Truck overrun and overload governance big data analysis system
By using the big data analysis system for managing overloaded trucks, the system comprehensively analyzes weighing data and travel route data, solving the problems of misjudgment and missed judgment in the detection of overloaded trucks, achieving more fair and efficient law enforcement, and forming a governance network with cross-departmental data sharing.
Patent Information
- Application Number
- CN202511315920.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-16
- Publication Date
- 2026-02-06
AI Technical Summary
In existing technologies, there are problems of misjudgment and missed judgment in the detection of overloaded trucks, especially in unattended open scenarios. Dynamic weighing results are easily affected by driving conditions, leading to wrongful penalties and unfair law enforcement.
Design a big data analysis system for the management of overloaded trucks. Through data acquisition and transmission devices and a system platform, comprehensively analyze the truck's weighing data, driving route data, and dynamic weighbridge status data, and conduct multi-dimensional verification, including the compliance of the weighing data, abnormal driving behavior, and metering performance, to achieve cross-departmental data sharing and collaborative management.
This effectively reduces misjudgments and omissions caused by technical malfunctions or human error, ensures the impartiality of law enforcement, improves the accuracy of detection and the efficiency of data sharing, and forms a more comprehensive and accurate network for the management of overloaded trucks.
Smart Images
Figure CN121483048A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of overload and oversize vehicle control technology, specifically to a big data analysis system for overload and oversize vehicle control. Background Technology
[0002] Overloading and exceeding weight limits for freight vehicles refers to the management and punishment of behaviors that exceed nationally stipulated size, weight, and other restrictions during transportation, in order to ensure road traffic safety and the integrity of highway facilities. Specifically, exceeding the size limit means that the external dimensions of the vehicle and cargo, axle load, and total mass of the freight vehicle exceed the national standards or the load, height, width, and length limits indicated by highway traffic signs; overloading means that the freight vehicle is carrying cargo exceeding its approved load capacity.
[0003] Illegal overloading and exceeding weight limits are known as the number one killer on highways. First, they severely damage the structural safety of highways and bridges, directly endangering personal and property safety. Second, they seriously disrupt the transportation market order, creating a vicious cycle of disorderly competition such as low-price transportation. Third, they severely shorten the service life of highway infrastructure, wasting a large amount of national construction and maintenance funds. Fourth, vehicles are in a state of overload for a long time, reducing the safety performance of the vehicle braking system and making them prone to accidents such as tire blowouts and brake failures, causing road traffic accidents and posing a serious threat to traffic safety.
[0004] Common checkpoints for managing overloaded vehicles include highway toll stations, local road overload control stations, and non-site enforcement systems. These systems primarily involve installing dynamic weighbridges at these checkpoints for weighing and detection. Transportation law enforcement agencies can then review and retrieve relevant materials such as weighing data, photos, and video surveillance footage from highway toll stations, which, once confirmed, can be used as the basis for administrative penalties.
[0005] Since most of the aforementioned detection methods rely on dynamic weighing, inaccurate weighing results can occur due to equipment malfunctions. This is especially true at off-site enforcement stations for overload control, which operate in unattended, open environments where weighing results are significantly affected by traffic conditions. Inaccurate weighing results can lead to incorrect penalties and measurement disputes. To better manage overloaded trucks, drivers and passengers can provide weighing evidence from these stations. Verification by enforcement personnel can exempt them from penalties. However, currently, there are no dedicated service windows for this purpose, requiring drivers and passengers to travel to highway toll stations and enforcement agencies to collect evidence, increasing the burden on relevant personnel. Summary of the Invention
[0006] To address the aforementioned problems, this invention provides a big data analysis system for the management of overloaded and oversized trucks. This invention is achieved through the following technical solutions.
[0007] A big data analysis system for managing overloaded and oversized trucks includes:
[0008] The data acquisition and transmission device is installed at the front end of the dynamic truck scale to collect the status data of the dynamic truck scale and the weighing data of the trucks.
