Internet of vehicles remote control system and method based on data security

Abstract

The application relates to the technical field of Internet of Vehicles, and particularly discloses an Internet of Vehicles remote control system and method based on data security, the method comprising the following steps: acquiring a time point at which a request sent by a vehicle is received by an information platform, the request taking a license plate number of the vehicle as a label, determining a pending request based on the label and the time point; acquiring position information of a vehicle i corresponding to the pending request, determining a monitoring range fi of the vehicle i based on the position information, correcting the monitoring range fi based on a vehicle distribution situation in the monitoring range fi to obtain a monitoring range Fi; determining whether the pending request is an abnormal request based on the monitoring range Fi, and the information platform rejecting the abnormal request. The application improves the safety of the Internet of Vehicles.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Vehicles, in particular to an Internet of Vehicles remote control system based on data security and a method thereof. BACKGROUND

[0002] With the rapid development of Internet of Things technology and intelligent transportation, the number of vehicles is increasing year by year, and Internet of Vehicles has become an important research and application direction in the transportation industry. Internet of Vehicles refers to the vehicle-mounted devices on vehicles using wireless communication technology to effectively acquire and utilize the dynamic information of all vehicles in the information platform, and provide various functional services during vehicle operation. Through Internet of Vehicles, vehicles and information platforms can realize real-time traffic data sharing, navigation information updating and safety warning, etc.

[0003] However, with the rapid popularization of Internet of Vehicles, its data transmission security problem is increasingly prominent. Among them, the man-in-the-middle attack is a common and serious threat. The so-called man-in-the-middle attack refers to an attacker intercepting normal network communication data without being detected by the communication parties, and tampering or sniffing it. In the process of Internet of Vehicles communication, vehicles will send requests to the information platform, and the information platform will respond according to the request content. If there is a man-in-the-middle attack, the attacker may intercept the request sent by the vehicle and forge a new request to obtain the response of the information platform, thereby causing data leakage or improper use. SUMMARY

[0004] The purpose of the present application is to provide an Internet of Vehicles remote control system based on data security and a method thereof, which solves the following technical problems:

[0005] In the process of Internet of Vehicles communication, vehicles will send requests to the information platform, and the information platform will respond according to the request content. If there is a man-in-the-middle attack, the attacker may intercept the request sent by the vehicle and forge a new request to obtain the response of the information platform, thereby causing data leakage or improper use.

[0006] The purpose of the present application can be achieved by the following technical solutions:

[0007] The Internet of Vehicles remote control method based on data security comprises the following steps:

[0008] Obtaining the time point when the information platform receives the request sent by the vehicle, the request taking the license plate number of the vehicle as a label, determining the pending request based on the label and the time point;

[0009] Obtaining the location information of the vehicle i corresponding to the pending request, determining the monitoring range fi of the vehicle i based on the location information, correcting the monitoring range fi based on the distribution of vehicles in the monitoring range fi, and obtaining the monitoring range Fi;

[0010] determine whether the pending request is an abnormal request based on the monitoring range Fi, and the information platform rejects the abnormal request.

[0011] As a further aspect of the present application: determining a pending request based on the label and the time point includes:

[0012] Obtain the request with the same label as the target request, and obtain the time point at which the information platform receives the target request as the target time point.

[0013] Obtain the target time point within a preset collection period, the end of the collection period is the current time, sort the target time points in chronological order, calculate the time interval between the target time points at adjacent sorting positions in the sorting, and sort the time intervals in chronological order to obtain a first sorting.

[0014] From the time interval at the n-1th position in the first sorting, select n1 time intervals along the reverse chronological order, calculate the mean value t of the selected time intervals, n represents the total number of time intervals in the first sorting, and n1 is a preset number.

[0015] If the time difference Δt = T-t > Δt1, the last target request in the collection period is recorded as a pending request, and Δt1 represents a preset time difference threshold.

