Vehicle transportation method and device, electronic equipment and storage medium

Abstract

The application discloses a vehicle transportation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring position information, collision information and speed information of a loading vehicle of a target vehicle, wherein the collision information comprises collision strength information and collision position information between the target vehicle and the loading vehicle, and the loading vehicle represents a vehicle for transporting the target vehicle; generating driving warning information based on the position information and the speed information; generating collision warning information based on the collision information; and determining a vehicle transportation strategy based on the driving warning information and the collision warning information, wherein the vehicle transportation strategy is used for adjusting a vehicle transportation path and / or a vehicle transportation speed. The application solves the technical problems of poor real-time updating of logistics information and incomplete monitoring of vehicle safety in the related art.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and more specifically, to a vehicle transportation method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the growth of automobile sales and the development of the logistics industry, the safety monitoring of vehicles during the logistics process from manufacturing plants to car dealerships has become a critical issue. Current technologies for vehicle logistics monitoring primarily rely on the Global Positioning System (GPS) of transport vehicles and manual reporting mechanisms. For example, GPS devices are installed on transport vehicles to track their location. Logistics personnel report the vehicle's status and location to management via phone, SMS, or email at specific times or key points. Some logistics companies use internal management systems to record and track the transportation status of vehicles, including stages such as outbound, loading, transportation, and unloading.

[0003] However, existing technologies have the following drawbacks:

[0004] (1) Insufficient real-time data: Although GPS can provide location information, its update frequency is limited and it cannot achieve real-time monitoring, which may result in a time difference between the actual status and location of the transport vehicle and the information displayed by the monitoring system.

[0005] (2) Lack of transparency and safety hazards: Due to reliance on manual reporting, any problems during vehicle transportation may not be discovered or reported immediately, which may lead to accidents or safety issues not being dealt with in a timely manner.

[0006] (3) Lack of video evidence: When a vehicle is involved in a scratch or collision, GPS alone cannot provide enough evidence to determine liability for the accident. This lack of real-time video monitoring makes it difficult to obtain evidence quickly after the accident.

[0007] There is currently no effective solution to the above problems. Summary of the Invention

[0008] This invention provides a vehicle transportation method, apparatus, electronic device, and storage medium to at least solve the technical problems of poor real-time updates of logistics information and incomplete monitoring of vehicle safety during vehicle transportation in related technologies.

[0009] According to one embodiment of the present invention, a vehicle transportation method is provided, comprising: acquiring location information of a target vehicle, collision information, and speed information of a loading vehicle, wherein the collision information includes collision intensity information and collision location information between the target vehicle and the loading vehicle, and the loading vehicle is used to represent the vehicle transporting the target vehicle; generating driving warning information based on the location information and speed information; generating collision warning information based on the collision information; and determining a vehicle transportation strategy based on the driving warning information and the collision warning information, wherein the vehicle transportation strategy is used to adjust the vehicle transportation path and / or the vehicle transportation speed.

[0010] Optionally, generating driving warning information based on location information and speed information includes: using a preset path fitting algorithm to fit the location information to obtain a fitted transportation path; comparing the fitted transportation path with a preset transportation path to obtain a comparison result; and generating driving warning information based on the comparison result and speed information.

[0011] Optionally, generating driving warning information based on the comparison results and speed information includes: in response to the comparison result indicating that the deviation between the fitted transportation path and the preset transportation path is greater than or equal to a preset deviation threshold, and the speed information indicating that the speed of the loaded vehicle is greater than a preset speed threshold, determining the warning level of the driving warning information as a first driving warning level; in response to the comparison result indicating that the deviation between the fitted transportation path and the preset transportation path is less than a preset deviation threshold, and the speed information indicating that the speed of the loaded vehicle is greater than a preset speed threshold, determining the warning level of the driving warning information as a second driving warning level, wherein the first driving warning level is higher than the second driving warning level.

[0012] Optionally, generating collision warning information based on collision information includes: in response to the collision information indicating that the collision level of the target vehicle is a first collision level, determining the warning level of the collision warning information as a first collision warning level; in response to the collision information indicating that the collision level of the target vehicle is a second collision level, determining the warning level of the collision warning information as a second collision warning level, wherein the first collision warning level is lower than the second collision warning level.

[0013] Optionally, acquiring collision information of the target vehicle includes: in response to a collision between the target vehicle and the loading vehicle, acquiring target vehicle sensor data and video image information; determining collision intensity information based on the target vehicle sensor data; and determining collision location information based on the video image information.

[0014] Optionally, obtaining the location information of the target vehicle and the speed information of the loading vehicle includes: obtaining the location information fed back by the vehicle network control unit of the target vehicle for a preset time period; and obtaining the speed information fed back by the loading vehicle for a preset time period.

[0015] Optionally, the target vehicle can be distinguished based on the vehicle's unique identifier information.

[0016] Optionally, the method further includes: acquiring traffic condition information; and updating the expected timestamp of the target vehicle's arrival at the target location based on the location information, speed information, and traffic condition information.

[0017] According to one embodiment of the present invention, a vehicle transportation device is also provided, comprising: an acquisition module, configured to acquire location information of a target vehicle, collision information, and speed information of a loading vehicle, wherein the collision information includes collision intensity information and collision location information between the target vehicle and the loading vehicle, and the loading vehicle is used to represent a vehicle transporting the target vehicle; a first generation module, configured to generate driving warning information based on the location information and speed information; a second generation module, configured to generate collision warning information based on the collision information; and a determination module, configured to determine a vehicle transportation strategy based on the driving warning information and the collision warning information, wherein the vehicle transportation strategy is used to adjust the vehicle transportation route and / or the vehicle transportation speed.

[0018] Optionally, the first generation module is further configured to: use a preset path fitting algorithm to fit the location information to obtain a fitted transportation path; compare the fitted transportation path with the preset transportation path to obtain a comparison result; and generate driving warning information based on the comparison result and speed information.

[0019] Optionally, the first generation module is further configured to: generate driving warning information based on the comparison result and speed information, including: in response to the comparison result indicating that the deviation between the fitted transportation path and the preset transportation path is greater than or equal to a preset deviation threshold, and the speed information indicating that the speed of the loaded vehicle is greater than a preset speed threshold, determining the warning level of the driving warning information as a first driving warning level; in response to the comparison result indicating that the deviation between the fitted transportation path and the preset transportation path is less than a preset deviation threshold, and the speed information indicating that the speed of the loaded vehicle is greater than a preset speed threshold, determining the warning level of the driving warning information as a second driving warning level, wherein the first driving warning level is higher than the second driving warning level.

