In-tunnel construction vehicle meeting scheduling system based on positioning equipment

Abstract

The invention discloses an in-tunnel construction vehicle meeting scheduling system based on positioning equipment. The system comprises a basic service module which is used for storing basic data for business service analysis in an acquisition and collection mode; the business service module is used for carrying out detailed analysis of the corresponding service through the data acquired by the basic service, and providing an analysis result to the display end for display; and the display end module is used for displaying the analysis result of the business service module, wherein the display modes comprise a mobile phone APP, a webpage large screen, an LED panel, a tunnel loudspeaker and a tunnel traffic light. The system carries out weight grading on vehicle and personnel positioning labels by standardizing a tunnel construction process, and integrates data of avoidance points of a transverse tunnel. And in combination with an intelligent technology, efficient vehicle meeting scheduling, intelligent construction path planning and avoidance point path planning of the construction area are realized.

Description

Technical Field

[0001] The invention belongs to the technical field of engineering project material and equipment management, and in particular relates to a tunnel construction vehicle meeting dispatching system based on positioning equipment. Background Art

[0002] The control of materials and equipment is an extremely critical part of project management. In the construction of tunnels in the harsh environment of plateau railways, vehicle scheduling and management are particularly important. Traditional vehicle scheduling methods often rely on manual scheduling and monitoring, and there are problems such as low construction efficiency, poor safety, and environmental constraints. Therefore, it is necessary to use advanced intelligent technologies and intelligent management methods to improve tunnel construction efficiency and ensure construction quality. UWB (Ultra-Wideband) technology is a wireless positioning technology with high precision, high reliability and strong anti-interference ability, which is particularly suitable for precise positioning in complex environments. In tunnel construction, by deploying fixed base stations and equipping vehicles and personnel with positioning tags combined with construction management data, the precise location of vehicles can be tracked in real time. These data can not only support the three-dimensional visualization of tunnels, but also assist in vehicle scheduling, path planning, and intelligent reminders, providing data support for scheduling in tunnels.

[0003] There are several outstanding technical problems in the current project management of construction vehicle scheduling, especially for large-scale engineering projects such as plateau railway tunnel construction. First, the accuracy of vehicle and personnel positioning. The geological conditions in the plateau area are changeable, the space in the tunnel is closed, the frequent movement of construction equipment and personnel, the noise generated by the operation of construction machinery and blasting, etc. will affect the positioning accuracy. Secondly, the many types of work trolleys and the complex working environment make it difficult to schedule construction vehicles. This is mainly due to the complexity of the construction process and the variety of work trolleys required for tunnel construction projects in the high and cold plateau and complex geological conditions. In addition, the harsh environment leads to an increase in equipment failure rate, which increases the difficulty of maintenance and scheduling of construction vehicles. In addition, the internal space of the tunnel is limited, and the efficient organization between work trolleys, work processes, and work teams is also a major challenge; finally, the application system is highly complex, involving positioning equipment, construction, GIS, geology, machinery, etc., and there are many multi-source heterogeneous data.

[0004] Based on the shortcomings of these prior arts, the present invention proposes a new construction vehicle control system for tunnel construction under high-altitude and cold geological conditions, aiming to solve the above technical problems. By introducing UWB (Ultra-Wideband) technology and utilizing its strong penetration and good anti-interference characteristics, accurate positioning of vehicles and personnel can be achieved in complex geology and closed spaces. By optimizing the base station layout and algorithm, UWB technology can adapt to the dynamic movement of construction equipment and personnel, reduce the impact of mechanical noise on positioning accuracy, and thus improve the accuracy of tunnel construction, vehicle, and personnel data. At the same time, through the standardized combing of traditional tunnel construction procedures, the weight classification of positioning tags of vehicles and personnel in the tunnel, the integration of tunnel cross-hole avoidance points and construction data combined with intelligent technology, including data collection, analysis, scheduling and messaging services, efficient vehicle scheduling in the construction area is achieved. The system will automatically trigger the scheduling service according to the weight of the vehicle, and intelligently plan the construction path and the avoidance point path. Finally, through a unified data analysis platform, real-time equipment data is collected and integrated with construction data and GIS data for rapid analysis and response, realizing three-dimensional visualization, construction vehicle path planning, dispatch reminders, point-to-point avoidance reminders, construction area voice warnings, and LED visual prompts at key tunnel intersections, which comprehensively improves the safety of tunnel construction and dispatch efficiency.

[0005] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0006] The purpose of the present invention is to provide a tunnel construction vehicle meeting dispatching system based on positioning equipment, aiming to solve the challenges faced by the prior art. The system adopts UWB technology, with its excellent penetration and anti-interference, to achieve accurate positioning of vehicles and personnel in complex geological conditions and closed tunnel spaces. Through the layout of triangulated base stations and algorithm optimization, the system can adapt to the dynamic movement of construction equipment and reduce the interference of mechanical noise on positioning accuracy, thereby enhancing the accuracy of data.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions:

[0008] The present invention provides a tunnel construction vehicle meeting dispatching system based on a positioning device, comprising:

[0009] Basic service module: used to store basic data for business service analysis by collecting and gathering, including data collection, data analysis and basic database;

[0010] Business service module: used to conduct detailed analysis of corresponding services through data collected by basic services, and provide the analysis results to the display terminal for display, including message reminders, scheduling planning, intelligent traffic lights, tunnel visualization, voice reminders and meeting analysis;

[0011] Display module: used to display the analysis results of the business service module. Its display methods include mobile APP, large web screen, LED panel, tunnel loudspeaker and tunnel traffic lights.

[0012] Furthermore, the data collection includes four modules: positioning tags, positioning base stations, intelligent traffic lights and WeChat mini-programs; the positioning tags collect tag type, ID, longitude and latitude, and XYZ relative distance data in real time; the positioning base stations collect base station ID, base station type, longitude and latitude, XYZ relative distance, location, and time data; the intelligent traffic lights collect signal light status, signal light phase data, signal light control parameters, signal ID, signal light priority data, and signal light mode data; the WeChat mini-program is used to associate positioning tags with corresponding personnel, vehicle types, vehicle weights, basic face data, and electronic fence basic data.

