Bus dispatching system based on edge computing

Abstract

The present invention provides a bus dispatching system based on edge computing, including an edge computing system and a cloud server, wherein the edge computing system is set on a bus, and is used to obtain real-time driving data of the bus, and analyze and predict the future driving conditions of the bus based on the real-time driving data of the bus, obtain the analysis and prediction results of the future driving conditions of the bus, and send the analysis and prediction results of the future driving conditions of the bus to the cloud server; the cloud server is used to control the bus according to the analysis and prediction results of the future driving conditions of the bus.

Description

Technical Field

[0001] The present invention relates to the field of edge computing technology, and in particular to a bus dispatching system based on edge computing. Background Art

[0002] In the existing technology, bus scheduling mainly involves collecting bus driving data and sending the bus driving data to a server on the network side. The server on the network side calculates and analyzes the bus driving data and comprehensively schedules all buses.

[0003] During this process, the bus only collects its own driving data, while the network-side server performs the calculations, analysis, and final dispatch processing. This data must be transmitted between the bus and the network-side server, and all calculations, analysis, and dispatch processing are performed by the network-side server. This results in a longer dispatch process and lower efficiency. Summary of the Invention

[0004] An embodiment of the present invention provides a bus dispatching system based on edge computing.

[0005] An embodiment of the present invention provides a bus dispatching system based on edge computing, including an edge computing system and a cloud server, wherein:

[0006] The edge computing system is provided on the bus and is used to obtain real-time driving data of the bus, analyze and predict the future driving status of the bus based on the real-time driving data of the bus, obtain the analysis and prediction results of the future driving status of the bus, and send the analysis and prediction results of the future driving status of the bus to the cloud server;

[0007] The cloud server is used to control the bus based on the analysis and prediction results of the future driving conditions of the bus.

[0008] In one embodiment, the bus dispatching system further includes:

[0009] A bus real-time travel data collection device is provided on the bus, and is used to collect the real-time travel data of the bus;

[0010] The bus real-time driving data acquisition device includes any one or more of the following modules:

[0011] A positioning module, used for collecting the current location of the bus in real time;

[0012] A first image acquisition module is provided at the front of the bus and is used to acquire the road traffic image in front of the bus in real time;

[0013] A second image acquisition module is provided inside the bus compartment and is used to acquire images of passengers in the bus in real time;

[0014] A road condition information acquisition module is used to obtain traffic accident information on the route traveled by the bus from a road condition information server on the network side;

[0015] The bus dispatching system further includes:

[0016] The third image acquisition module is arranged at the next arrival platform of the bus, and is used to acquire images of passengers in the waiting area waiting for the bus at the next arrival platform.

[0017] In one embodiment, the edge computing system analyzes and predicts the future driving condition of the bus based on the real-time driving data of the bus, and obtains the analysis and prediction results of the future driving condition of the bus, including:

[0018] Obtaining current travel data of the next bus of the same number as the bus that is traveling behind the bus, the current travel data including an average travel speed of the first bus on the road section between the next bus and the bus, a picture of passengers on the next bus, and a current distance between the next bus and the bus;

[0019] Obtaining an average travel speed of a second bus on the road section between the bus and the next stop to be arrived at;

[0020] The driving priorities of the next bus and the bus are determined according to the current driving data of the next bus, the average driving speed of the second bus and the passenger image in the bus.

[0021] In one embodiment, determining the travel priority of the next bus and the bus based on the current travel data of the next bus, the average travel speed of the second bus, and the passenger image in the bus includes:

[0022] Determining the first number of passengers on the next bus according to the passenger screen on the next bus;

[0023] determining the number of second passengers in the bus based on the passenger image in the bus;

[0024] determining the number of third passengers in the waiting area according to the passenger screen of the waiting area;

[0025] When the second number of passengers is greater than the first number of passengers, or the sum of the second number of passengers and the third number of passengers is equal to or greater than a preset maximum number of passengers, determining the catching-up time required for the next bus to catch up with the bus based on the current distance between the next bus and the bus, the average speed of the first bus, and the average speed of the second bus;

[0026] When the catching-up time is equal to or less than a preset time threshold, and the bus does not reach the next platform to be arrived at after traveling at the average speed of the second bus for the catching-up time, and the distance between the bus and the next platform to be arrived at is equal to or greater than a preset distance threshold, it is determined that the next bus has a higher travel priority than the bus.

