Method, device, equipment and storage medium for autonomous delivery of goods by network point vehicles

Abstract

The present invention relates to the field of information processing technology, and in particular to a method, device, equipment and storage medium for autonomous delivery of parcels by network point vehicles, which creates a delivery task according to cargo information, allocates a unique task number to the delivery task, uses a path planning algorithm to calculate the delivery route of the delivery task, sends the task number and the delivery route to a transport vehicle, monitors the position information and speed information of the transport vehicle in real time, determines the vehicle driving state of the transport vehicle according to the position information and the speed information, generates low-speed warning information when the vehicle driving state is an abnormal stop state, and sends the low-speed warning information to the transport vehicle, obtains unloading scanning information of a delivery barcode, records the delivery distribution site location of the cargo according to the unloading scanning information, can monitor the vehicle position in real time, automatically complete the delivery task, improve the degree of automation, improve the accuracy and timeliness of delivery, and improve user satisfaction.

Description

Technical Field

[0001] The present invention relates to the field of information processing technology, and in particular to a method, device, equipment and storage medium for autonomous delivery of parcels by network point vehicles. Background Art

[0002] In modern logistics systems, the efficiency of delivery tasks is crucial because it is directly related to the operational efficiency and effectiveness of the entire supply chain. An efficient delivery process can ensure that goods are quickly and accurately transferred from one link to another, thereby reducing logistics delays, improving customer satisfaction, and reducing operating costs. However, traditional delivery methods often rely on manual operations, which are not only inefficient, but also prone to human errors, such as wrong delivery, missed delivery, or delayed delivery. It cannot monitor the location of vehicles in real time, and cannot automatically complete delivery tasks. The low degree of automation reduces the accuracy and timeliness of delivery. These problems will not only slow down the operation of the entire supply chain, but may also lead to a decline in customer trust. Summary of the invention

[0003] In order to overcome the shortcomings of the prior art, the purpose of the present invention is to provide a method, device, equipment and storage medium for autonomous delivery of parcels by network vehicles, which can monitor the vehicle position in real time, automatically complete the delivery task, improve the degree of automation, improve the accuracy and timeliness of delivery, and enhance user satisfaction.

[0004] The first aspect of the present invention provides a method for autonomous delivery of parcels by branch vehicles, comprising: creating a delivery task based on cargo information, and assigning a unique task number to the delivery task; using a path planning algorithm to calculate the delivery route of the delivery task, and sending the task number and the delivery route to a transport vehicle; real-time monitoring of the position information and speed information of the transport vehicle, and determining the vehicle driving status of the transport vehicle based on the position information and the speed information; when the vehicle driving status is an abnormal stop state, generating low-speed warning information, and sending the low-speed warning information to the transport vehicle; obtaining the unloading scanning information of the delivery barcode, and recording the location of the delivery distribution site for the goods based on the unloading scanning information.

[0005] Optionally, in a first implementation method of the first aspect of the present invention, creating a delivery task based on cargo information and assigning a unique task number to the delivery task includes: receiving a cargo delivery instruction, parsing the cargo delivery instruction to obtain cargo information; identifying cargo quantity information, cargo weight information and destination information in the cargo information; creating a delivery task based on the cargo quantity information, the cargo weight information and the destination information; and assigning a unique task number to the delivery task.

[0006] Optionally, in a second implementation method of the first aspect of the present invention, the use of a path planning algorithm to calculate the delivery route of the delivery task and sending the task number and the delivery route to the transport vehicle includes: using a path planning algorithm to calculate the delivery route of the delivery task; identifying the delivery points of the delivery route, and evaluating the transportation capacity and dispatchable vehicle capacity of the delivery points; specifying the transport vehicle according to the transportation capacity and the dispatchable vehicle capacity; binding the task number and the transport vehicle information, and sending the delivery route to the transport vehicle.

[0007] Optionally, in a third implementation method of the first aspect of the present invention, the real-time monitoring of the position information and speed information of the transport vehicle, and determining the vehicle driving status of the transport vehicle based on the position information and the speed information, includes: real-time monitoring of the position information and speed information corresponding to the transport vehicle according to the task number; drawing actual driving trajectory data based on the position information, and calculating the deviation rate between the actual driving trajectory data and the delivery route; judging whether the deviation rate is greater than a preset deviation threshold; if not, using a preset vehicle driving model to analyze the position information and the speed information to obtain an analysis result; and determining the vehicle driving status of the transport vehicle based on the analysis result.

[0008] Optionally, in a fourth implementation method of the first aspect of the present invention, when the vehicle's driving state is an abnormal stop state, low-speed warning information is generated, and the low-speed warning information is sent to the transport vehicle, including: when the vehicle's driving state is an abnormal stop state, low-speed warning information is generated; the low-speed warning information is sent to the transport vehicle, and real-time environmental information of the transport vehicle is received, the real-time environmental information including driving record images, weather conditions and traffic conditions; the real-time environmental information and the low-speed warning information are entered into a management report.

[0009] Optionally, in a fifth implementation of the first aspect of the present invention, the obtaining of the unloading scanning information of the delivery barcode and recording the location of the delivery distribution site for the goods according to the unloading scanning information include: creating a scanning listener and using the scanning listener to monitor the unloading scanning information of the delivery barcode; when the scanning listener monitors the unloading scanning information, obtaining the current unloading scanning information; and recording the location of the delivery distribution site for the goods according to the unloading scanning information.

[0010] Optionally, in a sixth implementation method of the first aspect of the present invention, after obtaining the unloading scanning information of the delivery barcode and recording the delivery distribution site location of the goods according to the unloading scanning information, it also includes: obtaining the weighed weight information of the goods; determining whether the weighed weight information is consistent with the original weight information of the goods; if so, identifying the delivery destination location of the delivery route; determining whether the delivery distribution site location is consistent with the delivery destination location; if so, generating delivery end information, and obtaining a timestamp from the timestamp service platform based on the generation time of the delivery end information; associating the timestamp with the delivery end information to obtain associated information, and uploading the associated information to the blockchain.

