Hazardous chemical vehicle GPS tamper-proof anomaly detection method, system and device, medium and product

Abstract

The invention discloses a hazardous chemical vehicle GPS tamper-proof anomaly detection method, system and device, a medium and a product, and relates to the field of anomaly detection, and the method comprises the steps: obtaining an expected route, driving process data and a historical track mode of a hazardous chemical vehicle; the expected route comprises expressways along the way, portal positions, toll stations, ETC clearance sequence and time segment arrangement; the driving process data comprises GPS positioning information acquired by a vehicle terminal, oil consumption acquired by a CAN bus, engine rotating speed and brake signals, speed and acceleration information, and license plates and passing time recorded by a monitoring platform through a highway portal / ETC (Electronic Toll Collection); carrying out vehicle state fusion on the expected route, the driving process data and the historical track mode; according to a vehicle state fusion result, performing real-time analysis by adopting a rule engine and a machine learning algorithm; according to the invention, accurate identification and real-time early warning of the GPS tampering behavior of the hazardous chemical vehicle can be realized.

Description

Technical Field

[0001] The present application relates to the field of anomaly detection, and in particular to a method, system, device, medium and product for detecting anomaly of GPS tamper-proofing of hazardous chemical vehicles. Background Art

[0002] With the continuous development of economy and industry, the demand for hazardous chemicals (hereinafter referred to as "hazardous chemicals") in long-distance road transportation is increasing. However, once an accident occurs in the transportation of hazardous chemicals, it is often characterized by strong suddenness, heavy losses, and wide social impact. Recently, some trucks have evaded supervision by tampering with GPS signals. In this context, in order to prevent drivers of hazardous chemicals vehicles from tampering with GPS signals to drive illegally at night, drive while fatigued, park illegally, and other illegal operations in order to catch up with the schedule or evade supervision, it is urgent to provide a GPS anti-tampering anomaly detection method for hazardous chemicals vehicles, so as to achieve accurate identification and real-time warning of GPS tampering of hazardous chemicals vehicles. Summary of the invention

[0003] The purpose of this application is to provide a method, system, equipment, medium and product for detecting GPS tampering anomalies in hazardous chemical vehicles, which can accurately identify and provide real-time warning of GPS tampering behavior in hazardous chemical vehicles.

[0004] To achieve the above objectives, this application provides the following solutions:

[0005] In a first aspect, the present application provides a method for detecting anomalies in the GPS anti-tampering of hazardous chemicals vehicles, the method comprising:

[0006] Obtain the expected route, driving process data and historical trajectory pattern of the hazardous chemical vehicle; the expected route includes: highways, gantry positions, toll stations and ETC clearance order and time schedule along the way; the driving process data includes: GPS positioning information obtained by the vehicle terminal at a set time, fuel consumption, engine speed and brake signal, speed and acceleration information obtained by the CAN bus, and license plate and passing time recorded by the monitoring platform through the highway gantry / ETC; the historical trajectory pattern is the trajectory of vehicles with high similarity to the expected route of the hazardous chemical vehicle;

[0007] Integrate vehicle status by integrating expected route, driving process data and historical trajectory patterns;

[0008] Based on the vehicle status fusion results, the rule engine and machine learning algorithm are used for real-time analysis to obtain abnormal identification results;

[0009] Provide corresponding warnings and emergency response based on the abnormal identification results.

[0010] Optionally, the obtaining of the expected route, driving process data and historical trajectory pattern of the hazardous chemicals vehicle also includes:

[0011] When the hazardous chemicals vehicle is started, the vehicle terminal is used to perform a status self-check on the GPS and CAN bus; the status self-check includes: firmware version, verification and signal strength;

[0012] When the self-inspection result is abnormal, the vehicle terminal will be used to issue a reminder and report to the monitoring platform.

[0013] Optionally, the obtaining of the expected route, driving process data and historical trajectory pattern of the hazardous chemicals vehicle specifically includes:

[0014] Determine the expected route based on the hazardous chemicals vehicle's vehicle transport qualifications, departure and destination information.