[0013] Furthermore, the basic database includes positioning tag basic data, construction basic data, and vehicle and personnel weight data; the positioning tag basic data includes basic personnel information, contact information, team information, vehicle type, operator name, and tag ID basic data, which are used for three-dimensional visualization of the tunnel to display the details of the current personnel and current vehicles; the construction basic data is used to initialize the three-dimensional display of the tunnel shape, and provide the necessary basic information for scheduling path planning, avoidance point calculation, message notification, and voice broadcast; the vehicle and personnel weight data maintains the weight information of personnel and vehicle tags, and tags with high weights have priority scheduling and priority access in the scheduling service.

[0014] Furthermore, the data analysis is responsible for providing the required analysis data for the application functions, mainly including four functions: tag location analysis, scheduling analysis, message reminder analysis, and path planning analysis;

[0015] The tag location analysis: provides vehicle and personnel location information in real time through the websocket interface, displays the current location of the personnel and vehicles represented by the positioning tags on a three-dimensional visualization interface, and records and analyzes the movement paths of personnel and vehicles to facilitate historical tracking and behavior analysis;

[0016] The dispatch analysis: plans the origin and destination routes according to the destination, monitors the possible risks of oncoming vehicles on the route in real time, and reasonably plans the route and avoidance routes according to the priority of the positioning tags to improve efficiency and avoid traffic congestion;

[0017] The message reminder analysis includes dispatch reminder, dispatch cancellation reminder, avoidance reminder, electronic fence reminder, and safe step distance reminder; scrolling display of dispatch information on the dispatch large screen homepage, display of LED panel messages at key intersections, and voice broadcasting of reminder content;

[0018] The path planning analysis includes avoidance path planning, oncoming vehicle path planning, and dispatching path planning.

[0019] Furthermore, when a user enters the system, the map layer will automatically locate an initial perspective based on the basic information of the project, usually the entrance or important intersection of the tunnel, so that the user can quickly understand the layout of the entire tunnel and the current traffic conditions; the map layer can receive the personnel and vehicle location data sent by the UWB positioning device in real time, and display it on the map in the form of three-dimensional icons. These icons can be dynamically updated as people and vehicles move, so that users can understand the traffic dynamics in the tunnel in real time; the intelligent scheduling server will send the scheduling instructions generated by the algorithm to the map layer for display, and the map layer will display the scheduling route with special lines; if there are vehicles that need to be avoided, the map layer will display the corresponding avoidance work point icons, which include the scope, type, starting mileage and ending mileage information of the construction area.

[0020] Furthermore, the dispatch planning: the dispatch analysis service captures the vehicle's position, speed, direction and status data in real time through positioning sensors; these real-time data are centrally integrated and constructed into a comprehensive vehicle operation view, providing necessary data support for the path planning module; using these data, the dispatch layer can plan a path for the vehicle and send it to the vehicle terminal. These path planning instructions can assist the driver in making the best driving decisions and effectively improve driving efficiency and safety message reminders.

[0021] Furthermore, the above-mentioned oncoming vehicle analysis: the dispatching service monitors 5 construction areas in real time, and predicts the oncoming vehicle's oncoming vehicle's intention to meet by analyzing the vehicle's current position, driving direction and continuous speed; at the same time, it intelligently determines whether the vehicle needs to be dispatched based on the weight factors of the vehicle's type, size and the urgency of the construction task; for vehicles that need to be dispatched, the system will automatically plan the optimal dispatching route and avoidance route based on the basic information, and display these routes in a three-dimensional visualization interface; in addition, the system will also send notifications to relevant vehicles and construction personnel through real-time messages and voice broadcasts to ensure that they can understand the dispatching information and avoidance requirements in a timely manner.

[0022] Furthermore, the intelligent traffic light: the dispatching component is integrated with the traffic light control system, which is responsible for controlling the switching of the traffic light according to the traffic conditions in the tunnel or the dispatching instructions, and by cooperating with the vehicle positioning system, it can grasp the position and speed of the vehicle in real time, thereby intelligently adjusting the timing plan of the traffic light.

[0023] Furthermore, the specific process of the intelligent scheduling server generating scheduling instructions according to the algorithm is as follows:

[0024] 1) Construction area division: five construction areas: left line long mileage, left line short mileage, right line long mileage, right line short mileage, and cross-through entrance, including multiple cross-through avoidance points;

[0025] 2) Vehicle weight algorithm: traffic vehicles and power supply vehicles have a first-level weight; muck trucks, excavators, and dump trucks have a second-level weight; measurement and monitoring vehicles and water pump vehicles have a third-level weight; three-arm drilling rigs, arch anchor integrated machines, wet spraying rigs, and anchor injection integrated machines have a fourth-level weight; secondary lining rigs have a fifth-level weight; vehicles with high weights have the right to pass first and be calculated;

[0026] 3) Meeting algorithm: Calculate the horizontal and vertical coordinates relative to the origin by subtracting the coordinates of the origin from the projection plane coordinates collected by the sensor;

[0027] The calculation of the meeting dispatch is initiated:

[0028] When the vehicle position changes linearly along the X axis, it enters the mobile monitoring queue and monitors the vehicle for 10 seconds. If the vehicle keeps moving during the monitoring time and does not move back and forth within the same construction area, the vehicle is determined to be a mobile vehicle and enters the path planning queue.

[0029] 4) Path planning algorithm: Based on the vehicle's current route analysis and prediction model LSTM, it is used for destination path planning. It monitors whether there are other vehicles on the current path that intend to meet in the same direction. It only analyzes the vehicles traveling in the opposite direction of the path planning vehicle, and does not analyze the vehicles traveling in the same direction. There is only one dispatching master process allowed for vehicles with the intention of meeting in the same construction area. After the dispatching is completed, the dispatched vehicles resume normal traffic and are notified by voice.

