A heavy haulage vehicle consist multimodal operating system

Abstract

The utility model discloses a kind of large piece transport vehicle group multimode operation system.The system includes road perception subsystem, vehicle-mounted monitoring subsystem, vehicle-mounted intelligent terminal, cloud monitoring platform and cross-department communication subsystem.Road perception subsystem is through the sensing unit group of distributed arrangement to gather road geometry parameter, road surface condition and structure stress data;Vehicle-mounted monitoring subsystem is according to the sensor of "vehicle-goods-environment" classification arrangement, realizes full-dimension monitoring;Vehicle-mounted intelligent terminal is as data processing and interaction core, integrates multiple communication modules;Cloud monitoring platform is responsible for data storage, calculation and decision-making;Cross-department communication subsystem realizes and the data interaction of national road information network and traffic management department.Realized route intelligent planning, transportation process real-time monitoring, complex intersection traffic coordination and networkless area emergency handling, effectively improve the special section traffic coordination efficiency and driving safety.

Description

Technical Field

[0001] This utility model relates to the field of heavy haulage technology, and in particular to a multimodal operation system for heavy haulage vehicle groups. Background Technology

[0002] In the current process of socio-economic development, the transportation of heavy-duty equipment, as a key logistics link in the industrial chain, is becoming increasingly important. The transportation of large equipment such as generators, transformers, reactors, and oil storage tanks is becoming more frequent, and the tonnage transported is increasing year by year. Despite continuous improvements in road infrastructure, the special size and weight of heavy-duty transport vehicles still present numerous challenges and problems on existing roads.

[0003] Oversized transport vehicles differ significantly from ordinary vehicles in size, wheelbase, and weight, and their load capacity differs considerably from the standard loads specified in regulations. When these vehicles travel on roads, especially through sharp bends, steep slopes, and special sections such as bridges, culverts, and tunnels, it is usually necessary to analyze and predict their passability in advance to ensure driving safety. In the transportation of oversized items to wind farms in mountainous areas, technicians typically carry testing equipment to measure road data on-site and analyze and calculate the space required for vehicle travel based on this data. However, this method is extremely inefficient. In addition, the complex terrain of mountainous areas, with numerous mountains and hills and winding roads, makes manual on-site measurement not only costly in terms of manpower, resources, and time, but also relies heavily on human experience to determine road modification plans and estimate modification costs, significantly reducing accuracy and reference value, leading to frequent accidents during the transportation of oversized items. Therefore, there is an urgent need to study the operating system of oversized transport vehicles. Utility Model Content

[0004] The purpose of this invention is to provide a multimodal operation system for heavy-duty transport vehicles to solve the problems existing in the prior art. To achieve the above-mentioned objective, the technical solution adopted by this invention is as follows:

[0005] A multimodal operation system for heavy-duty transport vehicles includes a road perception subsystem, an on-board monitoring subsystem, an on-board intelligent terminal, a cloud monitoring platform, and a cross-departmental communication subsystem;

[0006] The road perception subsystem includes a distributed array of sensor units and a local data acquisition module. The sensor units are connected to the local data acquisition module via signal, and the local data acquisition module integrates a communication module and communicates wirelessly with the cloud monitoring platform.

[0007] The vehicle-mounted monitoring subsystem includes a vehicle parameter acquisition unit, an operating status sensing unit, a cargo safety sensing unit, and a vehicle-mounted environment sensing unit. Each unit is connected to the vehicle-mounted intelligent terminal via signal.

[0008] The vehicle-mounted intelligent terminal includes an integrated vehicle-mounted communication module, which communicates bidirectionally with the cloud-based monitoring platform.

[0009] The cloud-based monitoring platform interacts with the national road information network and traffic management department systems through a cross-departmental communication subsystem.

[0010] Furthermore, the sensor unit groups are distributed according to road type;

[0011] Including geometric parameter sensing components: Several sets are set at intervals at sharp bends, bridge and culvert entrances, and both ends of tunnels. Each set includes two laser ranging sensors symmetrically installed on both sides of the road. For continuous curved road sections, gyroscope sensors are added and installed in pre-embedded boxes below the road centerline.