[0020] Optionally, the second generation module is further configured to: in response to the collision information indicating that the collision level of the target vehicle is a first collision level, determine the warning level of the collision warning information as a first collision warning level; in response to the collision information indicating that the collision level of the target vehicle is a second collision level, determine the warning level of the collision warning information as a second collision warning level, wherein the first collision warning level is lower than the second collision warning level.

[0021] Optionally, the acquisition module is further configured to acquire target vehicle sensor data and video image information in response to a collision between the target vehicle and the loading vehicle; the determination module is further configured to: determine collision intensity information based on the target vehicle sensor data; and determine collision location information based on the video image information.

[0022] Optionally, the acquisition module is also used to: acquire the location information fed back by the vehicle network control unit of the target vehicle for a preset time period; and acquire the speed information fed back by the loading vehicle for a preset time period.

[0023] Optionally, the target vehicle can be distinguished based on the vehicle's unique identifier information.

[0024] Optionally, the acquisition module is also used to acquire traffic condition information; the vehicle transport device also includes a processing module for updating the expected timestamp of the target vehicle's arrival at the target location based on the location information, speed information and traffic condition information.

[0025] According to one embodiment of the present invention, an electronic device is also provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the vehicle transportation method described above when it runs.

[0026] According to one embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is executed, it controls the device where the storage medium is located to perform the above-described vehicle transportation method.

[0027] According to one embodiment of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the above-described vehicle transportation method.

[0028] In this embodiment of the invention, the method of acquiring the location information, collision information, and speed information of the target vehicle and the loading vehicle is adopted. Driving warning information is generated based on the location information and speed information, and collision warning information is generated based on the collision information. Finally, the vehicle transportation strategy is determined based on the driving warning information and collision warning information. This achieves the purpose of updating the logistics information of the target vehicle in real time during transportation and comprehensively monitoring the safety status of the target vehicle during transportation. This improves the transportation efficiency and safety of the target vehicle during transportation, and solves the technical problems of poor real-time updates of logistics information and incomplete monitoring of vehicle safety in related technologies. Attached Figure Description

[0029] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0030] Figure 1 This is a flowchart of a vehicle transportation method according to one embodiment of the present invention;

[0031] Figure 2This is a schematic diagram of a vehicle transportation method according to one embodiment of the present invention;

[0032] Figure 3 This is a flowchart of another vehicle transportation method according to one embodiment of the present invention;

[0033] Figure 4 This is a schematic diagram of another vehicle transportation method according to one embodiment of the present invention;

[0034] Figure 5 This is a schematic diagram of another vehicle transportation method according to one embodiment of the present invention;

[0035] Figure 6 This is a structural block diagram of a vehicle transport device according to one embodiment of the present invention. Detailed Implementation

[0036] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0037] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0038] According to an embodiment of the present invention, a method embodiment of a vehicle transportation method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0039] This method embodiment can be executed in an electronic device or similar computing device that includes a memory and a processor. Taking operation on a vehicle terminal as an example, the vehicle terminal may include one or more processors (processors may include, but are not limited to, central processing units (CPUs), graphics processing units (GPUs), digital signal processing (DSP) chips, microcontroller units (MCUs), field-programmable gate arrays (FPGAs), neural network processors (NPUs), tensor processors (TPUs), artificial intelligence (AI) type processors, etc.) and a memory for storing data. Optionally, the vehicle terminal may also include transmission devices, input / output devices, and display devices for communication functions. Those skilled in the art will understand that the above structural description is merely illustrative and does not limit the structure of the vehicle terminal. For example, the vehicle terminal may include more or fewer components than described above, or have a different configuration than described above.

[0040] The memory can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the vehicle transportation method in this embodiment of the invention. The processor executes various functional applications and data processing by running the computer program stored in the memory, thereby realizing the aforementioned vehicle transportation method. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the mobile terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0041] The transmission device is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the mobile terminal's communication provider. In one example, the transmission device includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0042] Display devices can be, for example, touchscreen liquid crystal displays (LCDs) and touch displays (also referred to as "touchscreens" or "touch displays"). The LCD allows users to interact with the user interface of the mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GUI), which allows users to interact with the GUI through finger contact and / or gestures on a touch-sensitive surface. Optional human-computer interaction functions include: creating web pages, drawing, word processing, creating electronic documents, playing games, video conferencing, instant messaging, sending and receiving emails, call interfaces, playing digital video, playing digital music, and / or web browsing, etc. Executable instructions for performing the above human-computer interaction functions are configured / stored in one or more processor-executable computer program products or readable storage media.

[0043] Figure 1 This is a flowchart of a vehicle transportation method according to one embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0044] Step S10: Obtain the location information of the target vehicle, collision information, and speed information of the loading vehicle. The collision information includes the collision intensity information and collision location information between the target vehicle and the loading vehicle. The loading vehicle is used to represent the vehicle transporting the target vehicle.

[0045] In step S10, the target vehicle is used to characterize a vehicle transported from the vehicle manufacturing plant to the vehicle dealership.

[0046] The aforementioned loading vehicles are used to describe vehicles that carry the target vehicle during transportation from the vehicle manufacturer to the vehicle dealership.

[0047] The collision information described above is used to characterize the collision intensity and location of the target vehicle when a collision occurs between the target vehicle and the loading vehicle during transportation from the vehicle manufacturer to the vehicle dealership.

[0048] Step S12: Generate driving warning information based on location information and speed information;

[0049] In step S12, the driving warning information is divided into different driving warning levels, and different driving warning levels correspond to different reminder methods. The driving warning information includes, but is not limited to: driving warning level indicator, type of deviation (such as directional deviation, speed deviation, etc.), degree of deviation, and suggested corrective measures.

[0050] Specifically, during the transportation from the vehicle manufacturer to the vehicle dealership, the system determines whether the current transportation route deviates from the target route and whether the current speed of the loaded vehicle exceeds the speed limit based on the location information of the target vehicle and the speed information of the loaded vehicle. Based on the determination results, driving warning information is generated to remind vehicle transportation logistics monitoring personnel and the driver of the loaded vehicle. This allows vehicle transportation logistics monitoring personnel to obtain logistics transportation information in real time and reminds the driver to take timely action to reduce the risk of accidents.