[0030] The path planning algorithm is specifically implemented as follows:

[0031] ④LSTM network architecture:

[0032] Input layer: receives the real-time projection coordinates, relative coordinates, work area, and basic data of the vehicle avoidance point; Hidden layer: LSTM unit, capturing the long-term dependencies in the time series; Output layer: predicts the vehicle destination work area;

[0033] ⑤LSTM unit formula:

[0034] Input gate: i t =σ(W i ·[h t-1 ,x t ]+b i )

[0035] Forget gate: f t =σ(W f ·[h t-1 ,x t ]+b f )

[0036] Output gate: o t =σ(W o ·[h t-1 ,x t ]+b o )

[0037] Candidate memory cells:

[0038] Update memory unit:

[0039] The final output is h t =o t tanh(C t )

[0040] h t : The hidden state of the current time step, which contains information about the vehicle’s current driving state, such as position, speed, etc.

[0041] x t : Input data for the current time step, which may include the vehicle's position, velocity, acceleration, and possible sensor inputs.

[0042] W and b: weight matrix and bias term in LSTM network, which are parameters of the model and are learned through training data.

[0043] f t : The forget gate activation value at the current time step, which determines how much information to retain from the previous state.

[0044] i t : The input gate activation value of the current time step, which determines the amount of new information added.

[0045] C t : The unit state at the current time step, representing the memory information of the vehicle at time step t.

[0046] The candidate cell state at the current time step is the candidate value of the new information and is used to update the cell state.

[0047] ot : The output gate activation value of the current time step determines the output amount of the hidden state.

[0048] The predicted output, such as position or velocity at the next time step.

[0049] The symbol σ represents the Sigmoid function:

[0050] In the analysis of the intention of meeting a vehicle, although the Sigmoid function is not directly used to represent the intention of meeting a vehicle, its principle can be analogized to the "gating" mechanism in the decision-making process, for example

[0051] The Sigmoid function is used to evaluate whether a vehicle has the intention to meet other vehicles. Based on factors such as the vehicle's speed, position, and direction of travel, a threshold can be used to determine whether the vehicle is likely to meet other vehicles.

[0052] In the dispatching system, the Sigmoid function can be used to determine whether vehicles need to be dispatched. For example, if two vehicles are expected to meet in a construction area, the Sigmoid function can be used to evaluate whether the dispatching mechanism needs to be initiated.

[0053] ⑥Training process:

[0054] Loss function: Mean square error MSE:

[0055] MSE: An indicator that measures the prediction accuracy of the model in path planning and oncoming vehicle intention analysis tasks. A lower MSE value indicates that the model's prediction is closer to the actual situation.

[0056] N t : The number of samples in the dataset can represent the total number of independent traffic scenarios considered in the training data. Each scenario may contain different information such as vehicle position, speed, and meeting intention.

[0057] y ( : The true value of the i-th sample can represent the actual vehicle trajectory, the actual meeting event or other traffic parameters.

[0058] ^

[0059] y i : The predicted value of the i-th sample, representing the vehicle’s driving trajectory or meeting intention predicted by the model based on current and historical traffic data.

[0060] Train the LSTM model to predict the position of the vehicle after a specific time step, where y ( and are the actual position and the predicted position respectively.

[0061] Evaluate the model's prediction accuracy for oncoming vehicles, where y ( may represent an actual encounter, while Represents the oncoming probability or event predicted by the model.

[0062] Using the LSTM model to predict the vehicle's position at the next time step, the MSE can be used to quantify the error between the predicted position and the actual position, thereby guiding the model's training and optimization process.

[0063] In the context of meeting intention analysis and path planning, MSE can be used to evaluate the performance of prediction models to ensure that the models can provide accurate prediction results, achieve effective traffic management and avoid potential traffic conflicts.

[0064] Optimization algorithm: Adam optimizer;

[0065] ④ Prediction process: Use the trained LSTM model to input the current vehicle location information, basic information of the construction area, and basic information of the meeting and avoidance points to predict the future vehicle path and the avoidance route of the vehicle;

[0066] Same direction, object: The sensor transmits position data 10 times per second, and the path planning algorithm updates the vehicle direction information every 5 seconds: the larger the Xrel, the easterly direction; the smaller the Xrel, the westerly direction; the larger the Yrel, the northerly direction; the smaller the Yrel, the southerly direction;

[0067] Direction algorithm, current sensor Xrel, Yrel offset value algorithm implementation:

[0068] The origin coordinates of the sensor: Assume that the tunnel entrance is the origin of the map and use (X0, Y0) to represent that all data are 0;

[0069] Sensor direction: expressed as the angle of the sensor relative to the origin, denoted by θ;

[0070] Distance moved by the sensor: The distance the sensor moves from the origin, represented by d;

[0071] Calculate new position: Calculate the new position of the sensor (Xrel, Yrel) using the following formula:

[0072] Xrel=X0+d·cos(θ)

[0073] Yrel=Y0+d·sin(θ)

[0074] Where cos(θ) and sin(θ) are the cosine and sine of the angle θ respectively;

[0075] θ is the unit of radians, and the angle value needs to be converted. The conversion formula is: θ radians = θ degrees × 180π.

[0076] Furthermore, the mobile phone APP: display functions to initialize GIS positioning of the current work site, manually initiate dispatch, display message reminder texts, operator voice dialing service, and query the current dispatch vehicle route of the corresponding work area;

[0077] Web page screen: Display function initialization GIS positioning current work point, 3D visualization display of current tunnel, query dispatch route, message reminder, real-time display of vehicle and personnel labels, detailed information query, and path planning display;

[0078] LED panel: scrolling display of text content of message reminders and service reminders;

[0079] Tunnel loudspeaker: broadcasts the text of voice service reminders through the interface;

[0080] Tunnel traffic lights: control the display of red and green lights at tunnel intersections through vehicle dispatch information from the dispatch service.