[0011] The second aspect of the present invention provides an autonomous delivery device for branch vehicles, including: a creation and allocation module, used to create a delivery task according to cargo information, and assign a unique task number to the delivery task; a calculation and sending module, used to use a path planning algorithm to calculate the delivery route of the delivery task, and send the task number and the delivery route to the transport vehicle; a monitoring and determination module, used to monitor the position information and speed information of the transport vehicle in real time, and determine the vehicle driving state of the transport vehicle according to the position information and the speed information; a generation and sending module, used to generate low-speed warning information when the vehicle driving state is an abnormal stop state, and send the low-speed warning information to the transport vehicle; an acquisition and recording module, used to obtain the unloading scanning information of the delivery barcode, and record the location of the delivery distribution site of the goods according to the unloading scanning information.

[0012] Optionally, in a first implementation method of the second aspect of the present invention, the creation and allocation module includes: a receiving and parsing unit, used to receive a cargo delivery instruction, parse the cargo delivery instruction, and obtain cargo information; an identification unit, used to identify cargo quantity information, cargo weight information, and destination information in the cargo information; a creation unit, used to create a delivery task based on the cargo quantity information, the cargo weight information, and the destination information; and an allocation unit, used to assign a unique task number to the delivery task.

[0013] Optionally, in a second implementation method of the second aspect of the present invention, the calculation and sending module includes: a calculation unit, used to use a path planning algorithm to calculate the delivery route of the delivery task; an identification and evaluation unit, used to identify the delivery points of the delivery route, and evaluate the transportation capacity and dispatchable vehicle capacity of the delivery points; a designation unit, used to designate a transport vehicle based on the transportation capacity and the dispatchable vehicle capacity; a binding and sending unit, used to bind information between the task number and the transport vehicle, and send the delivery route to the transport vehicle.

[0014] Optionally, in a third implementation method of the second aspect of the present invention, the monitoring and determination module includes: a monitoring unit, used to monitor the position information and speed information corresponding to the transport vehicle in real time according to the task number; a drawing and calculation unit, used to draw actual driving trajectory data according to the position information, and calculate the deviation rate between the actual driving trajectory data and the delivery route; a judgment unit, used to judge whether the deviation rate is greater than a preset deviation threshold; an analysis unit, used to analyze the position information and the speed information using a preset vehicle driving model to obtain an analysis result if not; and a determination unit, used to determine the vehicle driving status of the transport vehicle according to the analysis result.

[0015] Optionally, in a fourth implementation method of the second aspect of the present invention, the generation and sending module includes: a generation unit, used to generate low-speed warning information when the vehicle's driving state is an abnormal stop state; a sending and receiving unit, used to send the low-speed warning information to the transport vehicle and receive real-time environmental information of the transport vehicle, the real-time environmental information including driving record images, weather conditions and traffic conditions; an entry unit, used to enter the real-time environmental information and the low-speed warning information into a management report.

[0016] Optionally, in a fifth implementation of the second aspect of the present invention, the record acquisition module includes: creating a monitoring unit, used to create a code scanning monitor, and using the code scanning monitor to monitor the unloading scanning information of the delivery barcode; an acquisition unit, used to obtain the current unloading scanning information when the code scanning monitor monitors the unloading scanning information; and a recording unit, used to record the delivery and distribution site location of the goods according to the unloading scanning information.

[0017] Optionally, in a sixth implementation method of the second aspect of the present invention, it also includes: an acquisition module for acquiring the weighed weight information of the goods; a first judgment module for judging whether the weighed weight information is consistent with the original weight information of the goods; an identification module for identifying the delivery destination position of the delivery route if so; a second judgment module for judging whether the delivery distribution site position is consistent with the delivery destination position; a generation acquisition module for generating delivery end information if so, and obtaining a timestamp from a timestamp service platform based on the generation time of the delivery end information; an association upload module for associating the timestamp with the delivery end information to obtain associated information, and uploading the associated information to the blockchain.

[0018] The third aspect of the present invention provides an autonomous parcel delivery device for network point vehicles, and the autonomous parcel delivery device for network point vehicles includes: a memory and at least one processor, and instructions are stored in the memory; at least one of the processors calls the instructions in the memory to enable the autonomous parcel delivery device for network point vehicles to execute each step of the autonomous parcel delivery method for network point vehicles described in any one of the above items.

[0019] A fourth aspect of the present invention provides a computer-readable storage medium having instructions stored thereon, and when the instructions are executed by a processor, the various steps of any of the above-mentioned methods for autonomous delivery of parcels by vehicles at network points are implemented.

[0020] In the technical solution of the present invention, a delivery task is created according to the cargo information, a unique task number is assigned to the delivery task, a path planning algorithm is used to calculate the delivery route of the delivery task, the task number and the delivery route are sent to the transport vehicle, the position information and speed information of the transport vehicle are monitored in real time, the vehicle driving state of the transport vehicle is determined according to the position information and the speed information, when the vehicle driving state is an abnormal stop state, a low-speed warning information is generated and sent to the transport vehicle, the unloading scanning information of the delivery barcode is obtained, and the delivery distribution site location of the goods is recorded according to the unloading scanning information, so that the vehicle position can be monitored in real time, the delivery task is automatically completed, the degree of automation is improved, the accuracy and timeliness of the delivery are improved, and user satisfaction is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A first flow chart of a method for autonomous delivery of parcels by a network vehicle provided in an embodiment of the present invention;

[0022] Figure 2 A second flow chart of the method for autonomous delivery of parcels by a network vehicle provided in an embodiment of the present invention;

[0023] Figure 3 A third flow chart of the method for autonomous delivery of parcels by a network vehicle provided in an embodiment of the present invention;

[0024] Figure 4 A fourth flow chart of the method for autonomous delivery of parcels by a network vehicle provided in an embodiment of the present invention;

[0025] Figure 5 A schematic diagram of the structure of a network point vehicle autonomous delivery device provided by an embodiment of the present invention;

[0026] Figure 6 Another structural schematic diagram of a network point vehicle autonomous delivery device provided by an embodiment of the present invention;

[0027] Figure 7A schematic diagram of the structure of an autonomous delivery device for a network vehicle provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The present invention provides a method, device, equipment and storage medium for autonomous delivery of parcels by branch vehicles, which can monitor the vehicle position in real time, automatically complete the delivery task, improve the degree of automation, improve the accuracy and timeliness of delivery, and enhance user satisfaction.

