Mining truck driver state monitoring and anti-collision early warning system and working method

Abstract

The invention belongs to the field of early warning systems, and particularly relates to a mining truck driver state monitoring and anti-collision early warning system which integrates vehicle positioning and driver state monitoring, can stably operate in various complex mining area environments and adapts to severe working conditions such as dust, high temperature, vibration and illumination variation. The positioning module is fixed outside the vehicle, and the state monitoring module is arranged in the cab, so that the environment protection and information acquisition accuracy of equipment are considered, and the applicability and reliability of the system in an extreme environment are improved. According to the invention, not only is the spatial position of the vehicle monitored, but also multi-dimensional data fusion is carried out by using the processing unit in combination with information such as mental state and abnormal behavior of a driver, so that the accuracy of danger identification is improved. The method supports comparison with a preset threshold (such as distance, driver fatigue and the like), and can perform self-adaptive adjustment according to the actual situation on site, so that the false alarm rate and the missing report rate are effectively reduced.

Description

Technical Field

[0001] The present invention belongs to the field of early warning systems, and in particular relates to a mining truck driver status monitoring and anti-collision early warning system and a working method. Background Art

[0002] Among existing technical solutions, the most representative is an integrated collision avoidance system based on GPS positioning and radar detection. For example, Chinese patent CN201510123456.X, "Collision Warning Device for Mining Vehicles," utilizes a multi-sensor fusion design. The system hardware configuration includes: a ublox M8N GPS positioning module, providing ±2.5-meter positioning accuracy; a Continental ARS408 millimeter-wave radar operating at 77GHz, with a detection range of 0.2-150 meters and a horizontal field of view of ±45 degrees; and a Bosch ultrasonic sensor for rearward detection, with a detection range of 0.3-5 meters. The system's software algorithm utilizes a layered architecture: the bottom layer performs sensor data acquisition and preprocessing, the middle layer implements multi-source data fusion, and the top layer performs collision risk assessment based on a pre-set safety distance model. When the detected obstacle is closer than the dynamic braking distance, the system issues a graded warning signal via the in-cab audio and visual alarms. However, such systems have exposed obvious defects in actual mining applications: first, GPS signals are severely attenuated in mining canyon areas and dusty environments, and the positioning update frequency may drop from 10Hz to below 1Hz; second, the false alarm rate of millimeter-wave radar in high-dust environments in mining areas can reach 35%, and there are blind spots in the detection of metal obstacles; third, the fixed-parameter safety distance model used by the system cannot adapt to the changes in the braking characteristics of mining trucks under different load conditions.

[0003] Another mainstream technical solution is a standalone system focused on driver status monitoring. According to a special research report published in Mining Safety Technology, Issue 4, 2018 (author: Wang Wei, pp. 23-25), this type of system typically employs a computer vision-based monitoring solution. The hardware configuration includes a Hikvision MV-CA013-20GC industrial camera (1280×720 resolution, 30fps) coupled with an 850nm infrared fill light; and an STMicroelectronics LSM6DS3 triaxial accelerometer for head posture detection. The system's algorithm consists of four key steps: first, face detection using the AdaBoost algorithm, then locating 68 facial feature points using the ASM active shape model, calculating fatigue characteristic parameters such as PERCLOS (Percentage of Eyelid Closure Over the Pupil Time), and finally, classification using a support vector machine (SVM). Although such systems can monitor the driver's status to a certain extent, they have obvious application limitations: the system operates completely independently and lacks data interaction and coordinated control with other vehicle safety systems; under the strong direct light conditions common in mining areas, the success rate of face detection may drop from 95% to 68%; in addition, the system has poor adaptability to situations where the driver wears personal protective equipment such as sunglasses and dust masks.