[0081] By adopting the above technical solution, the present invention has the following beneficial effects:

[0082] First of all, in complex environments such as mountain tunnels, UWB technology can provide centimeter-level positioning accuracy to ensure the accuracy of vehicle location. High-precision positioning helps to achieve more precise vehicle dispatch and reduce information errors caused by positioning errors. The high real-time performance of the UWB positioning system enables the dispatch center to grasp the distribution of vehicles and personnel in the tunnel in real time; it can also provide self-reminders for construction restricted areas, construction safe step distances, etc.

[0083] Secondly, the scheduling efficiency is optimized and the construction process is standardized.

[0084] Optimize dispatch efficiency: Through the precise positioning of vehicles and personnel achieved by UWB technology, the system can track and analyze the location and status of construction vehicles in real time, thereby making more accurate and efficient dispatch decisions. The introduction of a weighted classification system intelligently assigns priorities based on the type, size and urgency of the construction task, ensuring that traffic congestion is not caused by vehicles passing each other in small construction areas.

[0085] Standardized construction process: The tunnel construction process was standardized and a set of standardized operating procedures was established to reduce uncertainty and confusion during the construction process. Through the standardized process, construction personnel can more clearly understand their responsibilities and construction sequence, improving the coordination and efficiency of construction.

[0086] Finally, management efficiency is improved, construction safety is enhanced, and operating costs are reduced.

[0087] Improve management efficiency: Through UWB positioning technology, the location data of vehicles and personnel in tunnel construction are collected and analyzed in real time, allowing construction managers to monitor the construction site more efficiently and make scheduling decisions quickly. In addition, through standardized construction processes, the reliance on manual monitoring is reduced, the level of automation of construction is improved, and thus the overall management efficiency is improved.

[0088] Enhanced construction safety: The precise positioning system ensures real-time monitoring of construction personnel and vehicles, effectively preventing potential construction conflicts and accidents. The intelligent dispatching system automatically plans the optimal route based on vehicle weight and construction requirements, reducing traffic congestion and the risk of oncoming vehicles in the tunnel. In addition, the system also includes safe step distance reminders and electronic fence reminders, further improving the safety of the construction site.

[0089] Reduced operating costs: Automated scheduling and route planning reduce costs caused by human errors or inefficient scheduling. By reducing congestion and accidents during construction, it also reduces the additional expenses caused by maintenance and shutdowns. At the same time, the efficient management of the system reduces the reliance on a large number of human resources, further reducing labor costs and management costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0090] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0091] Figure 1 This is an overall framework diagram of the in-tunnel construction vehicle meeting and dispatching system based on positioning equipment according to the present invention.

[0092] Figure 2 This is a service structure diagram of the tunnel construction vehicle meeting dispatching system based on positioning equipment according to the present invention.

[0093] Figure 3 This is a schematic diagram of the construction area division described in the present invention. DETAILED DESCRIPTION

[0094] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0095] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0096] Combination Figure 1-3 As shown, this embodiment provides a method and system for dispatching construction vehicles in a tunnel based on UWB positioning equipment, which includes three major parts: basic services, business services, and display terminals.

[0097] Basic services: mainly store basic data for business service analysis through collection and aggregation, including three modules (data collection, data analysis, and basic database).

[0098] Data collection: It includes four modules: positioning tags, positioning base stations, smart traffic lights, and WeChat applet terminals. The positioning tags collect data such as tag type, ID, longitude and latitude, XYZ relative distance (meters) in real time. The positioning base stations collect data such as base station ID, base station type, longitude and latitude, XYZ relative distance (meters), location, time, etc. The smart traffic lights collect data such as signal light status, signal light phase data, signal light control parameters, signal ID, signal light priority data, signal light mode, etc. The positioning tags are associated with personnel, vehicle type, vehicle weight, face basic data (pile number, mileage, construction area name, update date), and electronic fence basic data (longitude and latitude coordinates, relative position XY, warning registration, fence area name) through WeChat applet.

[0099] Basic database: Contains basic data of positioning tags, basic construction data, and vehicle and personnel weight data. Positioning tags contain basic data such as basic personnel information, contact information, team information, vehicle type, operator name, tag ID, etc., which are mainly used for 3D visualization of tunnels to display the details of current personnel and vehicles; basic construction data is used to initialize the 3D display of tunnel shape, and provide necessary basic information for dispatching path planning, avoidance point calculation, message notification and voice broadcast; vehicle and personnel weights maintain weight information for personnel and vehicle tags, and tags with high weights have priority dispatching, priority passage and other permissions in dispatching services;

[0100] Data analysis: mainly responsible for providing the required analytical data for application functions, including four major functions: tag location analysis, scheduling analysis, message reminder analysis, and path planning analysis;

[0101] Tag location analysis: Provides real-time vehicle and personnel location information through the websocket interface, displays the current location of the personnel and vehicles represented by the positioning tags on a three-dimensional visualization interface, and records and analyzes the movement paths of personnel and vehicles to facilitate historical tracking and behavior analysis.

[0102] Dispatching route analysis: Plan the origin and destination routes based on the destination, monitor the risks of oncoming vehicles in real time, and reasonably plan the route and avoidance routes based on the priority of the positioning tags to improve efficiency and avoid traffic congestion.

[0103] Message reminder analysis: including dispatch reminder, dispatch cancellation reminder, avoidance reminder, electronic fence reminder, safe step distance reminder, etc. It mainly displays dispatch information on the dispatch large screen home page, displays messages on the LED panel at key intersections, and plays reminder content in the form of voice broadcast. The specific functions are as follows:

[0104] Dispatch reminder: After the vehicle initiates the dispatch, the message service starts to refresh the dispatch large screen system homepage every 10 seconds based on the vehicle's origin location, destination location, current location, and basic vehicle information; Dispatch cancellation reminder: When the dispatch service determines that the vehicle has arrived at the destination, the message service starts to display the vehicle's basic information, origin, destination, and remind the end of the dispatch, and other vehicles can pass normally;

[0105] Avoidance reminder: After the dispatch service is initiated, vehicles with higher weights have priority path planning and the right to pass. The dispatch service for vehicles with lower weights will plan the nearest cross-tunnel avoidance point nearby and send avoidance route notifications to designated vehicles through mobile phone APP, operator voice service, LED panel display and other functions.