[0027] In one embodiment, the cloud server controls the bus based on the analysis and prediction results of the future driving conditions of the bus, including:

[0028] The cloud server controls the next bus and / or the sound player in the bus to play preset information, and the preset information includes: the driver of the next bus can travel at a preset maximum bus speed and can overtake the bus.

[0029] In one embodiment, determining the travel priority of the next bus and the bus based on the current travel data of the next bus, the average travel speed of the second bus, and the passenger image in the bus includes:

[0030] Determining the first number of passengers on the next bus according to the passenger screen on the next bus;

[0031] determining the number of second passengers in the bus based on the passenger image in the bus;

[0032] determining the number of third passengers in the waiting area according to the passenger screen of the waiting area;

[0033] When the second number of passengers is greater than the first number of passengers, and the sum of the second number of passengers and the third number of passengers is equal to or greater than the preset maximum number of passengers, it is determined that the next bus has a higher travel priority than the bus.

[0034] In one embodiment, the cloud server controls the bus based on the analysis and prediction results of the future driving conditions of the bus, including:

[0035] The cloud server controls the first communication device on the bus to connect with the second communication device on the next bus, and controls both the first communication device and the second communication device to issue a preset prompt, wherein the preset prompt is used to prompt the driver of the bus and the driver of the next bus to communicate with each other about the driving plan of the bus and the next bus.

[0036] The above-mentioned technical solution provided by the embodiment of the present invention assigns the task of analyzing and predicting the future driving conditions of the bus to the edge computing system set up by the bus itself, and hands over the deployment of the bus to the cloud server, thereby greatly reducing the task volume of the cloud server compared with the existing server and reducing the working pressure of the cloud server; and, since the task of analyzing and predicting each bus is dispersed among the edge computing systems set up on each bus, the speed of analyzing and predicting the future driving conditions of each bus is accelerated and the efficiency is improved, which ultimately makes the deployment of the bus more timely and ensures the timeliness of the deployment.

[0037] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0038] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0040] Figure 1 This is a structural diagram of a bus dispatching system based on edge computing in an embodiment of the present invention. DETAILED DESCRIPTION

[0041] The preferred embodiments of the present invention are described below with reference to 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.

[0042] like Figure 1 As shown, an embodiment of the present invention provides a bus dispatching system based on edge computing, including an edge computing system and a cloud server, wherein:

[0043] The edge computing system is provided on the bus and is used to obtain real-time driving data of the bus, analyze and predict the future driving status of the bus based on the real-time driving data of the bus, obtain the analysis and prediction results of the future driving status of the bus, and send the analysis and prediction results of the future driving status of the bus to the cloud server;

[0044] The cloud server is used to control the bus based on the analysis and prediction results of the future driving conditions of the bus.

[0045] The beneficial effects of the above technical solution are as follows: the above system provided by the embodiment of the present invention assigns the task of analyzing and predicting the future driving conditions of the bus to the edge computing system set up by the bus itself, and hands over the deployment of the bus to the cloud server, thereby greatly reducing the task volume of the cloud server compared with the existing server, reducing the working pressure of the cloud server; and, since the tasks of analyzing and predicting each bus are dispersed in the edge computing system set up on each bus, the speed of analyzing and predicting the future driving conditions of each bus is accelerated and the efficiency is improved, which ultimately makes the deployment of the bus more timely and ensures the timeliness of the deployment.

[0046] In one embodiment, the bus dispatching system further includes:

[0047] A bus real-time travel data collection device is provided on the bus, and is used to collect the real-time travel data of the bus;

[0048] The bus real-time driving data acquisition device includes any one or more of the following modules:

[0049] A positioning module, used for collecting the current location of the bus in real time;

[0050] A first image acquisition module is provided at the front of the bus and is used to acquire the road traffic image in front of the bus in real time;

[0051] A second image acquisition module is provided inside the bus compartment and is used to acquire images of passengers in the bus in real time;

[0052] A road condition information acquisition module is used to obtain traffic accident information on the route traveled by the bus from a road condition information server on the network side;

[0053] The bus dispatching system further includes:

[0054] The third image acquisition module is arranged at the next arrival platform of the bus, and is used to acquire images of passengers in the waiting area waiting for the bus at the next arrival platform.

[0055] In one embodiment, the edge computing system analyzes and predicts the future driving condition of the bus based on the real-time driving data of the bus, and obtains the analysis and prediction results of the future driving condition of the bus, including:

[0056] Obtaining current travel data of the next bus of the same number as the bus that is traveling behind the bus, the current travel data including an average travel speed of the first bus on the road section between the next bus and the bus, a picture of passengers on the next bus, and a current distance between the next bus and the bus;

[0057] Obtaining an average travel speed of a second bus on the road section between the bus and the next stop to be arrived at;

[0058] The driving priorities of the next bus and the bus are determined according to the current driving data of the next bus, the average driving speed of the second bus and the passenger image in the bus.