[0029] The terms "first", "second", "third", "fourth", etc. (if any) 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 described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "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.

[0030] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 , an embodiment of the method for autonomous delivery of parcels by a network vehicle in an embodiment of the present invention includes:

[0031] 101. Create a delivery task based on the cargo information and assign a unique task number to the delivery task;

[0032] In this embodiment, cargo information is provided by the warehousing, production or order system. Based on the collected cargo information, the system will generate a dispatch task, which includes a detailed description of the cargo information, transportation schedule, vehicle type and capacity. To ensure the traceability and management of the task, each dispatch task needs to be assigned a unique task number, which is generated in ascending order based on the number of tasks generated in the system.

[0033] 102. Use the path planning algorithm to calculate the delivery route of the delivery task, and send the task number and the delivery route to the transport vehicle;

[0034] In this embodiment, the A* algorithm is used to calculate the delivery route of the delivery task. The A* algorithm is an improved shortest path algorithm that combines the Dijkstra algorithm and heuristic search. It can consider the shortest path while also considering complex factors such as time and cargo type. Once the path planning algorithm completes the calculation, the system will obtain an optimal path and send the task number and route data to the transport vehicle through the transportation management system (TMS) or the vehicle scheduling system. These data can be transmitted to the on-board terminal on the transport vehicle through a real-time data transmission protocol (such as GPRS, 4G / 5G and other wireless communication protocols). The navigation system on the vehicle will receive the path information and load the specific route data according to the task number. The navigation system will fine-tune the route according to the real-time traffic conditions, road conditions, etc., and provide navigation guidance for the driver. The task number, as the unique identifier of the transport task, will be associated with the task information in the vehicle navigation system. The driver views the detailed information of the task through the on-board terminal and confirms the route. The uniqueness of the task number ensures that the driver can clearly identify the relevant details of the current task and track the progress of the task.

[0035] 103. Monitor the location information and speed information of the transport vehicle in real time, and determine the driving status of the transport vehicle according to the location information and speed information;

[0036] In this embodiment, the vehicle-mounted positioning system is relied upon to continuously receive satellite signals and calculate its precise position based on the vehicle's current latitude and longitude. The vehicle-mounted sensors are relied upon to obtain the vehicle's current speed in real time. The position information and speed information are transmitted to the central management system via a wireless network (such as 4G, 5G or a dedicated wireless communication network). When the vehicle's speed is within a reasonable range and the vehicle's position is in accordance with the predetermined route, the system determines that the vehicle is in a "normal driving" state. When the vehicle stays at a certain location for a long time and the speed is zero, the system can determine that the vehicle is in a "stopped state."

[0037] 104. When the vehicle driving state is in an abnormal stop state, a low speed warning message is generated and sent to the transport vehicle;

[0038] In this embodiment, when a vehicle stays at a certain location for too long and the vehicle speed is zero, and there is no obvious reason for the pause (such as a traffic accident, road conditions, etc.), it is determined to be an abnormal pause. An abnormal pause indicates that the vehicle has a malfunction, the driver suddenly stops operating, a traffic jam occurs, or other unexpected reasons. A pause time threshold is set (for example, a pause within 3 minutes is not considered abnormal, but a pause exceeding 3 minutes is considered an abnormal pause). When the vehicle's stay time exceeds the threshold, the system will trigger a low-speed warning, generate a low-speed warning message, and send the low-speed warning message to the transport vehicle.

[0039] 105. Obtain the unloading scanning information of the delivery barcode, and record the location of the delivery distribution site of the goods according to the unloading scanning information;

[0040] In this embodiment, after the goods arrive at the destination, the unloading personnel unload the goods according to the predetermined operating procedures. When unloading, the staff uses a barcode scanner or a handheld terminal device to scan the delivery barcode on the goods. This device is usually connected to the background system through Bluetooth, Wi-Fi or other wireless communication technologies, and the scanned information is transmitted to the central database or transportation management system in real time. Once the unloading information is obtained through scanning, the system will record the current specific distribution location of the goods in the database.

[0041] In an embodiment of the present invention, a delivery task is created according to cargo information, a unique task number is assigned to the delivery task, a path planning algorithm is used to calculate the delivery route of the delivery task, the task number and the delivery route are sent to the transport vehicle, the position information and speed information of the transport vehicle are monitored in real time, the vehicle driving state of the transport vehicle is determined according to the position information and the speed information, when the vehicle driving state is an abnormal stop state, a low-speed warning message is generated and sent to the transport vehicle, the unloading scanning information of the delivery barcode is obtained, and the delivery distribution site location of the goods is recorded according to the unloading scanning information. The vehicle position can be monitored in real time, the delivery task is automatically completed, the degree of automation is improved, the accuracy and timeliness of the delivery are improved, and user satisfaction is improved.

[0042] See also Figure 2 The second embodiment of the method for autonomous delivery of parcels by a network vehicle in the embodiment of the present invention includes:

[0043] 201. Receive a cargo delivery instruction, parse the cargo delivery instruction, and obtain cargo information;

[0044] In this embodiment, a cargo delivery instruction is received and parsed. The parsing of the cargo delivery instruction includes extracting the basic information from the received data format and converting it into a structure that the system can understand and further process. Specifically, the data in these formats are first parsed into a data structure for internal use. According to the structure of the delivery instruction, the system extracts the necessary cargo information therefrom, for example, cargo quantity information, cargo weight information, destination information, cargo ID, destination, transportation requirements and other key data.