[0106] Electronic fence reminder: When a person tag enters the electronic fence area, the voice and message functions will remind you.

[0107] Safety step distance reminder: If the position data obtained by the personnel positioning tag exceeds the safety step distance threshold maintained by the basic construction data, the system will pay attention to the current tag for more than 1 minute and send a voice or message reminder "XX construction area, construction personnel XX please pay attention to the safety step distance".

[0108] Path planning analysis: including avoidance path planning, meeting path planning, and dispatching path planning;

[0109] Avoidance route planning: When the dispatch service detects that a vehicle needs to avoid, it will select the nearest cross-hole avoidance point to plan a route for the avoiding vehicle to choose. After the dispatch is completed, the avoidance reminder ends and the vehicle can pass freely.

[0110] Meeting route planning: The dispatch service monitors five construction areas (cross tunnel, left line with large mileage, left line with small mileage, right line with large mileage, and right line with small mileage) in real time. For vehicles with the intention of meeting, the dispatch service will calculate whether the vehicle needs to be dispatched according to the vehicle weight and basic vehicle information (for large operating equipment, traffic congestion is easy to occur due to limited space in the tunnel), and plan the vehicle dispatch route and avoidance route. At the same time, messages and voice reminders are sent that there is a large operating trolley starting from XXX to the destination XXX for construction. Construction vehicles in the XXX work area should pay attention to avoid it. After the vehicle arrives at the destination, the dispatch service ends.

[0111] Dispatching route planning: The basic data divides the tunnel into five construction sites (cross tunnel, left line long mileage, left line short mileage, right line long mileage, right line short mileage). Special operation vehicles select the dispatching vehicle and the dispatching destination through the mobile phone APP. The dispatching service will plan the vehicle route according to the basic information, and monitor the risk of oncoming vehicles at the same time. The message reminds that there are special operation vehicles going to the destination for construction. Other vehicles should pay attention to avoid the risk of oncoming vehicles. The dispatching service ends when the vehicle arrives at the destination.

[0112] Business services: Main analysis services, including (message reminders, scheduling planning, intelligent traffic lights, tunnel visualization, voice reminders, and vehicle meeting analysis). Through the data collected by basic services, detailed analysis of corresponding services is carried out, and the results of the analysis are provided to the display terminal for display.

[0113] Tunnel visualization: When the user enters the system, the map layer will automatically locate an initial perspective based on the basic information of the project, usually the entrance or important intersection of the tunnel, so that the user can quickly understand the layout of the entire tunnel and the current traffic conditions; the map layer can receive the personnel and vehicle location data sent by the UWB positioning device in real time, and display it on the map in the form of three-dimensional icons. These icons can be dynamically updated as people and vehicles move, so that users can understand the traffic dynamics in the tunnel in real time; the intelligent scheduling server will send the scheduling instructions generated by the algorithm to the map layer for display, and the map layer will display the scheduling route with special lines; if there are vehicles that need to be avoided, the map layer will display the corresponding avoidance work point icons, which usually include information such as the scope, type, starting mileage and ending mileage of the construction area.

[0114] Dispatch planning: The dispatch analysis service captures key data such as the vehicle's location, speed, direction, and status in real time through positioning sensors. These real-time data are centrally integrated and constructed into a comprehensive view of vehicle operation, providing necessary data support for the path planning module. Using these data (path planning, vehicle priority weights, and traffic signal control), the dispatch layer can plan a path for the vehicle and send it to the vehicle terminal. These path planning instructions can assist the driver in making the best driving decisions, effectively improving driving efficiency and safety message reminders.

[0115] Message reminder: Responsible for displaying key information (such as traffic status, dispatch instructions, safety warnings, etc.) on the decision-making large screen homepage and the LED board in the tunnel for information scrolling and floating reminders. It can receive real-time data from different components, and process these messages according to preset rules and analysis service areas to generate corresponding message reminder texts.

[0116] Intelligent traffic lights: The dispatching component is integrated with the traffic light control system. It is responsible for controlling the on / off switching of traffic lights according to the traffic conditions in the tunnel or dispatching instructions. By cooperating with the vehicle positioning system, it can grasp the position and speed of the vehicle in real time, thereby intelligently adjusting the timing plan of the traffic lights.

[0117] Voice reminder: responsible for converting dispatch instructions, safety warnings or other important information into voice form and playing it through the speaker system in the tunnel. It can receive text information from the dispatch center or other related components;

[0118] Meeting analysis: The dispatch service monitors five construction areas (cross tunnel, left line long mileage, left line short mileage, right line long mileage, right line short mileage) in real time, and predicts the meeting intention of oncoming vehicles by analyzing the current position, driving direction and continuous speed of the vehicle. At the same time, based on weight factors such as the type and size of the vehicle and the urgency of the construction task, it intelligently determines whether the vehicle needs to be dispatched. For vehicles that need to be dispatched, the system will automatically plan the optimal dispatch route and avoidance route based on basic information, and display these routes in a three-dimensional visualization interface. In addition, the system will send notifications to relevant vehicles and construction personnel through real-time messages and voice broadcasts to ensure that they can understand the dispatch information and avoidance requirements in a timely manner.

[0119] Display end: mainly presents pages, including (mobile phone APP, web screen, LED panel, tunnel loudspeaker, tunnel traffic lights);

[0120] Mobile APP: The main display functions include initializing GIS to locate the current work site, manually initiating dispatch, displaying message reminder texts, providing operator voice dialing services, and querying the current dispatch vehicle route of the corresponding work area (visual display).

[0121] Web screen: The main display functions are initialization of GIS positioning of the current work site, 3D visualization, display of the current tunnel, query of dispatch routes, message reminders (scrolling display), real-time display of vehicle and personnel labels, detailed information query, and path planning display.

[0122] LED panel: mainly scrolls and displays the text content of message reminders and service reminders.

[0123] Tunnel loudspeaker: broadcasts the text of voice service reminders through the interface.