[0004] Existing technologies still have several common defects: First, there is a lack of effective data fusion mechanism between subsystems, which leads to delays and misjudgments in safety warnings. For example, when the driver shows signs of fatigue, the system cannot automatically associate the vehicle's current operating status with the risks of the surrounding environment. Secondly, the system's environmental adaptability is insufficient, especially for the harsh working conditions unique to mining areas, such as high dust, strong vibration, and large changes in temperature and humidity. There is a lack of targeted optimization design. Furthermore, existing solutions generally adopt a warning mechanism with a fixed threshold, which fails to fully consider the dynamic performance changes of mining trucks under different loads, slopes, and road conditions. Finally, from the perspective of system integration, existing solutions often require the installation of multiple independent control units, which not only increases the complexity of the system, but also increases the difficulty of troubleshooting and maintenance.

[0005] It's worth noting that with the advancement of autonomous driving technology, some innovative solutions are attempting to migrate passenger car ADAS systems to mining trucks. However, this technology migration faces numerous challenges: While mining trucks operate at relatively low speeds (typically 20-40 km / h), they are heavy (30-50 tons unladen, 100-300 tons fully laden) and experience significant inertia, requiring a higher level of system response speed. The unstructured nature of mining roads renders lane-detection-based warning algorithms ineffective. Furthermore, the unique body structure and operating methods of mining trucks (such as reverse unloading) create new safety monitoring requirements. These factors make it difficult to directly apply existing passenger car safety technologies to meet the actual needs of mining trucks. Summary of the Invention

[0006] The purpose of the present invention is to overcome the significant deficiencies in environmental adaptability, data fusion, dynamic warning and integration of existing mining vehicle collision avoidance and driver monitoring systems, and to provide a mining truck driver status monitoring and collision avoidance warning system and working method.

[0007] In order to achieve the above object, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a mining truck driver status monitoring and anti-collision warning system, comprising: A positioning processing module is used to collect the three-dimensional position information of the mining truck in real time and send the collected three-dimensional position information to the processing unit; A driver status monitoring module is used to collect driver status data in real time and send the driver status data to the processing unit; The processing unit is used to compare the collected three-dimensional position information with the preset vehicle position threshold. If the vehicle position threshold is exceeded, it is determined that the mining truck exceeds the preset vehicle position, and a vehicle position alarm message is sent to the host computer; the collected driver status data is compared with the preset driver status. If the current driver status does not conform to the preset driver status, a driver status alarm message is sent to the host computer.

[0008] A further improvement of the present invention is that the positioning processing module includes: RTK high-precision positioning terminal, including Beidou RTK dual-antenna system, is used to collect three-dimensional position information of mining trucks in real time; Filter and dynamic compensator, used to filter and perform multi-level data verification on the three-dimensional position information of mining trucks; The position information synchronization and management unit is used to establish a three-dimensional environment model based on the three-dimensional position information of the mining truck processed by the filter and dynamic compensator.

[0009] A further improvement of the present invention is that the positioning processing module adopts Huace Navigation iRTK5.

[0010] A further improvement of the present invention is that the driver status monitoring module includes a dual-spectrum vision acquisition device, which is placed in the driver's cabin of the mining truck and faces the driver.

[0011] A further improvement of the present invention is that the driver status monitoring module adopts a Seeing Machines FOVIODMS camera.

[0012] A further improvement of the present invention is that the processing unit includes a memory and a comparator, the memory is used to store preset thresholds of the driver status and vehicle position, and the comparator is used to compare the collected driver status and vehicle position with the preset thresholds to generate a comparison result.

[0013] A further improvement of the present invention is that the processing unit adopts Huawei Atlas 200 DK edge computing box.

[0014] A further improvement of the present invention is that the positioning processing module is connected to the processing unit wirelessly.

[0015] A further improvement of the present invention is that the driver status monitoring module is connected to the processing unit via a CAN bus.

[0016] In a second aspect, the present invention provides a method for monitoring the driver status of a mining truck and providing an anti-collision warning, comprising the following steps: The positioning processing module collects the three-dimensional position information of the mining truck in real time and sends the collected three-dimensional position information to the processing unit; The driver status monitoring module collects driver status data in real time and sends the driver status data to the processing unit; The processing unit compares the collected three-dimensional position information with the preset vehicle position threshold. If the vehicle position threshold is exceeded, it is determined that the mining truck exceeds the preset vehicle position, and a vehicle position alarm message is sent to the host computer; the collected driver status data is compared with the preset driver status. If the current driver status does not conform to the preset driver status, a driver status alarm message is sent to the host computer.

