Unmanned logistics vehicle intelligent control method and system

Abstract

The invention discloses an unmanned logistics vehicle intelligent control method and system, and the method comprises the steps: building an emergency manual end connected with a control cloud platform through the network connection of the control cloud platform and an unmanned logistics vehicle, and carrying out the sampling of a surrounding scene of the unmanned logistics vehicle through a vehicle-mounted radar on the unmanned logistics vehicle; a speed sensor is arranged to detect the speed of the unmanned logistics vehicle; when the vehicle-mounted radar detects that the surrounding scene is in a crowded state, the vehicle speed is reduced, and slow passing is carried out; when the unmanned logistics vehicle is in the stop state, the stop time of the unmanned logistics vehicle is timed; if yes, the unmanned logistics vehicle is connected with the emergency manual end through the control cloud platform, and the unmanned logistics vehicle is controlled to perform manual driving through the emergency manual end, so that when crowding occurs, the emergency manual end is accessed to perform control, and the situation that the unmanned logistics vehicle stops due to crowding during automatic control is avoided; therefore, the traffic congestion state of the intersection is aggravated.

Description

Technical Field

[0001] The present invention relates to the technical field related to intelligence of unmanned logistics vehicles, and specifically to an intelligent control method and system for unmanned logistics vehicles. Background Art

[0002] With the development of the new generation of Internet technology and the increasing application of robots, the coordination and cooperation between unmanned logistics vehicles and the Internet of Vehicles technology are combined and applied to complex work, that is, the network connection between unmanned logistics vehicles and X (unmanned logistics vehicles and unmanned logistics vehicles, people, roads, and service platforms) is realized, and the coordination and cooperation capabilities of multiple unmanned logistics workshops are improved, which can greatly improve work efficiency and save costs. With the rise of online shopping, the logistics industry has gradually become a major driving force of my country's economy. Therefore, the intelligent control of unmanned control vehicles to achieve the effect of improving logistics efficiency has become the focus of major logistics companies; and with the use of unmanned logistics vehicles, it has greatly facilitated people. Although the existing unmanned vehicles can be unmanned, when the road is congested, it is difficult for unmanned vehicles to make adaptive changes and always stop, which will further cause congestion. Summary of the invention

[0003] In order to solve the defects of the prior art, the present invention provides an intelligent control method and system for an unmanned logistics vehicle.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0005] The intelligent control method of the unmanned logistics vehicle of the present invention comprises the following steps:

[0006] Step 1: Build a control cloud platform, where the control cloud platform is connected to the unmanned logistics vehicle network, and build an emergency manual terminal connected to the control cloud platform;

[0007] Step 2: First, the on-board radar of the unmanned logistics vehicle is used to sample the surrounding scene of the unmanned logistics vehicle; and the speed of the unmanned logistics vehicle is detected by setting a speed sensor;

[0008] Step 3: When the vehicle-mounted radar detects that the surrounding scene is in a crowded state, the vehicle speed is reduced to pass slowly; when the unmanned logistics vehicle is in a stopped state, the stopping time of the unmanned logistics vehicle is timed;

[0009] Step 4: When the unmanned logistics vehicle stays for longer than the set value, the unmanned logistics vehicle is connected to the emergency manual terminal through the control cloud platform, and the unmanned logistics vehicle is controlled by the emergency manual terminal for manual driving.

[0010] As a preferred technical solution of the present invention, the control cloud platform is connected to the traffic system to obtain the real-time traffic signals of the red and green traffic lights at the intersection.

[0011] As a preferred technical solution of the present invention, the emergency manual terminal is provided with a display screen and a sound player. The display screen is used to display the surrounding scene of the unmanned logistics vehicle to ensure that the operator knows the environment in which the unmanned logistics vehicle is located, and the sound in the scene is played through the sound player.

[0012] As a preferred technical solution of the present invention, the emergency manual terminal is provided with an alarm signal receiving terminal and a priority allocation terminal, wherein the alarm signal receiving terminal is used to receive a parking alarm signal issued by an unmanned logistics vehicle and mark each unmanned logistics vehicle that issues a parking alarm signal;

[0013] The priority allocation end analyzes the surrounding scenes of each unmanned logistics vehicle based on the parking alarm signal of the unmanned logistics vehicle, obtains the congestion situation of the traffic environment without each unmanned logistics vehicle, and then gives priority to manual operation of the unmanned logistics vehicles with lower congestion levels.

