Vehicle transportation method and device, electronic equipment and storage medium

Abstract

The invention discloses a vehicle transportation method and device, electronic equipment and a storage medium. The method comprises the steps that position information and collision information of a target vehicle and speed information of a loading vehicle are obtained, the collision information comprises collision strength information and collision position information between the target vehicle and the loading vehicle, and the loading vehicle is used for representing a vehicle for transporting the target vehicle; generating driving early warning information based on the position information and the speed information; generating collision early warning information based on the collision information; and determining a vehicle transportation strategy based on the driving early warning information and the collision early warning information, the vehicle transportation strategy being used for adjusting a vehicle transportation path and / or a vehicle transportation speed. According to the invention, the technical problems of poor logistics information updating real-time performance and incomplete vehicle safety monitoring in the vehicle transportation process in the prior art are solved.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to a vehicle transportation method, device, electronic equipment and storage medium. Background Art

[0002] With the growth of automobile sales and the development of the logistics industry, the safety monitoring of vehicles in the logistics process from manufacturers to car dealerships has become an important issue. Existing technologies mainly rely on the Global Positioning System (GPS) of transport vehicles and manual reporting mechanisms in vehicle logistics monitoring. For example, by installing GPS devices on transport vehicles, the location information of the vehicles can be tracked. Logistics personnel report the status and location of the vehicles to managers via phone, text messages or emails at specific time points or key nodes. Some logistics companies use internal management systems to record and track the transportation status of vehicles, including outbound, loading, transportation, unloading and other links.

[0003] However, the prior art has the following disadvantages:

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

[0005] (2) Information opacity and safety hazards: Due to reliance on manual reporting, any problems during vehicle transportation may not be discovered or reported immediately, which may result in accidents or safety issues not being handled in a timely manner.

[0006] (3) Lack of video evidence: When a vehicle is scratched or collided, relying solely on GPS cannot provide sufficient evidence to determine responsibility for the accident. As a result, the lack of real-time video surveillance makes it difficult to quickly obtain evidence after an accident occurs.

[0007] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0008] The embodiments of the present invention provide a vehicle transportation method, device, electronic device and storage medium to at least solve the technical problems in the related art of poor real-time update of logistics information and incomplete monitoring of vehicle safety during vehicle transportation.

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

[0010] Optionally, generating driving warning information based on position information and speed information includes: fitting the position information using a preset path fitting algorithm to obtain a fitted transportation path; comparing the fitted transportation path with the 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 result and speed information includes: in response to the comparison result being that the deviation between the fitted transport path and the preset transport path is greater than or equal to a preset deviation threshold, and the speed information indicates that the speed of the loading vehicle is greater than a preset speed threshold, determining that the warning level of the driving warning information is a first driving warning level; in response to the comparison result being that the deviation between the fitted transport path and the preset transport path is less than a preset deviation threshold, and the speed information indicates that the speed of the loading vehicle is greater than a 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.

[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 to be 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 to be a second collision warning level, wherein the first collision warning level is lower than the second collision warning level.

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

[0014] Optionally, obtaining the position information of the target vehicle and the speed information of the loaded vehicle includes: obtaining the position information fed back by the Internet of Vehicles control unit of the target vehicle according to a preset time duration; and obtaining the speed information fed back by the loaded vehicle according to a preset time duration.

[0015] Optionally, the target vehicle is distinguished based on vehicle unique identifier information.

[0016] Optionally, the method further includes: acquiring traffic condition information; and updating an expected timestamp of the target vehicle arriving 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 transport device is also provided, including: an acquisition module, used to acquire position information, collision information and speed information of a target vehicle, wherein the collision information includes collision intensity information and collision position information between the target vehicle and the loading vehicle, and the loading vehicle is used to represent a vehicle that transports the target vehicle; a first generation module, used to generate driving warning information based on the position information and speed information; a second generation module, used to generate collision warning information based on the collision information; a determination module, used to determine a vehicle transport strategy based on the driving warning information and the collision warning information, wherein the vehicle transport strategy is used to adjust the vehicle transport route and / or the vehicle transport speed.

[0018] Optionally, the first generating module is further used 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 generating module is also used to: generate driving warning information based on the comparison result and the speed information, including: in response to the comparison result being that the deviation between the fitted transport path and the preset transport path is greater than or equal to a preset deviation threshold, and the speed information indicates 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 first driving warning level; in response to the comparison result being that the deviation between the fitted transport path and the preset transport path is less than the preset deviation threshold, and the speed information indicates 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.

[0020] Optionally, the second generation module is also used 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 also used 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 also used to: determine collision intensity information based on the target vehicle sensor data; determine collision position information based on the video image information.

[0022] Optionally, the acquisition module is also used to: obtain the position information fed back by the Internet of Vehicles control unit of the target vehicle according to a preset time duration; and obtain the speed information fed back by the loaded vehicle according to a preset time duration.

[0023] Optionally, the target vehicle is distinguished based on vehicle unique identifier information.