[0051] Step S14: Generate collision warning information based on collision information;

[0052] In step S14, collision warning information is divided into different collision warning levels, and different collision warning levels correspond to different reminder methods. Collision warning information includes, but is not limited to: collision warning level identifier, detailed location of the collision, collision severity, and suggested emergency handling measures.

[0053] Specifically, during transportation from the vehicle manufacturing plant to the vehicle dealership, collision warning information is generated based on the collision intensity and location of the target vehicle when it collides with the loading vehicle. This information is used to alert vehicle transportation logistics monitoring personnel and vehicle dealership staff. Additionally, images of the collision location and video footage of the collision are retained to improve the efficiency of staff in handling collision incidents.

[0054] Step S16: Determine a vehicle transportation strategy based on driving warning information and collision warning information, wherein the vehicle transportation strategy is used to adjust the vehicle transportation route and / or vehicle transportation speed.

[0055] Specifically, based on driving warning information and collision warning information, the driver of the loaded vehicle will adjust the vehicle's transportation strategy. This may involve changing the transportation route to avoid high-risk areas or adjusting the transportation speed to reduce the risk of collision. Simultaneously, the adjustment of the vehicle transportation strategy is performed in real time to ensure that the target vehicle is always in the safest and most efficient state. The logistics visualization system continuously monitors the status of the loaded and target vehicles and updates the vehicle transportation strategy based on the latest data. This logistics visualization system integrates the vehicle transportation method of this invention.

[0056] Based on steps S10 to S16 above, by acquiring the location information, collision information, and speed information of the target vehicle and the loading vehicle, driving warning information is generated based on the location information and speed information, and collision warning information is generated based on the collision information. Finally, the vehicle transportation strategy is determined based on the driving warning information and collision warning information. This achieves the goal of updating the logistics information of the target vehicle in real time during transportation and comprehensively monitoring the safety status of the target vehicle during transportation. This improves the transportation efficiency and safety of the target vehicle during transportation, and solves the technical problems of poor real-time updates of logistics information and incomplete monitoring of vehicle safety in related technologies.

[0057] Optionally, in step S12, generating driving warning information based on location information and speed information includes:

[0058] Step S121: Use a preset path fitting algorithm to fit the location information to obtain the fitted transportation path;

[0059] In step S121, the aforementioned preset path fitting algorithm is used to infer the transportation path of the target vehicle from a series of discrete location data points. The preset path fitting algorithm includes, but is not limited to, Gaussian process regression, Bayesian network or other machine learning algorithms.

[0060] The above-mentioned fitted transportation path is used to characterize the target vehicle transportation path predicted by the preset path fitting algorithm.

[0061] Specifically, a preset path fitting algorithm is used to extract transportation route features from the location information. This involves inputting the target vehicle's location information into the selected preset path algorithm, which then processes the input location information to obtain a fitted transportation route. This fitted transportation route reflects both the route the target vehicle has already traveled during transportation and can predict the route the target vehicle will travel during transportation.

[0062] Step S122: Compare the fitted transportation route with the preset transportation route to obtain the comparison result;

[0063] In step S122, the aforementioned preset transportation route is used to characterize the transportation route planned in advance by the logistics visualization system from the vehicle manufacturing plant to the vehicle sales store.

[0064] The comparison results described above are used to characterize whether the deviation between the fitted transportation route and the preset transportation route exceeds a preset deviation threshold. Different preset deviation thresholds can be set for different preset transportation routes. The preset deviation threshold can be determined based on factors such as the characteristics of the transportation route, the type of target vehicle and loading vehicle, and safety requirements.

[0065] Specifically, the fitted transportation route is compared with the preset transportation route to identify the differences between the two. If the deviation between the fitted and preset routes is greater than or equal to a preset deviation threshold, it indicates that the current transportation route deviates significantly from the preset route; if the deviation is less than or equal to the preset deviation threshold, it indicates that the current transportation route conforms to the preset route. For example, for a vehicle transported from a manufacturing plant in Shanghai to a sales outlet in Beijing, the logistics visualization system pre-plans an optimal transportation route, i.e., the preset route, including major highways and expected stopping points. The preset deviation threshold is 10 kilometers. The preset transportation route is: Shanghai -> Nanjing -> Xuzhou -> Jinan -> Beijing. During transportation, the vehicle's actual route may deviate from the preset route due to traffic conditions, weather factors, or driver decisions. The loaded vehicle detoured due to an accident on the highway between Nanjing and Xuzhou. The fitted transportation route is obtained based on location information. Comparing the fitted route with the preset route reveals that the vehicle actually traveled the route Nanjing -> Hefei -> Xuzhou. Since the deviation between the actual route and the preset route exceeds 10 kilometers, the comparison result indicates that the current transportation route deviates significantly from the preset route.

[0066] Step S123: Generate driving warning information based on the comparison results and speed information.

[0067] Specifically, by combining the comparison results and speed information, the system determines whether to generate a driving warning. If the fitted transportation route deviates significantly from the preset transportation route, or if the loaded vehicle exhibits abnormal speed changes, the logistics visualization system will generate corresponding driving warning information.

[0068] Based on the above steps S121 to S123, a preset path fitting algorithm is used to fit the location information to obtain a fitted transportation path. The fitted transportation path is compared with the preset transportation path to obtain the comparison result. Based on the comparison result and speed information, driving warning information is generated. By monitoring the location information of the target vehicle in real time and predicting the future driving path, it is helpful to detect deviations in a timely manner and take preventive measures. Furthermore, by comparing the fitted transportation path and the preset transportation path, deviations from the predetermined route can be quickly identified, reducing transportation risks and improving vehicle transportation safety.

[0069] Optionally, in step S123, generating driving warning information based on the comparison results and speed information includes:

[0070] Step S1231: In response to the comparison result that the deviation between the fitted transportation path and the preset transportation path is greater than or equal to the preset deviation threshold, and the speed information indicates that the speed of the loaded vehicle is greater than the preset speed threshold, the warning level of the driving warning information is determined to be the first driving warning level.