[0014] As a preferred technical solution of the present invention, the priority allocation method of the priority allocation end is:

[0015] The priority score of each unmanned logistics vehicle parking alarm signal data is calculated through the scoring matrix; and the weight coefficient is introduced;

[0016] Assigning a priority to the unmanned logistics vehicle parking alarm signal according to the adjusted priority score, and executing the task according to the assigned priority of the unmanned logistics vehicle parking alarm signal;

[0017] The priority of the parking alarm signal of the unmanned logistics vehicle is divided into 8 levels from A to H, among which A is the highest level and H is the lowest level;

[0018] Scl=(k lv ×Sc lv +k com ×Sc com )×k re

[0019] Where Scl represents the priority score of the parking alarm signal of the unmanned logistics vehicle, k lv Sc represents the weight coefficient of the parking alarm signal level of the unmanned logistics vehicle, lv represents the parking alarm signal level score of the unmanned logistics vehicle, k com Indicates the priority instruction weight coefficient, Sc com represents the priority instruction score; k re Indicates the historical alarm tag value;

[0020] When the priority score weight coefficient is introduced, the priority score expression in the scoring matrix is: In the above formula, Sc2 represents the priority score of each unmanned logistics vehicle parking alarm signal in the scoring matrix; k i Represents the weight coefficient of static influencing factors; Sc stat Represents the static influencing factor score; Sc dyn represents the dynamic influencing factor score; k j Indicates the weight coefficient of dynamic influencing factors.

[0021] As a preferred technical solution of the present invention, the distribution end is used to read the logistics information on the unmanned logistics vehicle that sends out a parking alarm signal, obtain the information of each logistics item on the unmanned logistics vehicle, and then analyze the value of the items on each unmanned logistics vehicle based on the logistics item information, and give priority to controlling the unmanned logistics vehicles with the most valuable items.

[0022] As a preferred technical solution of the present invention, the unmanned logistics vehicle also has a voice player, and the voice player is used to play the real-time voice of the personnel operating at the emergency manual end.

[0023] An unmanned logistics vehicle intelligent control system, used to implement the above-mentioned unmanned logistics vehicle intelligent control method, characterized in that it includes a control cloud platform, an unmanned logistics vehicle, and an emergency manual operation terminal, wherein the control cloud platform is provided with a real-time traffic information access terminal, a logistics item information collection terminal, a manual operation allocation terminal, and a path setting terminal;

[0024] The unmanned logistics vehicle is connected to the emergency manual operation terminal via the control cloud platform. The path setting terminal is used to remember and set the driving path of the unmanned logistics vehicle, and the logistics item information collection terminal is used to collect information on logistics items in the unmanned logistics vehicle. The real-time traffic information access terminal is used to access the traffic system to read the real-time traffic information on the path according to the planned driving path of the unmanned logistics vehicle. The manual operation distribution terminal, and the manual operation distribution terminal, when the manual operation distribution terminal is based on the unmanned logistics vehicle parking alarm signal, analyzes the surrounding scenes of each unmanned logistics vehicle to obtain the congestion situation of the traffic environment without each unmanned logistics vehicle, and then gives priority to manual operation of unmanned logistics vehicles with lower congestion.

[0025] The beneficial effects of the present invention are:

[0026] 1. The intelligent control method of the unmanned logistics vehicle is implemented by building a control cloud platform, wherein the control cloud platform is connected to the network of the unmanned logistics vehicle, building an emergency manual terminal connected to the control cloud platform, sampling the surrounding scene of the unmanned logistics vehicle through the on-board radar on the unmanned logistics vehicle; and detecting the speed of the unmanned logistics vehicle by setting a speed sensor; when the on-board radar detects that the surrounding scene is in a congested state, the speed is reduced to pass slowly; when the unmanned logistics vehicle is in a stopped state, the stop time of the unmanned logistics vehicle is counted; when the unmanned logistics vehicle stays for more than a set time, the unmanned logistics vehicle is connected to the emergency manual terminal through the control cloud platform, and the unmanned logistics vehicle is controlled to be manually driven through the emergency manual terminal, so that when congestion occurs, control is performed by accessing the emergency manual terminal to avoid the unmanned logistics vehicle from stopping due to congestion when it is controlled by itself, which aggravates the traffic congestion at the intersection. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0028] In the attached picture:

[0029] Figure 1 It is a structural schematic diagram of the intelligent control method of the unmanned logistics vehicle of the present invention;

[0030] Figure 2 It is a system block diagram of the intelligent control system of the unmanned logistics vehicle of the present invention.

