Taximeter anti-cheating method and device, electronic equipment and computer program product

Abstract

The invention is suitable for the technical field of traffic operation, and provides a taximeter anti-cheating method and device, electronic equipment and a computer program product. The method comprises the following steps: acquiring the time when N vehicle speed pulse signals of a first vehicle reach a taximeter of the first vehicle, wherein N is an integer greater than 2; based on the time when the N vehicle speed pulse signals reach the taximeter of the first vehicle, determining pulse intervals of adjacent vehicle speed pulse signals in the N vehicle speed pulse signals, and obtaining N-1 pulse intervals; and if the change rule of the N-1 pulse intervals is not matched with the change rule of the target pulse interval in different driving states, determining that the taximeter of the first vehicle has a mileage cheating behavior. According to the invention, the risk of mileage cheating of the taximeter can be reduced.

Description

Technical Field

[0001] The present application belongs to the field of traffic operation technology, and in particular relates to a meter anti-cheating method, device, electronic equipment and computer program product. Background Art

[0002] Currently, taxi meter fraud prevention relies primarily on methods such as raw pulse encryption, hardware-based anti-cheating, and Global Positioning System (GPS) mileage detection. However, individuals can exploit these methods to cheat by inserting fraudulent pulses into the pulse encryption source, physically breaking wires to insert pulses, or installing GPS signal blockers, thereby enabling mileage fraud. Therefore, reducing the risk of meter mileage fraud is a pressing technical issue. Summary of the Invention

[0003] The embodiments of the present application provide a meter anti-cheating method, device, electronic device and computer program product, which can reduce the risk of meter mileage cheating.

[0004] In a first aspect, an embodiment of the present application provides a method for preventing meter cheating, comprising:

[0005] Obtaining the time at which each of N vehicle speed pulse signals of the first vehicle arrives at the meter of the first vehicle, where N is an integer greater than 2;

[0006] determining pulse intervals between adjacent vehicle speed pulse signals among the N vehicle speed pulse signals based on the time when each of the N vehicle speed pulse signals arrives at the meter of the first vehicle, to obtain N-1 pulse intervals;

[0007] If the changing pattern of the N-1 pulse intervals does not match the target pulse interval changing pattern under different driving conditions, it is determined that the meter of the first vehicle has mileage cheating behavior. The target pulse interval changing pattern refers to the changing pattern of the pulse interval under the corresponding driving state and when the meter does not have mileage cheating behavior.

[0008] In an embodiment of the present application, by obtaining the time when each of the N vehicle speed pulse signals of the first vehicle arrives at the meter of the first vehicle, the pulse intervals of adjacent vehicle speed pulse signals can be determined based on the time when each of the N vehicle speed pulse signals arrives at the meter of the first vehicle, and N-1 pulse intervals are obtained. The changing pattern of the N-1 pulse intervals is matched with the target pulse interval changing pattern. Since the target pulse interval changing pattern refers to the changing pattern of the pulse interval under the corresponding driving state and when there is no mileage cheating behavior in the meter, if the changing pattern of the N-1 pulse intervals does not match the target pulse interval changing pattern under different driving states, it can be determined that there is mileage cheating in the meter of the first vehicle. On this basis, timely measures can be taken to stop and correct it, thereby reducing the risk of meter mileage cheating.

[0009] In a second aspect, an embodiment of the present application provides a meter anti-cheating device, comprising:

[0010] a time acquisition module, configured to acquire the time at which each of N vehicle speed pulse signals of the first vehicle arrives at the meter of the first vehicle, where N is an integer greater than 2;

[0011] an interval determination module, configured to determine the pulse intervals between adjacent vehicle speed pulse signals in the N vehicle speed pulse signals based on the time when each of the N vehicle speed pulse signals arrives at the meter of the first vehicle, to obtain N-1 pulse intervals;

[0012] The cheating determination module is used to determine that the meter of the first vehicle has mileage cheating if the variation pattern of the N-1 pulse intervals does not match the target pulse interval variation pattern under different driving conditions, and the target pulse interval variation pattern refers to the variation pattern of the pulse interval under the corresponding driving condition and when the meter does not have mileage cheating.

[0013] In a third aspect, an embodiment of the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the electronic device implements the meter anti-cheating method as described in any one of the first aspects above.

[0014] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a computer, the anti-cheating method for the meter as described in the first aspect above is implemented.

[0015] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program. When the computer program is run, the anti-cheating method for a taximeter as described in any one of the first aspects above is executed.

[0016] It can be understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. 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 any creative work.

[0018] Figure 1 Schematic diagram of a taximeter anti-cheating system provided in an embodiment of the present application;

[0019] Figure 2 1 is a flow chart of a method for preventing meter cheating provided by an embodiment of the present application;

[0020] Figure 3 This is a structural diagram of a taximeter provided in an embodiment of the present application;

[0021] Figure 4 is another structural diagram of the taximeter provided in an embodiment of the present application;

[0022] Figure 5 Schematic diagram of the structure of the anti-cheating device for taximeters provided in an embodiment of the present application;

[0023] Figure 6 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] In the following description, specific details such as specific system structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0025] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0026] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0027] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0028] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0029] The anti-cheating method for taximeters provided in the embodiments of the present application can be applied to electronic devices such as mobile phones, tablet computers, wearable devices, taximeters, laptop computers, ultra-mobile personal computers (UMPCs), netbooks, and personal digital assistants (PDAs). The embodiments of the present application do not impose any restrictions on the specific types of electronic devices.