[0059] The beneficial effects of the above technical solution are:

[0060] In one embodiment, determining the travel priority of the next bus and the bus based on the current travel data of the next bus, the average travel speed of the second bus, and the passenger image in the bus includes:

[0061] Determining the first number of passengers on the next bus according to the passenger screen on the next bus;

[0062] determining the number of second passengers in the bus based on the passenger image in the bus;

[0063] determining the number of third passengers in the waiting area according to the passenger screen of the waiting area;

[0064] When the second number of passengers is greater than the first number of passengers, or the sum of the second number of passengers and the third number of passengers is equal to or greater than a preset maximum number of passengers (i.e., the preset maximum number of passengers that the bus can carry), and the sum of the first number of passengers and the third number of passengers is less than the preset maximum number of passengers, the catching-up time required for the next bus to catch up with the bus is determined based on the current distance between the next bus and the bus, the average speed of the first bus, and the average speed of the second bus;

[0065] When the catching-up time is equal to or less than a preset time threshold, and the bus does not reach the next platform to be arrived at after traveling at the average speed of the second bus for the catching-up time, and the distance between the bus and the next platform to be arrived at is equal to or greater than a preset distance threshold, it is determined that the next bus has a higher travel priority than the bus.

[0066] The beneficial effect of the above technical solution is: through the above logical processing, when the bus cannot carry all the passengers waiting to arrive at the next stop, an intelligent decision can be made as to whether the next bus can replace the bus to give priority to carrying the passengers waiting to arrive at the next stop (when it is determined that the driving priority of the next bus is higher than that of the bus, it can be decided that the next bus can replace the bus to give priority to carrying the passengers waiting to arrive at the next stop), so as to achieve the purpose of reasonable deployment of buses, so that the two adjacent buses can flexibly adjust the order when performing the passenger carrying task, and pick up as many passengers as possible and as quickly as possible.

[0067] In one embodiment, the cloud server controls the bus based on the analysis and prediction results of the future driving conditions of the bus, including:

[0068] The cloud server controls the next bus and / or the sound player in the bus to play preset information, and the preset information includes: the driver of the next bus can travel at a preset maximum bus speed and can overtake the bus.

[0069] The beneficial effects of the above technical solution are: the cloud server promptly notifies the driver of the next bus of the latest driving plan, so that the next bus can arrive at the next arrival platform as soon as possible; of course, the preset information can also include the reason why the next bus is allowed to overtake the said bus, for example, the carrying capacity of the said bus is insufficient, and the next bus needs to arrive at the next arrival platform in advance to relieve the passenger pressure of the said bus.

[0070] In one embodiment, determining the travel priority of the next bus and the bus based on the current travel data of the next bus, the average travel speed of the second bus, and the passenger image in the bus includes:

[0071] Determining the first number of passengers on the next bus according to the passenger screen on the next bus;

[0072] determining the number of second passengers in the bus based on the passenger image in the bus;

[0073] determining the number of third passengers in the waiting area according to the passenger screen of the waiting area;

[0074] When the second number of passengers is greater than the first number of passengers, or the sum of the second number of passengers and the third number of passengers is equal to or greater than the preset maximum number of passengers (i.e., the preset maximum number of passengers that the bus can carry), and the sum of the first number of passengers and the third number of passengers is less than the preset maximum number of passengers, it is determined that the next bus has a higher travel priority than the first bus.

[0075] In one embodiment, the cloud server controls the bus based on the analysis and prediction results of the future driving conditions of the bus, including:

[0076] The cloud server controls the first communication device on the bus to connect with the second communication device on the next bus, and controls both the first communication device and the second communication device to issue a preset prompt, wherein the preset prompt is used to prompt the driver of the bus and the driver of the next bus to communicate with each other about the driving plan of the bus and the next bus.

[0077] The beneficial effects of the above technical solution are: through the above logical processing, when the bus cannot carry all the passengers waiting to arrive at the next stop, an intelligent decision can be made whether the next bus can replace the bus to give priority to performing the task of carrying the passengers waiting to arrive at the next stop, thereby achieving the purpose of reasonable allocation of buses; in addition, the cloud server controls the first communication device on the bus to connect with the second communication device on the next bus, and controls the first communication device and the second communication device to issue preset prompts, so that the driver of the bus and the driver of the next bus can communicate with each other on the driving plan of the bus and the next bus, which is convenient for the driver to flexibly negotiate how to allocate the two buses according to the actual road conditions at the time, thereby improving the autonomy of the driver in allocation.