[0031] In the figure: 1. Control cloud platform; 2. Unmanned logistics vehicle; 3. Emergency manual operation terminal; 4. Real-time traffic information access terminal; 5. Logistics item information collection terminal; 6. Manual operation allocation terminal; 7. Path setting terminal. DETAILED DESCRIPTION

[0032] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0033] Example: Figure 1 As shown, the intelligent control method of the unmanned logistics vehicle of the present invention comprises the following steps:

[0034] Step 1: Build a control cloud platform, where the control cloud platform is connected to the unmanned logistics vehicle network, and build an emergency manual terminal connected to the control cloud platform;

[0035] Step 2: First, the on-board radar of the unmanned logistics vehicle is used to sample the surrounding scene of the unmanned logistics vehicle; and the speed of the unmanned logistics vehicle is detected by setting a speed sensor;

[0036] Step 3: When the vehicle-mounted radar detects that the surrounding scene is in a crowded state, the vehicle speed is reduced to pass slowly; when the unmanned logistics vehicle is in a stopped state, the stopping time of the unmanned logistics vehicle is timed;

[0037] Step 4: When the unmanned logistics vehicle stays for longer than the set value, the unmanned logistics vehicle is connected to the emergency manual terminal through the control cloud platform, and the unmanned logistics vehicle is controlled by the emergency manual terminal for manual driving. In this way, when congestion occurs, the unmanned logistics vehicle can be controlled by connecting to the emergency manual terminal to avoid the unmanned logistics vehicle from stopping due to congestion when it is controlled by itself, which aggravates the traffic congestion at the intersection.

[0038] Among them, the control cloud platform is connected to the traffic system to obtain the real-time traffic signals of the red and green traffic lights at the intersection, which makes it easy to timely understand the traffic conditions of the road section where the unmanned logistics vehicle is located.

[0039] The emergency manual terminal is equipped with a display screen and a sound player. The display screen is used to display the surrounding scene of the unmanned logistics vehicle to ensure that the operator knows the environment in which the unmanned logistics vehicle is located, and the sound in the scene is played through the sound player. This makes it easy for humans to communicate with people around the unmanned logistics vehicle and facilitates traffic evacuation.

[0040] The emergency manual terminal is provided with an alarm signal receiving terminal and a priority allocation terminal, wherein the alarm signal receiving terminal is used to receive a parking alarm signal issued by an unmanned logistics vehicle and mark each unmanned logistics vehicle that issues a parking alarm signal;

[0041] The priority allocation end analyzes the surrounding scenes of each unmanned logistics vehicle based on the parking alarm signal of the unmanned logistics vehicle, and obtains the congestion situation of the traffic environment without each unmanned logistics vehicle. It then gives priority to manual operation of the unmanned logistics vehicles with lower congestion levels, which can effectively reduce the pressure on road traffic.

[0042] The priority allocation method of the priority allocation terminal is:

[0043] The priority score of each unmanned logistics vehicle parking alarm signal data is calculated through the scoring matrix; and the weight coefficient is introduced;

[0044] Assigning a priority to the unmanned logistics vehicle parking alarm signal according to the adjusted priority score, and executing the task according to the assigned priority of the unmanned logistics vehicle parking alarm signal;

[0045] The priority of the parking alarm signal of the unmanned logistics vehicle is divided into 8 levels from A to H, among which A is the highest level and H is the lowest level;

[0046] Scl=(k lv ×Sc lv +k com ×Sc com )×k re

[0047] Where Scl represents the priority score of the parking alarm signal of the unmanned logistics vehicle, k lv Sc represents the weight coefficient of the parking alarm signal level of the unmanned logistics vehicle, lv represents the parking alarm signal level score of the unmanned logistics vehicle, k com Indicates the priority instruction weight coefficient, Sc com represents the priority instruction score; k re Indicates the historical alarm tag value;