[0009] The system platform, which is wirelessly connected to the data acquisition and transmission device via a network, is used to receive data collected by the data acquisition and transmission device. The system platform is also used to receive weighing data from other weighing stations along the truck's route, and when it detects illegal overloading of trucks, it performs the following operations:
[0010] Obtain the weighing data of the truck along the driving path of the dynamic truck scale. If the weighing data meets the requirements, the truck will be exempt from punishment.
[0011] If the weighing data and passage time do not meet the requirements, the system will analyze whether there is any abnormal driving behavior when the truck is driving. If there is abnormal driving behavior, the truck will be exempt from punishment.
[0012] If abnormal driving behavior is found, the measurement performance of the dynamic truck scale will be evaluated. If the measurement performance evaluation level is average or poor, no penalty will be imposed.
[0013] If the metrological performance evaluation level is excellent or good, the absolute error value of the truck's weighing data on the dynamic truck scale will be compared with the weighing data of other weighing stations along its driving route. If the absolute error value exceeds the threshold, no penalty will be imposed; if the absolute error value does not exceed the threshold, the truck will be penalized according to the regulations on overloading.
[0014] As a further aspect of the present invention, the status data of the dynamic truck scale includes instrument communication status data and sensor channel code status data; the weighing data includes, but is not limited to, the time, speed, acceleration, axle load, and wheelbase of the truck passing through the dynamic truck scale.
[0015] As a further aspect of the present invention, other weighing stations include, but are not limited to, highway toll stations, local road overload stations, and non-site enforcement stations for overload control.
[0016] As a further aspect of the present invention, the abnormal driving behavior includes, but is not limited to, driving on S-curves, driving over weighbridges, and driving over lane lines.
[0017] As a further aspect of the present invention, when evaluating the metrological performance of a dynamic truck scale, the following operations are performed:
[0018] Search for trucks weighed via this dynamic truck scale, as well as those with weighing data from other weighing stations.
[0019] Filter the search results for trucks with the same model and speed range;
[0020] Error analysis is performed on the dynamic truck scale weighing data of the selected trucks and the weighing data of other weighing stations to determine the number of trucks that meet the error, and the proportion of the number of trucks that meet the error relative to the total number of selected trucks is calculated and denoted as the error compliance ratio.
[0021] The metrological performance of dynamic truck scales is classified into levels based on the proportion of compliance error.
[0022] As a further aspect of the present invention, the grade of metrological performance is determined in the following manner:
[0023] If the error rate is ≥95%, the evaluation level is excellent.
[0024] If the compliance error rate is between 80% and 95%, the evaluation level is good.
[0025] If the compliance error rate is between 60% and 80%, the evaluation level is average.
[0026] If the error rate is less than 60%, the evaluation level is poor.
[0027] As a further aspect of the present invention, the threshold value of the absolute error is 5%.
[0028] The beneficial effects of this invention are as follows:
[0029] 1. When the system detects that a truck is overloaded, it will conduct multi-dimensional verification, including checking whether the weighing data meets the regulations, whether the truck has abnormal driving behavior, and evaluating the metrological performance of the dynamic truck scale. This comprehensive judgment mechanism effectively reduces misjudgments and omissions caused by technical failures or human operation, and ensures the impartiality of law enforcement.
[0030] 2. The system platform can receive and integrate data from different weighing stations, including highway toll stations, local road overload stations, and non-site enforcement stations for overload control, realizing data sharing and collaborative governance. This cross-departmental and cross-regional data integration helps to form a more comprehensive and accurate network for the governance of overloaded trucks. Attached Figure Description
[0031] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description of the specific embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0032] Figure 1 A connection diagram of a big data analysis system for managing overloaded and oversized trucks;
[0033] Figure 2A flowchart illustrating the process of determining overloading in a big data analysis system for managing overloaded trucks. Detailed Implementation
[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0035] A big data analysis system for managing overloaded and oversized trucks includes:
[0036] The data acquisition and transmission device, installed at the front end of the dynamic truck scale, is used to collect the status data of the dynamic truck scale and the weighing data of the trucks.
[0037] The status data of the dynamic truck scale includes instrument communication status data and sensor channel code status data; the weighing data includes, but is not limited to, the time, speed, acceleration, axle load and wheelbase of the truck passing through the dynamic truck scale.