[0071] Specifically, if the analysis and comparison results confirm that the deviation between the fitted transportation route and the preset transportation route is greater than or equal to a preset deviation threshold, and the speed information analysis confirms that the speed of the loading vehicle is greater than a preset speed threshold, then the logistics visualization system determines the warning level of the driving warning information to be the first driving warning level. The first driving warning level indicates a relatively urgent situation requiring immediate action. The generated driving warning information will include a warning level indicator, as well as specific deviation degree and speed information. Furthermore, the logistics visualization system needs to provide emergency operational suggestions for the loading vehicle, such as immediate deceleration and route adjustment.

[0072] Step S1232: In response to the comparison result that the deviation between the fitted transportation path and the preset transportation path is less than the preset deviation threshold, and the speed information indicates that the speed of the loaded vehicle is greater than the preset speed threshold, the warning level of the driving warning information is determined to be the second driving warning level, wherein the first driving warning level is higher than the second driving warning level.

[0073] Specifically, if the analysis and comparison results confirm that the deviation between the fitted transportation route and the preset transportation route is less than a preset deviation threshold, and the speed information analysis confirms that the speed of the loading vehicle exceeds a preset speed threshold, then the logistics visualization system determines the warning level of the driving warning information to be the second driving warning level. The second driving warning level represents a lower urgency than the first level, but still requires attention. The generated driving warning information will include a warning level indicator and specific speed information. The logistics visualization system provides suggested operations, such as appropriately slowing down and maintaining attention to the route. For example, a vehicle departs from a manufacturing plant in Shanghai to a sales store in Beijing, with a preset route via Nanjing and Xuzhou to Beijing, a preset deviation threshold of 5 kilometers, and a preset speed threshold of 100 kilometers per hour. Scenario 1: The actual driving route of the loading vehicle deviates from the preset route, the actual route is Shanghai via Hangzhou to Xuzhou, and the average speed in the Hangzhou to Xuzhou section is 120 kilometers per hour. The deviation exceeds 5 kilometers, and the speed exceeds 100 kilometers per hour. At this time, a driving warning information is triggered, and the warning level of the driving warning information is the first driving warning level. The logistics visualization system broadcasts to the loading vehicle: Emergency Warning! The vehicle has deviated from the planned route by more than 5 kilometers, and its speed exceeds the safety threshold. It is recommended to immediately slow down and adjust the route back to the pre-set path from Nanjing to Xuzhou. Scenario Two: The vehicle's actual driving path largely follows the pre-set path, but the average speed on the Nanjing-Xuzhou section is 120 km / h. The deviation is less than 5 kilometers, but the speed exceeds 100 km / h. At this time, a driving warning information is triggered, and the warning level is the second driving warning level. The logistics visualization system broadcasts to the loading vehicle: Warning! The vehicle speed exceeds the safety threshold. It is recommended to slow down appropriately to ensure transportation safety while maintaining adherence to the pre-set path.

[0074] Based on steps S1231 to S1232 above, in response to the comparison result that the deviation between the fitted transportation path and the preset transportation path is greater than or equal to a preset deviation threshold, and the speed information indicates that the speed of the loaded vehicle is greater than a preset speed threshold, the warning level of the driving warning information is determined to be the first driving warning level; in response to the comparison result that the deviation between the fitted transportation path and the preset transportation path is less than a preset deviation threshold, and the speed information indicates that the speed of the loaded vehicle is greater than a preset speed threshold, the warning level of the driving warning information is determined to be the second driving warning level. By setting different warning levels, relevant personnel can respond quickly and take timely measures according to the urgency of the situation, and the setting of different warning levels enables the logistics visualization system to implement more refined transportation management based on the degree of deviation and speeding.

[0075] Optionally, in step S14, generating collision warning information based on collision information includes:

[0076] Step S141: In response to the collision information indicating that the collision level of the target vehicle is the first collision level, determine the warning level of the collision warning information as the first collision warning level;

[0077] Specifically, if the collision information indicates that the target vehicle's collision level is Level 1, meaning the collision is relatively minor or the potential risk is low, the logistics visualization system determines the collision warning information's alert level as Level 1. The generated collision warning information will include the alert level identifier and detailed collision information. Furthermore, the logistics visualization system will provide preliminary operational suggestions, such as checking the target vehicle's condition, reminding the loading vehicle to pay attention to driving safety, and advising the loading vehicle to slow down.

[0078] Step S142: In response to the collision information indicating that the collision level of the target vehicle is the second collision level, the warning level of the collision warning information is determined to be the second collision warning level, wherein the first collision warning level is lower than the second collision warning level.

[0079] Specifically, the system analyzes collision information to assess the collision level of the target vehicle. If the collision information indicates a Level 2 collision, this typically means the collision is severe or the potential risk is high. The logistics visualization system then determines the warning level of the collision warning message to be Level 2. The generated collision warning message will include the warning level identifier and detailed collision information. Furthermore, the logistics visualization system provides emergency operational suggestions, such as immediately stopping for inspection, contacting roadside assistance or repair services, and advising loaded vehicles to slow down.

[0080] Based on steps S141 to S142 above, in response to the collision information indicating that the collision level of the target vehicle is the first collision level, the warning level of the collision warning information is determined to be the first collision warning level; in response to the collision information indicating that the collision level of the target vehicle is the second collision level, the warning level of the collision warning information is determined to be the second collision warning level. Different collision levels correspond to different warning levels, enabling the logistics visualization system to provide different levels of emergency information according to different situations, enhancing the timeliness and relevance of the information. Furthermore, by setting multiple collision levels and corresponding warning levels, the safety status of vehicles can be monitored more comprehensively, which helps to reduce the risk of accidents and ensure the safety of the target vehicle.

[0081] Optionally, in step S10, obtaining the collision information of the target vehicle includes:

[0082] Step S101: In response to a collision between the target vehicle and the loading vehicle, acquire sensor data and video image information of the target vehicle;

[0083] Step S102: Determine collision intensity information based on target vehicle sensor data;

[0084] Step S103: Determine the collision location information based on the video image information.

[0085] Specifically, the target vehicle is equipped with multiple onboard sensors, such as acceleration sensors and vibration sensors, which monitor the vehicle's dynamic status in real time. Based on a service-oriented architecture (SOA), the target vehicle's control system is designed to be modular, allowing each sensor service to be activated as needed. When a sensor detects a collision event, it automatically wakes up the vehicle's cockpit controller. The cockpit controller then activates the surround-view cameras, which begin recording photos of the collision site and video of the surrounding environment.