[0012] Road surface condition sensing components: Several road surface smoothness sensors are installed at intervals on steep slopes, long downhill slopes and easily damaged road sections, and temperature and humidity sensors are installed on roadside poles in areas prone to rain and snow.

[0013] Structural stress sensing components: Dynamic weighing sensors are installed underground at the bridge deck entrance;

[0014] The local data acquisition module is connected to all sensors, and the local data acquisition module is connected to the communication module; the communication module communicates bidirectionally with the cloud monitoring platform.

[0015] Furthermore, the vehicle parameter acquisition unit includes:

[0016] The front wheel steering angle sensor is fixed to the vehicle steering knuckle arm via a flange.

[0017] The wheelbase acquisition module is integrated into the vehicle-mounted intelligent terminal.

[0018] The operating status sensing unit includes:

[0019] Axle load sensors are installed at the bearing housings at both ends of each axle;

[0020] The vehicle body tilt sensor is mounted on the chassis beam;

[0021] The cargo safety sensing unit includes:

[0022] Dual-axis tilt sensors are symmetrically mounted at the center of gravity of the cargo via a magnetic base.

[0023] Rope tension sensor, connected to the tensioner of the cargo securing rope;

[0024] Cargo temperature sensor, installed inside the cargo packaging;

[0025] The vehicle-mounted environment sensing unit includes:

[0026] The vehicle-mounted millimeter-wave radar is installed in the center of the vehicle's front bumper.

[0027] A high-definition camera is installed below the rearview mirror in the driver's cab.

[0028] Furthermore, the human-machine interaction module includes a touch screen installed on the right side of the dashboard in the driver's cab and an audible and visual alarm installed on the top of the driver's cab.

[0029] The vehicle interface module is connected to each sensor of the vehicle monitoring subsystem and the vehicle ECU signal respectively;

[0030] The vehicle-mounted intelligent terminal is fixed to the passenger side of the driver's cab using a shock-absorbing bracket.

[0031] Furthermore, the cloud monitoring platform includes a data storage server, a computing server, and a monitoring terminal;

[0032] The data storage server includes an integrated road infrastructure database, vehicle information database, and route planning database.

[0033] Furthermore, the cross-departmental communication subsystem includes a communication interface module and a traffic management communication terminal;

[0034] The traffic management communication terminal achieves two-way data interaction with the cloud monitoring platform through the communication interface module;

[0035] The communication interface module includes a gigabit Ethernet interface for connecting to the national road information network, a dedicated VPN interface for connecting to the traffic management department's system, a traffic light control interface, and an emergency early warning module.

[0036] Furthermore, the communication path between the road perception subsystem and the cloud monitoring platform is as follows: sensor unit group → local data acquisition module → communication module → TCP / IP protocol → data storage server of the cloud monitoring platform;

[0037] The vehicle-mounted intelligent terminal also integrates a main control module, a storage module, a human-machine interaction module, and a vehicle interface module;

[0038] The vehicle monitoring subsystem is connected to the vehicle intelligent terminal by means of electrical signals from each sensing unit and the high-definition camera to the vehicle interface module.

[0039] This utility model has the following beneficial effects:

[0040] The structure is rigorous and reliable: the vehicle-mounted monitoring subsystem deploys sensors according to the categories of "vehicle-cargo-environment" to achieve full-dimensional monitoring.

[0041] Highly efficient and coordinated: The system constructs a four-level communication structure of "road-vehicle-cloud-traffic management", enabling multi-mode communication and significantly improving the efficiency of traffic coordination in special road sections, thus enabling emergency communication in areas without network coverage.

[0042] Easy installation and maintenance: Standardized interfaces for each system, anti-vibration brackets for the vehicle-mounted intelligent terminal, and solar power for the road perception subsystem, adaptable to different road conditions and vehicle types, reducing subsequent maintenance costs.