[0124] Tunnel traffic lights: The display of red and green lights at tunnel intersections is controlled through the vehicle dispatch information (direction, destination, current location, current work area) of the dispatch service.

[0125] Scheduling algorithm:

[0126] 1. Construction area division: five construction areas: left line long mileage, left line short mileage, right line long mileage, right line short mileage, and cross-entrance, and also includes multiple cross-entry avoidance points ( Figure 3 ).

[0127] 2. Vehicle weight algorithm: first-level weight for transportation vehicles and power supply vehicles; second-level weight for muck trucks, excavators, and dump trucks; third-level weight for measurement and monitoring vehicles and water pump vehicles; fourth-level weight for three-arm drilling rigs, arch-anchor integrated machines, wet-spraying rigs, and anchor-injection integrated machines; fifth-level weight for second-lining rigs; vehicles with high weights have the right to priority passage and calculation.

[0128] 3. Meeting algorithm: Calculate the horizontal and vertical coordinates relative to the origin by subtracting the coordinates of the origin from the projection plane coordinates collected by the sensor. For example, if the plane coordinates of the origin are (X0, Y0) and the plane coordinates of the sensor are (Xs, Ys), the relative coordinates are:

[0129] Xrel=Xs-X0

[0130] Yrel=Ys-Y0

[0131] The calculation of the meeting dispatch is initiated:

[0132] When the vehicle position changes linearly along the X-axis, it enters the mobile monitoring queue and continues to monitor the vehicle for 10 seconds. During the monitoring time, the vehicle keeps moving and is not in a construction state of going back and forth in the same range. The vehicle is determined to be a mobile vehicle and enters the path planning queue.

[0133] 4. Path planning algorithm: Based on the vehicle's current route analysis and prediction model LSTM (Long Short Term Memory Network), it is used for destination path planning, monitoring whether there are other vehicles on the current path with the intention of meeting in the same direction, and only analyzing the vehicles traveling in the opposite direction of the path planning vehicle, and not analyzing the vehicles traveling in the same direction. For vehicles with the intention of meeting, only one scheduling master process is allowed in the same construction area (scheduling is initiated based on vehicle weights). After the scheduling is completed, the scheduled vehicles resume normal traffic and voice notification is given at the same time.

[0134] Algorithm implementation:

[0135] 1.LSTM network architecture:

[0136] Input layer: receives basic data such as real-time projection coordinates, relative coordinates, work area, and vehicle avoidance points of sensors. Hidden layer: LSTM units, capturing long-term dependencies in time series. Output layer: predicts the vehicle destination work area.

[0137] 2.LSTM unit formula:

[0138] Input gate: i t =σ(W i ·[h t-1 ,x t ]+b i )

[0139] Forget gate: f t =σ(W f ·[h t-1 ,x t ]+b f )

[0140] Output gate: o t =σ(W o ·[h t-1 ,x t ]+b o )

[0141] Candidate memory cells:

[0142] Update memory unit:

[0143] The final output is h t =o t tanh(C t )

[0144] 3. Training process:

[0145] Loss function: Mean Squared Error (MSE):

[0146] Optimization algorithm: Adam optimizer.

[0147] 4. Prediction process: Use the trained LSTM model to input the current vehicle location information, basic information of the construction area, and basic information of the meeting and avoidance points to predict the future vehicle path and the avoidance route of the vehicle; Same direction, object: The sensor transmits location data 10 times per second, and the path planning algorithm updates the vehicle direction information every 5 seconds: the larger the Xrel, the direction is eastward; the smaller the Xrel, the direction is westward; the larger the Yrel, the direction is northward; the smaller the Yrel, the direction is southward.

[0148] Direction algorithm, current sensor Xrel, Yrel offset value algorithm implementation:

[0149] The origin coordinates of the sensor: Assume that the tunnel entrance is the origin of the map and use (X0, Y0) to represent that all data are 0.

[0150] Sensor orientation: This is usually expressed as the orientation of the sensor relative to the origin, denoted by θ. This angle is usually the deflection angle relative to some reference direction (such as north).

[0151] Distance traveled by the sensor: This is the distance the sensor moves from the origin, denoted by d.

[0152] Calculate new position: Calculate the new position of the sensor (Xrel, Yrel) using the following formula:

[0153] Xrel=X0+d·cos(θ)

[0154] Yrel=Y0+d·sin(θ)

[0155] Where cos(θ) and sin(θ) are the cosine and sine of the angle θ, respectively.

[0156] θ should be in radians, and the angle value needs to be converted. The conversion formula is: θ radians = θ degrees × 180π.

[0157] In summary, the present invention proposes a new method and system for tunnel construction vehicle control under high-altitude and cold geological conditions, aiming to solve the challenges faced by existing technologies. The system adopts UWB technology, with its excellent penetration and anti-interference performance, to achieve accurate positioning of vehicles and personnel in complex geological conditions and closed tunnel spaces. Through triangulation base station layout and algorithm optimization, the system can adapt to the dynamic movement of construction equipment and reduce the interference of mechanical noise on positioning accuracy, thereby enhancing the accuracy of data.

[0158] In addition, the system uses standardized tunnel construction processes to weight and classify vehicle and personnel location tags, and integrates data on tunnel cross-hole avoidance points. Combined with intelligent technology, efficient vehicle scheduling, intelligent construction path planning, and avoidance point path planning in the construction area are achieved. The system can also automatically initiate scheduling services based on vehicle weights and provide intelligent planning of construction paths and avoidance points. Finally, through a unified data analysis platform, the system can collect and integrate equipment data, construction data, and GIS data in real time, and quickly analyze and respond. It realizes three-dimensional visualization, construction vehicle path planning, scheduling reminders, avoidance reminders, voice warnings in the construction area, and LED visual prompts at key tunnel intersections, greatly improving the safety and management efficiency of tunnel construction.