[0017] Compared with the prior art, the present invention has the following beneficial effects: This system integrates vehicle positioning and driver status monitoring, enabling stable operation in complex mining environments and adapting to harsh conditions such as dust, high temperatures, vibration, and varying light levels. However, the positioning module is fixed to the vehicle's exterior, while the status monitoring module is located within the cockpit. This balances environmental protection and information collection accuracy, improving the system's applicability and reliability in extreme environments. This system not only monitors the vehicle's spatial position but also integrates information such as the driver's mental state and behavioral anomalies, utilizing a processing unit for multi-dimensional data fusion to enhance the accuracy of hazard identification. This system supports comparisons with preset thresholds (such as distance and driver fatigue) and can adaptively adjust based on actual site conditions, effectively reducing false alarm and missed alarm rates. The processing unit collects, analyzes, and determines the risk status of both the vehicle and the driver in real time, dynamically generating warning information to ensure timely and effective warnings. This system integrates positioning and driver monitoring, reducing data silos between systems and achieving a unified data interface and management platform. This improves overall system integration and operational efficiency. This system not only addresses external collision risks but also monitors potential safety hazards caused by driver anomalies (such as fatigue and distraction), expanding safety management coverage. In conclusion, the present invention realizes the deep integration monitoring of vehicle positioning and driver status, enhances the adaptability to harsh environments, dynamic risk warning capability and system integration, and improves the safety management level of mining areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a structural schematic diagram of the present invention. DETAILED DESCRIPTION

[0019] In order to further understand the content of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the embodiments are only for explaining the present invention and are not intended to limit it.

[0020] Example 1: See also Figure 1 , mining truck driver status monitoring and anti-collision warning system, including: A positioning processing module is used to collect the three-dimensional position information of the mining truck in real time and send the collected three-dimensional position information to the processing unit; A driver status monitoring module is used to collect driver status data in real time and send the driver status data to the processing unit; The processing unit is used to compare the collected three-dimensional position information with the preset vehicle position threshold. If the vehicle position threshold is exceeded, it is determined that the mining truck exceeds the preset vehicle position, and a vehicle position alarm message is sent to the host computer; the collected driver status data is compared with the preset driver status. If the current driver status does not conform to the preset driver status, a driver status alarm message is sent to the host computer.

[0021] Example 2: The mining truck driver status monitoring and anti-collision warning system includes a positioning processing module, a driver status monitoring module and a processing unit. The positioning processing module is fixed on the mining truck to collect the position of the mining truck. The driver status monitoring module is set inside the mining truck to collect the driver's status. The processing unit is used to obtain data from the positioning processing module and the driver status monitoring module, and compare them with preset thresholds, and output the results to the host computer.

[0022] The positioning processing module is fixedly mounted on the mining truck and is responsible for collecting, processing, and managing the vehicle's three-dimensional position information. This module transmits high-precision position information, filtered and dynamically compensated, to the processing unit via a wireless connection.

[0023] The driver status monitoring module is located inside the mining truck's cockpit, facing the driver, and collects driver status data. This module interacts with the processing unit via the CAN bus, allowing the collected data on the driver's facial, behavioral, and physiological status to be uploaded to the processing unit in real time.

[0024] The processing unit, the core of the system, communicates with the positioning processing module via wireless connections and with the driver status monitoring module via the CAN bus. Data and results are uploaded to the host computer via a wired or wireless network, and commands are also returned to the processing unit via the network, achieving closed-loop control of the system.

[0025] Preferably, the positioning processing module can use an RTK high-precision positioning terminal, a filter and dynamic compensator, and a position information synchronization and management unit. The driver status monitoring module can use a dual-spectrum visual acquisition device or a SeeingMachines FOVIO DMS camera. The processing unit can use a Huawei Atlas 200 DK edge computing box equipped with memory and a comparator.

