanned vehicle.

[0084] Step S204 : determining a driving state based on the road condition information and the preset distance, and then driving in the driving state based on the driving path.

[0085] The logistics unmanned vehicle will also adjust its driving path and driving status as the driving path status of the small pathfinder unmanned vehicle is adjusted while following the small pathfinder unmanned vehicle.

[0086] Step S205 , in response to detecting an obstacle, triggering an obstacle avoidance process to execute a corresponding obstacle avoidance program based on the obstacle and perform a corresponding obstacle avoidance action.

[0087] The obstacle avoidance sensors on the logistics unmanned vehicles will also enable the logistics unmanned vehicles to take timely obstacle avoidance actions to ensure safety when encountering emergencies.

[0088] For example, consider the collaborative delivery of goods using an unmanned logistics vehicle and a small-sized pathfinder vehicle. The small-sized pathfinder vehicle is equipped with a comprehensive suite of autonomous driving sensors that monitor road conditions in real time. As the unmanned logistics vehicle performs its delivery mission, route information is transmitted simultaneously to both vehicles. The small-sized pathfinder vehicle is small and can operate along the roadside to minimize traffic flow, minimizing impact on traffic safety. The small-sized pathfinder vehicle maintains a fixed distance from the logistics vehicle and drives ahead of it. The small-sized pathfinder vehicle transmits road condition data detected in advance to the logistics vehicle via wireless communication. Based on this data, the logistics vehicle makes autonomous driving predictions, effectively preventing collisions caused by unexpected road conditions ahead. This collaborative route-finding process improves the efficiency and safety of the logistics vehicle's delivery.

[0089] Specifically, the sensors installed on the small pathfinder unmanned vehicle include: top radar, blind spot radar, surround perception camera, millimeter wave radar, IMU inertial measurement unit, and GPS positioning module.

[0090] The sensors installed on the logistics unmanned vehicle include: IMU inertial measurement unit, GPS positioning module, obstacle avoidance module, and autonomous driving computing unit.

[0091] Communication between the unmanned vehicles involves the following: Both vehicles are equipped with wireless communication modules, enabling data exchange via wireless communication. The delivery routes for the logistics unmanned vehicles are pre-set, and various sensors are installed to ensure the vehicles can automatically follow the routes to their destinations and avoid obstacles and unexpected situations along the way. The IMU (Inertial Measurement Unit) ensures the vehicle's driving stability and prevents rollovers. The delivery routes of the logistics unmanned vehicles are stored in the autonomous driving computing unit, which transmits them to the small pathfinder unmanned vehicle via wireless communication. When a delivery is scheduled, the small pathfinder unmanned vehicle first follows the route. The onboard GPS module provides the small pathfinder with real-time GPS location information, ensuring it stays on the set route. After the small pathfinder has traveled the set distance, the logistics unmanned vehicle starts and follows behind it. The GPS location and path information on the small pathfinder is transmitted to the logistics unmanned vehicle in real time via the wireless communication module, allowing the logistics unmanned vehicle to follow the small pathfinder's route. The logistics unmanned vehicle's GPS information is also transmitted to the small pathfinder unmanned vehicle via a wireless communication module. The two vehicles exchange GPS location information in real time to ensure they maintain a set distance along the path. As the small pathfinder unmanned vehicle drives, its autonomous driving sensors—including overhead radar, blind spot radar, surround-view cameras, and millimeter-wave radar—detect road conditions in real time and transmit them to the logistics unmanned vehicle's autonomous driving computing unit via the wireless communication module. The autonomous driving unit on the logistics unmanned vehicle calculates the received sensor information to determine the unmanned vehicle's precise driving path and driving status. This information is then transmitted to the small pathfinder unmanned vehicle via the wireless communication module. The small pathfinder unmanned vehicle adjusts its driving path and status based on this information to avoid obstacles and comply with traffic regulations. The logistics unmanned vehicle also adjusts its driving path and status as the small pathfinder unmanned vehicle adjusts its driving status. The obstacle avoidance sensors on the logistics unmanned vehicle also enable the logistics unmanned vehicle to take timely evasive action in the event of an emergency, ensuring safety. This detailed communication process between the two unmanned vehicles is presented above. By using a small unmanned pathfinder vehicle equipped with autonomous driving sensors to operate in coordination with the unmanned logistics vehicle, the autonomous driving perception range of the unmanned logistics vehicle can be expanded, enabling the unmanned logistics vehicle to perceive the road conditions ahead in advance, thereby increasing driving speed and improving delivery efficiency and safety.