[0045] 202. Identify cargo quantity information, cargo weight information and destination information in cargo information;

[0046] In this embodiment, the information about the quantity of goods is extracted from the goods information. The delivery instruction will contain information about the quantity of goods, which is usually indicated in a field. For example, the order may indicate "5 boxes", "10 pieces", or a more complex format such as "2 pallets, 10 pieces per pallet", etc. The system parses these fields to extract the specific quantity. The quantity of goods may be accompanied by units (such as "pieces", "boxes", etc.). The system needs to identify and correctly understand these units. If it is a case across multiple units (for example, a box contains 10 pieces of goods), the units need to be converted and summarized to ensure data consistency. The delivery instruction will contain Contains weight information for each type of cargo. For example, there may be labels such as "each piece weighs 10kg" or "total weight 100kg". The system needs to extract the specific weight value from the instruction. Usually, the weight information is in "kilograms (kg)" or "tons (t)". ​​The system needs to correctly identify these units and convert them according to actual conditions. For example, if the delivery instruction contains "total weight 1000g", the system should convert it to "1kg". The destination information usually includes the consignee's name, company name, detailed address, telephone number, postal code, etc. The system needs to extract this information from the delivery instruction and ensure the integrity of each field.

[0047] 203. Create a delivery task based on the cargo quantity information, cargo weight information and destination information;

[0048] In this embodiment, the task type is determined based on the quantity and weight of the goods. For example, if the quantity of the goods is small and the weight is light, a standard mode of transportation may be selected; if the quantity of the goods is large and the weight is heavy, the system may generate a special transportation task, such as arranging a special large truck or pallet for transportation. According to the total weight and volume information of the goods, the system will select a suitable means of transportation. If the goods are heavy or large in volume, a large truck or container transportation may be required, while lighter and smaller goods may be delivered by a small truck or express delivery. The system will generate specific delivery tasks based on the cargo information, destination information, means of transportation, route arrangements, etc.

[0049] 204. Assign a unique task number to the delivery task;

[0050] In this embodiment, when a new delivery task is created, the system will first obtain the current timestamp and related identifiers (such as warehouse ID, delivery route ID, customer number, etc.), and then automatically generate a unique number. The task number can ensure that each delivery task has a unique identifier to avoid duplicate task information or confusion. The generated task number will be verified to ensure that the number is unique in the system. If the current number conflicts with an existing task number (for example, the timestamp and serial number are exactly the same), the system will automatically adjust the serial number to ensure that the number is not repeated.

[0051] 205. Calculate the delivery route of the delivery task using a path planning algorithm;

[0052] In this embodiment, the A* algorithm is used to calculate the delivery route of the delivery task. The A* algorithm is a path planning algorithm based on heuristic search. It not only considers the cost of the current path (such as distance and time), but also estimates the cost from the current point to the end point through the heuristic function, which can find the shortest path more efficiently.

[0053] 206. Identify the delivery points on the delivery routes and evaluate the transportation capacity and dispatchable vehicle capacity of the delivery points;

[0054] In this embodiment, the delivery points of the delivery route are identified. The delivery points refer to distribution centers, warehouses, distribution centers, or final customer delivery points distributed in different locations. The transportation capacity of the delivery points is evaluated. Some delivery points may face seasonal demand fluctuations. For example, during certain holidays, some points may face a surge in order volume. By analyzing historical order data, the system can predict demand in the future, thereby helping to reasonably arrange transportation resources and dispatch vehicles, and evaluate the capacity of dispatchable vehicles. Different delivery tasks may require different types of transportation tools. For example, bulk commodities may require heavy trucks, while small items can be delivered by light delivery vehicles or electric vehicles. When evaluating the capacity of vehicles for delivery, the adaptability of the vehicles must be taken into account to ensure that the selected vehicles can meet the specific requirements of the task. The vehicles at each delivery point have different load limits. When evaluating the capacity of vehicles, it is necessary to ensure that the transported goods do not exceed the maximum load of the vehicle. In addition, the loading efficiency of the vehicle must also be considered to ensure that the vehicle for each delivery can maximize its transportation capacity and avoid waste of resources. The availability of vehicles refers to the number of vehicles that can be dispatched within a specific time period, which is closely related to factors such as the vehicle's maintenance status, operating arrangements, and staffing. When evaluating the dispatchable vehicle capacity of a point, the vehicle's dispatch efficiency and whether there are enough vehicles available when needed must be taken into account.

[0055] 207. Designate transport vehicles based on transport capacity and dispatchable vehicle capacity;

[0056] In this embodiment, based on a comprehensive evaluation of factors such as transportation demand, vehicle resources, route restrictions, etc., the most suitable transportation vehicle is designated based on the evaluation results based on the transportation capacity and dispatchable vehicle capacity.

[0057] 208. Bind the task number and the transport vehicle, and send the delivery route to the transport vehicle;

[0058] In this embodiment, by binding the task number with the information of a specific transport vehicle, the problem of vehicle mismatch that may occur during the transportation process is avoided. The task number, as the unique identifier of each transport task, can be tracked throughout the entire transportation process to ensure that the progress and status of each task can be fed back in a timely manner. When the path planning is completed, the system will generate a task information package containing a detailed route, and send this information package to the transport vehicle bound to the task through wireless communication or an intelligent scheduling platform (such as a transport management system, an on-board navigation system, etc.). Through on-board equipment, a GPS system, or a mobile application, the transport vehicle can receive the route information of the delivery in real time. After the vehicle receives the route planning, the on-board navigation system or the mobile device used by the driver will display the route map in real time, and provide turn instructions, traffic condition reminders, etc.

[0059] In the embodiment of the present invention, cargo information is automatically parsed and dispatch tasks are created based on the quantity, weight and destination of the cargo, ensuring the accuracy and completeness of task assignment. Through path planning and evaluation of dispatch points and vehicle capabilities, transportation resources are rationally deployed to reduce ineffective transportation and waste of resources. By calculating the optimal route and binding the task with a suitable transport vehicle, it is ensured that the transport task is completed on time and efficiently. The binding of the task number with the vehicle information makes the task execution process more transparent and easy to track and manage.