[0026] Example 3: The method for monitoring the driver status of a mining truck and preventing collisions comprises the following steps: Step 1: The positioning processing module collects the three-dimensional position information of the mining truck in real time and sends the collected three-dimensional position information to the processing unit; Step 2: The driver status monitoring module collects driver status data in real time and sends the driver status data to the processing unit; In step three, the processing unit compares the collected three-dimensional position information with the preset vehicle position threshold. If the vehicle position threshold is exceeded, it is determined that the mining truck exceeds the preset vehicle position, and a vehicle position alarm message is sent to the host computer; the collected driver status data is compared with the preset driver status. If the current driver status does not conform to the preset driver status, a driver status alarm message is sent to the host computer.

[0027] Example 4: While the mining truck is in motion, the positioning processing module uses the Beidou RTK dual-antenna system to collect three-dimensional position information in real time. After filtering and multi-level verification, the processed data is synchronized to the processing unit via a wireless link. Simultaneously, the driver status monitoring module collects real-time driver status data (such as fatigue, attention, and abnormal behavior) and transmits it to the processing unit via the CAN bus.

[0028] All data from the positioning processing module and the driver status monitoring module is aggregated in the processing unit. Upon receiving the data, the processing unit automatically aligns timestamps and synchronizes data from different sources, integrating information related to driver status and vehicle spatial location.

[0029] The processing unit's internal memory stores threshold values for driver status and vehicle operating location. The received data is automatically compared with a comparator to determine in real time whether the current driver status and vehicle operating environment deviate from safety standards.

[0030] Example 5: If the data comparison result exceeds the preset threshold, the processing unit immediately generates an early warning signal and transmits the analysis results and alarm information to the host computer via wired or wireless means, assisting management personnel in intervention or scheduling. At the same time, all process data can be uploaded to the host computer periodically or in real time, enabling remote monitoring and historical data tracing.

[0031] Example 6: The mining truck driver status monitoring and anti-collision warning system of the present invention was deployed in an actual operating environment of an open-pit coal mine. Three mining trucks were selected as test objects, with a total of three drivers. The test lasted for five days, with continuous operation for eight hours per day.

[0032] The positioning processing module uses the Huace Navigation iRTK5 RTK dual-antenna positioning device, with a position sampling frequency of 10Hz and a positioning accuracy of ±2cm.

[0033] The driver status monitoring module uses a Seeing Machines FOVIO DMS camera. It monitors metrics including eye closure duration, gaze deviation angle, and head tilt, with a sampling frequency of 30 FPS. Abnormal conditions include: eyes closed for more than two seconds, considered fatigue; and gaze deviation greater than 30° for more than three seconds, considered inattention.

[0034] The processing unit uses Huawei's Atlas 200 DK edge computing box, which stores preset thresholds including the vehicle's allowable deviation from the path of ±1.5 m and an alarm response time of ≤500ms.

[0035] The data obtained from monitoring the mining trucks are as follows:

[0036] In this embodiment, the total monitoring operation time is 120 hours, the total number of alarms is 17, including 6 position alarms (all of which are deviations from the set route >1.5m), and 11 driver status alarms, including closing eyes and attention deviation. The system alarm accuracy rate is 94.1%, of which 16 are confirmed as real anomalies by manual review.

[0037] According to the data above, at 1:45 PM on February 10th, driver T01 became distracted after three hours of continuous driving. The system detected a 47° deviation in his gaze for 4.3 seconds, triggering a status alarm. The host computer then notified the dispatch center, which instructed the driver to rest for 30 minutes, successfully avoiding a fatigue driving accident.

[0038] The above embodiments show that the present invention ensures efficient and real-time transmission of vehicle spatial position information through the wireless connection between the positioning processing module and the processing unit, adapts to the complex and open environment of the mining area, and improves the continuity and timeliness of data acquisition. The present invention ensures high-reliability data exchange through the CAN bus connection between the driver status monitoring module and the processing unit, adapts to the standard communication protocol inside the mining vehicle, and enables changes in driver behavior and status to be captured and uploaded in a timely manner. The multi-source data aggregation and comparison mechanism of the processing unit realizes the organic linkage and dynamic management of the driver status and the vehicle operating environment, so that the early warning function is based on multi-dimensional, cross-validated data, effectively improving the accuracy and practicality of the system. Through the interconnection with the host computer, the present invention breaks through the information barriers between on-site perception, data processing and management decision-making, and provides a data foundation and decision-making support for intelligent scheduling, accident prevention and remote operation and maintenance of mining trucks.