[0015] Optionally, the vehicle state fusion of the expected route, the driving process data and the historical trajectory pattern may also include:

[0016] Generate a continuous driving trajectory based on the expected route and driving process data as well as the corresponding timestamps and vehicle identification.

[0017] Optionally, the expected route, driving process data and historical trajectory patterns are integrated into the vehicle state, specifically including:

[0018] The GPS positioning information is fused and compared with the highway gantry / ETC record information to obtain a first fusion comparison result;

[0019] The speed and acceleration information obtained by the CAN bus are fused and compared with the vehicle position change speed and acceleration reported by the GPS to obtain a second fusion comparison result;

[0020] The average travel time and speed of the road section are determined according to the historical trajectory pattern, and are fused and compared with the speed obtained by the vehicle terminal to obtain a third fusion comparison result.

[0021] Optionally, based on the vehicle status fusion results, a rule engine and a machine learning algorithm are used for real-time analysis to obtain abnormality recognition results, including:

[0022] According to the first fusion comparison result and the second fusion comparison result, a rule engine is used to determine an abnormal scene;

[0023] Based on the third fusion comparison results, a machine learning algorithm is used to predict tampering behavior.

[0024] In a second aspect, the present application provides a hazardous chemicals vehicle GPS anti-tampering anomaly detection system, the hazardous chemicals vehicle GPS anti-tampering anomaly detection system comprising:

[0025] A multi-source data acquisition module is used to acquire the expected route, driving process data and historical trajectory pattern of hazardous chemical vehicles; the expected route includes: highways, gantry positions, toll stations and ETC clearance sequences and time schedules along the way; the driving process data includes: GPS positioning information acquired by the vehicle terminal at a set time, fuel consumption, engine speed and brake signal, speed and acceleration information acquired by the CAN bus, and license plate and passing time recorded by the monitoring platform through the highway gantry / ETC; the historical trajectory pattern is the trajectory of vehicles with high similarity to the expected route of hazardous chemical vehicles;

[0026] The vehicle state fusion module is used to fuse the expected route, driving process data and historical trajectory patterns into vehicle state;

[0027] The anomaly recognition and algorithm module is used to obtain anomaly recognition results based on the vehicle status fusion results, using the rule engine and machine learning algorithm for real-time analysis;

[0028] The alarm and emergency processing module is used to perform corresponding alarm and emergency processing according to the abnormality identification results.

[0029] In a third aspect, the present application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the GPS anti-tampering anomaly detection method for hazardous chemicals vehicles.

[0030] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the GPS anti-tampering anomaly detection method for hazardous chemicals vehicles.

[0031] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the GPS anti-tampering anomaly detection method for hazardous chemicals vehicles.

[0032] According to the specific embodiments provided in this application, this application has the following technical effects:

[0033] The present application provides a method, system, device, medium and product for detecting anomalies in the GPS tamper-proofing of hazardous chemical vehicles. First, multi-source data is obtained, such as the expected route, driving process data and historical trajectory pattern of the hazardous chemical vehicle; secondly, the multi-source data is fused; finally, based on the vehicle status fusion result, a rule engine and a machine learning algorithm are used for real-time analysis to obtain anomaly recognition results; that is, the present application uses different data sources such as gantries, videos, and vehicle sensors to form a closed-loop verification, and through multi-source fusion of the vehicle's positioning information, operating status data, and external monitoring data, a combination of rule detection and machine learning algorithms is used to capture suspicious behaviors, which can achieve accurate identification and real-time early warning of GPS tampering behaviors of hazardous chemical vehicles; and after suspicious behaviors are discovered, an alarm is triggered and emergency processing is performed, thereby achieving efficient supervision and safety protection of hazardous chemical vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 This is a flow chart of a method for detecting GPS tamper-proof anomalies in hazardous chemicals vehicles in one embodiment of the present application. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0037] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0038] In an exemplary embodiment, Figure 1 As shown, a method for detecting GPS tamper-proof anomalies in hazardous chemicals vehicles is provided, the method comprising the following S101 to S104. Among them:

[0039] S101, obtain the expected route, driving process data and historical trajectory mode of the hazardous chemical vehicle; the expected route includes: the highway along the way, the gantry position, the toll station and the ETC clearance order and the time arrangement; the driving process data includes: the GPS positioning information obtained by the vehicle terminal (OBU) at the set time, and the fuel consumption, engine speed and brake signal, speed, acceleration information obtained by the CAN bus, and the license plate and passing time recorded by the monitoring platform through the highway gantry / ETC; the historical trajectory mode is the trajectory of the vehicle with high similarity to the expected route of the hazardous chemical vehicle, that is, the similar vehicle model, similar cargo weight or the vehicle's own previous trajectory is retrieved from the historical database, and the average travel time and speed of each section are analyzed; the setting time range is 20 seconds to 30 seconds; wherein, the GPS positioning information can be other positioning information other than the GPS positioning system, such as the Beidou positioning system, the Galileo satellite navigation system, etc. This application is not limited to hazardous chemical vehicles, but can also be applied to vehicles such as buses and special trucks that require anti-tampering anomaly detection of positioning signals.

[0040] After obtaining multi-source data such as the expected route, driving process data, and historical trajectory patterns of hazardous chemical vehicles, if there are obvious contradictions or mismatches in time and space, it is preliminarily judged that there is an abnormality in the vehicle position, which provides an important basis for subsequent anomaly detection.

[0041] To prevent vehicles from being put on the road when safety hazards have not been eliminated, S101 and S101 also include:

[0042] S11, when the hazardous chemicals vehicle is started, the vehicle terminal is used to perform a status self-check on the GPS and CAN bus; the status self-check includes: firmware version, verification and signal strength;

[0043] S12, when the self-test result is abnormal, the vehicle terminal is used to give a reminder and report to the monitoring platform.

[0044] S101 specifically includes:

[0045] Determine the expected route based on the hazardous chemicals vehicle's transportation qualifications, departure and destination information. The vehicle terminal performs real-time comparison and abnormality monitoring based on the expected route;

[0046] S102, integrating the expected route, driving process data and historical trajectory patterns into vehicle status;

[0047] Before S102, it also included:

[0048] Store the expected routes, driving process data and historical trajectory patterns of all hazardous chemical vehicles in a real-time database or cache queue;

[0049] A continuous driving trajectory is generated based on the expected route and driving process data as well as the corresponding timestamps and vehicle identification, which facilitates subsequent multi-source data fusion and comparative analysis.

[0050] S103, based on the vehicle status fusion results, a rule engine and machine learning algorithm are used for real-time analysis to obtain abnormal identification results; if the vehicle's speed or fuel consumption does not match the positioning information, or the vehicle's dynamic characteristics (such as speed, acceleration, brake signal, fuel consumption, engine speed, etc.) are seriously deviated from the reported GPS trajectory, it can be determined that there is a suspicion of tampering, providing data support for subsequent alarms.

[0051] S103 specifically includes:

[0052] S31, fuse and compare the GPS positioning information with the highway gantry / ETC record information to obtain a first fusion comparison result; determine whether the driving of the corresponding road section is completed within a reasonable time interval based on the first fusion comparison result. If there is an obvious conflict between the GPS positioning position and the gantry record within the specified time window (such as the time is too short but the distance is too long), mark the data as a time-space anomaly.

[0053] S32, fuse and compare the speed and acceleration information obtained from the CAN bus with the vehicle position change speed and acceleration reported by the GPS to obtain a second fusion comparison result; obtain the speed difference and acceleration deviation between the two based on the second fusion comparison result; if the speed difference and acceleration deviation between the two have a large deviation for a long time (such as the GPS shows 10km / h, but the CAN speed remains at 60km / h), it is determined that there is a serious abnormality or suspicion of tampering.

[0054] S33, determine the average travel time and speed of the road section based on the historical trajectory pattern, and compare them with the speed obtained by the vehicle terminal to obtain the third fusion comparison result. If the current travel speed or time is too different from the historical average, and there is no reasonable reason such as congestion, accident, climate impact, etc., further submit it to the anomaly detection module for in-depth analysis.

[0055] S104: Perform corresponding warning and emergency processing according to the abnormality identification result.