[0024] Optionally, the acquisition module is further used to acquire traffic condition information; the vehicle transportation device also includes a processing module, 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.

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

[0026] According to one embodiment of the present invention, a computer-readable storage medium is further provided. The computer-readable storage medium includes a stored executable program, wherein when the executable program runs, the device where the storage medium is located is controlled to execute the above-mentioned vehicle transportation method.

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

[0028] In an embodiment of the present invention, a method of obtaining the position information, collision information and speed information of the target vehicle and the loaded vehicle is adopted, and driving warning information is generated based on the position information and speed information, and collision warning information is generated based on the collision information. Finally, a vehicle transportation strategy is determined based on the driving warning information and the collision warning information, thereby achieving the purpose of real-time updating of the logistics information of the target vehicle during transportation and comprehensive monitoring of the safety status of the target vehicle during transportation, thereby achieving the technical effect of improving the transportation efficiency and safety of the target vehicle during transportation, and further solving the technical problems of poor real-time updating of logistics information during vehicle transportation and incomplete monitoring of vehicle safety in related technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

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

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

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

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

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

[0035] Figure 6 is a structural block diagram of a vehicle transportation device according to one embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0037] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[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 of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0039] The method embodiment can be executed in an electronic device or a similar computing device including a memory and a processor. Taking running on a vehicle terminal as an example, the vehicle terminal may include one or more processors (the processor may include but is not limited to a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processing (DSP) chip, a microcontroller unit (MCU), a programmable logic device (Field Programmable Gate Array, FPGA), a neural network processor (Neural-network Processor Unit, NPU), a tensor processor (Tensor Processing Unit, TPU), an artificial intelligence (Artificial Intelligence, AI) type processor, etc.) and a memory for storing data. Optionally, the above-mentioned vehicle terminal may also include a transmission device, an input and output device, and a display device for communication functions. It can be understood by those of ordinary skill in the art that the above-mentioned structural description is only for illustration and does not limit the structure of the above-mentioned vehicle terminal. For example, the vehicle terminal may also include more or fewer components than the above-mentioned structural description, or have a configuration different from the above-mentioned structural description.

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

[0041] The transmission device is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the mobile terminal. In one example, the transmission device includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0042] The display device may be, for example, a touch screen type liquid crystal display (LCD) and a touch display (also referred to as a "touch screen" or "touch display screen"). The liquid crystal display may enable a user to interact with a user interface of a mobile terminal. In some embodiments, the mobile terminal has a graphical user interface (GUI), and a user may interact with the GUI by finger contacts and / or gestures on a touch-sensitive surface, wherein the human-computer interaction functions here may optionally include the following interactions: creating web pages, drawing, word processing, making electronic documents, games, video conferencing, instant messaging, sending and receiving emails, call interfaces, playing digital videos, playing digital music and / or web browsing, etc. The executable instructions for executing the above human-computer interaction functions are configured / stored in a computer program product or readable storage medium executable by one or more processors.

[0043] Figure 1 is a flow chart of a vehicle transportation method according to one embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0044] Step S10, obtaining the position information, collision information and speed information of the target vehicle, wherein the collision information includes the collision intensity information and collision position information between the target vehicle and the loading vehicle, and the loading vehicle is used to represent the vehicle that transports the target vehicle;

[0045] In step S10 , the target vehicle is used to represent a vehicle transported from a vehicle manufacturing plant to a vehicle sales store.

[0046] The above-mentioned loaded vehicle is used to represent a vehicle loaded with a target vehicle during transportation from a vehicle manufacturing plant to a vehicle sales store.

[0047] The collision information is used to characterize the collision intensity suffered by the target vehicle and the collision position of the target vehicle when a collision occurs between the target vehicle and a loading vehicle during transportation from a vehicle manufacturing plant to a vehicle sales store.

[0048] Step S12, generating driving warning information based on the position information and speed information;

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

[0050] Specifically, during transportation from the vehicle manufacturing plant to the vehicle sales store, it is judged whether the current transportation path deviates from the target transportation route and whether the current loading vehicle is speeding according to the location information of the target vehicle and the speed information of the loading vehicle. According to the judgment result, driving warning information is generated to remind the vehicle transportation logistics monitoring personnel and the loading vehicle driver, which can not only enable the vehicle transportation logistics monitoring personnel to obtain logistics transportation information in real time, but also remind the driver to take timely action to reduce the risk of accidents.

[0051] Step S14, generating collision warning information based on the collision information;

[0052] In step S14, the collision warning information is divided into different collision warning levels, and the collision warning information of different collision warning levels corresponds to different reminder methods. The collision warning information includes but is not limited to: collision warning level identification, detailed location of collision, collision degree and recommended emergency treatment measures, etc.

[0053] Specifically, during transportation from the vehicle manufacturing plant to the vehicle sales store, collision warning information is generated based on the collision intensity suffered by the target vehicle and the position where the target vehicle was collided when the target vehicle collides with the loading vehicle to remind the vehicle transportation logistics monitoring personnel and the staff of the vehicle sales store, and the picture of the collision position of the target vehicle and the video information when the collision occurs are retained to improve the efficiency of the staff in handling collision accidents.