[0030] For example, Figure 1 The schematic diagram of the meter anti-cheating system provided by the embodiment of the present application is shown. Figure 1 As shown, the system includes a meter 101 and at least one terminal device 102 .

[0031] The above-mentioned meter may be a meter on a vehicle providing travel services (such as a taxi).

[0032] The above-mentioned terminal devices may include display screens inside vehicles, driver's smartphones, servers equipped with vehicle management platforms, etc. The vehicle management platform is used to conduct all-round management and scheduling of vehicles providing travel services to achieve efficient, safe and orderly operation services.

[0033] The meter can determine whether it has mileage cheating based on the changing pattern of the pulse interval, and send a cheating prompt to the terminal device if mileage cheating occurs, so that passengers, drivers or vehicle supervision centers can promptly discover the vehicle's meter mileage cheating and take timely measures to stop and correct it, thereby reducing the risk of meter mileage cheating, improving the meter's measurement reliability and accuracy, solving the long-standing mileage cheating problem in taxis, reducing the losses and troubles caused to citizens by taxi mileage cheating, and improving the positive image of taxi drivers.

[0034] See also Figure 2 , Figure 2 The flowchart of the method for preventing meter cheating provided by an embodiment of the present application is shown. As an example and not a limitation, the method includes the following steps:

[0035] Step 201: Obtain the time when each of N vehicle speed pulse signals of the first vehicle arrives at the meter of the first vehicle.

[0036] Wherein, N is an integer greater than 2. On this basis, this application does not limit the specific value of N. As an example and not a limitation, N is 11.

[0037] The first vehicle may be any vehicle equipped with a meter, such as a taxi equipped with a meter that provides travel services.

[0038] To more accurately calculate the pulse interval variation pattern (i.e., the pulse interval variation pattern) of the first vehicle, the N vehicle speed pulse signals may be N consecutive vehicle speed pulse signals. Of course, it is understood that the N vehicle speed pulse signals may also be N vehicle speed pulse signals spaced by the same number of vehicle speed pulse signals, i.e., the number of vehicle speed pulse signals spaced between adjacent vehicle speed pulse signals is the same.

[0039] In one embodiment, a pulse sensor (such as a speed sensor) can be used to collect the speed pulse signal of the first vehicle in real time, and the speed pulse signal can be sent to the meter of the first vehicle in real time. After the meter receives the speed pulse signal, it records the time when the speed pulse signal is received, which is the time when the speed pulse signal reaches the meter. After the meter accumulates and counts the time when N speed pulse signals each arrive at the meter, step 202 and subsequent steps are executed to realize mileage cheating detection of the meter based on the above steps, increase the accuracy of the real-time verification of the meter mileage statistics, and increase the difficulty of mileage cheating from the source.

[0040] like Figure 3 As shown, the taximeter may include a pulse sensor, that is, the pulse sensor is integrated into the taximeter. Of course, it should be understood that the pulse sensor may not be integrated into the taximeter, and this application does not limit this.

[0041] In one possible implementation, obtaining the time when each of the N vehicle speed pulse signals of the first vehicle arrives at the meter of the first vehicle includes:

[0042] During the running of the first vehicle, the time when each of N vehicle speed pulse signals reaches the meter of the first vehicle is obtained.

[0043] Because passengers can easily detect a fraudulent pulse signal when the vehicle is not moving, meter mileage fraud typically occurs when the vehicle is in motion. Therefore, the arrival time of each of N vehicle speed pulse signals at the meter can be obtained during the vehicle's driving process. This prevents pulse fraud during driving, reducing the risk of meter mileage fraud.

[0044] Step 202 : Based on the time when each of the N vehicle speed pulse signals arrives at the meter, the pulse intervals between adjacent vehicle speed pulse signals in the N vehicle speed pulse signals are determined to obtain N-1 pulse intervals.

[0045] The pulse interval between adjacent vehicle speed pulse signals may refer to the time interval or time difference between two adjacent vehicle speed pulse signals.