[0056] S104 specifically includes:

[0057] According to the first fusion comparison result and the second fusion comparison result, the rule engine (such as "position instantaneous shift", "speed fuel consumption contradiction", "gantry time and space conflict", etc.) is used to determine the abnormal scene (such as position instantaneous shift, speed and gantry record contradiction);

[0058] Based on the third fusion comparison results, a machine learning algorithm (such as LSTM) is used to predict tampering behavior. If the deviation between the actual observed value and the model predicted value exceeds the set threshold, the system determines that there may be tampering or data anomaly and issues a warning.

[0059] When an abnormality is detected, the alarm information will be pushed to the monitoring platform and relevant law enforcement or emergency departments as soon as possible, and the location and driving trajectory of the suspicious vehicle will be highlighted on the map or system interface. With the help of the multi-party collaborative linkage mechanism, highway traffic police or other law enforcement personnel can conduct on-site inspections of vehicles at nearby toll stations, service areas, etc. If the GPS is found to be tampered with or there are other violations, they will be dealt with in accordance with the law and recorded for evidence.

[0060] After receiving the alarm, the operator of the monitoring center will quickly contact the highway traffic police or the corresponding law enforcement department, and suggest intercepting the suspicious vehicle at the nearest toll station or service area. Check on-site whether the vehicle's GPS module has been dismantled, blocked or modified. If it is true, it will be severely punished and the relevant responsibilities will be investigated according to law.

[0061] For the purpose of subsequent accident investigation and responsibility determination, all data records (GPS, gantry, CAN) and video screenshots of abnormal periods will be retained; if it is confirmed that the vehicle has GPS tampering or other illegal operations, the vehicle and its affiliated company will be blacklisted and synchronized with the relevant regulatory authorities to strengthen subsequent supervision and punishment.

[0062] Based on the same inventive concept, the embodiment of the present application also provides a hazardous chemicals vehicle GPS anti-tampering anomaly detection system for implementing the hazardous chemicals vehicle GPS anti-tampering anomaly detection method involved above. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more hazardous chemicals vehicle GPS anti-tampering anomaly detection system embodiments provided below can refer to the limitations of the hazardous chemicals vehicle GPS anti-tampering anomaly detection method above, and will not be repeated here.

[0063] In an exemplary embodiment, a hazardous chemicals vehicle GPS anti-tampering anomaly detection system is provided, comprising:

[0064] A multi-source data acquisition module is used to acquire the expected route, driving process data and historical trajectory pattern of hazardous chemical vehicles; the expected route includes: highways, gantry positions, toll stations and ETC clearance sequences and time schedules along the way; the driving process data includes: GPS positioning information acquired by the vehicle terminal at a set time, fuel consumption, engine speed and brake signal, speed and acceleration information acquired by the CAN bus, and license plate and passing time recorded by the monitoring platform through the highway gantry / ETC; the historical trajectory pattern is the trajectory of vehicles with high similarity to the expected route of hazardous chemical vehicles;

[0065] The vehicle state fusion module is used to fuse the expected route, driving process data and historical trajectory patterns into vehicle state;

[0066] The anomaly recognition and algorithm module is used to obtain anomaly recognition results based on the vehicle status fusion results, using the rule engine and machine learning algorithm for real-time analysis;

[0067] The alarm and emergency processing module is used to perform corresponding alarm and emergency processing according to the abnormality identification results.

[0068] In an exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O for short) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for detecting anomalies of GPS anti-tampering of hazardous chemical vehicles is implemented.

[0069] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0070] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0071] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0072] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0073] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0074] In this application, all actions to obtain signals, information or data are carried out in compliance with the relevant data protection laws and policies of the country where they are located and with the authorization given by the owner of the corresponding device.

[0075] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0076] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for detecting GPS tamper-proof anomalies in hazardous chemicals vehicles, characterized in that: The method for detecting GPS tamper-proof anomalies in hazardous chemicals vehicles includes: Obtain the expected route, driving process data and historical trajectory pattern of the hazardous chemical vehicle; the expected route includes: highways, gantry positions, toll booths and ETC clearance order and time schedule along the way; the driving process data includes: GPS positioning information obtained by the vehicle terminal at a set time, fuel consumption, engine speed and brake signal, speed and acceleration information obtained by the CAN bus, and license plate and passing time recorded by the monitoring platform through the highway gantry / ETC; the historical trajectory pattern is the trajectory of vehicles with high similarity to the expected route of the hazardous chemical vehicle; Integrate vehicle status by integrating expected route, driving process data and historical trajectory patterns; Based on the vehicle status fusion results, the rule engine and machine learning algorithm are used for real-time analysis to obtain abnormal identification results; Provide corresponding warnings and emergency response based on the abnormal identification results.