[0054] Step S16, 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.

[0055] Specifically, based on the driving warning information and the collision warning information, the driver of the loading vehicle will adjust the transportation strategy of the vehicle. By changing the transportation route to avoid high-risk areas, or adjusting the transportation speed to reduce the risk of collision. At the same time, the adjustment of the vehicle transportation strategy is carried out in real time to ensure that the target vehicle is always in the safest and most efficient state. The logistics visualization system will continuously monitor the status of the loading vehicle and the target vehicle, and update the vehicle transportation strategy according to the latest data, wherein the logistics visualization system integrates the vehicle transportation method of the present invention.

[0056] Based on the above steps S10 to S16, the location information, collision information and speed information of the loaded vehicle of the target vehicle are obtained, 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 the collision warning information, thereby achieving the purpose of real-time updating of the logistics information of the target vehicle during transportation and comprehensive monitoring of the safety status of the target vehicle during transportation, thereby achieving the technical effect of improving the transportation efficiency and safety of the target vehicle during transportation, and further solving the technical problems of poor real-time updating of logistics information during vehicle transportation and incomplete monitoring of vehicle safety in related technologies.

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

[0058] Step S121, using a preset path fitting algorithm to fit the location information to obtain a fitting transportation path;

[0059] In step S121, the preset path fitting algorithm is used to infer the transportation path of the target vehicle from a series of discrete location data points, wherein 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 transport path is used to characterize the transport path of the target vehicle predicted by using a preset path fitting algorithm.

[0061] Specifically, a preset path fitting algorithm is used to extract the transport path features from the position information. That is, the position information of the target vehicle is input into the selected preset path algorithm, and the preset path algorithm processes the input position information to obtain a fitted transport path. The fitted transport path can not only reflect the transport path that the target vehicle has traveled during the transport process, but also predict the path that the target vehicle will travel during the transport process.

[0062] Step S122, comparing the fitted transport path with the preset transport path to obtain a comparison result;

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

[0064] The above comparison result is used to indicate whether the deviation between the fitted transport path and the preset transport path is greater than a preset deviation threshold, wherein different preset deviation thresholds can be set according to different preset transport paths. The preset deviation threshold can be determined according to factors such as the characteristics of the transport route, the types of target vehicles and loading vehicles, and safety requirements.

[0065] Specifically, the fitted transport path is compared with the preset transport path to identify the difference between the two. If the deviation between the fitted transport path and the preset transport path is greater than or equal to the preset deviation threshold, it means that the current transport path seriously deviates from the preset transport path; if the deviation between the fitted transport path and the preset transport path is less than or equal to the preset deviation threshold, it means that the current transport path meets the preset transport path. For example, for a vehicle transported from a Shanghai manufacturing plant to a Beijing sales store, the logistics visualization system plans an optimal transport path in advance, namely the preset transport path, including major highways and expected parking points. The preset deviation threshold is 10 kilometers. Preset transport path: Shanghai->Nanjing->Xuzhou->Jinan->Beijing. During transportation, the actual driving path of the vehicle may deviate from the preset path due to traffic conditions, weather factors or driver's decision. The loading vehicle detoured because of an accident on the highway between Nanjing and Xuzhou. The fitted transport path obtained according to the location information. The fitted transport path is compared with the preset transport path, and it is found that the vehicle actually passes through the route of Nanjing->Hefei->Xuzhou. Since the deviation between the actual driving path of the vehicle and the preset transport path exceeds 10 kilometers, the comparison result shows that the current transport path seriously deviates from the preset transport path.

[0066] Step S123, generating driving warning information based on the comparison result and speed information.

[0067] Specifically, the comparison result and speed information are combined to determine whether a driving warning message needs to be generated. If the fitted transport path deviates significantly from the preset transport path, or there is an abnormal speed change in the loading vehicle, the logistics visualization system will generate corresponding driving warning messages.

[0068] Based on the above steps S121 to S123, the position information is fitted using a preset path fitting algorithm to obtain a fitted transport path, the fitted transport path is compared with the preset transport path to obtain a comparison result, and driving warning information is generated based on the comparison result and speed information. By real-time monitoring of the position information of the target vehicle and predicting the future driving path, it is helpful to promptly discover deviations and take preventive measures. By comparing the fitted transport path with the preset transport path, deviations from the scheduled route can be quickly identified, thereby reducing transportation risks and improving vehicle transportation safety.