[0038] The instrument communication status data and sensor channel code status data are used to determine whether the dynamic truck scale hardware is faulty. If a fault occurs, it indicates that the measurement result is invalid, and the system platform will promptly contact staff for repair.
[0039] The weighing data includes, but is not limited to, the time, speed, acceleration, axle load, and wheelbase of the truck as it passes through the dynamic truck scale. This data fully reflects the truck's condition during the weighing process.
[0040] The system platform, which is wirelessly connected to the data acquisition and transmission device via a network, is used to receive data collected by the data acquisition and transmission device. The system platform is also used to receive weighing data from other weighing stations along the truck's route, including but not limited to highway toll stations, local road overload stations, and non-site enforcement stations for overload control. When detecting overloaded or oversized truck violations, the system platform performs the following operations:
[0041] The system acquires the weighing data of trucks along the dynamic weighbridge's path. If the weighing data meets the requirements, the truck will be exempt from penalties.
[0042] The weighing data obtained includes the total weight of the truck, i.e., the sum of the axle loads, which is the main basis for judging whether the truck is overloaded; secondly, the wheelbase is the basis for judging whether the truck exceeds the limit; when the truck is traveling on the dynamic truck scale, the measurement results are different at different speeds, and the weighing data obtained by the truck is only accurate within the limited speed. For example, under normal circumstances, the speed limit for trucks traveling on highways is generally limited to within 100km / h.
[0043] If the weighing data and passage time do not meet the regulations, the system will analyze whether there is any abnormal driving behavior during the truck's journey. If there is abnormal driving behavior, the truck will be exempt from punishment.
[0044] Abnormal driving behaviors include, but are not limited to, driving on S-curves, driving over weighbridges, and driving over lane lines.
[0045] Abnormal driving behavior can lead to distorted weighing data and unreliable grounds for penalties, for example:
[0046] S-curve driving: The vehicle's center of gravity shifts left and right, causing uneven force on the sensor, which may briefly create a false impression of "overweight on one side"; rushing through the weighing platform: The vehicle passes through the weighing platform quickly, using inertia to reduce the actual pressure transmission, resulting in a lower weighing result; driving over the line: The wheels are not completely in the effective area of the weighing platform, and some weight is not collected.
[0047] This can avoid technical misjudgments.
[0048] Once abnormal driving behavior is detected, it can be determined that there is an attempt to evade detection.
[0049] If abnormal driving behavior is found, the measurement performance of the dynamic truck scale will be evaluated. If the measurement performance evaluation level is average or poor, no penalty will be imposed.
[0050] When evaluating the metrological performance of a dynamic truck scale, the following operations are performed:
[0051] Search for trucks weighed via this dynamic truck scale, as well as trucks with weighing data from other weighing stations.
[0052] Filter the search results for trucks with the same model and speed range.
[0053] Different vehicle models or speed ranges can affect the weighting results. For example, in this application, the search is for 80 six-axle 157 trucks with speeds between 70-80 km / h within the past week.
[0054] Error analysis is performed on the dynamic truck scale weighing data of the selected trucks and the weighing data of other weighing stations to determine the number of trucks that meet the error, and the proportion of the number of trucks that meet the error relative to the total number of selected trucks is calculated and denoted as the error compliance ratio.
[0055] The weight of these 80 trucks measured at this dynamic truck scale is A, and the weight at other weighing stations is B. The relative error is (AB) / B. The error requirement of the dynamic truck scale is determined according to its grade. For example, for a dynamic truck scale with an accuracy grade of 5, the error during use is ±5%. If the absolute value of (AB) / B does not exceed 5%, then the truck meets the error. Assuming that the number of trucks meeting the error is D, the percentage of the error meeting the error is D / 80. Determining the value of D / 80 determines the metrological performance grade of the dynamic truck scale.
[0056] The metrological performance of dynamic truck scales is classified into levels based on the proportion of compliance error.
[0057] The grade of metrological performance is determined in the following way:
[0058] If the error rate is ≥95%, the evaluation level is excellent.
[0059] If the compliance error rate is between 80% and 95%, the evaluation level is good.