[0046] As an example but not a limitation, N is 11, and the taximeter receives 11 vehicle speed pulse signals, namely A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, and A11, in sequence. Subtract the time when A2 arrives at the meter from the time when A1 arrives at the meter to get the pulse interval between A1 and A2; subtract the time when A3 arrives at the meter from the time when A2 arrives at the meter to get the pulse interval between A2 and A3; subtract the time when A4 arrives at the meter from the time when A3 arrives at the meter to get the pulse interval between A3 and A4; subtract the time when A4 arrives at the meter from the time when A5 arrives at the meter to get the pulse interval between A4 and A5; subtract the time when A6 arrives at the meter from the time when A5 arrives at the meter to get the pulse interval between A5 and A6; subtract the time when A7 arrives at the meter from the time when A8 arrives at the meter to get the pulse interval between A8 and A9; Subtract the time A6 arrives at the meter from the time A6 arrives at the meter to get the pulse interval between A6 and A7. Subtract the time A7 arrives at the meter from the time A8 arrives at the meter to get the pulse interval between A7 and A8. Subtract the time A8 arrives at the meter from the time A9 arrives at the meter to get the pulse interval between A8 and A9. Subtract the time A9 arrives at the meter from the time A10 arrives at the meter to get the pulse interval between A9 and A10. Subtract the time A10 arrives at the meter from the time A11 arrives at the meter to get the pulse interval between A10 and A11. A total of 10 pulse intervals can be obtained.

[0047] In one embodiment, after obtaining N-1 pulse intervals, a variation pattern of the N-1 pulse intervals may be determined. The variation pattern of the N-1 pulse intervals may refer to a change in the size of the N-1 pulse intervals. The variation pattern of the N-1 pulse intervals may be determined as follows:

[0048] Calculate the mean of N-1 pulse intervals;

[0049] Calculate the error between the N-1 pulse intervals and the mean;

[0050] If the errors of the N-1 pulse intervals and the mean are all within the preset error range, then the errors of the N-1 pulse intervals and the mean are all within the preset error range as the change law of the N-1 pulse intervals;

[0051] If there is a pulse interval in the N-1 pulse intervals whose error with the mean is not within a preset error range, then determine a comparison result between the first pulse interval and the second pulse interval in each group of adjacent pulse intervals to obtain N-2 comparison results, each comparison result being used to indicate a magnitude relationship between the first pulse interval and the second pulse interval, the N-1 pulse intervals corresponding to the N-2 groups of adjacent pulse intervals, the first pulse interval and the second pulse interval in each group of adjacent pulse intervals being adjacent pulse intervals in the N-1 pulse intervals, and the first pulse interval precedes the second pulse interval;

[0052] The pulse intervals in the N-1 pulse intervals whose errors from the mean are not within a preset error range and the N-2 comparison results are determined as the variation rule of the N-1 pulse intervals.

[0053] The errors of the N-1 pulse intervals from the mean can be absolute errors, relative errors, etc., and this application does not limit the specific type of error. The errors of the N-1 pulse intervals from the mean can represent the degree to which the N-1 pulse intervals deviate from the mean, and can reflect the overall variation pattern of the N-1 pulse intervals.

[0054] Optionally, a preset error range may be set according to scenario requirements and the selected error type.

[0055] As an example but not a limitation, the errors between the N-1 pulse intervals and the mean are relative errors between the N-1 pulse intervals and the mean, and the preset error range may be 5%.

[0056] It should be understood that the N-1 pulse intervals are arranged in order from first to last according to the N pulse signals. There are N-2 groups of adjacent pulse intervals in the N-1 pulse intervals. One group of adjacent pulse intervals corresponds to one comparison result, so there are N-2 comparison results in the N-1 pulse intervals.

[0057] By way of example and not limitation, the taximeter sequentially receives 11 vehicle speed pulse signals, namely A1, A2, A3, A4, A5, A6, A7, A8, A9, A10, and A11. The order of the 10 pulse intervals of these 11 vehicle speed pulse signals is: the pulse interval between A1 and A2, the pulse interval between A2 and A3, the pulse interval between A3 and A4, the pulse interval between A4 and A5, the pulse interval between A5 and A6, the pulse interval between A6 and A7, the pulse interval between A7 and A8, the pulse interval between A8 and A9, the pulse interval between A9 and A10, and the pulse interval between A10 and A11. Taking the adjacent pulse intervals consisting of A1 and A2 as an example, A1 precedes A2, so A1 is the first pulse interval and A2 is the second pulse interval.

[0058] By determining whether the errors of the N-1 pulse intervals and the mean are all within the preset error range, it is possible to determine whether the N-1 pulse intervals remain relatively stable; if the errors of the N-1 pulse intervals and the mean are all within the preset error range, it can be determined that the N-1 pulse intervals remain relatively stable; if there is a pulse interval in the N-1 pulse intervals whose error with the mean is not within the preset error range, it can be determined that the N-1 pulse intervals do not remain relatively stable. In this case, the comparison result of the first pulse interval and the second pulse interval in each group of adjacent pulse intervals in the N-1 pulse intervals can be determined to obtain N-2 comparison results; based on the N-2 comparison results, it can be determined whether the N-1 pulse interval is gradually increasing, gradually decreasing, or fluctuating. The above-mentioned maintaining relative stability, gradually increasing, gradually decreasing, and fluctuating can all characterize the change pattern of the N-1 pulse interval.