[0159] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A tunnel construction vehicle meeting dispatching system based on positioning equipment, characterized in that: include: Basic service module: used to store basic data for business service analysis by collecting and gathering, including data collection, data analysis and basic database; Business service module: used to conduct detailed analysis of corresponding services through data collected by basic services, and provide the analysis results to the display terminal for display, including message reminders, scheduling planning, intelligent traffic lights, tunnel visualization, voice reminders and meeting analysis; Display module: used to display the analysis results of the business service module. Its display methods include mobile APP, large web screen, LED panel, tunnel loudspeaker and tunnel traffic lights.

2. The tunnel construction vehicle meeting dispatching system based on positioning equipment according to claim 1 is characterized in that: The data collection includes four modules: positioning tags, positioning base stations, intelligent traffic lights and WeChat mini-programs; the positioning tags collect tag type, ID, longitude and latitude, and XYZ relative distance data in real time; the positioning base stations collect base station ID, base station type, longitude and latitude, XYZ relative distance, location, and time data; the intelligent traffic lights collect signal light status, signal light phase data, signal light control parameters, signal ID, signal light priority data, and signal light mode data; the WeChat mini-program is used to associate positioning tags with corresponding personnel, vehicle types, vehicle weights, basic face data, and electronic fence basic data.

3. The tunnel construction vehicle meeting dispatching system based on positioning equipment according to claim 1 is characterized in that: The basic database includes positioning tag basic data, construction basic data, vehicle and personnel weight data; the positioning tag basic data includes basic personnel information, contact information, team information, vehicle type, operator name, tag ID basic data, which is used for three-dimensional visualization of tunnels to display the current personnel and current vehicle details; The basic construction data is used to initialize the three-dimensional display of the tunnel shape and provide the necessary basic information for dispatching path planning, avoidance point calculation, message notification and voice broadcasting; the vehicle and personnel weight data maintains the weight information of personnel and vehicle tags. Tags with high weights have priority dispatching and priority access in the dispatching service.

4. The tunnel construction vehicle meeting dispatching system based on positioning equipment according to claim 1 is characterized in that: The data analysis is responsible for providing the required analysis data for the application functions, mainly including four functions: tag location analysis, scheduling analysis, message reminder analysis, and path planning analysis; The tag location analysis: provides vehicle and personnel location information in real time through the websocket interface, displays the current location of the personnel and vehicles represented by the positioning tags on a three-dimensional visualization interface, and records and analyzes the movement paths of personnel and vehicles to facilitate historical tracking and behavior analysis; The dispatch analysis: plans the origin and destination routes according to the destination, monitors the possible risks of oncoming vehicles on the route in real time, and reasonably plans the route and avoidance routes according to the priority of the positioning tags to improve efficiency and avoid traffic congestion; The message reminder analysis includes dispatch reminder, dispatch cancellation reminder, avoidance reminder, electronic fence reminder, and safe step distance reminder; scrolling display of dispatch information on the dispatch large screen homepage, display of LED panel messages at key intersections, and voice broadcasting of reminder content; The path planning analysis includes avoidance path planning, oncoming vehicle path planning, and dispatching path planning.

5. The tunnel construction vehicle meeting dispatching system based on positioning equipment according to claim 1, characterized in that: The tunnel visualization is that when the user enters the system, the map layer will automatically locate an initial perspective according to the basic information of the project, usually the entrance or important intersection of the tunnel, so that the user can quickly understand the layout of the entire tunnel and the current traffic conditions; the map layer can receive the personnel and vehicle location data sent by the UWB positioning device in real time, and display it on the map in the form of three-dimensional icons. These icons can be dynamically updated as the personnel and vehicles move, so that users can understand the traffic dynamics in the tunnel in real time; the intelligent scheduling server will send the scheduling instructions generated by the algorithm to the map layer for display, and the map layer will display the scheduling route with special lines; if there are vehicles that need to be avoided, the map layer will display the corresponding avoidance work point icons, which include the scope, type, starting mileage and ending mileage information of the construction area.

6. The tunnel construction vehicle meeting dispatching system based on positioning equipment according to claim 1, characterized in that: The dispatch planning: dispatch analysis service captures the position, speed, direction and status data of vehicles in real time through positioning sensors; these real-time data are centrally integrated and constructed into a comprehensive view of vehicle operation, providing necessary data support for the path planning module; Using these data, the scheduling layer can plan routes for vehicles and send them to vehicle terminals. These route planning instructions can assist drivers in making the best driving decisions, effectively improving driving efficiency and safety message reminders.

7. The tunnel construction vehicle meeting dispatching system based on positioning equipment according to claim 1 is characterized in that: The above-mentioned oncoming vehicle analysis: The dispatch service monitors the five construction areas in real time, and predicts the oncoming vehicle's oncoming vehicle's intention to meet by analyzing the vehicle's current position, driving direction and continuous speed. At the same time, it intelligently determines whether the vehicle needs to be dispatched based on the weight factors of the vehicle's type, size and the urgency of the construction task. For vehicles that need to be dispatched, the system will automatically plan the optimal dispatch route and avoidance route based on basic information, and display these routes in a three-dimensional visualization interface. In addition, the system will also send notifications to relevant vehicles and construction personnel through real-time messages and voice broadcasts to ensure that they can understand the dispatch information and avoidance requirements in a timely manner.

8. The tunnel construction vehicle meeting dispatching system based on positioning equipment according to claim 1, characterized in that: The intelligent traffic light: the dispatching component is integrated with the traffic light control system, and is responsible for controlling the switching of the traffic light according to the traffic conditions in the tunnel or the dispatching instructions. By cooperating with the vehicle positioning system, the position and speed of the vehicle are grasped in real time, thereby intelligently adjusting the timing plan of the traffic light.