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

[0070] Step S1231, in response to the comparison result that the deviation between the fitted transport path and the preset transport path is greater than or equal to the preset deviation threshold, and the speed information indicates 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 the first driving warning level;

[0071] Specifically, if the deviation between the fitted transport path and the preset transport path is greater than or equal to the preset deviation threshold based on the analysis and comparison results. At the same time, the speed information is analyzed to confirm that the speed of the loading vehicle is greater than the preset speed threshold, then the logistics visualization system determines that the warning level of the driving warning information is the first driving warning level. The first driving warning level means that the situation is more urgent and immediate measures need to be taken. The generated driving warning information will include a warning level identification, as well as specific deviation degree and speed information. In addition, the logistics visualization system needs to provide emergency operation suggestions for the loading vehicle, such as immediate deceleration, route adjustment, etc.

[0072] Step S1232, in response to the comparison result that the deviation between the fitted transport path and the preset transport path is less than the preset deviation threshold, and the speed information indicates 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 the second driving warning level, wherein the first driving warning level is higher than the second driving warning level.

[0073] Specifically, if the deviation between the fitted transport path and the preset transport path is less than the preset deviation threshold based on the analysis and comparison results. At the same time, the speed information is analyzed to confirm that the speed of the loading vehicle is greater than the preset speed threshold, then the logistics visualization system determines that the warning level of the driving warning information is the second driving warning level, which means that the situation is less urgent than the first level, but still needs attention. The generated driving warning information will include a warning level indicator and specific speed information. The logistics visualization system provides recommended operation suggestions, such as slowing down appropriately and keeping attention on the route. For example, a vehicle departs from a Shanghai manufacturing plant to a Beijing sales store. The preset route is from Nanjing and Xuzhou to Beijing. The preset deviation threshold is 5 kilometers and the preset speed threshold is 100 kilometers per hour. Case 1: The actual driving path of the loading vehicle deviates from the preset path. The actual path is from Shanghai to Hangzhou via Hangzhou, 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, the 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 scheduled route by more than 5 kilometers, and the speed exceeds the safety threshold. It is recommended to slow down immediately and adjust the route to return to the preset route from Nanjing to Xuzhou. Case 2: The actual driving path of the vehicle basically follows the preset path, but the average speed in the Nanjing to Xuzhou section is 120 kilometers per hour. The deviation does not exceed 5 kilometers, and the speed exceeds 100 kilometers per hour. At this time, the driving warning information is triggered, and the warning level of the driving warning information is the second driving warning level. The logistics visualization system broadcasts to the loading vehicle: Pay attention to the warning! The vehicle speed exceeds the safety threshold. It is recommended to slow down appropriately to ensure transportation safety while maintaining compliance with the preset path.

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

[0075] Optionally, in step S14, generating collision warning information based on the 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, determining that the warning level of the collision warning information is the first collision warning level;

[0077] Specifically, if the collision information indicates that the collision level of the target vehicle is the first collision level, which means that the collision is relatively minor or the potential risk is low, the logistics visualization system determines that the warning level of the collision warning information is the first collision warning level. The generated collision warning information will include the warning level identification and detailed information of the collision. In addition, the logistics visualization system will provide preliminary operational suggestions, such as checking the status of the target vehicle, reminding the loading vehicle to pay attention to driving safety, and suggesting that the loading vehicle 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, determining that the warning level of the collision warning information is the second collision warning level, wherein the first collision warning level is lower than the second collision warning level.

[0079] Specifically, the collision information is analyzed to evaluate the collision level of the target vehicle. If the collision information indicates that the collision level of the target vehicle is the second collision level, this usually means that the collision is more serious or the potential risk is higher. The logistics visualization system determines that the warning level of the collision warning information is the second collision warning level. The generated collision warning information will include the warning level identification and detailed information of the collision. In addition, the logistics visualization system provides emergency operation suggestions, such as immediate parking inspection, contacting rescue or maintenance services, and suggesting that the loading vehicle slow down.

[0080] Based on the above steps S141 to S142, 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, so that the logistics visualization system can provide different degrees of emergency information according to different situations, enhance the timeliness and pertinence of the information, and by setting multiple collision levels and corresponding warning levels, the safety status of the vehicle 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 collision information of the target vehicle includes:

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

[0083] Step S102, determining collision intensity information based on target vehicle sensor data;

[0084] Step S103: determining collision position information based on the video image information.

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

[0086] Furthermore, when a collision occurs, the control system of the target vehicle will synchronously upload the location information of the target vehicle and retain the image of the collision site to the vehicle storage space. These data are transmitted to the logistics visualization system through the vehicle's communication module. After receiving the sensor data, the logistics visualization system analyzes the data of the acceleration sensor and the vibration sensor. The intensity of the collision is determined through algorithm processing, such as peak detection and energy calculation. The collision intensity information includes the amplitude of the acceleration change, the duration and intensity of the vibration, etc. After receiving the photos and videos taken by the surround view camera, the logistics visualization system performs image recognition and analysis. Use computer vision technology, such as feature point matching and deep learning, to determine the specific location of the collision. The collision location information includes the coordinates of the collision point relative to the vehicle, the size of the collision area, etc.