[0060] See also Figure 3 The third embodiment of the method for autonomous delivery of parcels by a network vehicle in the embodiment of the present invention includes:

[0061] 301. Monitor the location information and speed information of the transport vehicle in real time according to the task number;

[0062] In this embodiment, the vehicle's location information is usually collected in real time through GPS (Global Positioning System) and sent to the central dispatching platform through the vehicle-mounted communication system (such as wireless network or satellite communication). The location information includes the current longitude and latitude of the vehicle. The speed information is also usually provided by the vehicle-mounted GPS system or the vehicle's electronic control unit (ECU). The speed information helps the dispatching platform to determine the vehicle's driving status and whether there are problems such as speeding or underspeed. The transport vehicle uses the vehicle-mounted GPS and sensor system to regularly collect the vehicle's real-time location information and speed information.

[0063] 302. Plotting actual driving trajectory data according to the location information, and calculating the deviation rate between the actual driving trajectory data and the delivery route;

[0064] In this embodiment, the current position of the vehicle is acquired in real time, and then these position points are connected into a path, that is, the actual driving trajectory of the vehicle, which is then compared with the scheduled route for delivery, and the offset rate between the two is calculated.

[0065] 303. Determine whether the deviation rate is greater than a preset deviation threshold;

[0066] In this embodiment, the deviation rate refers to the difference between the actual driving trajectory and the planned route, which can be represented by the geometric distance or time difference between the two routes (actual trajectory and planned route). The Euclidean distance (i.e., the straight-line distance between two points) is used to calculate the distance from each actual driving point to the nearest planned route point. If the time factor is considered, the time deviation between the actual driving trajectory and the planned route can also be calculated. For example, if the planned route is based on time, the position error at the same time node is calculated. The deviation threshold is a pre-set standard for determining whether the deviation between the actual trajectory and the planned route is within an acceptable range. After calculating the deviation rate between the actual driving trajectory and the planned route, the deviation rate is compared with the preset deviation threshold. If the deviation rate is greater than the deviation threshold, it means that the vehicle's driving trajectory has deviated from the planned route, which may cause delays, waste of resources or other operational problems. If the deviation rate is less than or equal to the deviation threshold, it means that the vehicle is driving within a reasonable range and there is no excessive deviation. The system can continue to monitor or confirm the normal execution of the task.

[0067] 304. If not, analyze the position information and the vehicle speed information using a preset vehicle driving model to obtain an analysis result;

[0068] In this embodiment, if the deviation rate is less than or equal to the deviation threshold, the preset vehicle driving model is used to analyze the position information and speed information to obtain an analysis result. The vehicle driving model can output the expected driving trajectory within a certain period of time in the future, as well as the deviation from the planned route. If the vehicle speed is too fast, the model may warn the driver to slow down.

[0069] 305. Determine the vehicle driving state of the transport vehicle according to the analysis result;

[0070] In this embodiment, if the vehicle's current position and speed match the predetermined path and driving rules, and there is no obvious deviation or dangerous behavior, the system will determine that the vehicle is in a normal driving state. If the analysis results show that the vehicle has deviated from the predetermined route, but the deviation is small, and the speed and other driving behaviors still meet the safety standards, the system can determine that the vehicle is in a slight deviation state. If the vehicle's current position is significantly different from the predetermined path, or information such as speed and acceleration shows that it does not meet safety standards, the system will determine that the vehicle is at greater risk, which may lead to further deviation or even an accident.

[0071] 306. When the vehicle is in an abnormal stop state, a low speed warning message is generated;

[0072] In this embodiment, when the vehicle is in a stopped state for a long time (such as the vehicle speed is lower than the set normal driving speed threshold), and this state continues for more than a set time threshold (such as 5 minutes), the system determines it as an abnormal stop. Once the vehicle is determined to be in an abnormal stop state, the system will generate a low-speed warning information based on the duration and location of the stop.

[0073] 307. Send low-speed warning information to the transport vehicle and receive real-time environmental information of the transport vehicle, the real-time environmental information including driving record images, weather conditions and traffic conditions;

[0074] In this embodiment, once the vehicle is determined to be in an abnormal stop state and generates a low-speed warning message, the system will transmit the warning message to the transport vehicle through the on-board communication equipment. The low-speed warning message is transmitted to the vehicle's on-board system through the wireless network, and is usually prompted through the on-board display screen, voice prompts, dashboard warnings, etc., to receive real-time environmental information of the transport vehicle. The vehicle's front-view camera, rear-view camera and other devices will take real-time images and upload them to the system. These images can help the system determine the specific environment when the vehicle is stagnant, such as whether there are other vehicles blocking the way, weather influences, traffic accidents, etc. The vehicle obtains the weather conditions at the current location in real time through the integrated meteorological data interface. For example, the system can obtain information such as "the current weather is foggy and visibility is low" or "it is raining and the road is slippery". The vehicle obtains information such as traffic flow, traffic accidents, and construction on surrounding roads by connecting to the traffic management system or the real-time traffic information platform.

[0075] 308. Enter real-time environmental information and low-speed warning information into management reports;

[0076] In this embodiment, the real-time environmental information and low-speed warning information are integrated and entered into the management report through the system's built-in automated report generation tool, providing visual analysis data for operation management personnel, facilitating monitoring of risk conditions in the transportation process, optimizing resource allocation, making decisions, and providing a basis for subsequent improvements. Once the management report is generated, the system will automatically send the report to relevant managers, dispatchers, drivers and other relevant personnel. According to the needs of different users, the report can be distributed through e-mail, management platform, mobile application, etc. All report data will be stored in the data warehouse for subsequent query, statistics and in-depth analysis.

[0077] 309. Create a code scanning monitor and use the code scanning monitor to monitor the unloading scanning information of the delivery barcode;

[0078] In this embodiment, the barcode scanning listener is a program module used to capture and respond to the input signals of the barcode scanning device. The barcode scanning listener is paired with the barcode scanning device. When the scanning device (such as a barcode scanning gun, smart terminal, etc.) reads the barcode information, the listener will trigger the corresponding event processing logic to monitor and process the unloading scanning information of the delivery barcode in real time.