[0043] Wide range of applications: It can be adapted to different transport vehicles and is compatible with different transportation scenarios such as mountainous areas, plains, and urban roads, thus solving the problem of narrow applicability of existing systems. Attached Figure Description

[0044] Figure 1 This is a schematic diagram of the process structure of this utility model. Detailed Implementation

[0045] The technical solutions of the present invention will be clearly and completely described below with reference to the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Unless otherwise specified, the technical means used in the embodiments are conventional means well known to those skilled in the art.

[0046] In the description of this utility model, it should be understood that the terms "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this utility model and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this utility model.

[0047] like Figure 1 As shown, a multimodal operation system for heavy-duty transport vehicles includes a road perception subsystem, an on-board monitoring subsystem, an on-board intelligent terminal, a cloud monitoring platform, and a cross-departmental communication subsystem. Each subsystem achieves signal linkage through standardized hardware interfaces and communication protocols. The specific structure is as follows:

[0048] (I) Road Perception Subsystem

[0049] The road perception subsystem is used to collect basic road data in real time, including:

[0050] Sensor unit group: At key locations such as sharp bends, bridge and culvert entrances, and both ends of tunnels, at least one set of laser ranging sensors should be installed. Each set should contain two laser ranging sensors (model: HLG-150), symmetrically installed on both sides of the road. The sensors should collect data such as road width and curve radius of curvature using the laser ranging principle. For continuous curved road sections, gyroscope sensors (model: MPU-6050) should be added and installed in a pre-embedded box below the road centerline to assist in calculating the curve center angle and improve the accuracy of turning radius calculation.

[0051] Road surface condition sensing components: On steep slopes, long downhill slopes and easily damaged road sections, multiple road surface smoothness sensors (model: LDV-300) are installed to collect the road surface unevenness and degree of damage; in areas with frequent rain and snow, temperature and humidity sensors (model: DHT22) are added and installed on roadside poles to collect ambient temperature and humidity.

[0052] Structural stress sensing components: Install one dynamic weighing sensor (model: QS-200) at key load-bearing locations such as the bottom of the bridge and the sidewall of the tunnel. The sensor is located underground at the entrance of the bridge deck and is used to detect the load when vehicles pass through.

[0053] Local data acquisition module: One data acquisition unit (model can be: STM32F407) is deployed at each point, which is connected to the sensor through RS485 interface and integrates a 4G / 5G communication module (model can be: EC20) to upload the collected data to the cloud monitoring platform.

[0054] Power supply module: It adopts a combination structure of solar panels and lithium batteries, which is suitable for road sections without power supply.

[0055] (II) Vehicle-mounted monitoring subsystem

[0056] The vehicle-mounted monitoring subsystem is used to collect vehicle parameters, operating status, cargo safety status, and road environment data, including:

[0057] Vehicle parameter acquisition unit:

[0058] Front wheel steering angle sensor (model can be: WDD35D4): fixed to the vehicle steering knuckle arm via a flange to collect steering angle data;

[0059] Wheelbase acquisition module: Integrated into the vehicle's intelligent terminal, it directly reads inherent information such as vehicle speed and engine parameters from the vehicle's ECU.

[0060] Operating status sensing unit:

[0061] Axle load sensor (model can be: YZC-320): installed at the bearing housing at both ends of each axle;

[0062] Vehicle tilt sensor (model: BWT901CL): mounted on the chassis beam, used to monitor the roll and pitch angles of the vehicle while it is in motion.

[0063] Cargo safety sensing unit:

[0064] Dual-axis tilt sensor (model can be: SCA60C): It is fixed to the center of gravity of the cargo via a magnetic base to collect the tilt angle of the cargo;

[0065] Rope tension sensor (model can be: TQ-100): connected to the tensioner of the cargo fixing rope, with the warning threshold set to 80%-120% of the design tension to prevent the rope from slack or breakage;

[0066] Cargo temperature sensor (model can be: PT100): installed inside the cargo packaging to collect cargo temperature.

[0067] Vehicle-mounted environmental sensing unit:

[0068] Vehicle-mounted millimeter-wave radar (model may be: LRB100): installed in the center of the front bumper of the vehicle to collect the position of road obstacles and lane lines ahead;

[0069] High-definition camera (model may be: IMX307): installed below the rearview mirror in the driver's cab to capture real-time road conditions.