[0087] Based on the above steps S101 to S103, in response to a collision between the target vehicle and the loading vehicle, the sensor data and video image information of the target vehicle are obtained, the collision intensity information is determined based on the sensor data of the target vehicle, and the collision position information is determined based on the video image information. The sensor data and video image information at the moment of the collision can be quickly obtained, and the instant response mechanism ensures the real-time collection and transmission of the collision information, so that the logistics visualization system can obtain accurate collision information at the first time, thereby enhancing the real-time nature of the logistics information.

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

[0089] Step S104, obtaining the location information fed back by the Internet of Vehicles control unit of the target vehicle according to a preset time period;

[0090] Specifically, the logistics visualization system sets a preset duration according to the needs of transportation monitoring, which is used to regularly obtain the location information of the target vehicle. The preset duration can be determined based on factors such as the length of the preset transportation route, the average speed of the loaded vehicle, and the accuracy requirements of monitoring. Based on the whole vehicle SOA architecture of the target vehicle, the logistics visualization system issues a wake-up command on a daily basis to wake up only the vehicle-mounted information terminal (T-Box) in the vehicle without waking up the whole vehicle, which can reduce power consumption during transportation and prevent battery feeding. After the target vehicle wakes up, high-precision GPS technology is used to obtain the vehicle's real-time location information. The location information includes the longitude, latitude, and altitude of the vehicle. Through 4G / 5G communication technology, the location information is uploaded to the cloud server in real time. The logistics visualization system reads the location information from the cloud and stores it in the database for subsequent analysis and use.

[0091] Step S105, obtaining speed information fed back by the loading vehicle according to a preset time period.

[0092] Specifically, the speed information of the loaded vehicle is obtained regularly according to the preset duration. The on-board sensor (such as the speed sensor) obtains the speed information of the loaded vehicle. The speed information includes the current speed, acceleration, deceleration, etc. of the vehicle. Through 4G / 5G communication technology, the speed information is uploaded to the cloud server in real time. The logistics visualization system reads the speed information from the cloud and stores it in the database for subsequent analysis and use.

[0093] Specifically, Figure 2 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 phone application (Application, APP) end, a logistics outbound system end and a logistics visualization system end, wherein the logistics outbound system is used to bind the user order with the vehicle VIN code when the logistics end receives the user mobile phone APP order, and input the VIN code into the logistics visualization system after the vehicle starts transportation. The logistics visualization system is used to obtain the logistics information of the target vehicle in the transportation process in real time, and push the logistics information to the user APP end.

[0094] Furthermore, the logistics visualization system obtains the location information of the target vehicle at regular intervals according to the needs of transportation monitoring. Based on the SOA architecture of the target vehicle, the logistics visualization system sends a wake-up command at regular intervals every day, waking up only the vehicle networking control unit (T-Box) in the vehicle, but not the entire vehicle, which can reduce power consumption during transportation and prevent battery power feeding. After the target vehicle is awakened, the T-Box uses GPS technology to obtain the vehicle's real-time location information and uploads the location information to the cloud server in real time. The logistics visualization system reads the location information from the cloud and stores it in the database for subsequent analysis and use. At the same time, when a collision occurs, the control system of the target vehicle will synchronously upload the location information of the target vehicle and retain the picture of the collision site to the vehicle computer storage space. These data are transmitted to the logistics visualization system through the communication module. After receiving the sensor data, the logistics visualization system analyzes the data of the acceleration sensor and the vibration sensor. The intensity of the collision is determined by algorithm processing. After receiving the photos and videos taken by the surround view camera, the logistics visualization system performs image recognition and analysis to determine the specific location of the collision.

[0095] Based on the above steps S104 to S105, the location information fed back by the vehicle networking control unit of the target vehicle is obtained according to the preset time; the speed information fed back by the loading vehicle is obtained according to the preset time. When obtaining the location information, only the vehicle information terminal (T-Box) in the vehicle is awakened without waking up the entire vehicle, thereby reducing the power consumption during transportation. This helps to extend the life of the battery and reduce operating costs.

[0096] Optionally, the target vehicle is distinguished based on vehicle unique identifier information.

[0097] Specifically, the vehicle unique identifier information is used to represent the vehicle identification number (VIN) of the target vehicle. The logistics visualization system distinguishes the target vehicle according to the VIN.

[0098] Optionally, the vehicle transportation method further comprises:

[0099] Step S171, obtaining traffic condition information;

[0100] In step S171, the above traffic condition information includes road congestion, accident reports, construction areas, traffic control, weather conditions, etc.

[0101] Step S172, updating the expected timestamp of the target vehicle arriving at the target location based on the location information, speed information and traffic condition information.

[0102] Specifically, traffic condition information can be obtained from multiple sources, including traffic monitoring cameras, vehicle-mounted GPS systems, etc. In addition, traffic condition information is updated in real time to ensure the timeliness and accuracy of the data. The real-time location information and speed information of the target vehicle are combined with the acquired traffic condition information to estimate the expected time from the current location to the target location. The updated expected timestamp is notified to relevant parties such as drivers, logistics dispatch centers, consignees, etc. through the logistics visualization system.