[0039] Therefore, this invention achieves efficient integration of vehicle positioning and driver status through clear hardware connections (wireless, CAN bus, etc.) and information flow paths. The data interaction and coordination between these modules provide comprehensive, three-dimensional safety monitoring and early warning capabilities for mining trucks. This not only improves the system's environmental adaptability and integration, but also provides technical support for safe operations in actual mining areas.

[0040] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. Mining truck driver status monitoring and anti-collision warning system, characterized by: include: A positioning processing module is used to collect the three-dimensional position information of the mining truck in real time and send the collected three-dimensional position information to the processing unit; A driver status monitoring module is used to collect driver status data in real time and send the driver status data to the processing unit; The processing unit is used to compare the collected three-dimensional position information with the preset vehicle position threshold. If the vehicle position threshold is exceeded, it is determined that the mining truck exceeds the preset vehicle position, and a vehicle position alarm message is sent to the host computer; the collected driver status data is compared with the preset driver status. If the current driver status does not conform to the preset driver status, a driver status alarm message is sent to the host computer.

2. The mining truck driver status monitoring and anti-collision warning system according to claim 1 is characterized in that: The positioning processing module includes: RTK high-precision positioning terminal, including Beidou RTK dual-antenna system, is used to collect three-dimensional position information of mining trucks in real time; Filter and dynamic compensator, used to filter and perform multi-level data verification on the three-dimensional position information of mining trucks; The position information synchronization and management unit is used to establish a three-dimensional environment model based on the three-dimensional position information of the mining truck processed by the filter and dynamic compensator.

3. The mining truck driver status monitoring and anti-collision warning system according to claim 1 or 2, characterized in that: The positioning processing module uses Huace Navigation iRTK5.

4. The mining truck driver status monitoring and anti-collision warning system according to claim 1 is characterized in that: The driver status monitoring module includes a dual-spectrum vision acquisition device, which is placed in the cab of the mining truck and faces the driver.

5. The mining truck driver status monitoring and anti-collision warning system according to claim 1 or 4, characterized in that: The driver status monitoring module uses the Seeing Machines FOVIO DMS camera.

6. The mining truck driver status monitoring and anti-collision warning system according to claim 1 is characterized in that: The processing unit includes a memory and a comparator. The memory is used to store preset thresholds of the driver status and vehicle position. The comparator is used to compare the collected driver status and vehicle position with the preset thresholds to generate a comparison result.

7. The mining truck driver status monitoring and anti-collision warning system according to claim 1 or 6, characterized in that: The processing unit uses Huawei Atlas 200 DK edge computing box.

8. The mining truck driver status monitoring and anti-collision warning system according to claim 1 is characterized in that: The positioning processing module is connected to the processing unit via wireless.

9. The mining truck driver status monitoring and anti-collision warning system according to claim 1, characterized in that: The driver status monitoring module is connected to the processing unit via the CAN bus.

10. A method for monitoring the state of a mining truck driver and preventing collisions, based on the mining truck driver monitoring and preventing collisions system according to claim 1, characterized in that: The following steps are involved: The positioning processing module collects the three-dimensional position information of the mining truck in real time and sends the collected three-dimensional position information to the processing unit; The driver status monitoring module collects driver status data in real time and sends the driver status data to the processing unit; The processing unit compares the collected three-dimensional position information with the preset vehicle position threshold. If the vehicle position threshold is exceeded, it is determined that the mining truck exceeds the preset vehicle position, and a vehicle position alarm message is sent to the host computer; the collected driver status data is compared with the preset driver status. If the current driver status does not conform to the preset driver status, a driver status alarm message is sent to the host computer.

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