[0060] If the compliance error rate is between 60% and 80%, the evaluation level is average.
[0061] If the error rate is less than 60%, the evaluation level is poor.
[0062] If the metrological performance evaluation level is excellent or good, the absolute error value of the truck's weighing data on the dynamic truck scale will be compared with the weighing data of other weighing stations along its driving route. If the absolute error value exceeds the threshold, no penalty will be imposed; if the absolute error value does not exceed the threshold, the truck will be penalized according to the regulations on overloading.
[0063] The threshold for absolute error is 5%.
[0064] Assuming the truck has five weights at other weighing stations, namely W1, W2, W3, W4, and W5, and the truck's weight at this dynamic truck scale is W, the absolute error value is calculated as follows:
[0065]
[0066] If MAE > 5%, no penalty will be imposed; if MAE ≤ 5%, penalties will be imposed in accordance with the regulations on overloading.
[0067] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention.
Claims
1. A big data analysis system for managing overloaded and oversized trucks, characterized in that, include: The data acquisition and transmission device is installed at the front end of the dynamic truck scale to collect the status data of the dynamic truck scale and the weighing data of the trucks. The system platform, which is wirelessly connected to the data acquisition and transmission device via a network, is used to receive data collected by the data acquisition and transmission device. The system platform is also used to receive weighing data from other weighing stations along the truck's route, and when it detects illegal overloading of trucks, it performs the following operations: Obtain the weighing data of the truck along the driving path of the dynamic truck scale. If the weighing data meets the requirements, the truck will be exempt from punishment. If the weighing data does not meet the requirements, the system will analyze whether there is any abnormal driving behavior while the truck is in motion. If there is abnormal driving behavior, the truck will be exempt from punishment. If abnormal driving behavior is found, the measurement performance of the dynamic truck scale will be evaluated. If the measurement performance evaluation level is average or poor, no penalty will be imposed. If the metrological performance evaluation level is excellent or good, the absolute error value of the truck's weighing data on the dynamic truck scale will be compared with the weighing data of other weighing stations along its driving route. If the absolute error value exceeds the threshold, no penalty will be imposed; if the absolute error value does not exceed the threshold, the truck will be penalized according to the regulations on overloading.
2. The big data analysis system for managing overloaded and oversized trucks according to claim 1, characterized in that, The status data of the dynamic truck scale includes instrument communication status data and sensor channel code status data; the weighing data includes, but is not limited to, the time, speed, acceleration, axle load and wheelbase of the truck passing through the dynamic truck scale.
3. The big data analysis system for managing overloaded and oversized trucks according to claim 1, characterized in that, Other weighing stations include, but are not limited to, highway toll stations, local road overload stations, and non-site enforcement stations for overload control.
4. The big data analysis system for managing overloaded and oversized trucks according to claim 1, characterized in that, The abnormal driving behaviors include, but are not limited to, driving on S-curves, driving over weighbridges, and driving over lane lines.
5. The big data analysis system for managing overloaded and oversized trucks according to claim 1, characterized in that, When evaluating the metrological performance of a dynamic truck scale, the following operations are performed: Search for trucks weighed via this dynamic truck scale, as well as those with weighing data from other weighing stations. Filter the search results for trucks with the same model and speed range; Error analysis is performed on the dynamic truck scale weighing data of the selected trucks and the weighing data of other weighing stations to determine the number of trucks that meet the error, and the proportion of the number of trucks that meet the error relative to the total number of selected trucks is calculated and denoted as the error compliance ratio. The metrological performance of dynamic truck scales is classified into levels based on the proportion of compliance error.
6. The big data analysis system for managing overloaded and oversized trucks according to claim 5, characterized in that, The grade of metrological performance is determined in the following way: If the error rate is ≥95%, the evaluation level is excellent. If the compliance error rate is between 80% and 95%, the evaluation level is good. If the compliance error rate is between 60% and 80%, the evaluation level is average. If the error rate is less than 60%, the evaluation level is poor.
7. The big data analysis system for managing overloaded and oversized trucks according to claim 1, characterized in that, The threshold for the absolute error value is 5%.