Method and system for monitoring and early warning driving state of urban muck transport vehicle

Abstract

The invention provides a method for monitoring and early warning the driving state of an urban muck transport vehicle. The monitoring and early warning method comprises the following steps: step 1, setting muck vehicle driving parameters and storing rules in a platform; step 2, acquiring various data of the vehicle in the monitoring process from a multi-party data source; 3, cleaning vehicle driving process data, preprocessing the data uploaded to the platform, and carrying out data aggregation, data correction and error processing; and step 4, carrying out early warning setting on the state of the slag car, sending out early warning information when an early warning condition is reached, and synchronizing the early warning information to a platform in real time. The problems of weak satellite signals, accuracy deficiency, large early warning errors and the like which are easily caused by weather or environmental factors in the monitoring process are solved, the real-time performance and accuracy of muck truck transportation monitoring and early warning are improved, and the early warning intelligence of muck truck monitoring is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of real-time early warning of vehicle driving status, and in particular to a method and system for monitoring and early warning of the driving status of a city muck transport vehicle. Background Art

[0002] With the acceleration of urbanization, muck trucks, as an indispensable part of urban construction, are increasingly frequent in their transportation activities. However, muck trucks are often the source of high-incidence traffic accidents due to their large load capacity, large size, and complex driving routes. Therefore, in the process of digital information management of cities, it is particularly important to standardize the on-road transportation behavior of muck trucks, combine artificial intelligence, mobile Internet, Internet of Things, cloud platform, big data, GIS, GPS and other advanced technical means, and establish an integrated and fully covered smart muck monitoring system through on-board intelligent devices, construction site intelligent probes, and road intelligent vehicle checkpoints. It is very helpful to improve the efficiency of abnormal reporting and handling of managers of the urban operation management service platform system (hereinafter referred to as the platform), which can greatly improve the efficiency of urban information management.

[0003] However, the existing technology for monitoring muck trucks cannot comprehensively monitor the vehicle and the driver's driving status. There are also problems such as weak satellite signals, lack of accuracy, and large warning errors caused by meteorological or environmental factors during the monitoring process. Therefore, the real-time and accuracy of monitoring and warning of muck truck transportation are insufficient. Summary of the invention

[0004] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a method and system for monitoring and warning the driving status of urban garbage trucks, so as to solve the problems raised in the above-mentioned background technology. The present invention solves the problems that traditional garbage truck monitoring cannot comprehensively monitor the vehicle and the driver's driving status, and that the satellite signal is weak, the accuracy is lacking, and the warning error is large due to meteorological or environmental factors during the monitoring process. The present invention improves the real-time and accuracy of garbage truck transportation monitoring and warning, and also ensures the intelligence of the warning of garbage truck monitoring.

[0005] In order to achieve the above object, the present invention is implemented through the following technical solution: a method for monitoring and early warning the driving state of a city muck transport vehicle, comprising the following steps:

[0006] Step 1: Set the driving parameters of the muck truck and save the rules to the platform;

[0007] Step 2: Obtain various data of the vehicle during the monitoring process from multiple data sources;

[0008] Step 3: Clean the vehicle driving process data, pre-process the data uploaded to the platform, and perform data aggregation, data correction and error processing;

[0009] Step 4: Set up early warning for the status of the dump truck. When the early warning conditions are met, send out early warning information and synchronize it to the platform in real time.

[0010] Furthermore, the step one includes the following contents: drawing a planned vehicle route through a workstation map, and storing the route data in the platform; drawing an electronic fence through a workstation map, and storing the surface data in the platform; setting the construction site location information and the disposal site location information, and setting the working hours and the prohibited entry time, and storing the surface data in the platform.

[0011] Furthermore, detailed road network data of the area is set, and the surface space data is stored in the platform, wherein the detailed road network data includes expressways, trunk roads, secondary trunk roads and branch roads.

[0012] Furthermore, the step two includes the following contents: collecting hardware data and status data of various components of the vehicle through a driving assistance system device; obtaining the driver's status in real time through the internal camera of the vehicle, and checking whether the driver has fatigue characteristics such as yawning and closing eyes; obtaining the pedestrian situation on the right side of the vehicle in real time through the right blind spot monitoring camera outside the vehicle, and checking whether there are pedestrians on the right side of the vehicle and the distance from the vehicle reaches a certain threshold; obtaining the driving time, driving distance, and real-time speed data after the vehicle is started through the on-board GPS device.