2. The method for detecting GPS tamper-proof anomalies of hazardous chemicals vehicles according to claim 1, characterized in that: The acquisition of the expected route, driving process data and historical trajectory pattern of the hazardous chemicals vehicle also includes: When the hazardous chemicals vehicle is started, the vehicle terminal is used to perform a status self-check on the GPS and CAN bus; the status self-check includes: firmware version, verification and signal strength; When the self-inspection result is abnormal, the vehicle terminal will be used to issue a reminder and report to the monitoring platform.

3. The method for detecting GPS tamper-proof anomalies of hazardous chemicals vehicles according to claim 1, characterized in that: The acquisition of the expected route, driving process data and historical trajectory pattern of the hazardous chemicals vehicle specifically includes: Determine the expected route based on the hazardous chemicals vehicle's vehicle transport qualifications, departure and destination information.

4. The method for detecting GPS tamper-proof anomalies of hazardous chemicals vehicles according to claim 1, characterized in that: The vehicle status fusion of the expected route, the driving process data and the historical trajectory pattern also includes: Generate a continuous driving trajectory based on the expected route and driving process data as well as the corresponding timestamps and vehicle identification.

5. The method for detecting GPS tamper-proof anomalies of hazardous chemicals vehicles according to claim 1, characterized in that: The expected route, driving process data and historical trajectory patterns are integrated into the vehicle status, including: The GPS positioning information is fused and compared with the highway gantry / ETC record information to obtain a first fusion comparison result; The speed and acceleration information obtained by the CAN bus are fused and compared with the vehicle position change speed and acceleration reported by the GPS to obtain a second fusion comparison result; The average travel time and speed of the road section are determined according to the historical trajectory pattern, and are fused and compared with the travel time and speed obtained by the vehicle terminal to obtain a third fusion comparison result.

6. The method for detecting GPS tamper-proof anomalies of hazardous chemicals vehicles according to claim 5, characterized in that: Based on the vehicle status fusion results, the rule engine and machine learning algorithm are used for real-time analysis to obtain abnormal identification results, including: According to the first fusion comparison result and the second fusion comparison result, a rule engine is used to determine an abnormal scene; Based on the third fusion comparison results, a machine learning algorithm is used to predict tampering behavior.

7. A GPS anti-tampering anomaly detection system for hazardous chemicals vehicles, characterized in that: The hazardous chemicals vehicle GPS anti-tampering anomaly detection system includes: A multi-source data acquisition module is used to acquire the expected route, driving process data and historical trajectory pattern of hazardous chemical vehicles; the expected route includes: highways, gantry positions, toll stations and ETC clearance sequences and time schedules along the way; the driving process data includes: GPS positioning information acquired by the vehicle terminal at a set time, fuel consumption, engine speed and brake signal, speed and acceleration information acquired by the CAN bus, and license plate and passing time recorded by the monitoring platform through the highway gantry / ETC; the historical trajectory pattern is the trajectory of vehicles with high similarity to the expected route of hazardous chemical vehicles; The vehicle state fusion module is used to fuse the expected route, driving process data and historical trajectory patterns into vehicle state; The anomaly recognition and algorithm module is used to obtain anomaly recognition results based on the vehicle status fusion results, using the rule engine and machine learning algorithm for real-time analysis; The alarm and emergency processing module is used to perform corresponding alarm and emergency processing according to the abnormality identification results.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the GPS anti-tampering anomaly detection method for hazardous chemicals vehicles according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the hazardous chemicals vehicle GPS anti-tampering anomaly detection method described in any one of claims 1-6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the hazardous chemicals vehicle GPS anti-tampering anomaly detection method described in any one of claims 1-6 is implemented.

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