[0078] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A bus dispatching system based on edge computing, characterized in that: Includes edge computing systems and cloud servers, including: The edge computing system is provided on the bus and is used to obtain real-time driving data of the bus, analyze and predict the future driving status of the bus based on the real-time driving data of the bus, obtain the analysis and prediction results of the future driving status of the bus, and send the analysis and prediction results of the future driving status of the bus to the cloud server; The cloud server is used to control the bus according to the analysis and prediction results of the future driving conditions of the bus; The edge computing system analyzes and predicts the future driving condition of the bus based on the real-time driving data of the bus, and obtains the analysis and prediction results of the future driving condition of the bus, including: Obtaining current travel data of the next bus of the same number as the bus that is traveling behind the bus, the current travel data including an average travel speed of the first bus on the road section between the next bus and the bus, a picture of passengers on the next bus, and a current distance between the next bus and the bus; Obtaining an average travel speed of a second bus on the road section between the bus and the next stop to be arrived at; determining the driving priority of the next bus and the bus according to the current driving data of the next bus, the average driving speed of the second bus, and the passenger image in the bus; The step of determining the travel priority between the next bus and the bus based on the current travel data of the next bus, the average travel speed of the second bus, and the passenger image in the bus includes: Determining the first number of passengers on the next bus according to the passenger screen on the next bus; determining the number of second passengers in the bus based on the passenger image in the bus; determining the number of third passengers in the waiting area based on a passenger screen in the waiting area; When the second number of passengers is greater than the first number of passengers, or the sum of the second number of passengers and the third number of passengers is equal to or greater than a preset maximum number of passengers, determining the catching-up time required for the next bus to catch up with the bus based on the current distance between the next bus and the bus, the average speed of the first bus, and the average speed of the second bus; When the catching-up time is equal to or less than a preset time threshold, and the bus does not reach the next platform to be arrived at after traveling at the average speed of the second bus for the catching-up time, and the distance between the bus and the next platform to be arrived at is equal to or greater than a preset distance threshold, it is determined that the next bus has a higher travel priority than the bus.

2. The system according to claim 1, wherein The bus dispatching system further includes: A bus real-time travel data collection device is provided on the bus, and is used to collect the real-time travel data of the bus; The bus real-time driving data acquisition device includes any one or more of the following modules: A positioning module, used for collecting the current location of the bus in real time; A first image acquisition module is provided at the front of the bus and is used to acquire the road traffic image in front of the bus in real time; A second image acquisition module is provided inside the bus compartment and is used to acquire images of passengers in the bus in real time; A road condition information acquisition module is used to obtain traffic accident information on the route traveled by the bus from a road condition information server on the network side; The bus dispatching system further includes: The third image acquisition module is arranged at the next arrival platform of the bus, and is used to acquire images of passengers in the waiting area waiting for the bus at the next arrival platform.

3. The system according to claim 1, wherein: The cloud server controls the bus according to the analysis and prediction results of the future driving conditions of the bus, including: The cloud server controls the next bus and / or the sound player in the bus to play preset information, and the preset information includes: the driver of the next bus can travel at a preset maximum bus speed and can overtake the bus.

4. The system according to claim 1, wherein: The determining of the driving priority between the next bus and the bus according to the current driving data of the next bus, the average driving speed of the second bus, and the passenger image in the bus includes: Determining the first number of passengers on the next bus according to the passenger screen on the next bus; determining the number of second passengers in the bus based on the passenger image in the bus; determining the number of third passengers in the waiting area according to the passenger screen of the waiting area; When the second number of passengers is greater than the first number of passengers, and the sum of the second number of passengers and the third number of passengers is equal to or greater than the preset maximum number of passengers, it is determined that the next bus has a higher travel priority than the bus.

5. The system according to claim 4, wherein: The cloud server controls the bus according to the analysis and prediction results of the future driving conditions of the bus, including: The cloud server controls the first communication device on the bus to connect with the second communication device on the next bus, and controls both the first communication device and the second communication device to issue a preset prompt, wherein the preset prompt is used to prompt the driver of the bus and the driver of the next bus to communicate with each other about the driving plan of the bus and the next bus.

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