[0013] Furthermore, by monitoring the road vehicle checkpoints, the location and time information of the vehicle passing the checkpoints can be obtained. Through license plate recognition and vehicle feature recognition of the pictures taken by the checkpoints, the precise time and checkpoint location, checkpoint direction, checkpoint lane, etc. of the target vehicle passing the checkpoint can be obtained.

[0014] Furthermore, the step three includes the following contents: performing machine vision recognition by taking pictures captured by the construction site camera; performing machine vision recognition by taking pictures captured by the road checkpoint camera; and performing machine vision recognition by taking pictures captured by the disposal site camera.

[0015] Furthermore, the real-time position of the vehicle is obtained through the on-board GPS device. At the same time, the real-time position correction is performed based on the precise time and position obtained in the above three steps; the actual driving trajectory of the vehicle is calculated in real time based on the vehicle driving data coordinate points combined with the road network data.

[0016] A monitoring and early warning system used in the above method includes a vehicle-mounted GPS tracking module, a cloud platform, an intelligent monitoring system for road network data, a road checkpoint collection system, a vehicle-mounted terminal and an early warning module. The vehicle-mounted GPS tracking module is installed in the vehicle-mounted terminal to obtain the location information, driving time, driving distance and real-time speed data of the vehicle after it is started.

[0017] Furthermore, the monitoring and early warning system obtains the real-time trajectory of the vehicle through the on-board GPS tracking module, cooperates with the trajectory correction algorithm of the road network, the intelligent recognition technology of human and vehicle images, and the real-time calculation technology of the on-board terminal status data, accesses the intelligent interconnected equipment to build a dump truck data early warning model, and obtains the real-time status of the vehicle from the constructed model for comparison with the preset trajectory and the preset normal status threshold, so as to obtain vehicle warnings and violations.

[0018] Furthermore, the warning module is used to provide vehicle fault warning, vehicle-mounted equipment warning, vehicle cargo box or tarpaulin sealing warning, vehicle illegal lifting warning, vehicle acceleration status warning, vehicle speeding warning, vehicle blind spot pedestrian warning, vehicle appearance status warning, vehicle driver behavior warning, vehicle driver fatigue driving warning, vehicle trajectory warning, vehicle electronic fence warning, and vehicle qualification behavior warning.

[0019] Beneficial effects of the present invention:

[0020] 1. The present invention constructs a trajectory correction algorithm based on the real-time trajectory of the vehicle and the road network, an intelligent recognition technology for human and vehicle images, and a real-time calculation technology for the status data of the vehicle terminal. By accessing the intelligent interconnected device to build a data early warning model for a muck truck, the real-time status of the vehicle can be obtained from the constructed model, and then compared with the preset trajectory and the preset normal status threshold, the vehicle early warning and violation behavior can be accurately obtained, which is helpful to timely discover the early warning vehicle early warning and report it in real time.

[0021] 2. The present invention monitors the status of dump trucks through the platform, which can reduce the initial vehicle configuration of each dump truck and reduce the management cost of the dump trucks. At the same time, the platform can be applicable to dump trucks of different brands and models, and can facilitate the dump trucks to update the platform data without hardware modification, thereby completing the platform's adjustment of monitoring data processing and monitoring status processing.

[0022] 3. The present invention uses GPS vehicle-mounted terminals, RFID intelligent identification equipment, video surveillance, and smart clients on handheld terminals as carriers, uses mobile communication networks to connect to server systems, and uses technologies such as license plate recognition to extend the scope of construction waste (engineering debris) supervision from partial on-site and transportation supervision to the entire process of generation, removal, and disposal, and to provide assessment reports. It also provides information support for the collaborative cooperation of urban management, public security, transportation management, construction committees (construction management stations), environmental protection and other departments, and realizes efficient operation of evidence collection and reporting of problems, handling in accordance with the law, and joint rectification. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a structural schematic diagram of an application embodiment of the present invention;

[0024] Figure 2 The figure is a schematic diagram of the process of the application method of the present invention. DETAILED DESCRIPTION

[0025] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0026] See also Figure 1 to Figure 2 The present invention provides the following technical solution: a method for monitoring and early warning the driving status of a city muck transport vehicle, specifically comprising the following process:

[0027] 1. Set the driving parameters of the muck truck and save the rules to the platform

[0028] (1) Draw the vehicle planning route through the workstation map and store the route data in the platform.