[0086] Furthermore, upon the occurrence of a collision, the target vehicle's control system simultaneously uploads its location information and saves images of the collision site to the vehicle's storage. This data is transmitted to the logistics visualization system via the vehicle's communication module. After receiving the sensor data, the logistics visualization system analyzes the data from the acceleration and vibration sensors. Through algorithmic processing, such as peak detection and energy calculation, it determines the intensity of the collision. Collision intensity information includes the magnitude of acceleration changes, the duration and intensity of vibrations, etc. After receiving photos and videos from the surround-view cameras, the logistics visualization system performs image recognition and analysis. Using computer vision technologies, such as feature point matching and deep learning, it determines the specific location of the collision. Collision location information includes the coordinates of the collision point relative to the vehicle and the size of the collision area.

[0087] Based on steps S101 to S103 above, the system responds to a collision between the target vehicle and the loading vehicle by acquiring sensor data and video image information of the target vehicle. The collision intensity information is determined based on the target vehicle sensor data, and the collision location information is determined based on the video image information. This allows for the rapid acquisition of sensor data and video image information at the moment of collision. The instant response mechanism ensures the real-time collection and transmission of collision information, enabling the logistics visualization system to obtain accurate collision information in the first instance and enhancing the real-time nature of logistics information.

[0088] Optionally, in step S10, obtaining the location information of the target vehicle and the speed information of the loading vehicle includes:

[0089] Step S104: Obtain the location information fed back by the vehicle network control unit of the target vehicle according to the preset time period;

[0090] Specifically, the logistics visualization system sets a preset time interval for periodically acquiring the location information of target vehicles based on transportation monitoring needs. This preset time interval can be determined based on factors such as the length of the preset transportation route, the average speed of the loaded vehicles, and the required monitoring accuracy. Based on the target vehicle's overall SOA architecture, the logistics visualization system issues a wake-up command daily, waking only the in-vehicle information terminal (T-Box) without waking the entire vehicle, thus reducing power consumption during transportation and preventing battery depletion. After the target vehicle is woken up, high-precision GPS technology is used to acquire the vehicle's real-time location information, including its longitude, latitude, and altitude. This location information is then uploaded to a cloud server in real time via 4G / 5G communication technology. The logistics visualization system reads the location information from the cloud and stores it in a database for subsequent analysis and use.

[0091] Step S105: Obtain the speed information fed back by the loading vehicle according to the preset time.

[0092] Specifically, the system periodically acquires the speed information of the loading vehicle according to a preset time interval. Onboard sensors (such as speed sensors) obtain this speed information, including the vehicle's current speed, acceleration, and deceleration. This speed information is then uploaded to a cloud server in real time via 4G / 5G communication technology. The logistics visualization system reads the speed information from the cloud and stores it in a database for subsequent analysis and use.

[0093] Specifically, Figure 2 This is a schematic diagram of a vehicle transportation method according to one embodiment of the present invention, such as... Figure 2 As shown, the vehicle transportation method includes a user mobile application (APP), a logistics outbound system, and a logistics visualization system. The logistics outbound system is used to bind the user's order with the vehicle's VIN code after the logistics terminal receives the order from the user's mobile APP. After the vehicle starts transportation, the VIN code is entered into the logistics visualization system. The logistics visualization system is used to obtain the logistics information of the target vehicle in real time during the transportation process and push the logistics information to the user's APP.

[0094] Furthermore, the logistics visualization system periodically acquires the location information of target vehicles based on transportation monitoring needs. Based on the target vehicle's SOA architecture, the system issues wake-up commands daily, waking only the vehicle's connected control unit (T-Box) without waking the entire vehicle, reducing power consumption during transport and preventing battery depletion. Once the target vehicle is awakened, the T-Box uses GPS technology to obtain the vehicle's real-time location information and uploads it to a cloud server. The logistics visualization system reads the location information from the cloud and stores it in a database for subsequent analysis and use. Simultaneously, when a collision occurs, the target vehicle's control system synchronously uploads its location information and saves images of the collision site to the vehicle's storage. This data is transmitted to the logistics visualization system via a communication module. Upon receiving sensor data, the system analyzes the data from the acceleration and vibration sensors, determining the collision intensity through algorithmic processing. Finally, upon receiving photos and videos from the surround-view cameras, the system performs image recognition and analysis to determine the specific location of the collision.

[0095] Based on steps S104 to S105 above, the location information fed back by the vehicle network control unit of the target vehicle is acquired for a preset time period; the speed information fed back by the loading vehicle is acquired for a preset time period. When acquiring location information, the power consumption during transportation is reduced by only waking up the in-vehicle information terminal (T-Box) without waking up the entire vehicle. This helps to extend the battery life and reduce operating costs.

[0096] Optionally, the target vehicle can be distinguished based on the vehicle's unique identifier information.

[0097] Specifically, the unique vehicle identifier information is used to identify the target vehicle's Vehicle Identification Number (VIN). The logistics visualization system distinguishes target vehicles based on their VINs.

[0098] Alternatively, vehicle transportation methods may also include:

[0099] Step S171: Obtain traffic condition information;

[0100] In step S171, the aforementioned traffic condition information includes road congestion, accident reports, construction areas, traffic control, and the impact of weather conditions.

[0101] Step S172: Update the expected timestamp of the target vehicle's arrival at the target location based on location information, speed information, and traffic condition information.

[0102] Specifically, traffic information can be obtained from multiple sources, including traffic surveillance cameras and vehicle GPS systems. Furthermore, traffic information is updated in real time to ensure data timeliness and accuracy. The real-time location and speed information of the target vehicle are combined with the acquired traffic information to estimate the estimated time from the current location to the target location. The updated estimated timestamp is then communicated to relevant parties, such as drivers, logistics dispatch centers, and recipients, through a logistics visualization system.

[0103] Based on steps S171 to S172 above, by acquiring traffic condition information, the expected timestamp of the target vehicle's arrival at the target location is updated based on location information, speed information, and traffic condition information. The real-time updated expected timestamp provides relevant parties with accurate information about the transportation progress. Drivers, logistics dispatch centers, and consignees can all know the expected arrival time of the target vehicle in real time, which helps to enhance the transparency of the entire transportation process and reduce misunderstandings and anxiety caused by information asymmetry.