[0079] 310. When the code scanning monitor monitors the unloading scanning information, the current unloading scanning information is obtained;

[0080] In this embodiment, the barcode scanning listener is always in a listening state, waiting for the input signal from the barcode scanning device. When the scanning device scans the barcode of the delivery item, the listener will capture the scanning event, and the barcode scanning device will transmit the scanned unloading scanning information to the barcode scanning listener. The unloading scanning information includes barcode information, scanning time, scanning device information, scanning location and operator information.

[0081] 311. Record the location of the delivery and distribution site of the goods based on the unloading scanning information;

[0082] In this embodiment, the scanning position in the unloading scanning information is identified, and the location of the delivery and distribution site of the goods is recorded according to the scanning position.

[0083] In the embodiment of the present invention, by real-time monitoring of the vehicle's position information and speed information and comparing them with the preset route, deviations from the driving trajectory can be discovered in a timely manner to ensure that the vehicle travels as planned and avoid problems such as deviations from the route and delays. When an abnormal deviation rate is found, the system will further analyze and evaluate the vehicle status based on a preset model, thereby accurately judging abnormal pauses and other situations, quickly generating a low-speed warning, ensuring timely intervention, and reducing the impact of emergencies on transportation efficiency. By real-time acquisition of environmental information of transport vehicles (such as driving record images, weather, traffic, etc.), comprehensive decision-making support can be provided to management, helping to evaluate potential risks and obstacles in the transportation process and make better adjustments. By real-time monitoring of unloading scanning information through a scanning code monitor, the handover and distribution of goods can be accurately recorded, the accuracy of cargo management can be improved, information in each link can be smoothly connected, and detailed tracking records can be provided for subsequent logistics.

[0084] See also Figure 4 The fourth embodiment of the method for autonomous delivery of parcels by a network vehicle in the embodiment of the present invention includes:

[0085] 401. Obtain the weighing weight information of the goods;

[0086] In this embodiment, during the process of goods being put into storage or unloaded, when the goods arrive at the designated weighing area, the operator needs to weigh the goods. The weighing uses an electronic scale, a floor scale or an automated weighing device to obtain the accurate weight of the goods. The weighing device will automatically record the weight of the goods. Through automated equipment, after the goods are weighed, the electronic scale will automatically display and record the weight data.

[0087] 402. Determine whether the weighed weight information is consistent with the original weight information of the goods;

[0088] In this embodiment, the original weight information is obtained from the goods order, delivery note, supplier document, etc., and the weighed weight is automatically compared with the original weight information. For example, the system can set an allowable error range between the two (such as within 2%). If the weight difference between the two exceeds the specified tolerance, it will be marked as "abnormal" and trigger an alarm.

[0089] 403. If yes, identify the delivery destination location of the delivery route;

[0090] In this embodiment, if the weighed weight information is consistent with the original weight information of the goods, the delivery destination location of the delivery route is identified.

[0091] 404. Determine whether the location of the delivery distribution site is consistent with the location of the delivery destination;

[0092] In this embodiment, the delivery distribution site location refers to the current location of the goods, the delivery destination location is the target location of the goods, and it is determined whether the delivery distribution site location is consistent with the delivery destination location.

[0093] 405. If yes, generate delivery completion information, and obtain a timestamp from the timestamp service platform based on the generation time of the delivery completion information;

[0094] In this embodiment, if the delivery distribution site location is consistent with the delivery destination location, indicating that the goods have reached the specified final target location, delivery completion information is generated, and a timestamp is obtained from the timestamp service platform based on the generation time of the delivery completion information.

[0095] 406. Associate the timestamp with the delivery completion information to obtain associated information, and upload the associated information to the blockchain;

[0096] In this embodiment, the delivery completion information and the timestamp are combined to form a "delivery event" containing complete delivery information. The associated information usually includes the content of the delivery completion information, the content of the timestamp, and the unique identifier. Once the timestamp is associated with the delivery completion information, a data structure can be created to package the associated data into a transaction data unit. The data unit is packaged through an encryption algorithm to generate a new block. The data is uploaded to the blockchain network, and the validity of the transaction is confirmed through a consensus mechanism to ensure the uniqueness and consistency of the information on the blockchain. The blockchain node will store the data in a distributed ledger to ensure that all verification nodes can access and store the data.

[0097] In the embodiment of the present invention, by comparing the weighed weight with the original weight, the data deviation in the transportation process is discovered and corrected in time to ensure the accuracy of the cargo weight information. By judging the consistency of the handover site and the destination, the smooth delivery is ensured and the risk of misdelivery is reduced. By associating the handover end information and the timestamp and uploading them to the blockchain, the authenticity and non-tamperability of the data are ensured, providing a reliable audit basis for the transportation process. The introduction of the timestamp enables each step of the operation to have a clear time record, which is helpful for subsequent responsibility tracking and process optimization.

[0098] The above describes the method for autonomous delivery of parcels by a network point vehicle in an embodiment of the present invention. The following describes the device for autonomous delivery of parcels by a network point vehicle in an embodiment of the present invention. Figure 5 In one embodiment of the present invention, an autonomous delivery device for a network point vehicle includes:

[0099] A creation and allocation module 501 is used to create a delivery task according to the cargo information and allocate a unique task number to the delivery task;

[0100] The calculation and sending module 502 is used to calculate the delivery route of the delivery task using a path planning algorithm, and send the task number and the delivery route to the transport vehicle;

[0101] The monitoring and determining module 503 is used to monitor the position information and speed information of the transport vehicle in real time, and determine the vehicle driving state of the transport vehicle according to the position information and speed information;

[0102] A generating and sending module 504 is used to generate low-speed warning information when the vehicle driving state is an abnormal stop state, and send the low-speed warning information to the transport vehicle;

[0103] The acquisition and recording module 505 is used to acquire the unloading scanning information of the delivery barcode, and record the location of the delivery and distribution site of the goods according to the unloading scanning information.