[0048] When the priority score weight coefficient is introduced, the priority score expression in the scoring matrix is: In the above formula, Sc2 represents the priority score of each unmanned logistics vehicle parking alarm signal in the scoring matrix; k j Represents the weight coefficient of static influencing factors, which is determined by the fixed obstacles to the road section in daily logistics and the average value of historical fixed traffic flow; Sc stat Represents the static influencing factor score and the influence weight of the historical average value of fixed traffic flow; Sc dyn represents the dynamic influencing factor score, which is determined by the dynamic traffic flow; k j Represents the weight coefficient of dynamic influencing factors, including dynamic traffic flow.

[0049] Among them, the distribution end is used to read the logistics information on the unmanned logistics vehicle that sends out a parking alarm signal, obtain the information of each logistics item on the unmanned logistics vehicle, and then analyze the value of the items on each unmanned logistics vehicle based on the logistics item information, and give priority to controlling the unmanned logistics vehicles with the most valuable items.

[0050] Among them, the unmanned logistics vehicle also has a voice player, and the voice player is used to play the real-time voice of the personnel operating at the emergency manual end, which is convenient for humans to communicate with the people around the unmanned logistics vehicle and facilitate traffic evacuation.

[0051] An unmanned logistics vehicle intelligent control system is used to implement the above-mentioned unmanned logistics vehicle intelligent control method, such as Figure 2As shown, it includes a control cloud platform 1, an unmanned logistics vehicle 2, and an emergency manual operation terminal 3. The control cloud platform is provided with a real-time traffic information access terminal 4, a logistics item information collection terminal 5, a manual operation allocation terminal 6, and a path setting terminal 7;

[0052] The unmanned logistics vehicle 2 is connected to the emergency manual operation terminal 3 via the control cloud platform 1, the path setting terminal 7 is used to remember and set the driving path of the unmanned logistics vehicle 2, and the logistics item information collection terminal 5 is used to collect information on logistics items in the unmanned logistics vehicle 2, and the real-time traffic information access terminal 4 is used to access the traffic system to read the real-time traffic information on the path according to the planned driving path of the unmanned logistics vehicle. The manual operation distribution terminal and the manual operation distribution terminal 6, when the manual operation distribution terminal is based on the unmanned logistics vehicle parking alarm signal, analyze the surrounding scenes of each unmanned logistics vehicle to obtain the congestion situation of the traffic environment without each unmanned logistics vehicle, and then give priority to manual operation of unmanned logistics vehicles with lower congestion.

[0053] Finally, it should be noted that the above description is only a preferred embodiment 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. An intelligent control method and system for unmanned logistics vehicles, characterized in that: The following steps are involved: Step 1: Build a control cloud platform, where the control cloud platform is connected to the unmanned logistics vehicle network, and build an emergency manual terminal connected to the control cloud platform; Step 2: First, the on-board radar of the unmanned logistics vehicle is used to sample the surrounding scene of the unmanned logistics vehicle; and the speed of the unmanned logistics vehicle is detected by setting a speed sensor; Step 3: When the vehicle-mounted radar detects that the surrounding scene is in a crowded state, the vehicle speed is reduced to pass slowly; when the unmanned logistics vehicle is in a stopped state, the stopping time of the unmanned logistics vehicle is timed; Step 4: When the unmanned logistics vehicle stays for longer than the set value, the unmanned logistics vehicle is connected to the emergency manual terminal through the control cloud platform, and the unmanned logistics vehicle is controlled by the emergency manual terminal for manual driving.

2. The intelligent control method of unmanned logistics vehicle according to claim 1 is characterized in that: The control cloud platform is connected to the traffic system to obtain the real-time traffic signals of the red and green traffic lights at the intersection.

3. The intelligent control method of unmanned logistics vehicle according to claim 2 is characterized in that: The emergency manual terminal is provided with a display screen and a sound player. The display screen is used to display the surrounding scene of the unmanned logistics vehicle to ensure that the operator knows the environment in which the unmanned logistics vehicle is located, and the sound in the scene is played through the sound player.