[0104] Figure 3 This is a flowchart of another vehicle transportation method according to one embodiment of the present invention, such as... Figure 3 As shown, the method includes the following steps:

[0105] Step S301: Obtain the location information fed back by the vehicle network control unit of the target vehicle according to the preset time period;

[0106] Step S302: Obtain the speed information fed back by the loading vehicle according to the preset time;

[0107] Step S303: In response to a collision between the target vehicle and the loading vehicle, acquire sensor data and video image information of the target vehicle;

[0108] Step S304: Determine collision intensity information based on target vehicle sensor data;

[0109] Step S305: Determine the collision location information based on the video image information;

[0110] Step S306: In response to the collision information indicating that the collision level of the target vehicle is the first collision level, determine the warning level of the collision warning information as the first collision warning level;

[0111] Step S307: In response to the collision information indicating that the collision level of the target vehicle is the second collision level, determine the warning level of the collision warning information as the second collision warning level;

[0112] Step S308: Use a preset path fitting algorithm to fit the location information to obtain the fitted transportation path;

[0113] Step S309: Compare the fitted transportation route with the preset transportation route to obtain the comparison result;

[0114] Step S310: In response to the comparison result that the deviation between the fitted transportation path and the preset transportation path is greater than or equal to the preset deviation threshold, and the speed information indicates that the speed of the loaded vehicle is greater than the preset speed threshold, the warning level of the driving warning information is determined to be the first driving warning level.

[0115] Step S311: In response to the comparison result that the deviation between the fitted transportation path and the preset transportation path is less than the preset deviation threshold, and the speed information indicates that the speed of the loaded vehicle is greater than the preset speed threshold, the warning level of the driving warning information is determined to be the second driving warning level.

[0116] Step S312: Determine the vehicle transportation strategy based on driving warning information and collision warning information.

[0117] Based on steps S301 to S312 above, by acquiring the location information, collision information, and speed information of the target vehicle and the loading vehicle, driving warning information is generated based on the location information and speed information, and collision warning information is generated based on the collision information. Finally, the vehicle transportation strategy is determined based on the driving warning information and collision warning information. This achieves the goal of updating the logistics information of the target vehicle in real time during transportation and comprehensively monitoring the safety status of the target vehicle during transportation. This improves the transportation efficiency and safety of the target vehicle during transportation, and solves the technical problems of poor real-time updates of logistics information and incomplete monitoring of vehicle safety in related technologies.

[0118] The following example will provide a detailed explanation of the workflow of the above vehicle transportation method:

[0119] Specifically, Figure 4 This is a schematic diagram of another vehicle transportation method according to one embodiment of the present invention, such as... Figure 4 As shown,

[0120] ① User Mobile Application (APP): Users can independently select and order vehicles through the mobile APP. After placing an order, users can monitor the vehicle's status and location information in real time from its departure from the factory to its destination, as well as its arrival time, on the APP. ② Logistics Outbound System: After receiving the user's order through the mobile APP, the logistics system binds the order to the vehicle's VIN code. Once the vehicle begins transportation, the VIN code is entered into the logistics visualization system. ③ Vehicle Location Upload System: Based on the whole vehicle SOA architecture, the logistics visualization system issues wake-up and location information acquisition commands daily at set intervals. Each time, only the vehicle's T-Box is woken up, not the entire vehicle, reducing power consumption during transportation and preventing battery depletion. After the vehicle is woken up, high-precision GPS and 4G / 5G communication technology are used to update the vehicle's real-time location information and return the location information to the cloud. The logistics visualization system reads the data from the cloud and stores it in the database for use by the mobile APP. ④ Automatic Video Upload System After Vehicle Collision: The target vehicle is equipped with multiple onboard sensors, such as acceleration sensors and vibration sensors, which monitor the vehicle's dynamic status in real time. Based on a service-oriented architecture (SOA), the target vehicle's control system is designed modularly, allowing each sensor service to be activated as needed. When a sensor detects a collision event, it automatically wakes up the vehicle's cockpit controller. The cockpit controller then activates the surround-view camera, starting to record photos of the collision site and video of the surrounding environment. Upon collision, the target vehicle's control system simultaneously uploads the vehicle's location information and saves images of the collision site to the vehicle's storage. This data is transmitted to the logistics visualization system via the vehicle's communication module. The logistics visualization system is responsible for periodically waking up the vehicle, reading the location data uploaded to the cloud, using it for interface display and writing to a database for use by the mobile app. Furthermore, after receiving sensor data, the logistics visualization system analyzes the data from the accelerometer and vibration sensors, determining the collision intensity through algorithmic processing. Finally, after receiving photos and videos from the surround-view camera, the logistics visualization system performs image recognition and analysis to determine the specific location of the collision.

[0121] Specifically, Figure 5 This is a schematic diagram of another vehicle transportation method according to one embodiment of the present invention, such as... Figure 5As shown. First, users place an order for their desired vehicle via a mobile app. After a successful order, the logistics outbound system matches the vehicle's VIN code with the user's order information and automatically writes the vehicle's VIN code, daily location acquisition time, and vehicle transportation start and end times to the logistics visualization system via relevant interfaces. Then, based on the logistics end's input requirements, the logistics visualization system sends a daily command to the TSP (Transport Service Provider) to obtain the vehicle's location information. It then uses the returned location information to perform route fitting, estimate estimated arrival time, and formulate relevant early warning strategies. Logistics personnel can consider recalling vehicles or replacing drivers based on the severity and frequency of early warnings. Specific early warning strategies:

[0122] ① The warning level for the driving warning information is the first driving warning level: If, based on the analysis and comparison results, it is confirmed that the deviation between the fitted transportation route and the preset transportation route is greater than or equal to the preset deviation threshold, and simultaneously, the speed information is analyzed and confirmed that the speed of the loading vehicle is greater than the preset speed threshold, then the logistics visualization system determines the warning level of the driving warning information to be the first driving warning level. The first driving warning level indicates a relatively urgent situation requiring immediate action. The generated driving warning information will include a warning level indicator, as well as specific deviation and speed information. Furthermore, the logistics visualization system needs to provide emergency operational suggestions for the loading vehicle, such as immediate deceleration or route adjustment.