[0059] In one embodiment, different driving states include a constant speed driving state, an accelerating driving state, and a decelerating driving state. After determining the variation pattern of the N-1 pulse intervals, the variation pattern of the N-1 pulse intervals can be matched with the target pulse interval variation pattern under different driving states. The matching method is as follows:

[0060] If the variation pattern of the N-1 pulse intervals is such that the errors between the N-1 pulse intervals and the mean are all within a preset error range, it is determined that the variation pattern of the N-1 pulse intervals matches the target variation pattern of the pulse intervals under the uniform speed driving state;

[0061] If there is a pulse interval in the N-1 pulse intervals whose error from the mean is not within the preset error range, and the N-2 comparison results all indicate that the first pulse interval is greater than the second pulse interval, then it is determined that the variation pattern of the N-1 pulse intervals matches the variation pattern of the target pulse interval under the accelerated driving state;

[0062] If there is a pulse interval among the N-1 pulse intervals whose error from the mean is not within the preset error range, and the N-2 comparison results all indicate that the first pulse interval is smaller than the second pulse interval, then determine that the change pattern of the N-1 pulse intervals is consistent with the change pattern of the target pulse interval under the deceleration state;

[0063] If there is a pulse interval among the N-1 pulse intervals whose error with the mean is not within the preset error range, and there is a comparison result indicating that the first pulse interval is greater than or equal to the second pulse interval among the N-2 comparison results, and there is a comparison result indicating that the first pulse interval is less than or equal to the second pulse interval, then it is determined that the change pattern of the N-1 pulse intervals does not match the change pattern of the target pulse intervals under different driving conditions.

[0064] The target pulse interval variation pattern refers to the variation pattern of the pulse interval when there is no mileage meter fraud, including but not limited to gradual increase, gradual decrease, and relative stability. For example, a gradually decreasing pulse interval indicates that the vehicle may be accelerating; a gradually increasing pulse interval indicates that the vehicle may be decelerating; and a relatively stable pulse interval indicates that the vehicle may be traveling at a constant speed.

[0065] When a vehicle is traveling at a constant speed, the variation pattern of its pulse interval is usually relatively stable, and the error between the pulse interval and the mean is usually within the preset error range. Therefore, if the errors between the N-1 pulse intervals and the mean are all within the preset error range, it can be determined that the variation pattern of the N-1 pulse intervals matches the target pulse interval variation pattern under the constant speed driving state.

[0066] When the vehicle is accelerating, the previous pulse interval in adjacent pulse intervals is usually larger than the next pulse interval. Therefore, when N-2 comparison results all indicate that the first pulse interval is larger than the second pulse interval, it can be determined that the change pattern of the N-1 pulse intervals matches the target pulse change pattern under the accelerating state.

[0067] When the vehicle is in a decelerating state, the previous pulse interval in adjacent pulse intervals is usually smaller than the next pulse interval. Therefore, when N-2 comparison results all indicate that the first pulse interval is smaller than the second pulse interval, it can be determined that the change pattern of the N-1 pulse intervals matches the target pulse change pattern in the accelerating state.

[0068] When a cheating pulse signal is implanted into the original pulse signal of the vehicle, the pulse interval will fluctuate. Therefore, if there is a pulse interval in the N-1 pulse intervals whose error with the mean is not within the preset error range, and there are both comparison results indicating that the first pulse interval is greater than or equal to the second pulse interval and comparison results indicating that the first pulse interval is less than or equal to the second pulse interval in the N-2 comparison results, it can be determined that the N-1 pulse intervals fluctuate and the meter is cheating on mileage.

[0069] The method for determining the changing pattern of the above-mentioned N-1 pulse intervals and the method for matching the changing pattern of the N-1 pulse intervals with the changing pattern of the target pulse intervals under different driving conditions are achieved through statistical methods, without relying on external hardware and positioning information and other conditions. This increases the difficulty of cheating pulses from the perspective of mileage statistics and reduces the possibility of pulse mileage cheating.

[0070] In another embodiment, an artificial intelligence module can also be used to determine the variation pattern of N-1 pulse intervals, and match the variation pattern of N-1 pulse intervals with the variation pattern of target pulse intervals under different driving conditions, and output a matching result. The specific implementation method is as follows:

[0071] N-1 pulse intervals are input into the artificial intelligence module to obtain a matching result between the changing pattern of the N-1 pulse intervals and the changing pattern of the target pulse intervals under different driving conditions; the matching result indicates that the changing pattern of the N-1 pulse intervals does not match the changing pattern of the target pulse intervals under different driving conditions, or that the changing pattern of the N-1 pulse intervals matches the changing pattern of the target pulse intervals under any driving condition.

[0072] Optionally, the artificial intelligence module may be a large artificial intelligence model. A large artificial intelligence model refers to a type of artificial intelligence model with a large number of parameters constructed by an artificial neural network.

[0073] like Figure 4 As shown, both the pulse sensor and the artificial intelligence module can be integrated into the meter. After N-1 pulse intervals are input into the artificial intelligence module, the artificial intelligence module can output the matching result of the changing pattern of the N-1 pulse intervals and the changing pattern of the target pulse interval under different driving conditions.

[0074] It should be understood that the changing pattern of the above-mentioned N-1 pulse intervals matches the changing pattern of the target pulse intervals in any driving state, which may mean that the changing pattern of the N-1 pulse intervals matches the changing pattern of the target pulse intervals in any driving state, including a uniform driving state, an accelerated driving state, or a decelerated driving state.