[0104] In this embodiment, a delivery task is created based on the cargo information, a unique task number is assigned to the delivery task, a path planning algorithm is used to calculate the delivery route of the delivery task, the task number and the delivery route are sent to the transport vehicle, the position information and speed information of the transport vehicle are monitored in real time, the vehicle driving status of the transport vehicle is determined based on the position information and speed information, when the vehicle driving status is an abnormal stop state, a low-speed warning information is generated and sent to the transport vehicle, the unloading scanning information of the delivery barcode is obtained, and the delivery distribution site location of the goods is recorded based on the unloading scanning information. The vehicle position can be monitored in real time, the delivery task is automatically completed, the degree of automation is improved, the accuracy and timeliness of the delivery are improved, and user satisfaction is improved.

[0105] See also Figure 6 Another embodiment of the network point vehicle autonomous delivery device in the embodiment of the present invention includes:

[0106] A creation and allocation module 501 is used to create a delivery task according to the cargo information and allocate a unique task number to the delivery task;

[0107] The calculation and sending module 502 is used to calculate the delivery route of the delivery task using a path planning algorithm, and send the task number and the delivery route to the transport vehicle;

[0108] The monitoring and determining module 503 is used to monitor the position information and speed information of the transport vehicle in real time, and determine the vehicle driving state of the transport vehicle according to the position information and speed information;

[0109] A generating and sending module 504 is used to generate low-speed warning information when the vehicle driving state is an abnormal stop state, and send the low-speed warning information to the transport vehicle;

[0110] The acquisition record module 505 is used to acquire the unloading scanning information of the delivery barcode, and record the location of the delivery distribution site of the goods according to the unloading scanning information;

[0111] In this embodiment, the creation and allocation module 501 includes: a receiving and parsing unit 5011, which is used to receive a cargo delivery instruction, parse the cargo delivery instruction, and obtain cargo information; an identification unit 5012, which is used to identify cargo quantity information, cargo weight information and destination information in the cargo information; a creation unit 5013, which is used to create a delivery task based on the cargo quantity information, cargo weight information and destination information; and an allocation unit 5014, which is used to assign a unique task number to the delivery task.

[0112] In this embodiment, the calculation and sending module 502 includes: a calculation unit 5021, which is used to use a path planning algorithm to calculate the delivery route of the delivery task; an identification and evaluation unit 5022, which is used to identify the delivery points of the delivery route, and evaluate the transportation capacity and dispatchable vehicle capacity of the delivery points; a designation unit 5023, which is used to designate a transport vehicle based on the transportation capacity and dispatchable vehicle capacity; a binding and sending unit 5024, which is used to bind the task number and the transport vehicle information, and send the delivery route to the transport vehicle.

[0113] In this embodiment, the monitoring and determination module 503 includes: a monitoring unit 5031, which is used to monitor the position information and speed information corresponding to the transport vehicle in real time according to the task number; a drawing and calculation unit 5032, which is used to draw the actual driving trajectory data according to the position information, and calculate the deviation rate between the actual driving trajectory data and the delivery route; a judgment unit 5033, which is used to judge whether the deviation rate is greater than a preset deviation threshold; an analysis unit 5034, which is used to analyze the position information and speed information using a preset vehicle driving model to obtain an analysis result if not; a determination unit 5035, which is used to determine the vehicle driving status of the transport vehicle according to the analysis result.

[0114] In this embodiment, the generation and sending module 504 includes: a generation unit 5041, which is used to generate low-speed warning information when the vehicle's driving state is an abnormal stop state; a sending and receiving unit 5042, which is used to send the low-speed warning information to the transport vehicle and receive the real-time environmental information of the transport vehicle, the real-time environmental information including driving record images, weather conditions and traffic conditions; an input unit 5043, which is used to input the real-time environmental information and low-speed warning information into the management report.

[0115] In this embodiment, the acquisition record module 505 includes: a monitoring unit 5051 for creating a code scanning monitor, and using the code scanning monitor to monitor the unloading scanning information of the delivery barcode; an acquisition unit 5052 for acquiring the current unloading scanning information when the code scanning monitor monitors the unloading scanning information; a recording unit 5053 for recording the delivery distribution site location of the goods according to the unloading scanning information.

[0116] In this embodiment, it also includes: an acquisition module 506, which is used to obtain the weighed weight information of the goods; a first judgment module 507, which is used to judge whether the weighed weight information is consistent with the original weight information of the goods; an identification module 508, which is used to identify the delivery destination position of the delivery route if so; a second judgment module 509, which is used to judge whether the delivery distribution site position is consistent with the delivery destination position; a generation acquisition module 510, which is used to generate delivery end information if so, and obtain a timestamp from the timestamp service platform based on the generation time of the delivery end information; an association upload module 511, which is used to associate the timestamp with the delivery end information, obtain the associated information, and upload the associated information to the blockchain.

[0117] above Figure 5 and Figure 6 The autonomous delivery device for network point vehicles in the embodiment of the present invention is described in detail from the perspective of modular functional entities. The autonomous delivery device for network point vehicles in the embodiment of the present invention is described in detail from the perspective of hardware processing.

[0118] Figure 7 6 is a schematic diagram of the structure of a network point vehicle autonomous delivery device provided by an embodiment of the present invention. The network point vehicle autonomous delivery device 600 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 610 (for example, one or more processors) and a memory 620, and one or more storage media 630 (for example, one or more mass storage devices) storing application programs 633 or data 632. Among them, the memory 620 and the storage medium 630 can be temporary storage or permanent storage. The program stored in the storage medium 630 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the network point vehicle autonomous delivery device 600. Furthermore, the processor 610 can be configured to communicate with the storage medium 630, and execute a series of instruction operations in the storage medium 630 on the network point vehicle autonomous delivery device 600 to implement the steps of the network point vehicle autonomous delivery method provided by the above-mentioned method embodiments.