9. The tunnel construction vehicle meeting dispatching system based on positioning equipment according to claim 5, characterized in that: The specific process of the intelligent scheduling server generating scheduling instructions according to the algorithm is as follows: 1) Construction area division: five construction areas: left line long mileage, left line short mileage, right line long mileage, right line short mileage, and cross-through entrance, including multiple cross-through avoidance points; 2) Vehicle weight algorithm: traffic vehicles and power supply vehicles have a first-level weight; muck trucks, excavators, and dump trucks have a second-level weight; measurement and monitoring vehicles and water pump vehicles have a third-level weight; three-arm drilling rigs, arch anchor integrated machines, wet spraying rigs, and anchor injection integrated machines have a fourth-level weight; secondary lining rigs have a fifth-level weight; vehicles with high weights have the right to pass first and be calculated; 3) Meeting algorithm: Calculate the horizontal and vertical coordinates relative to the origin by subtracting the coordinates of the origin from the projection plane coordinates collected by the sensor; The calculation of the meeting dispatch is initiated: When the vehicle position changes linearly along the X axis, it enters the mobile monitoring queue and monitors the vehicle for 10 seconds. If the vehicle keeps moving during the monitoring time and does not move back and forth within the same construction area, the vehicle is determined to be a mobile vehicle and enters the path planning queue. 4) Path planning algorithm: Based on the vehicle's current route analysis and prediction model LSTM, it is used for destination path planning. It monitors whether there are other vehicles on the current path that intend to meet in the same direction. It only analyzes the vehicles traveling in the opposite direction of the path planning vehicle, and does not analyze the vehicles traveling in the same direction. There is only one dispatching master process allowed for vehicles with the intention of meeting in the same construction area. After the dispatching is completed, the dispatched vehicles resume normal traffic and are notified by voice. The specific implementation of the path planning algorithm is as follows: ①LSTM network architecture: Input layer: receives the real-time projection coordinates, relative coordinates, work area, and basic data of the vehicle avoidance point of the sensor; Hidden layer: LSTM unit, capturing the long-term dependency in the time series; Output layer: predict the vehicle destination work area; ②LSTM unit formula: Input gate: i t =σ(W i ·[h t-1 ,x t ]+b i ) Forget gate: f t =σ(W f ·[h t-1 ,x t ]+b f ) Output gate: o t =σ(W o ·[h t-1 ,x t ]+b o ) Candidate memory cells: Update memory unit: The final output is h t =o t tanh(C t ) h t : The hidden state of the current time step, which contains the information of the current driving state of the vehicle; x t : Input data for the current time step, including the vehicle's position, velocity, acceleration, and sensor input; W and b: weight matrix and bias term in LSTM network, which are parameters of the model and are learned through training data; f t : The activation value of the forget gate at the current time step, which determines how much information is retained from the previous state; i t : The input gate activation value at the current time step, which determines the amount of new information added; C t : The unit state at the current time step, representing the memory information of the vehicle at time step t; The candidate cell state at the current time step is the candidate value of the new information and is used to update the cell state; o t : The output gate activation value of the current time step determines the output amount of the hidden state; The predicted output; The symbol σ represents the Sigmoid function; ③Training process: Loss function: Mean square error MSE: MSE: An indicator that measures the prediction accuracy of the model in path planning and oncoming vehicle intention analysis tasks. A lower MSE value indicates that the model's prediction is closer to the actual situation. N t : The number of samples in the dataset, representing the total number of independent traffic scenarios considered in the training data; each scenario contains different vehicle positions, speeds, and meeting intention information; y i : The true value of the sample, representing the actual vehicle trajectory, the actual vehicle encounter event or other traffic parameters; The predicted value of the sample represents the vehicle's driving trajectory or meeting intention predicted by the model based on current and historical traffic data; Train the LSTM model to predict the position of the vehicle after a specific time step, where y i and are the actual position and the predicted position respectively; Optimization algorithm: Adam optimizer; ④ Prediction process: Use the trained LSTM model to input the current vehicle location information, basic information of the construction area, and basic information of the meeting and avoidance points to predict the future vehicle path and the avoidance route of the vehicle; ⑤ Analysis of the intention of meeting vehicles: v ego : the speed of the vehicle; v other : speed of other vehicles; p ego : The current position of the vehicle; p other : The position of other vehicles; D min : The minimum safe distance between the vehicle and other vehicles; T arrival : Estimated time of arrival at a location; Predict whether the ego vehicle and the target vehicle will meet at a certain time point t: WillMeet = (p ego +v ego ·t)≈(p other +v other t); Determine whether scheduling is needed: DispatchNeede = (D min <ThresholdDistance)∧WillMeet; Same direction, object: The sensor transmits position data 10 times per second, and the path planning algorithm updates the vehicle direction information every 5 seconds: the larger the Xrel, the easterly direction; the smaller the Xrel, the westerly direction; the larger the Yrel, the northerly direction; the smaller the Yrel, the southerly direction; Direction algorithm, current sensor Xrel, Yrel offset value algorithm implementation: The origin coordinates of the sensor: Assume that the tunnel entrance is the origin of the map and use (X0, Y0) to represent that all data are 0; Sensor direction: expressed as the angle of the sensor relative to the origin, denoted by θ; Distance moved by the sensor: The distance the sensor moves from the origin, represented by d; Calculate new position: Calculate the new position of the sensor (Xrel, Yrel) using the following formula: Xrel=X0+d·cos(θ) Yrel=Y0+d·sin(θ) Where cos(θ) and sin(θ) are the cosine and sine of the angle θ respectively; θ is the unit of radians, and the angle value needs to be converted. The conversion formula is: θ radians = θ degrees × 180π.

10. The tunnel construction vehicle meeting dispatching system based on positioning equipment according to claim 1, characterized in that: The mobile phone APP: Display functions: initializing GIS positioning of the current work site, manually initiating dispatch, message reminder text display, operator voice dialing service, querying the current dispatch vehicle route of the corresponding work area; Web page screen: Display function initialization GIS positioning current work point, 3D visualization display of current tunnel, query dispatch route, message reminder, real-time display of vehicle and personnel labels, detailed information query, and path planning display; LED panel: scrolling display of text content of message reminders and service reminders; Tunnel loudspeaker: broadcasts the text of voice service reminders through the interface; Tunnel traffic lights: control the display of red and green lights at tunnel intersections through vehicle dispatch information from the dispatch service.

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