[0075] If the variation pattern of the N-1 pulse intervals matches the target pulse interval variation pattern under any driving state, it can be determined that there is no mileage cheating in the meter of the first vehicle.

[0076] In one embodiment, before inputting N-1 pulse intervals into the artificial intelligence module, the artificial intelligence module may be trained to obtain matching results using the trained artificial intelligence module. The training process is as follows:

[0077] In the case where the meter of at least one second vehicle does not cheat on mileage, a first pulse interval variation rule set of each second vehicle in a uniform speed driving state, a second pulse interval variation rule set of each second vehicle in an accelerated driving state, and a third pulse interval variation rule set of each second vehicle in a decelerated driving state are obtained, wherein each pulse interval variation rule in the first pulse interval variation rule set corresponds to a different vehicle speed or a different second vehicle, each pulse interval variation rule in the second pulse interval variation rule set corresponds to a different acceleration or a different second vehicle, and each pulse interval variation rule in the third pulse interval variation rule set corresponds to a different deceleration or a different second vehicle;

[0078] The control artificial intelligence module learns the first pulse interval variation law set, the second pulse interval variation law set, and the third pulse interval variation law set respectively to obtain target pulse interval variation laws under different driving conditions;

[0079] The target pulse interval change rules under different driving conditions are implanted into the artificial intelligence module.

[0080] The second vehicle and the first vehicle may be the same vehicle or different vehicles, and this application does not limit this. As an example and not a limitation, the first vehicle is vehicle A, and the second vehicle may be vehicle A, vehicle B, vehicle C, vehicle D, etc.

[0081] In order to improve the performance and generalization ability of the artificial intelligence module, the first pulse interval change rule set, the second pulse interval change rule set and the third pulse interval change rule set may include multiple pulse interval change rules.

[0082] Taking into account that different vehicles have different pulse interval variation patterns when traveling at a uniform speed due to the influence of vehicle characteristics (engine performance, transmission system differences, vehicle load, etc.), and their pulse interval variation patterns will also be different at different vehicle speeds, the artificial intelligence module continuously learns the first pulse interval variation pattern set covering different vehicles and different speeds, and can integrate multi-source information to obtain a more universal pulse interval variation pattern under a uniform speed driving state (i.e., the target pulse interval variation pattern under a uniform speed driving state), thereby improving the adaptability of the target pulse interval variation pattern under a uniform speed driving state to various vehicles and driving conditions.

[0083] Taking into account that different vehicles have different pulse interval variation patterns when traveling in an accelerated state due to the influence of vehicle characteristics, and their pulse interval variation patterns will also be different at different accelerations, the artificial intelligence module continuously learns a second set of pulse interval variation patterns covering different vehicles and different accelerations, and can integrate multi-source information to obtain a more universal pulse interval variation pattern in an accelerated state (i.e., a target pulse interval variation pattern in an accelerated state), thereby improving the adaptability of the target pulse interval variation pattern in an accelerated state to various vehicles and driving conditions.

[0084] Taking into account that different vehicles have different pulse interval change patterns due to the influence of vehicle characteristics when traveling in a decelerated driving state, and their pulse interval change patterns will also be different at different decelerations, the artificial intelligence module continuously learns a third set of pulse interval change patterns covering different vehicles and different decelerations. It can integrate multi-source information to obtain a more universal pulse interval change pattern under a decelerated driving state (i.e., a target pulse interval change pattern under a decelerated driving state), thereby improving the adaptability of the target pulse interval change pattern under a decelerated driving state to various vehicles and driving conditions.

[0085] By controlling the artificial intelligence module to continuously learn the set of pulse interval change rules under different driving conditions, the artificial intelligence module can obtain the target pulse interval change rules under different driving conditions such as uniform speed driving state, accelerated driving state, and decelerated driving state. By implanting the target pulse interval change rules under different driving conditions into the artificial intelligence module, the artificial intelligence module can achieve the matching of the change rules of N-1 pulse intervals with the target pulse interval change rules under different driving conditions.

[0086] This embodiment introduces an improvement in the artificial intelligence large model method, without relying on external hardware, positioning information and other conditions, and increases the difficulty of cheating pulses from the mileage statistics method, thereby reducing the possibility of pulse mileage cheating.

[0087] Step 203: If the variation pattern of the N-1 pulse intervals does not match the variation pattern of the target pulse intervals under different driving conditions, it is determined that the meter of the first vehicle has engaged in mileage cheating.

[0088] The mileage cheating behavior of the meter may refer to the vehicle speed pulse signal received by the meter being implanted with a cheating pulse signal.

[0089] If the variation pattern of the N-1 pulse intervals does not match the variation pattern of the target pulse intervals under different driving conditions, it means that the N-1 pulse intervals fluctuate and the meter is cheating on mileage.

[0090] When the electronic device determines that the meter of the first vehicle has engaged in mileage cheating, it can control the meter to stop mileage counting and prompt that the mileage is abnormal.