[0092] Figure 3It is a schematic diagram of an application scenario of the driving method provided according to an embodiment of the present application. The driving method of the embodiment of the present application can be applied to an autonomous driving scenario. In the autonomous driving scenario, a logistics unmanned vehicle and a small pathfinder unmanned vehicle carrying a pathfinder device may be included. The logistics unmanned vehicle and the small pathfinder unmanned vehicle cooperate to realize the delivery of goods. The small pathfinder unmanned vehicle is in front and the logistics unmanned vehicle is behind. The logistics unmanned vehicle receives the road condition information returned by the pathfinder device on the small pathfinder unmanned vehicle to replan the driving path and adjust the driving state based on the road condition information, so as to ensure safe driving. Among them, the pathfinder device may include sensors installed on the small pathfinder unmanned vehicle, such as: top radar, blind spot radar, surround view perception camera, millimeter wave radar, IMU inertial measurement unit and GPS positioning module. The sensors installed on the logistics unmanned vehicle include: IMU inertial measurement unit, GPS positioning module, obstacle avoidance module, and autonomous driving computing unit. Figure 3 The left and right sides of the block diagram do not represent the order of the unmanned vehicles. In the embodiment of the present application, the small unmanned pathfinder vehicle has been driving in front of the logistics unmanned vehicle to explore the way for the logistics unmanned vehicle. Both the logistics unmanned vehicle and the small unmanned pathfinder vehicle are equipped with wireless communication modules. Specifically, Figure 3 As shown, wireless communication module 1 is installed on the unmanned logistics vehicle, and wireless communication module 2 is installed on the small unmanned pathfinder vehicle. The unmanned logistics vehicle and the small unmanned pathfinder vehicle can exchange data through wireless communication module 1 and wireless communication module 2. The information sent by the unmanned logistics vehicle to wireless communication module 1 includes: the unmanned logistics vehicle's position, speed, and direction information, as well as the unmanned logistics vehicle's control information for the small unmanned pathfinder vehicle. The information sent by wireless communication module 1 to the unmanned logistics vehicle includes: information about obstacles ahead, traffic lights at intersections, lane markings on the road ahead, information about pedestrians ahead, information about vehicles ahead, road traffic signs, and the position, speed, and direction information of the small unmanned pathfinder vehicle. The information sent by wireless communication module 1 to wireless communication module 2 includes: information about obstacles ahead, traffic lights at intersections, lane markings on the road ahead, information about pedestrians ahead, information about vehicles ahead, road traffic signs, and the position, speed, and direction information of the small unmanned pathfinder vehicle. The information sent by wireless communication module 2 to wireless communication module 1 includes: information about obstacles ahead, traffic lights at intersections, lane markings on the road ahead, information about pedestrians ahead, information about vehicles ahead, road traffic signs, and the position, speed, and direction information of the small unmanned pathfinder vehicle. Wireless communication module 2 sends information to the small unmanned pathfinder vehicle, including the logistics vehicle's position, speed, and direction, as well as the logistics vehicle's control information over the small unmanned pathfinder vehicle. The small unmanned pathfinder vehicle also sends information to wireless communication module 2, including information about obstacles ahead, traffic lights at intersections, lane markings ahead, pedestrians ahead, vehicles ahead, road signs, and the small unmanned pathfinder vehicle's position, speed, and direction.

[0093] Through data interaction between the logistics unmanned vehicle and the small pathfinder unmanned vehicle, the logistics unmanned vehicle can obtain road condition information ahead of the driving route in advance, so as to make timely route adjustments when there are obstacles ahead of the driving route, thereby ensuring the driving safety and efficiency of the logistics unmanned vehicle.

[0094] Figure 4 Schematic diagram of the main units of the driving device according to an embodiment of the present application. Figure 4 As shown, the driving device 400 includes an acquisition unit 401 , a parsing unit 402 , a path planning unit 403 and a driving unit 404 .

[0095] The acquisition unit 401 is configured to trigger the driving process in response to detecting that the distance to the pathfinder device reaches a preset distance, and acquire the road condition information returned by the pathfinder device.