[0103] Based on the above steps S171 to S172, the traffic condition information is obtained, and the expected timestamp of the target vehicle arriving at the target location is updated based on the location information, speed information and traffic condition information. The real-time updated expected timestamp provides the relevant parties with accurate information about the transportation progress. The driver, logistics dispatch center and consignee can all understand 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 is a flow chart of another vehicle transportation method according to one embodiment of the present invention, such as Figure 3 As shown, the method comprises the following steps:

[0105] Step S301, obtaining the location information fed back by the Internet of Vehicles control unit of the target vehicle according to a preset time period;

[0106] Step S302, obtaining speed information fed back by the loading vehicle according to a preset time period;

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

[0108] Step S304, determining collision intensity information based on target vehicle sensor data;

[0109] Step S305, determining collision position 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, determining that the warning level of the collision warning information is 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, determining that the warning level of the collision warning information is the second collision warning level;

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

[0113] Step S309, comparing the fitted transport path with the preset transport path to obtain a comparison result;

[0114] Step S310, in response to the comparison result that the deviation between the fitted transport path and the preset transport path is greater than or equal to the preset deviation threshold, and the speed information indicates 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 the first driving warning level;

[0115] Step S311, in response to the comparison result that the deviation between the fitted transport path and the preset transport path is less than the preset deviation threshold, and the speed information indicates 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 the second driving warning level;

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

[0117] Based on the above steps S301 to S312, the location information, collision information and speed information of the loaded vehicle of the target vehicle are obtained, and 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 the collision warning information, thereby achieving the purpose of real-time updating of the logistics information of the target vehicle during transportation and comprehensive monitoring of the safety status of the target vehicle during transportation, thereby achieving the technical effect of improving the transportation efficiency and safety of the target vehicle during transportation, and further solving the technical problems of poor real-time updating of logistics information during vehicle transportation and incomplete monitoring of vehicle safety in related technologies.

[0118] The following is an example to introduce the workflow of the above vehicle transportation method in detail:

[0119] Specifically, Figure 4 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 (Application, APP): Users can select and order vehicles independently through mobile APP. After placing an order for a vehicle, you can follow the various status and positioning information of the vehicle from the factory to the logistics transportation location, and the arrival time of the vehicle in real time on the APP. ② Logistics outbound system: After the logistics end receives the user's mobile APP order, it binds the user's order with the vehicle VIN code, and enters the VIN code into the logistics visualization system after the vehicle starts to be transported. ③ Vehicle positioning upload system: Based on the vehicle SOA architecture, the logistics visualization system sends wake-up and location information acquisition instructions on a daily basis. Each time the vehicle only wakes up the T-Box in the vehicle, not the entire vehicle, to reduce power consumption during transportation and prevent battery feeding. After the vehicle wakes up, high-precision GPS and 4G / 5G communication technology are used to update the vehicle's real-time positioning information, and the positioning information is returned to the cloud. The logistics visualization system reads the data back 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 on-board sensors, such as acceleration sensors and vibration sensors, which monitor the dynamic status of the vehicle in real time. Based on the service-oriented architecture (SOA), the control system of the target vehicle is designed to be modular, and each sensor service can be activated when needed. When the sensor detects a collision event, it automatically wakes up the vehicle's cockpit controller. The cockpit controller then activates the surround view camera and starts recording photos of the target vehicle's collision site and videos of the surrounding environment. When a collision occurs, the control system of the target vehicle will synchronously upload the target vehicle's location information and retain the pictures of the collision site to the vehicle's storage space. These data are transmitted to the logistics visualization system through the vehicle's communication module. ⑤ Logistics visualization system: responsible for waking up the vehicle at a fixed time, reading the positioning data information uploaded by the vehicle to the cloud, for interface display and writing to the database for use by mobile phone APP. In addition, after receiving the sensor data, the logistics visualization system analyzes the data of the acceleration sensor and vibration sensor. The intensity of the collision is determined through algorithm processing. After receiving the photos and videos taken by 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 is a schematic diagram of another vehicle transportation method according to one embodiment of the present invention, such as Figure 5As shown. First, the user places an order for the desired vehicle on the mobile APP; after the order is successfully placed on the mobile APP, the logistics outbound system matches the relevant vehicle VIN code according to the user's order information, and automatically writes the vehicle-related VIN code, daily positioning time, and vehicle transportation start and end time related information to the logistics visualization system through the relevant interface. Then, the logistics visualization system sends the vehicle positioning information instruction to the TSP on a daily basis according to the input requirements of the logistics end; and performs path fitting, estimated arrival time estimation and related early warning strategy formulation based on the positioning information returned by the vehicle. Logistics personnel can consider recalling vehicles or replacing transportation drivers based on the severity of the warning and the number of warnings. Specific early warning strategies:

[0122] ① The warning level of the driving warning information is the first driving warning level: if it is confirmed based on the analysis and comparison results that the deviation between the fitted transport path and the preset transport path is greater than or equal to the preset deviation threshold. At the same time, the speed information is analyzed to confirm that the speed of the loading vehicle is greater than the preset speed threshold, then the logistics visualization system determines that the warning level of the driving warning information is the first driving warning level. The first driving warning level means that the situation is more urgent and immediate measures need to be taken. The generated driving warning information will include a warning level identification, as well as specific deviation degree and speed information. In addition, the logistics visualization system needs to provide emergency operation suggestions for the loading vehicle, such as immediate deceleration, route adjustment, etc.;

[0123] ② The warning level of the driving warning information is the second driving warning level: if the deviation between the fitted transport path and the preset transport path is confirmed to be less than the preset deviation threshold based on the analysis and comparison results. At the same time, the speed information is analyzed to confirm that the speed of the loading vehicle is greater than the preset speed threshold, then the logistics visualization system determines that the warning level of the driving warning information is the second driving warning level. The second driving warning level means that the situation is less urgent than the first level, but still requires attention. The generated driving warning information will include a warning level identifier and specific speed information. The logistics visualization system provides suggested operational suggestions, such as slowing down appropriately and keeping an eye on the route;

[0124] ③ The warning level of the collision warning information is the first collision warning level: If the collision information indicates that the collision level of the target vehicle is the first collision level, this means that the collision is relatively minor or the potential risk is low. The logistics visualization system determines that the warning level of the collision warning information is the first collision warning level. The generated collision warning information will contain the warning level identification and detailed information of the collision. In addition, the logistics visualization system will provide preliminary operational suggestions, such as checking the status of the target vehicle, reminding the loading vehicle to pay attention to driving safety, and suggesting that the loading vehicle slow down, etc.;

[0125] ④ The warning level of the collision warning information is the second collision warning level: If the collision information indicates that the collision level of the target vehicle is the second collision level, this usually means that the collision is more serious or the potential risk is higher. The logistics visualization system determines that the warning level of the collision warning information is the second collision warning level. The generated collision warning information will contain the warning level identification and detailed information of the collision. In addition, the logistics visualization system provides emergency operation suggestions, such as immediate parking inspection, contacting rescue or maintenance services, and suggesting that the loading vehicle slow down.

[0126] Furthermore, TSP automatically forwards the command to obtain vehicle positioning information; when the target vehicle receives the wake-up positioning information, only the T-Box in the vehicle wakes up and uploads the positioning information and the current vehicle transportation speed information, and the entire vehicle does not wake up to prevent the battery from being powered during transportation; the vehicle returns the positioning information to the logistics visualization system through TSP, and the logistics visualization system writes the data information into the database for the mobile phone APP to read the positioning information and the logistics visualization system to perform path fitting and estimated arrival time estimation. In addition, after the logistics end vehicle leaves the warehouse, it automatically enters the vehicle transportation mode. The target vehicle automatically starts the vehicle collision detection system and the body piezoelectric sensor scratch detection system according to the transportation mode identification, automatically monitors during vehicle transportation, and automatically transmits the signal to the smart cockpit system after a collision is detected. The smart cockpit system automatically wakes up the in-vehicle / body / out-of-vehicle cameras based on the collision signal to record the video and upload the image to the logistics visualization system.

[0127] Finally, after the target vehicle arrives at the store, the logistics end automatically goes to the vehicle outbound system, ends the vehicle location upload and exits the vehicle transportation mode.

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

[0129] In the embodiments of the present invention, a vehicle transportation device is also provided, which is used to implement the above embodiments and preferred embodiments, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0130] Figure 6 1 is a structural block diagram of a vehicle transportation device according to one embodiment of the present invention. Figure 6 As shown, the device comprises:

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

[0132] A first generating module 602, configured to generate driving warning information based on the position information and the speed information;

[0133] A second generating module 603, configured to generate collision warning information based on the collision information;

[0134] The determination module 604 is used 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.

[0135] Optionally, the first generating module 602 is further used 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 also used to: generate driving warning information based on the comparison result and the speed information, including: in response to the comparison result being that the deviation between the fitted transport path and the preset transport path is greater than or equal to a preset deviation threshold, and the speed information indicates 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 first driving warning level; in response to the comparison result being that the deviation between the fitted transport path and the preset transport path is less than the preset deviation threshold, and the speed information indicates 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.

[0137] Optionally, the second generation module 603 is also used 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 also used to obtain 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 also used to: determine collision intensity information based on the target vehicle sensor data; determine collision position information based on the video image information.

[0139] Optionally, the acquisition module 601 is further used to: acquire the position information fed back by the Internet of Vehicles control unit of the target vehicle according to a preset time duration; and acquire the speed information fed back by the loaded vehicle according to a preset time duration.

[0140] Optionally, the target vehicle is distinguished based on vehicle unique identifier information.

[0141] Optionally, the acquisition module 601 is further used to acquire traffic condition information; the vehicle transportation 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, it can be implemented in the following ways, but not limited to: the above modules are all 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, there is also provided an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the above-mentioned vehicle transportation method is executed when the program is running.