[0091] In a possible implementation, step 204 may include:

[0092] If the variation pattern of the N-1 pulse intervals does not match the variation pattern of the target pulse interval, then the duration of the mismatch is determined;

[0093] If the duration exceeds the preset time, it is determined that the meter has engaged in mileage cheating.

[0094] Optionally, you can set a preset duration based on scenario requirements. By setting a preset duration, you can further identify meter anomalies. If the mismatch is only momentary, it may be due to environmental factors or temporary equipment failure. If the mismatch persists for a certain period of time and exceeds the preset duration, then this persistent anomaly is more likely to indicate mileage fraud.

[0095] In an embodiment of the present application, by obtaining the time when each of the N vehicle speed pulse signals of the first vehicle arrives at the meter of the first vehicle, the pulse intervals of adjacent vehicle speed pulse signals can be determined based on the time when each of the N vehicle speed pulse signals arrives at the meter of the first vehicle, and N-1 pulse intervals are obtained. The changing pattern of the N-1 pulse intervals is matched with the target pulse interval changing pattern. Since the target pulse interval changing pattern refers to the changing pattern of the pulse interval under the corresponding driving state and when there is no mileage cheating behavior in the meter, if the changing pattern of the N-1 pulse intervals does not match the target pulse interval changing pattern under different driving states, it can be determined that there is mileage cheating in the meter of the first vehicle. On this basis, timely measures can be taken to stop and correct it, thereby reducing the risk of meter mileage cheating.

[0096] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0097] Corresponding to the anti-cheating method for taximeters described in the above embodiment, Figure 5 A schematic structural diagram of a taximeter anti-cheating device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0098] Reference Figure 5 , the device comprises:

[0099] A time acquisition module 501 is configured to acquire the time at which each of N vehicle speed pulse signals of a first vehicle arrives at the meter of the first vehicle, where N is an integer greater than 2;

[0100] an interval determination module 502 for determining the pulse intervals between adjacent vehicle speed pulse signals in the N vehicle speed pulse signals based on the time when each of the N vehicle speed pulse signals arrives at the meter of the first vehicle, to obtain N-1 pulse intervals;

[0101] The cheating determination module 503 is used to determine that the meter of the first vehicle has mileage cheating if the changing pattern of the N-1 pulse intervals does not match the target pulse interval changing pattern under different driving conditions. The target pulse interval changing pattern refers to the changing pattern of the pulse interval under the corresponding driving condition and when the meter does not have mileage cheating.

[0102] Optionally, the above device further includes a rule determination module, which is specifically configured to:

[0103] Calculating the mean of the N-1 pulse intervals;

[0104] Calculating the errors between the N-1 pulse intervals and the mean value;

[0105] If the errors between the N-1 pulse intervals and the mean are both within a preset error range, then the errors between the N-1 pulse intervals and the mean are both within the preset error range as the variation rule of the N-1 pulse intervals;

[0106] If there is a pulse interval in the N-1 pulse intervals whose error with the mean is not within the preset error range, determining a comparison result between the first pulse interval and the second pulse interval in each group of adjacent pulse intervals, to obtain N-2 comparison results, each comparison result being used to indicate a size relationship between the first pulse interval and the second pulse interval, the N-1 pulse intervals corresponding to N-2 groups of adjacent pulse intervals, the first pulse interval and the second pulse interval in each group of adjacent pulse intervals being adjacent pulse intervals in the N-1 pulse intervals, and the first pulse interval precedes the second pulse interval;

[0107] The pulse intervals among the N-1 pulse intervals whose errors from the mean are not within the preset error range and the N-2 comparison results are determined as the variation rule of the N-1 pulse intervals.

[0108] Optionally, the different driving states include a constant speed driving state, an accelerated driving state, and a decelerated driving state. The above device further includes a matching module, which is specifically configured to:

[0109] If the variation pattern of the N-1 pulse intervals is such that the errors between the N-1 pulse intervals and the mean are both within the preset error range, then determining that the variation pattern of the N-1 pulse intervals matches the target pulse interval variation pattern under the uniform speed driving state;

[0110] If there is a pulse interval among the N-1 pulse intervals whose error from the mean is not within the preset error range, and the N-2 comparison results all indicate that the first pulse interval is greater than the second pulse interval, then it is determined that the variation pattern of the N-1 pulse intervals matches the variation pattern of the target pulse interval in the accelerated driving state;

[0111] If there is a pulse interval among the N-1 pulse intervals whose error from the mean is not within the preset error range, and the N-2 comparison results all indicate that the first pulse interval is smaller than the second pulse interval, determining whether the variation pattern of the N-1 pulse intervals is consistent with the variation pattern of the target pulse interval in the deceleration state;

[0112] If there is a pulse interval among the N-1 pulse intervals whose error with the mean is not within the preset error range, and there is a comparison result indicating that the first pulse interval is greater than or equal to the second pulse interval among the N-2 comparison results, and there is a comparison result indicating that the first pulse interval is less than or equal to the second pulse interval, then it is determined that the change pattern of the N-1 pulse intervals does not match the change pattern of the target pulse intervals under the different driving conditions.