[0070] (III) Vehicle-mounted intelligent terminal

[0071] The in-vehicle intelligent terminal is the core of in-vehicle data processing and interaction, including:

[0072] Hardware components:

[0073] Main control module: STM32H743 microcontroller can be used;

[0074] Vehicle-mounted communication module: integrates a 4G / 5G module and a Beidou positioning module as the main link, and integrates a Beidou short message module as an emergency backup link;

[0075] Storage module: Built-in eMMC storage chip for storing locally collected data and route information sent from the cloud;

[0076] Human-machine interaction module: including a touch screen installed on the right side of the instrument panel in the cab and an audible and visual alarm installed on the top of the cab;

[0077] Vehicle interface module: Includes RS485, CAN and other interfaces, which connect to the signals of various sensors in the vehicle monitoring subsystem and the vehicle ECU.

[0078] Installation structure: It is fixed to the co-driver's position in the cab by a shock-absorbing bracket.

[0079] (iv) Cloud monitoring platform

[0080] The cloud-based monitoring platform serves as the core for data storage, computation, and decision-making, including:

[0081] Data storage server: Equipped with a MySQL database, divided into a road infrastructure database (including map data), a vehicle information database, and a route planning database;

[0082] Calculation server: used for route matching and data comparison analysis. Based on the vehicle's inherent parameters (such as wheelbase and steering angle) and real-time data, it calculates the minimum turning radius and compares it with map data.

[0083] Monitoring terminals include PCs and mobile apps for administrators.

[0084] (V) Cross-departmental communication subsystem

[0085] Software and interface modules for enabling external collaboration:

[0086] Communication interface module:

[0087] National Road Information Network Interface: A gigabit Ethernet interface that connects to the National Road Information Network to obtain real-time traffic conditions via API;

[0088] Traffic Management Dedicated VPN Interface: A dedicated VPN interface that interfaces with the traffic management department's system, reporting traffic plans, vehicle locations, and early warning information via standard data protocols (such as JSON);

[0089] Traffic light control interface: Supports sending control requests to the traffic management department's traffic light control system, including information such as the estimated time for vehicles to pass and the required green light duration;

[0090] Emergency warning module (BeiDou short message module): In areas without 4G / 5G network, it sends emergency assistance signals to traffic management departments via BeiDou satellite.

[0091] Traffic management communication terminal: refers to the receiving system of the traffic management department, which realizes two-way data interaction with the cloud monitoring platform.

[0092] (vi) Inter-module linkage relationship

[0093] Data upload route:

[0094] Road perception subsystem: Sensing unit group → Local data acquisition module → Communication module → Data storage server of cloud monitoring platform;

[0095] Vehicle monitoring subsystem: Each sensing unit → Vehicle interface module of vehicle intelligent terminal → Main control module → Computing server of cloud monitoring platform.

[0096] Command issuance route:

[0097] Cloud-based monitoring platform: computing server → route planning results / emergency commands → vehicle-mounted intelligent terminal → display screen / audio-visual alarm (driver);

[0098] Cloud-based monitoring platform: Traffic plan / control request → cross-departmental communication subsystem → traffic management department system → traffic management communication terminal (management personnel).

[0099] Emergency response routes:

[0100] Vehicle-mounted sensor detects abnormality (cargo tilt / excessive axle load) → vehicle-mounted intelligent terminal triggers audible and visual alarm → synchronous upload to cloud → cross-departmental communication subsystem (VPN / BeiDou short message) → traffic management department emergency warning → traffic management feedback instruction → cloud → vehicle-mounted intelligent terminal.

[0101] Example 1: Route Planning and Advance Deployment

[0102] S1. Users input the origin and destination of transportation, vehicle parameters (such as wheelbase L = 5.2m, maximum steering angle of the front wheels α = 30°, vehicle width b = 2.5m), and load information (80t) through the vehicle-mounted intelligent terminal or monitoring terminal;

[0103] S2. The in-vehicle intelligent terminal reads vehicle parameters via the CAN bus and uploads them to the cloud monitoring platform;

[0104] S3. The cloud computing server calculates according to the formula:

[0105] The minimum turning radius is calculated as R = L / sinα = 5.2 / sin30° = 10.4m;

[0106] Minimum road width W = R + √(R) 2 -L 2 ) + b / 2 = 20.66m;

[0107] S4. The cloud accesses the road database and compares the data collected by the sensors, such as road width, turning radius, and load-bearing capacity, to select recommended routes and two alternative routes that meet the conditions.