4. The intelligent control method of unmanned logistics vehicle according to claim 2 is characterized in that: The emergency manual terminal is provided with an alarm signal receiving terminal and a priority allocation terminal, wherein the alarm signal receiving terminal is used to receive a parking alarm signal issued by an unmanned logistics vehicle and mark each unmanned logistics vehicle that issues a parking alarm signal; The priority allocation end analyzes the surrounding scenes of each unmanned logistics vehicle based on the parking alarm signal of the unmanned logistics vehicle, obtains the congestion situation of the traffic environment without each unmanned logistics vehicle, and then gives priority to manual operation of the unmanned logistics vehicles with lower congestion levels.

5. The intelligent control method of unmanned logistics vehicle according to claim 4 is characterized in that: The priority allocation method of the priority allocation terminal is: The priority score of each unmanned logistics vehicle parking alarm signal data is calculated through the scoring matrix; and the weight coefficient is introduced; Assigning a priority to the unmanned logistics vehicle parking alarm signal according to the adjusted priority score, and executing the task according to the assigned priority of the unmanned logistics vehicle parking alarm signal; The priority of the parking alarm signal of the unmanned logistics vehicle is divided into 8 levels from A to H, among which A is the highest level and H is the lowest level; Sc1=(k lv ×Sc lv +k com ×S com )×k re Sc1 represents the priority score of the parking alarm signal of the unmanned logistics vehicle, k lv Sc represents the weight coefficient of the parking alarm signal level of the unmanned logistics vehicle, lv represents the parking alarm signal level score of the unmanned logistics vehicle, k ccm Represents the priority instruction weight coefficient, Sc com represents the priority instruction score; k re Indicates the historical alarm tag value; When the priority score weight coefficient is introduced, the priority score expression in the scoring matrix is: In the above formula, Sc2 represents the priority score of each unmanned logistics vehicle parking alarm signal in the scoring matrix; k j Represents the weight coefficient of static influencing factors, which is determined by the fixed obstacles to the road section in daily logistics and the average value of historical fixed traffic flow; Sc stat Represents the static influencing factor score and the influence weight of the historical average value of fixed traffic flow; Sc dyn represents the dynamic influencing factor score, which is determined by the dynamic traffic flow; k j Represents the weight coefficient of dynamic influencing factors, including dynamic traffic flow.

6. The intelligent control method of unmanned logistics vehicle according to claim 1 is characterized in that: The distribution end is used to read the logistics information on the unmanned logistics vehicle that sends out a parking alarm signal, obtain the information of each logistics item on the unmanned logistics vehicle, and then analyze the value of the items on each unmanned logistics vehicle based on the logistics item information, and give priority to controlling the unmanned logistics vehicles with the most valuable items.

7. The intelligent control method of unmanned logistics vehicle according to claim 1 is characterized in that: The unmanned logistics vehicle also has a voice player, and the voice player is used to play the real-time voice of the personnel operating at the emergency manual end.

8. An unmanned logistics vehicle intelligent control system, used to implement the unmanned logistics vehicle intelligent control method according to claims 1-7, characterized in that: It comprises a control cloud platform (1), an unmanned logistics vehicle (2), and an emergency manual operation terminal (3), wherein the control cloud platform is provided with a real-time traffic information access terminal (4), a logistics item information collection terminal (5), a manual operation allocation terminal (6), and a path setting terminal (7); The unmanned logistics vehicle (2) is connected to the emergency manual operation terminal (3) via the control cloud platform (1); the path setting terminal (7) is used to memorize and set the driving path of the unmanned logistics vehicle (2); and the logistics item information collection terminal (5) is used to collect information on logistics items in the unmanned logistics vehicle (2); the real-time traffic information access terminal (4) is used to access the traffic system to read the real-time traffic information on the path planned for the unmanned logistics vehicle; and the manual operation distribution terminal (6) analyzes the surrounding scene of each unmanned logistics vehicle according to the parking alarm signal of the unmanned logistics vehicle in the manual operation distribution terminal to obtain the congestion situation of the traffic environment without each unmanned logistics vehicle, and then gives priority to the unmanned logistics vehicles with lower congestion for manual operation.

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