[0113] Optionally, the above device further includes:

[0114] A result acquisition module is used to input the N-1 pulse intervals into an artificial intelligence module to obtain a matching result between the changing pattern of the N-1 pulse intervals and the changing pattern of the target pulse intervals under the different driving conditions; the matching result indicates that the changing pattern of the N-1 pulse intervals does not match the changing pattern of the target pulse intervals under the different driving conditions, or that the changing pattern of the N-1 pulse intervals matches the changing pattern of the target pulse intervals under any driving condition.

[0115] Optionally, the above device further includes a training module, which is specifically used to:

[0116] In the case where the meter of at least one second vehicle does not cheat on mileage, a first pulse interval variation rule set of each second vehicle in a uniform speed driving state, a second pulse interval variation rule set of each second vehicle in an accelerated driving state, and a third pulse interval variation rule set of each second vehicle in a decelerated driving state are obtained, wherein each pulse interval variation rule in the first pulse interval variation rule set corresponds to a different vehicle speed or a different second vehicle, each pulse interval variation rule in the second pulse interval variation rule set corresponds to a different acceleration or a different second vehicle, and each pulse interval variation rule in the third pulse interval variation rule set corresponds to a different deceleration or a different second vehicle;

[0117] controlling the artificial intelligence module to respectively learn the first pulse interval variation rule set, the second pulse interval variation rule set, and the third pulse interval variation rule set to obtain target pulse interval variation rules under the different driving conditions;

[0118] The target pulse interval variation rules under the different driving conditions are implanted into the artificial intelligence module.

[0119] Optionally, the cheating determination module 503 is specifically configured to:

[0120] If the variation pattern of the N-1 pulse intervals does not match the variation pattern of the target pulse intervals under the different driving conditions, determining the duration of the mismatch;

[0121] If the duration exceeds a preset duration, it is determined that the meter of the first vehicle has engaged in mileage cheating.

[0122] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment section and will not be repeated here.

[0123] Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiment of the present application. Figure 6 As shown, the electronic device 6 of this embodiment includes: at least one processor 60 ( Figure 6 Only one is shown), a memory 61 and a computer program 62 stored in the memory 61 and executable on the at least one processor 60, wherein the processor 60 implements the steps of any of the above-mentioned method embodiments when executing the computer program 62.

[0124] The electronic device may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will appreciate that Figure 6 This is merely an example of the electronic device 6 and does not constitute a limitation on the electronic device 6 . The electronic device 6 may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the electronic device 6 may also include input and output devices, network access devices, etc.

[0125] The processor 60 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor may be a microprocessor or any conventional processor.

[0126] In some embodiments, the memory 61 may be an internal storage unit of the electronic device 6, such as a hard disk or memory of the electronic device 6. In other embodiments, the memory 61 may also be an external storage device of the electronic device 6, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 6. Furthermore, the memory 61 may also include both an internal storage unit of the electronic device 6 and an external storage device. The memory 61 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory 61 may also be used to temporarily store data that has been output or is about to be output.

[0127] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0128] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program, when executed by the processor, can implement the steps of the above-mentioned various method embodiments. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include at least: any entity or device that can carry the computer program code to the device / electronic device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electric carrier signal, a telecommunication signal and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk.

[0129] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0130] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0131] In the embodiments provided in the present application, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0132] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0133] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for preventing meter cheating, characterized in that: include: Obtaining the time at which each of N vehicle speed pulse signals of the first vehicle arrives at the meter of the first vehicle, where N is an integer greater than 2; determining pulse intervals between adjacent vehicle speed pulse signals among the N vehicle speed pulse signals based on the time when each of the N vehicle speed pulse signals arrives at the meter of the first vehicle, to obtain N-1 pulse intervals; If the changing pattern of the N-1 pulse intervals does not match the target pulse interval changing pattern under different driving conditions, it is determined that the meter of the first vehicle has mileage cheating behavior. The target pulse interval changing pattern refers to the changing pattern of the pulse interval under the corresponding driving state and when the meter does not have mileage cheating behavior.

2. The method for preventing meter cheating according to claim 1, characterized in that: After obtaining N-1 pulse intervals, it also includes: Calculating the mean of the N-1 pulse intervals; Calculating the errors between the N-1 pulse intervals and the mean value; If the errors between the N-1 pulse intervals and the mean are both within a preset error range, then the errors between the N-1 pulse intervals and the mean are both within the preset error range as the variation rule of the N-1 pulse intervals; If there is a pulse interval in the N-1 pulse intervals whose error with the mean is not within the preset error range, determining a comparison result between the first pulse interval and the second pulse interval in each group of adjacent pulse intervals, to obtain N-2 comparison results, each comparison result being used to indicate a size relationship between the first pulse interval and the second pulse interval, the N-1 pulse intervals corresponding to N-2 groups of adjacent pulse intervals, the first pulse interval and the second pulse interval in each group of adjacent pulse intervals being adjacent pulse intervals in the N-1 pulse intervals, and the first pulse interval precedes the second pulse interval; The pulse intervals among the N-1 pulse intervals whose errors from the mean are not within the preset error range and the N-2 comparison results are determined as the variation rule of the N-1 pulse intervals.