[0123] ② The warning level of the driving warning information is the second driving warning level: If the analysis and comparison results confirm that the deviation between the fitted transportation route and the preset transportation route is less than the preset deviation threshold, and the speed information analysis confirms that the speed of the loaded vehicle is greater than the preset speed threshold, then the logistics visualization system determines the warning level of the driving warning information to be the second driving warning level. The second driving warning level indicates that the situation is less urgent than the first level, but still requires attention. The generated driving warning information will include a warning level indicator and specific speed information. The logistics visualization system provides suggested operations, such as appropriately slowing down and maintaining attention to the route.

[0124] ③ The collision warning information is at the first collision warning level: If the collision information indicates that the target vehicle's collision level is the first collision level, this means the collision is relatively minor or the potential risk is low. The logistics visualization system determines the collision warning information's warning level to be the first collision warning level. The generated collision warning information will include the warning level indicator and detailed collision information. Furthermore, the logistics visualization system will provide preliminary operational suggestions, such as checking the target vehicle's condition, reminding the loading vehicle to pay attention to driving safety, and advising the loading vehicle to slow down, etc.

[0125] ④ The collision warning information is at the second collision warning level: If the collision information indicates that the target vehicle's collision level is the second collision level, this usually means that the collision is relatively serious or the potential risk is high. The logistics visualization system determines the collision warning information to be at the second collision warning level. The generated collision warning information will include the warning level indicator and detailed collision information. Furthermore, the logistics visualization system provides emergency operational suggestions, such as immediately stopping for inspection, contacting roadside assistance or repair services, and advising loaded vehicles to slow down.

[0126] Furthermore, the TSP automatically forwards commands to obtain vehicle location information. Upon receiving the wake-up location information, only the T-Box in the entire vehicle is activated and uploads its location information and current vehicle transport speed; the rest of the vehicle remains unactivated to prevent battery drain during transport. The vehicle sends location information back to the logistics visualization system via the TSP. The logistics visualization system writes the data to its database, allowing the mobile app to read the location information and the logistics visualization system to perform route fitting and estimated arrival time. Moreover, after the logistics vehicle leaves the warehouse, it automatically enters transport mode. The target vehicle automatically activates its vehicle collision detection system and body piezoelectric sensor scratch detection system based on the transport mode indicator. These systems automatically monitor the vehicle during transport, and upon detecting a collision, automatically transmit the signal to the intelligent cockpit system. The intelligent cockpit system automatically activates the in-vehicle / body / exterior cameras based on the collision signal to record video and upload images to the logistics visualization system.

[0127] Finally, once the target vehicle arrives at the store, the logistics system automatically processes the vehicle outbound shipment, ends the vehicle location upload, and exits the vehicle transportation mode.

[0128] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0129] This invention also provides a vehicle transport device for implementing the above embodiments and preferred embodiments, which will not be repeated hereafter. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0130] Figure 6 This is a structural block diagram of a vehicle transport device according to one embodiment of the present invention. Figure 6 As shown, the device includes:

[0131] The acquisition module 601 is used to acquire the location information of the target vehicle, the collision information, and the speed information of the loading vehicle. The collision information includes the collision intensity information and the collision location information between the target vehicle and the loading vehicle. The loading vehicle is used to represent the vehicle transporting the target vehicle.

[0132] The first generation module 602 is used to generate driving warning information based on location information and speed information;

[0133] The second generation module 603 is used to generate collision warning information based on collision information;

[0134] The determination module 604 is used to determine a vehicle transportation strategy based on driving warning information and collision warning information, wherein the vehicle transportation strategy is used to adjust the vehicle transportation route and / or vehicle transportation speed.

[0135] Optionally, the first generation module 602 is further configured to: use a preset path fitting algorithm to fit the location information to obtain a fitted transportation path; compare the fitted transportation path with the preset transportation path to obtain a comparison result; and generate driving warning information based on the comparison result and speed information.

[0136] Optionally, the first generation module 602 is further configured to: generate driving warning information based on the comparison result and speed information, including: in response to the comparison result indicating that the deviation between the fitted transportation path and the preset transportation path is greater than or equal to a preset deviation threshold, and the speed information indicating that the speed of the loaded vehicle is greater than a preset speed threshold, determining the warning level of the driving warning information as a first driving warning level; in response to the comparison result indicating that the deviation between the fitted transportation path and the preset transportation path is less than a preset deviation threshold, and the speed information indicating that the speed of the loaded vehicle is greater than a preset speed threshold, determining the warning level of the driving warning information as a second driving warning level, wherein the first driving warning level is higher than the second driving warning level.

[0137] Optionally, the second generation module 603 is further configured to: in response to the collision information indicating that the collision level of the target vehicle is a first collision level, determine the warning level of the collision warning information as a first collision warning level; in response to the collision information indicating that the collision level of the target vehicle is a second collision level, determine the warning level of the collision warning information as a second collision warning level, wherein the first collision warning level is lower than the second collision warning level.

[0138] Optionally, the acquisition module 601 is further configured to acquire target vehicle sensor data and video image information in response to a collision between the target vehicle and the loading vehicle; the determination module 604 is further configured to: determine collision intensity information based on the target vehicle sensor data; and determine collision location information based on the video image information.

[0139] Optionally, the acquisition module 601 is further configured to: acquire the location information fed back by the vehicle network control unit of the target vehicle for a preset duration; and acquire the speed information fed back by the loading vehicle for a preset duration.

[0140] Optionally, the target vehicle can be distinguished based on the vehicle's unique identifier information.

[0141] Optionally, the acquisition module 601 is also used to acquire traffic condition information; the vehicle transport device also includes a processing module 605, which is used to update the expected timestamp of the target vehicle arriving at the target location based on the location information, speed information and traffic condition information.

[0142] It should be noted that the above modules can be implemented by software or hardware. For the latter, they can be implemented in the following ways, but are not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0143] According to one embodiment of the present invention, an electronic device is also provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the vehicle transportation method described above when it runs.

[0144] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0145] Step S1: Obtain the location information, collision information and speed information of the target vehicle and the loading vehicle. The collision information includes the collision intensity information and collision location information between the target vehicle and the loading vehicle. The loading vehicle is used to represent the vehicle transporting the target vehicle.

[0146] Step S2: Generate driving warning information based on location and speed information;

[0147] Step S3: Generate collision warning information based on the collision information;

[0148] Step S4: Determine the vehicle transportation strategy based on driving warning information and collision warning information, wherein the vehicle transportation strategy is used to adjust the vehicle transportation route and / or vehicle transportation speed.