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

[0145] Step S1, obtaining the position information, collision information and speed information of the loading vehicle of the target vehicle, wherein the collision information includes the collision intensity information and collision position information between the target vehicle and the loading vehicle, and the loading vehicle is used to represent the vehicle that transports the target vehicle;

[0146] Step S2, generating driving warning information based on the position information and speed information;

[0147] Step S3, generating collision warning information based on the collision information;

[0148] Step S4, 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.

[0149] According to one embodiment of the present invention, a computer-readable storage medium is further provided. The computer-readable storage medium includes a stored executable program, wherein when the executable program runs, the device where the storage medium is located is controlled to execute the above-mentioned 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, obtaining the position information, collision information and speed information of the loading vehicle of the target vehicle, wherein the collision information includes the collision intensity information and collision position information between the target vehicle and the loading vehicle, and the loading vehicle is used to represent the vehicle that transports the target vehicle;

[0152] Step S2, generating driving warning information based on the position information and speed information;

[0153] Step S3, generating collision warning information based on the collision information;

[0154] Step S4, 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.

[0155] Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store computer programs.

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

[0157] Optionally, in this embodiment, the computer program product may be configured as a computer program for executing the following steps:

[0158] Step S1, obtaining the position information, collision information and speed information of the loading vehicle of the target vehicle, wherein the collision information includes the collision intensity information and collision position information between the target vehicle and the loading vehicle, and the loading vehicle is used to represent the vehicle that transports the target vehicle;

[0159] Step S2, generating driving warning information based on the position information and speed information;

[0160] Step S3, generating collision warning information based on the collision information;

[0161] Step S4, 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.

[0162] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0163] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0164] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made 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. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

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

[0167] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0168] If the integrated unit is implemented in the form of 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, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0169] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A vehicle transportation method, characterized in that: include: Acquire the position information, collision information and speed information of the target vehicle, wherein the collision information includes the collision intensity information and collision position 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 position information and the speed information; generating collision warning information based on the collision information; A vehicle transportation strategy is determined 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.

2. The vehicle transportation method according to claim 1, characterized in that: Generating the driving warning information based on the position information and the speed information includes: Using a preset path fitting algorithm to fit the location information to obtain a fitted transportation path; Compare the fitted transport path s with the preset transport path to obtain a comparison result; The driving warning information is generated based on the comparison result and the speed information.

3. The vehicle transportation method according to claim 2, characterized in that: Generating the driving warning information based on the comparison result and the speed information includes: In response to the comparison result being that the deviation between the fitted transport path and the preset transport 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 the warning level of the driving warning information is a first driving warning level; In response to the comparison result being that the deviation between the fitted transport path and the preset transport path is less than the preset deviation threshold, and the speed information indicates that the speed of the loading vehicle is greater than the preset speed threshold, the warning level of the driving warning information is determined to be a second driving warning level, wherein the first driving warning level is higher than the second driving warning level.

4. The vehicle transportation method according to claim 1, characterized in that: Generating the collision warning information based on the collision information includes: In response to the collision information indicating that the collision level of the target vehicle is a first collision level, determining that the 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 the warning level of the collision warning information to be a second collision warning level, wherein the first collision warning level is lower than the second collision warning level.

5. The vehicle transportation method according to claim 1, characterized in that: Acquiring the 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 the collision intensity information based on the target vehicle sensor data; The collision position information is determined based on the video image information.

6. The vehicle transportation method according to claim 1, characterized in that: Acquiring the position information of the target vehicle and the speed information of the loading vehicle includes: Acquire the location information fed back by the Internet of Vehicles control unit of the target vehicle according to a preset time period; The speed information fed back by the loading vehicle is obtained according to the preset time period.

7. The vehicle transportation method according to claim 1, characterized in that: The target vehicle is identified based on the vehicle unique identifier information.

8. The vehicle transportation method according to claim 1, characterized in that: The method further comprises: Get traffic condition information; An expected time stamp of the target vehicle arriving at a target location is updated based on the location information, the speed information, and the traffic condition information.

9. A vehicle transport device, characterized in that: include: an acquisition module, used to acquire the position information, collision information and speed information of the target vehicle, wherein the collision information includes the collision intensity information and collision position information between the target vehicle and the loading vehicle, and the loading vehicle is used to represent the vehicle transporting the target vehicle; A first generating module, configured to generate driving warning information based on the position information and the speed information; A second generating module, configured to generate collision warning information based on the collision information; A determination module is used 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.

10. An electronic device, characterized in that: include: A memory storing an executable program; A processor is used to run the program, wherein the vehicle transportation method according to any one of claims 1 to 8 is executed when the program is run.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is executed, the device where the storage medium is located is controlled to execute the vehicle transportation method according to any one of claims 1 to 8.

12. A computer program product, characterized in that It comprises a computer program which, when executed by a processor, implements the vehicle transportation method according to any one of claims 1 to 8.

Images