[0029] (2) Draw the electronic fence through the workstation map and store the surface data in the platform.

[0030] (3) Set the construction site location information and the disposal site location information, set the working hours and prohibited entry times, and store the surface data in the platform.

[0031] (4) Set up detailed road network data for the area (including expressways, trunk roads, secondary trunk roads and branch roads), and store the surface spatial data in the platform.

[0032] 2. Obtain various data of the vehicle during the monitoring process from multiple data sources.

[0033] (1) Collect hardware data and status data of various vehicle components through the driving assistance system device.

[0034] (2) The driver's status is obtained in real time through the internal camera of the vehicle to check whether the driver has signs of fatigue such as yawning or closing eyes.

[0035] (3) The right blind spot monitoring camera outside the vehicle is used to obtain real-time information about pedestrians on the right side of the vehicle, and to check whether there are pedestrians on the right side of the vehicle and whether the distance from the vehicle reaches a certain threshold.

[0036] (4) Obtain the driving time, driving distance, and real-time speed data after the vehicle is started through the vehicle-mounted GPS device.

[0037] (5) By monitoring the road vehicle checkpoints, the location and time information of the vehicle passing through the checkpoints can be obtained. By recognizing the license plate and vehicle features in the pictures taken by the checkpoints, the precise time and checkpoint location, checkpoint direction, checkpoint lane, etc. of the target vehicle passing through the checkpoint can be obtained.

[0038] 3. Clean the vehicle driving process data, pre-process the data uploaded to the platform, and perform data aggregation, data correction and error processing.

[0039] (1) Use machine vision recognition to capture images captured by cameras on the construction site to determine whether the vehicle's exterior surface is clear, whether the tarpaulin is sealed, and the departure time and location.

[0040] (2) Machine vision recognition is performed by taking pictures captured by road checkpoint cameras to determine the exact coordinates of the vehicle at the exact time, and to identify and compare the vehicle appearance through the license plate number.

[0041] (3) The images captured by the cameras at the disposal site are used for machine vision recognition to determine whether the vehicle arrives on time, as well as the time and location of arrival at the destination.

[0042] (4) The real-time position of the vehicle is obtained through the on-board GPS device. At the same time, the real-time position correction is performed based on the precise time and position obtained in the above three steps. If the real-time position of the dump truck is on the road network and the planned path, the position is considered accurate; if the real-time position of the dump truck is outside the planned path, the position is estimated based on the last accurate position of the dump truck and the driving direction at that point and the time difference from now. If the error between the estimated point and the actual point is greater than 50 meters, the current real-time position is considered to be wrong and can be discarded. If the positioning calibration still has deviations or fails for 10 consecutive minutes, a hardware device warning is issued.

[0043] (5) Based on the vehicle driving data coordinate points (after correction) and combined with the road network data, the actual vehicle driving trajectory is calculated in real time.

[0044] 4. Set up early warning for the status of the dump truck, and when the early warning conditions are met, issue early warning information and synchronize it to the platform in real time.

[0045] This embodiment also provides a monitoring and early warning system, including a vehicle-mounted GPS tracking module, a cloud platform, a road network data intelligent monitoring system, a road checkpoint collection system, a vehicle-mounted terminal, and an early warning module. The vehicle-mounted GPS tracking module is installed in the vehicle-mounted terminal to obtain the location information, driving time, driving distance, and real-time speed data of the vehicle after it is started. The monitoring and early warning system obtains the real-time trajectory of the vehicle through the vehicle-mounted GPS tracking module, cooperates with the trajectory correction algorithm of the road network, the intelligent recognition technology of people and vehicles, and the real-time calculation technology of the status data of the vehicle terminal, accesses the intelligent interconnected device to build a data early warning model for the muck truck, and obtains the real-time status of the vehicle from the constructed model and compares it with the preset trajectory and the preset normal state threshold, so as to obtain vehicle early warning and violation behavior.