[0108] S5. The cloud sends the traffic plan (route details, estimated passage time, vehicle parameters) to the traffic management departments in the transit areas through the VPN interface of the cross-departmental communication subsystem. The traffic management departments review the plan and provide feedback on the deployment results.

[0109] S6. The in-vehicle intelligent terminal receives route navigation information from the cloud and displays it to the driver through a touch screen.

[0110] Example 2: Transportation Process Monitoring and Early Warning

[0111] S1. During transportation, the axle load sensors of the vehicle monitoring subsystem collect the load of each axle in real time (e.g., if the load of a certain axle reaches 95t, exceeding the 80t load threshold), and transmit it to the vehicle intelligent terminal.

[0112] S2. The vehicle-mounted intelligent terminal main control module compares the data with a preset threshold and immediately triggers an audible and visual alarm, while simultaneously uploading the abnormal data to the cloud.

[0113] S3. After receiving abnormal data, the cloud monitoring platform sends early warning information (vehicle location, abnormality type) to the nearest traffic management department through the cross-departmental communication subsystem. The traffic management department dispatches personnel to the scene to coordinate.

[0114] S4. The driver slows down according to the warning prompts, and the cloud simultaneously analyzes the surrounding road data to recommend temporary stopping points and adjustment plans to ensure transportation safety.

[0115] Example 3: Traffic Coordination at Complex Intersections

[0116] S1. When a vehicle arrives at a certain intersection (road width 22m, meeting the minimum road width requirement), the on-board intelligent terminal obtains the real-time location through the Beidou positioning module and calculates the estimated crossing time (2 minutes later) based on the vehicle speed (30km / h);

[0117] S2. The cloud-based monitoring platform sends control requests to the traffic management department's signal light control system through the cross-departmental communication subsystem;

[0118] S3. After the traffic management department approves the adjustment, it will adjust the traffic light duration at the intersection and send the execution results to the cloud.

[0119] S4. The vehicle's intelligent terminal receives a "traffic light has been adjusted" prompt, and the driver proceeds normally according to the navigation instructions to avoid traffic congestion at the intersection.

[0120] Example 4: Emergency Handling in Areas Without Network

[0121] S1. When the vehicle travels to a mountainous section of road without 4G / 5G network, the cargo tilt sensor detects that the cargo tilt angle exceeds the threshold.

[0122] S2. The vehicle-mounted intelligent terminal immediately triggers an audible and visual alarm, and at the same time sends an emergency signal (vehicle location, cargo tilt angle, no network status) to the cloud via the Beidou short message module;

[0123] S3. After receiving the signal via BeiDou short message service, the cloud forwards it to the traffic management department's emergency command center, and the traffic management department then sends the rescue signal back via satellite communication.

[0124] S4. The vehicle's intelligent terminal receives feedback instructions, and the driver follows the navigation to the temporary stop point. Transportation will continue after the potential hazard is eliminated.

[0125] The embodiments described above are merely preferred embodiments of the present utility model and are not intended to limit the scope of the present utility model. Any modifications, alterations, alterations, or substitutions made by those skilled in the art to the technical solutions of the present utility model without departing from the spirit of the present utility model shall fall within the protection scope defined by the claims of the present utility model.