[0119] The autonomous delivery device 600 may also include one or more power supplies 640, one or more wired or wireless network interfaces 650, one or more input and output interfaces 660, and / or one or more operating systems 631, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, etc. It will be appreciated by those skilled in the art that Figure 7The structure of the autonomous delivery and dispatch equipment for network point vehicles shown does not constitute a limitation on the autonomous delivery and dispatch equipment based on network point vehicles, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0120] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the method for autonomous delivery of parcels by vehicles at a network point.

[0121] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device, or unit can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.

[0122] 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 is essentially 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. The computer software product is stored in a storage medium, including a number of instructions to enable 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, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0123] Finally, it should be noted that the above description is only a preferred example of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for autonomous delivery of parcels by network point vehicles, characterized in that: include: Create a delivery task according to the cargo information, and assign a unique task number to the delivery task; Calculate the delivery route of the delivery task using a path planning algorithm, and send the task number and the delivery route to the transport vehicle; Monitoring the position information and speed information of the transport vehicle in real time, and determining the vehicle driving state of the transport vehicle according to the position information and the speed information; When the vehicle driving state is an abnormal stop state, generating low speed warning information, and sending the low speed warning information to the transport vehicle; Obtain the unloading scanning information of the delivery barcode, and record the delivery distribution site location of the goods according to the unloading scanning information.

2. The method for autonomous delivery of parcels by network vehicles according to claim 1, characterized in that: The step of creating a delivery task according to the cargo information and assigning a unique task number to the delivery task includes: Receiving a cargo delivery instruction, parsing the cargo delivery instruction, and obtaining cargo information; Identifying cargo quantity information, cargo weight information and destination information in the cargo information; Creating a delivery task according to the cargo quantity information, the cargo weight information and the destination information; A unique task number is assigned to the delivery task.

3. The method for autonomous delivery of parcels by network vehicles according to claim 1, characterized in that: The method of using a path planning algorithm to calculate the delivery route of the delivery task and sending the task number and the delivery route to the transport vehicle includes: Calculate the delivery route of the delivery task using a path planning algorithm; Identify the delivery points of the delivery route, and evaluate the transportation capacity and dispatchable vehicle capacity of the delivery points; designating a transport vehicle according to the transport capacity and the dispatchable vehicle capacity; The task number and the transport vehicle are bound together, and the delivery route is sent to the transport vehicle.

4. The method for autonomous delivery of parcels by network point vehicles according to claim 1, characterized in that: The real-time monitoring of the position information and the speed information of the transport vehicle, and determining the vehicle driving state of the transport vehicle according to the position information and the speed information, includes: Monitor the location information and speed information of the transport vehicle in real time according to the task number; Plotting actual driving trajectory data according to the location information, and calculating a deviation rate between the actual driving trajectory data and the delivery route; Determining whether the deviation rate is greater than a preset deviation threshold; If not, the position information and the vehicle speed information are analyzed using a preset vehicle driving model to obtain an analysis result; The vehicle driving state of the transport vehicle is determined according to the analysis result.

5. The method for autonomous delivery of parcels by network vehicles according to claim 1, characterized in that: When the vehicle driving state is an abnormal stop state, generating low speed warning information and sending the low speed warning information to the transport vehicle comprises: When the vehicle is in an abnormal stopped state, a low speed warning message is generated; Sending the low-speed warning information to the transport vehicle and receiving real-time environmental information of the transport vehicle, the real-time environmental information including driving record images, weather conditions and traffic conditions; The real-time environmental information and the low-speed warning information are entered into a management report.

6. The method for autonomous delivery of parcels by network point vehicles according to claim 1, characterized in that: The step of obtaining the unloading scanning information of the delivery barcode and recording the location of the delivery distribution site of the goods according to the unloading scanning information includes: Create a barcode scanning listener, and use the barcode scanning listener to monitor the unloading scanning information of the delivery barcode; When the code scanning monitor monitors the unloading scanning information, the current unloading scanning information is obtained; The location of the delivery and distribution site of the goods is recorded according to the unloading scanning information.

7. The method for autonomous delivery of parcels by network point vehicles according to claim 1, characterized in that: After obtaining the unloading scanning information of the delivery barcode and recording the location of the delivery distribution site of the goods according to the unloading scanning information, the method further includes: Obtain the weighing weight information of the goods; Determining whether the weighed weight information is consistent with the original weight information of the goods; If yes, identifying the delivery destination location of the delivery route; Determine whether the location of the delivery distribution site is consistent with the location of the delivery destination; If yes, then generate delivery completion information, and obtain a timestamp from the timestamp service platform based on the generation time of the delivery completion information; The timestamp is associated with the delivery completion information to obtain associated information, and the associated information is uploaded to the blockchain.

8. A device for autonomous delivery of parcels by vehicles at network points, characterized in that: include: A creation and allocation module is used to create a delivery task according to the cargo information and allocate a unique task number to the delivery task; A calculation and sending module, used for calculating the delivery route of the delivery task by using a path planning algorithm, and sending the task number and the delivery route to a transport vehicle; A monitoring and determining module, used for monitoring the position information and speed information of the transport vehicle in real time, and determining the vehicle driving state of the transport vehicle according to the position information and the speed information; A generating and sending module, used for generating low-speed warning information when the driving state of the vehicle is an abnormal stop state, and sending the low-speed warning information to the transport vehicle; The acquisition record module is used to obtain the unloading scanning information of the delivery barcode, and record the delivery distribution site location of the goods according to the unloading scanning information.

9. A device for autonomous delivery of parcels by vehicles at network points, characterized in that: The autonomous delivery device for network point vehicles comprises: a memory and at least one processor, wherein instructions are stored in the memory; At least one of the processors calls the instructions in the memory to enable the network point vehicle autonomous delivery device to execute each step of the network point vehicle autonomous delivery method as described in any one of claims 1-7.

10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the various steps of the method for autonomous delivery of parcels by a network vehicle as described in any one of claims 1-7 are implemented.

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