[0096] The parsing unit 402 is configured to parse the road condition information to obtain corresponding obstacle type and obstacle position information.

[0097] The path planning unit 403 is configured to plan a driving path according to obstacle type and obstacle position information.

[0098] The driving unit 404 is configured to determine a driving state according to road condition information and a preset distance, and then drive in the driving state based on a driving path.

[0099] In some embodiments, the driving unit 404 is further configured to send the driving path and driving status to the pathfinder device, so that the pathfinder device updates the road condition information based on the driving path and driving status and returns the updated road condition information.

[0100] In some embodiments, the parsing unit 402 is further configured to: input the road condition information into the classification model to output the corresponding obstacles and obstacle types; and call the positioning program to determine the corresponding obstacle position information according to the output obstacles.

[0101] In some embodiments, the path planning unit 403 is further configured to input obstacle type and obstacle position information into a path planning model to output a driving path.

[0102] In some embodiments, the driving unit 404 is further configured to: obtain traffic information from the road condition information; determine the current driving speed, and then determine the time taken to travel the preset distance based on the driving speed and the preset distance; determine the driving status based on the traffic information and time.

[0103] In some embodiments, the driving unit 404 is further configured to: determine the color of the traffic light corresponding to the traffic information and the remaining time corresponding to the color; and determine the driving speed according to the color, the remaining time, and the time.

[0104] In some embodiments, the driving device further includes Figure 4 The obstacle avoidance unit not shown in the figure is configured to: trigger the obstacle avoidance process in response to detecting an obstacle, to execute the corresponding obstacle avoidance program based on the obstacle, and to make corresponding obstacle avoidance actions.

[0105] It should be noted that the driving method and the driving device in this application have a corresponding relationship in terms of specific implementation content, so the repeated content will not be explained again.

[0106] Figure 5 An exemplary system architecture 500 is shown to which a driving method or a driving device according to an embodiment of the present application can be applied.

[0107] like Figure 5 As shown, system architecture 500 may include terminal devices 501, 502, 503, a network 504, and a server 505. Network 504 is used to provide a medium for communication links between terminal devices 501, 502, 503 and server 505. Network 504 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0108] Users can use terminal devices 501, 502, and 503 to interact with server 505 via network 504 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 501, 502, and 503, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only as examples).

[0109] The terminal devices 501, 502, and 503 may be various electronic devices having a credit authorization inquiry processing screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

[0110] Server 505 can be a server that provides various services, such as a background management server (for example only) that executes a driving process triggered when the distance from the pathfinding device, detected by a user using terminal devices 501, 502, or 503, reaches a preset distance. In response to detecting that the distance from the pathfinding device has reached the preset distance, the background management server can trigger a driving process, obtain road condition information returned by the pathfinding device, analyze the road condition information to obtain corresponding obstacle types and obstacle location information, plan a driving path based on the obstacle type and obstacle location information, determine the driving state based on the road condition information and the preset distance, and then drive in the driving state based on the driving path. This improves driving efficiency and ensures driving safety.

[0111] It should be noted that the driving method provided in the embodiment of the present application is generally executed by the server 505 , and accordingly, the driving device is generally set in the server 505 .

[0112] It should be understood that Figure 5 The number of terminal devices, networks and servers in the embodiment is merely illustrative. Any number of terminal devices, networks and servers may be provided as required.

[0113] Reference below Figure 6 , which shows a structural diagram of a computer system 600 of a terminal device suitable for implementing an embodiment of the present application. Figure 6 The terminal device shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0114] like Figure 6 As shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage unit 608 into a random access memory (RAM) 603. Various programs and data required for the operation of the computer system 600 are also stored in the RAM 603. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0115] The following components are connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, and the like; an output section 607 including displays such as a cathode ray tube (CRT), a liquid crystal display (LCD), and a speaker; a storage section 608 including a hard disk; and a communication section 609 including a network interface card such as a LAN card or a modem. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. Removable media 611, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 610 as needed, so that computer programs read therefrom can be installed into the storage section 608 as needed.

[0116] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 609, and / or installed from a removable medium 611. When the computer program is executed by the central processing unit (CPU) 601, the above-mentioned functions defined in the system of the present application are executed.