3. The method for preventing meter cheating according to claim 2, characterized in that: The different driving states include a constant speed driving state, an accelerated driving state, and a decelerated driving state. After determining the changing pattern of the N-1 pulse intervals, the method further includes: If the variation pattern of the N-1 pulse intervals is such that the errors between the N-1 pulse intervals and the mean are both within the preset error range, then determining that the variation pattern of the N-1 pulse intervals matches the target pulse interval variation pattern under the uniform speed driving state; If there is a pulse interval among the N-1 pulse intervals whose error from the mean is not within the preset error range, and the N-2 comparison results all indicate that the first pulse interval is greater than the second pulse interval, then it is determined that the variation pattern of the N-1 pulse intervals matches the variation pattern of the target pulse interval in the accelerated driving state; If there is a pulse interval among the N-1 pulse intervals whose error from the mean is not within the preset error range, and the N-2 comparison results all indicate that the first pulse interval is smaller than the second pulse interval, determining whether the variation pattern of the N-1 pulse intervals is consistent with the variation pattern of the target pulse interval in the deceleration state; If there is a pulse interval among the N-1 pulse intervals whose error with the mean is not within the preset error range, and there is a comparison result indicating that the first pulse interval is greater than or equal to the second pulse interval among the N-2 comparison results, and there is a comparison result indicating that the first pulse interval is less than or equal to the second pulse interval, then it is determined that the change pattern of the N-1 pulse intervals does not match the change pattern of the target pulse intervals under the different driving conditions.

4. The method for preventing meter cheating according to claim 1, wherein: After obtaining N-1 pulse intervals, it also includes: The N-1 pulse intervals are input into an artificial intelligence module to obtain a matching result between the changing pattern of the N-1 pulse intervals and the changing pattern of the target pulse intervals under the different driving conditions; the matching result indicates that the changing pattern of the N-1 pulse intervals does not match the changing pattern of the target pulse intervals under the different driving conditions, or that the changing pattern of the N-1 pulse intervals matches the changing pattern of the target pulse intervals under any driving condition.

5. The method for preventing meter cheating according to claim 4, characterized in that: Before inputting the N-1 pulse intervals into the artificial intelligence module, the method further includes: In the case where the meter of at least one second vehicle does not cheat on mileage, a first pulse interval variation rule set of each second vehicle in a uniform speed driving state, a second pulse interval variation rule set of each second vehicle in an accelerated driving state, and a third pulse interval variation rule set of each second vehicle in a decelerated driving state are obtained, wherein each pulse interval variation rule in the first pulse interval variation rule set corresponds to a different vehicle speed or a different second vehicle, each pulse interval variation rule in the second pulse interval variation rule set corresponds to a different acceleration or a different second vehicle, and each pulse interval variation rule in the third pulse interval variation rule set corresponds to a different deceleration or a different second vehicle; controlling the artificial intelligence module to respectively learn the first pulse interval variation rule set, the second pulse interval variation rule set, and the third pulse interval variation rule set to obtain target pulse interval variation rules under the different driving conditions; The target pulse interval variation rules under the different driving conditions are implanted into the artificial intelligence module.

6. The method for preventing meter cheating according to any one of claims 1 to 5, characterized in that: If the variation pattern of the N-1 pulse intervals does not match the variation pattern of the target pulse intervals under different driving conditions, then determining that the meter of the first vehicle has mileage cheating behavior includes: If the variation pattern of the N-1 pulse intervals does not match the variation pattern of the target pulse intervals under the different driving conditions, determining the duration of the mismatch; If the duration exceeds a preset duration, it is determined that the meter of the first vehicle has engaged in mileage cheating.

7. The method for preventing meter cheating according to any one of claims 1 to 5, characterized in that: The obtaining of the time at which each of the N vehicle speed pulse signals of the first vehicle arrives at the meter of the first vehicle includes: During the driving of the first vehicle, the time when each of the N vehicle speed pulse signals arrives at the meter of the first vehicle is obtained.

8. A taximeter anti-cheating device, characterized in that: include: a time acquisition module, configured to acquire the time at which each of N vehicle speed pulse signals of the first vehicle arrives at the meter of the first vehicle, where N is an integer greater than 2; an interval determination module, configured to determine the pulse intervals between adjacent vehicle speed pulse signals in the N vehicle speed pulse signals based on the time when each of the N vehicle speed pulse signals arrives at the meter of the first vehicle, to obtain N-1 pulse intervals; The cheating determination module is used to determine that the meter of the first vehicle has mileage cheating if the variation pattern of the N-1 pulse intervals does not match the target pulse interval variation pattern under different driving conditions, and the target pulse interval variation pattern refers to the variation pattern of the pulse interval under the corresponding driving condition and when the meter does not have mileage cheating.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the electronic device implements the anti-cheating method for taximeters according to any one of claims 1 to 7.

10. A computer program product, characterized in that The method comprises a computer program, which enables the taximeter anti-cheating method according to any one of claims 1 to 7 to be executed when the computer program is executed.

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