[0149] According to one embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is executed, it controls the device where the storage medium is located to perform the above-described vehicle transportation method.

[0150] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0151] Step S1: Obtain the location information, collision information and speed information of the target vehicle and the loading vehicle. The collision information includes the collision intensity information and collision location information between the target vehicle and the loading vehicle. The loading vehicle is used to represent the vehicle transporting the target vehicle.

[0152] Step S2: Generate driving warning information based on location and speed information;

[0153] Step S3: Generate collision warning information based on the collision information;

[0154] Step S4: Determine the vehicle transportation strategy based on driving warning information and collision warning information, wherein the vehicle transportation strategy is used to adjust the vehicle transportation route and / or vehicle transportation speed.

[0155] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing computer programs, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0156] According to one embodiment of the present invention, a computer program product is also provided, including a computer program that, when executed by a processor, implements the above-described vehicle transportation method.

[0157] Optionally, in this embodiment, the above-mentioned computer program product can be configured as a computer program that performs the following steps:

[0158] Step S1: Obtain the location information, collision information and speed information of the target vehicle and the loading vehicle. The collision information includes the collision intensity information and collision location information between the target vehicle and the loading vehicle. The loading vehicle is used to represent the vehicle transporting the target vehicle.

[0159] Step S2: Generate driving warning information based on location and speed information;

[0160] Step S3: Generate collision warning information based on the collision information;

[0161] Step S4: Determine the vehicle transportation strategy based on driving warning information and collision warning information, wherein the vehicle transportation strategy is used to adjust the vehicle transportation route and / or vehicle transportation speed.

[0162] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0163] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0164] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0165] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0166] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0167] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0168] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0169] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method of transporting vehicles, characterized in that The method comprises: obtaining position information, collision information and speed information of a target vehicle, wherein the collision information comprises collision intensity information and collision position information between the target vehicle and a loading vehicle, and the loading vehicle represents a vehicle transporting the target vehicle; generating driving warning information based on the position information and the speed information; generating collision warning information based on the collision information; determining a vehicle transportation strategy based on the driving warning information and the collision warning information, wherein the vehicle transportation strategy is used to adjust a vehicle transportation path and / or a vehicle transportation speed; wherein generating the driving warning information based on the position information and the speed information comprises: fitting the position information using a preset path fitting algorithm to obtain a fitted transportation path; comparing the fitted transportation path with a preset transportation path to obtain a comparison result; and generating the driving warning information based on the comparison result and the speed information; generating the driving warning information based on the comparison result and the speed information comprises: in response to the comparison result being that a deviation between the fitted transportation path and the preset transportation path is greater than or equal to a preset deviation threshold, and the speed information indicating that the speed of the loading vehicle is greater than a preset speed threshold, determining that a warning level of the driving warning information is a first driving warning level; and in response to the comparison result being that the deviation between the fitted transportation path and the preset transportation path is less than the preset deviation threshold, and the speed information indicating that the speed of the loading vehicle is greater than the preset speed threshold, determining that the warning level of the driving warning information is a second driving warning level, wherein the first driving warning level is higher than the second driving warning level.

2. The vehicle transport method of claim 1, wherein, generating the collision warning information based on the collision information comprises: in response to the collision information indicating that a collision level of the target vehicle is a first collision level, determining that a warning level of the collision warning information is a first collision warning level; in response to the collision information indicating that the collision level of the target vehicle is a second collision level, determining that the warning level of the collision warning information is a second collision warning level, wherein the first collision warning level is lower than the second collision warning level.

3. The vehicle transport method of claim 1, wherein, obtaining the collision information of the target vehicle comprises: in response to a collision occurring between the target vehicle and the loading vehicle, obtaining target vehicle sensor data and video image information; determining the collision intensity information based on the target vehicle sensor data; determining the collision position information based on the video image information.

4. The vehicle transport method of claim 1, wherein, obtaining the position information of the target vehicle and the speed information of the loading vehicle comprises: obtaining the position information fed back by an Internet of Vehicles control unit of the target vehicle according to a preset time length; obtaining the speed information fed back by the loading vehicle according to the preset time length.

5. The vehicle transport method of claim 1, wherein, identifying the target vehicle based on vehicle unique identifier information.

6. The vehicle transport method of claim 1, wherein, The method further comprises: obtaining traffic condition information; updating an expected time stamp of the target vehicle reaching a target position based on the position information, the speed information and the traffic condition information.

7. A vehicle transport apparatus characterized by comprising: The method comprises: The acquisition module is configured to acquire position information of a target vehicle, collision information, and speed information of a loading vehicle, wherein the collision information includes collision strength information and collision position information between the target vehicle and the loading vehicle, and the loading vehicle is used to represent a vehicle transporting the target vehicle. The first generation module is configured to generate driving warning information based on the position information and the speed information. The second generation module is configured to generate collision warning information based on the collision information. The determination module is configured to determine a vehicle transportation strategy based on the driving warning information and the collision warning information, wherein the vehicle transportation strategy is used to adjust a vehicle transportation route and / or a vehicle transportation speed. The first generation module is further configured to perform fitting processing on the position information using a preset path fitting algorithm to obtain a fitted transportation path, compare the fitted transportation path with a preset transportation path to obtain a comparison result, and generate the driving warning information based on the comparison result and the speed information. The first generation module is further configured to determine a first driving warning level for the driving warning information in response to the comparison result being that a deviation between the fitted transportation path and the preset transportation path is greater than or equal to a preset deviation threshold and the speed information indicating that a speed of the loading vehicle is greater than a preset speed threshold, and determine a second driving warning level for the driving warning information in response to the comparison result being that the deviation between the fitted transportation path and the preset transportation path is less than the preset deviation threshold and the speed information indicating that the speed of the loading vehicle is greater than the preset speed threshold, wherein the first driving warning level is higher than the second driving warning level.

8. An electronic device, comprising: The memory stores an executable program. The processor is configured to run the program, and the program performs the vehicle transportation method of any one of claims 1 to 6 when running. The computer-readable storage medium includes a stored executable program, wherein the executable program controls a device where the storage medium is located to perform the vehicle transportation method of any one of claims 1 to 6 when running.

9. A computer-readable storage medium, characterized in that, The computer program is executed by the processor to implement the vehicle transportation method of any one of claims 1 to 6.

10. A computer program product, characterised in that, ​

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