Claims

1. A multi-modal operation system for heavy-duty transport vehicle groups, characterized in that: It includes a road perception subsystem, an on-board monitoring subsystem, an on-board intelligent terminal, a cloud monitoring platform, and a cross-departmental communication subsystem; The road perception subsystem includes a distributed sensor unit group and a local data acquisition module. The sensor unit group is signal-connected to the local data acquisition module, and the local data acquisition module integrates a communication module and communicates wirelessly with the cloud monitoring platform. The vehicle-mounted monitoring subsystem includes a vehicle parameter acquisition unit, an operating status sensing unit, a cargo safety sensing unit, and a vehicle-mounted environment sensing unit. Each unit is connected to the vehicle-mounted intelligent terminal via signal. The vehicle-mounted intelligent terminal includes an integrated vehicle-mounted communication module, a main control module, a storage module, a human-machine interaction module, and a vehicle-mounted interface module. The vehicle-mounted communication module communicates bidirectionally with the cloud monitoring platform. The cloud-based monitoring platform interacts with the national road information network and traffic management department systems through a cross-departmental communication subsystem.

2. The multi-modal operation system for heavy-duty transport vehicles according to claim 1, characterized in that: The sensor unit groups are distributed according to road type; Including geometric parameter sensing components: Several sets are set at intervals at sharp bends, bridge and culvert entrances, and both ends of tunnels. Each set includes two laser ranging sensors symmetrically installed on both sides of the road. For continuous curved road sections, gyroscope sensors are added and installed in pre-embedded boxes below the road centerline. Road surface condition sensing components: Several road surface smoothness sensors are installed at intervals on steep slopes, long downhill slopes and easily damaged road sections, and temperature and humidity sensors are installed on roadside poles in areas prone to rain and snow. Structural stress sensing components: Dynamic weighing sensors are installed underground at the bridge deck entrance; The local data acquisition module is connected to all sensors, and the local data acquisition module is connected to the communication module; the communication module communicates bidirectionally with the cloud monitoring platform.

3. The multi-modal operation system for heavy-duty transport vehicles according to claim 1, characterized in that: The vehicle parameter acquisition unit includes: The front wheel steering angle sensor is fixed to the vehicle steering knuckle arm via a flange. The wheelbase acquisition module is integrated into the vehicle-mounted intelligent terminal. The operating status sensing unit includes: Axle load sensors are installed at the bearing housings at both ends of each axle; The vehicle body tilt sensor is mounted on the chassis beam; The cargo safety sensing unit includes: Dual-axis tilt sensors are symmetrically mounted at the center of gravity of the cargo via magnetic bases. Rope tension sensor, connected to the tensioner of the cargo securing rope; Cargo temperature sensor, installed inside the cargo packaging; The vehicle-mounted environment sensing unit includes: The vehicle-mounted millimeter-wave radar is installed in the center of the vehicle's front bumper. A high-definition camera is installed below the rearview mirror in the driver's cab.

4. The multi-modal operation system for heavy-duty transport vehicles according to claim 1, characterized in that: The human-machine interaction module includes a touch screen installed on the right side of the dashboard in the driver's cab and an audible and visual alarm installed on the top of the driver's cab. The vehicle interface module is connected to each sensor of the vehicle monitoring subsystem and the vehicle ECU signal respectively; The vehicle-mounted intelligent terminal is fixed to the passenger side of the driver's cab using a shock-absorbing bracket.

5. The multi-modal operation system for heavy-duty transport vehicles according to claim 1, characterized in that: The cloud-based monitoring platform includes a data storage server, a computing server, and a monitoring terminal. The data storage server includes an integrated road infrastructure database, vehicle information database, and route planning database.

6. The multi-modal operation system for heavy-duty transport vehicles according to claim 1, characterized in that: The cross-departmental communication subsystem includes a communication interface module and a traffic management communication terminal; The traffic management communication terminal achieves two-way data interaction with the cloud monitoring platform through the communication interface module; The communication interface module includes a gigabit Ethernet interface for connecting to the national road information network, a dedicated VPN interface for connecting to the traffic management department's system, a traffic light control interface, and an emergency early warning module.

7. The multi-modal operation system for heavy-duty transport vehicles according to claim 3, characterized in that: The communication path between the road perception subsystem and the cloud monitoring platform is as follows: sensor unit group → local data acquisition module → communication module → TCP / IP protocol → data storage server of the cloud monitoring platform; The vehicle monitoring subsystem is connected to the vehicle intelligent terminal by means of electrical signals from each sensing unit and the high-definition camera to the vehicle interface module.

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