[0046] In this embodiment, the early warning module is used to provide vehicle fault warning, vehicle-mounted equipment warning, vehicle cargo box or tarpaulin sealing warning, vehicle illegal lifting warning, vehicle acceleration status warning, vehicle speeding warning, vehicle blind spot pedestrian warning, vehicle appearance status warning, vehicle driver behavior warning, vehicle driver fatigue driving warning, vehicle trajectory warning, vehicle electronic fence warning, and vehicle qualification behavior warning.

[0047] in:

[0048] (1) Vehicle Fault Warning: Set up warnings for vehicle faults. When the platform detects a fault or abnormality in the vehicle hardware data, it will automatically issue a warning.

[0049] (2) On-board equipment warning: The vehicle trajectory and real-time status are monitored. If the vehicle trajectory and driving status are detected to be abnormal for ten consecutive minutes, the platform will automatically issue a warning.

[0050] (3) Vehicle cargo box (tarpaulin) sealing warning: The construction waste supervision platform receives cargo box status information and video information during the vehicle's driving process. When the cargo box is not sealed under heavy load, the platform automatically issues a warning.

[0051] (4) Warning for illegal vehicle lifting: When a vehicle is lifted outside a disposal site, the platform will automatically issue a warning.

[0052] (5) Vehicle acceleration status warning: The vehicle acceleration sensor obtains the vehicle's driving acceleration. When the absolute value of the acceleration a ≥ 4.9 m / s2, the platform automatically issues a warning.

[0053] (6) Vehicle speeding warning: The construction waste supervision platform sets the vehicle speed, or the speed of a certain road section. If the actual vehicle speed exceeds the set speed for 10 seconds, the platform will automatically issue a warning.

[0054] (7) Pedestrian warning in vehicle blind spots: The construction waste supervision platform receives real-time video information from the right side of the vehicle. If a pedestrian appears on the right side of the vehicle and the distance between the pedestrian and the vehicle reaches a certain threshold, the platform automatically issues a warning.

[0055] (8) Vehicle appearance status warning: If a vehicle is found to have not been washed or has not been washed cleanly, the platform will automatically issue a warning.

[0056] (9) Vehicle driver behavior warning: through the driver's driving behavior monitoring, if the driver smokes, makes a phone call, looks away from the front or takes his hands off the steering wheel while driving, the platform will automatically issue a warning.

[0057] (10) Driver fatigue warning: The construction waste management platform can set a continuous driving time. If the vehicle is still running after the driving time is exceeded, the platform will automatically issue a warning. In addition, if the driver yawns or closes his eyes multiple times during driving, the platform will automatically issue a warning.

[0058] (11) Vehicle trajectory warning: Set up a warning for the vehicle’s real-time position. When the vehicle’s real-time position after correction deviates from the preset area or route by more than 8 meters, the platform automatically issues a warning.

[0059] (12) Vehicle electronic fence warning: Set up a warning based on the vehicle’s real-time position. When the vehicle enters or exits the fence after deviation, the platform automatically issues a warning.

[0060] (13) Vehicle qualification behavior warning: The license plate of the muck truck captured by the road vehicle checkpoint is checked against the muck truck information already entered into the system. If the muck truck is not included in the jurisdiction, the license plate and the vehicle cannot be matched, or the transportation company to which it belongs does not have transportation qualifications, the platform will automatically issue a warning.

[0061] The basic principles and main features of the present invention and the advantages of the present invention are shown and described above. For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention.

[0062] In addition, it should be understood that although the present specification is described according to implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment may also be appropriately combined to form other implementation modes that can be understood by those skilled in the art.

Claims

1. A method for monitoring and early warning the driving status of a city muck transport vehicle, characterized in that: The following steps are involved: Step 1: Set the driving parameters of the muck truck and save the rules to the platform; Step 2: Obtain various data of the vehicle during the monitoring process from multiple data sources; Step 3: Clean the vehicle driving process data, pre-process the data uploaded to the platform, and perform data aggregation, data correction and error processing; Step 4: Set up early warning for the status of the dump truck. When the early warning conditions are met, send out early warning information and synchronize it to the platform in real time.