[0117] It should be noted that the computer-readable medium described in this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. Computer-readable storage media can include, for example, but are not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or devices, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, 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 above. In this application, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, device, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. This propagated data signal can take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical fiber cable, RF, or any suitable combination thereof.

[0118] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of the boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0119] The units described in the embodiments of this application may be implemented in software or hardware. The units described may also be provided in a processor. For example, a processor may be described as including an acquisition unit, a parsing unit, a path planning unit, and a driving unit. The names of these units do not, in some cases, limit the units themselves.

[0120] As another aspect, the present application also provides a computer-readable medium, which may be included in the device described in the above embodiment; or it may exist independently and not be assembled into the device. The computer-readable medium carries one or more programs. When the one or more programs are executed by a device, the device triggers a driving process in response to detecting that the distance from the pathfinder device reaches a preset distance, obtains road condition information returned by the pathfinder device, parses the road condition information to obtain corresponding obstacle type and obstacle location information, plans a driving path based on the obstacle type and obstacle location information, determines a driving state based on the road condition information and the preset distance, and then drives in the driving state based on the driving path.

[0121] According to the technical solution of the embodiment of the present application, the automatic driving perception range of the logistics unmanned vehicle can be expanded, so that the logistics unmanned vehicle can perceive the road conditions ahead in advance, improve driving efficiency and ensure driving safety.

[0122] The above specific embodiments do not constitute a limitation on the scope of protection of this application. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the scope of protection of this application.

Claims

1. A driving method, characterized in that: include: In response to detecting that the distance between the unmanned logistics vehicle and the pathfinder device reaches a preset distance, triggering a driving process and obtaining road condition information returned by the pathfinder device; Analyzing the road condition information to obtain corresponding obstacle type and obstacle location information; Planning a driving path according to the obstacle type and the obstacle location information; A driving state is determined according to the road condition information and the preset distance, and the vehicle is driven in the driving state based on the driving path.

2. The method according to claim 1, characterized in that After determining the driving state, the method further includes: The driving path and the driving status are sent to the path finding device, so that the path finding device updates the road condition information based on the driving path and the driving status and returns the updated road condition information.

3. The method according to claim 1, characterized in that The analyzing the road condition information to obtain corresponding obstacle type and obstacle location information includes: Inputting the road condition information into a classification model to output corresponding obstacles and obstacle types; The positioning program is called to determine the corresponding obstacle position information according to the output obstacle.

4. The method according to claim 1, wherein Planning a driving path according to the obstacle type and the obstacle location information, including: The obstacle type and the obstacle position information are input into a path planning model to output a driving path.

5. The method according to claim 1, characterized in that The determining the driving state according to the road condition information and the preset distance includes: Obtaining traffic information from the road condition information; determining a current driving speed, and then determining a time taken to travel the preset distance based on the driving speed and the preset distance; A driving state is determined based on the traffic information and the time.

6. The method according to claim 5, characterized in that The determining the driving state according to the traffic information and the time includes: determining a color of a traffic light corresponding to the traffic information and a remaining time corresponding to the color; A driving speed is determined based on the color, the remaining time, and the time.

7. The method according to claim 1, characterized in that After driving in the driving state based on the driving path, the method further includes: In response to detecting an obstacle, an obstacle avoidance process is triggered to execute a corresponding obstacle avoidance program based on the obstacle and perform corresponding obstacle avoidance actions.

8. A driving device, characterized in that: include: an acquisition unit configured to trigger a driving process in response to detecting that the distance between the unmanned logistics vehicle and the pathfinder device reaches a preset distance, and acquire road condition information returned by the pathfinder device; a parsing unit configured to parse the road condition information to obtain corresponding obstacle type and obstacle position information; a path planning unit, configured to plan a driving path according to the obstacle type and the obstacle position information; The driving unit is configured to determine a driving state according to the road condition information and the preset distance, and then drive in the driving state based on the driving path.

9. The device according to claim 8, characterized in that The driving unit is further configured to: The driving path and the driving status are sent to the path finding device, so that the path finding device updates the road condition information based on the driving path and the driving status and returns the updated road condition information.

10. The device according to claim 8, characterized in that The parsing unit is further configured to: Inputting the road condition information into a classification model to output corresponding obstacles and obstacle types; The positioning program is called to determine the corresponding obstacle position information according to the output obstacle.

11. A driving electronic 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 method according to any one of claims 1 to 7.

12. A computer-readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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