2. A method for monitoring and warning the driving status of a city muck transport vehicle according to claim 1, characterized in that: The step 1 includes the following contents: Draw the vehicle planning route through the workstation map and store the route data in the platform; Draw the electronic fence through the workstation map and store the surface data in the platform; Set the construction site location information and disposal site location information, set the working hours and prohibited entry times, and store the surface data in the platform.

3. The method for monitoring and warning the driving status of a city muck transport vehicle according to claim 2 is characterized in that: The detailed road network data of the area is set, and the surface spatial data is stored in the platform, wherein the detailed road network data includes expressways, trunk roads, secondary trunk roads and branch roads.

4. The method for monitoring and warning the driving status of a city muck transport vehicle according to claim 1 is characterized in that: The step 2 includes the following contents: The driving assistance system collects hardware data and status data of various vehicle components; the internal camera of the vehicle obtains the driver's status in real time to check whether the driver has fatigue characteristics such as yawning and closing eyes; The right blind spot monitoring camera outside the vehicle is used to obtain real-time information about pedestrians on the right side of the vehicle, and to check whether there are pedestrians on the right side of the vehicle and whether the distance from the vehicle reaches a certain threshold; the driving time, driving distance, and real-time speed data after the vehicle is started are obtained through the on-board GPS device.

5. The method for monitoring and warning the driving status of a city muck transport vehicle according to claim 4 is characterized in that: By monitoring the road vehicle checkpoints, the location and time information of the vehicle passing the checkpoint can be obtained. Through license plate recognition and vehicle feature recognition in the pictures taken at the checkpoint, the precise time and checkpoint location, checkpoint direction, checkpoint lane, etc. of the target vehicle passing the checkpoint can be obtained.

6. The method for monitoring and warning the driving status of a city muck transport vehicle according to claim 1 is characterized in that: The step three includes the following contents: Machine vision recognition is performed through pictures captured by cameras on construction sites; machine vision recognition is performed through pictures captured by cameras at road checkpoints; machine vision recognition is performed through pictures captured by cameras at disposal sites.

7. The method for monitoring and warning the driving status of a city muck transport vehicle according to claim 6 is characterized by: The real-time position of the vehicle is obtained through the on-board GPS device. At the same time, the real-time position correction is performed based on the precise time and position obtained in the above three steps. The actual driving trajectory of the vehicle is calculated in real time based on the vehicle driving data coordinate points combined with the road network data.

8. A monitoring and early warning system used in the method of claim 1, characterized in that: It includes a vehicle-mounted GPS tracking module, a cloud platform, a road network data intelligent monitoring system, a road checkpoint collection system, a vehicle-mounted terminal and an early warning module. The vehicle-mounted GPS tracking module is installed in the vehicle-mounted terminal to obtain the location information, driving time, driving distance and real-time speed data after the vehicle is started.

9. The monitoring and early warning system according to claim 8, characterized in that: The monitoring and early warning system obtains the real-time trajectory of the vehicle through the on-board GPS tracking module, cooperates with the trajectory correction algorithm of the road network, the intelligent recognition technology of human and vehicle images, and the real-time calculation technology of the on-board terminal status data, accesses the intelligent interconnected equipment to build a dump truck data early warning model, and obtains the real-time status of the vehicle from the constructed model for comparison with the preset trajectory and the preset normal status threshold, so as to obtain vehicle warnings and violations.

10. The monitoring and early warning system according to claim 8, characterized in that: The warning module is used to provide vehicle failure warning, vehicle-mounted equipment warning, vehicle cargo box or tarpaulin sealing warning, vehicle illegal lifting warning, vehicle acceleration status warning, vehicle speeding warning, vehicle blind spot pedestrian warning, vehicle appearance status warning, vehicle driver behavior warning, vehicle driver fatigue driving warning, vehicle trajectory warning, vehicle electronic fence warning, and vehicle qualification behavior warning.

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