[0016] As a further aspect of the present application: obtaining the location information of the vehicle i corresponding to the pending request, and determining the monitoring range fi of the vehicle i based on the location information includes:

[0017] Mark the vehicles other than the vehicle corresponding to the pending request as target vehicles, and obtain the total number C of target vehicles within a preset radius r with the position of the vehicle i as the center.

[0018] If the total number C is less than a preset number threshold C1, increase the radius r by a preset radius interval Δr and obtain the total number of corresponding target vehicles, repeat the above steps until the radius is R1 and the total number of corresponding target vehicles is greater than the number threshold C1, and draw a circle with a radius of R1 with the position of the vehicle i as the center, and use it as the monitoring range fi.

[0019] Wherein, when R1 ≥ Rmax, R1 = Rmax, and Rmax represents a preset maximum radius.

[0020] If the total number C is greater than C1, the radius r is reduced by the radius interval Δr, and the total number of corresponding target vehicles is obtained, and the above steps are repeated until the radius is r1, and the total number of corresponding target vehicles is less than the number threshold C1, and a circle with the position of the vehicle i as the center and a radius of R2=r1+Δr is drawn as the monitoring range fi.

[0021] As a further aspect of the application: the monitoring range fi is corrected based on the distribution of vehicles in the monitoring range fi, and the monitoring range Fi is obtained, including:

[0022] The theoretical center of gravity of the monitoring range fi is obtained, and when the distance between the theoretical center of gravity and the vehicle i is greater than a preset distance threshold, a target direction is obtained, and the target direction is directed from the position of the vehicle i to the theoretical center of gravity;

[0023] A circle with a radius of r is constructed with the position of the vehicle i as the center, denoted as the initial circle, and the initial circle is moved along the target direction on the target line at a preset speed, and the total number of target vehicles in the initial circle is recorded in real time, denoted as the undetermined number, and the target line is the line connecting the vehicle i and the theoretical center of gravity;

[0024] The center j of the position of the initial circle corresponding to the maximum undetermined number is obtained, and the center j is taken as the position of the vehicle i to determine the monitoring range Fi.

[0025] As a further aspect of the application: based on the monitoring range Fi, it is determined whether the pending request is an abnormal request, including:

[0026] The proportion c of the number of target vehicles in the monitoring range Fi to the total number of vehicles is obtained, and a judgment coefficient K is calculated , RR represents the radius of the monitoring range Fi, and η is a preset empirical coefficient;

[0027] If the judgment coefficient K is greater than K1, it is determined that the pending request is an abnormal request, and K1 represents a preset judgment coefficient threshold.

[0028] As a further aspect of the application: the position information of the vehicle i is obtained based on GPS or Beidou.

[0029] As a further aspect of the application: after the information platform rejects the abnormal request, the following steps are further included:

[0030] The number of abnormal requests in a preset time period is counted, and if the number exceeds a preset threshold, a prompt message is sent to a preset manager.

[0031] The vehicle networking remote control system based on data security includes:

[0032] The collection module: the information platform receives the time point of the request sent by the vehicle, the request takes the license plate number of the vehicle as a label, determines the pending request based on the label and the time point;

[0033] The correction module: obtaining the position information of the vehicle i corresponding to the pending request, determining the monitoring range fi of the vehicle i based on the position information, correcting the monitoring range fi based on the vehicle distribution in the monitoring range fi, and obtaining the monitoring range Fi;

[0034] The control module: determining whether the pending request is an abnormal request based on the monitoring range Fi, and the information platform rejecting the abnormal request.

[0035] The beneficial effects of the present application are as follows:

[0036] 1) By statistically analyzing the request time interval for the same license plate number and comparing it with the historical average value, suspicious requests that deviate significantly from the normal time sequence can be quickly identified with low computational complexity;

[0037] 2) By adaptively adjusting the size of the monitoring radius, sufficient vehicle information can be accurately collected in different vehicle density scenarios (such as urban and suburban areas), avoiding both the computational redundancy caused by excessive expansion of the monitoring range and the inability to reflect the actual situation of the surrounding environment due to a too small range. At the same time, by dynamically correcting the center position near the vehicle distribution center of gravity, the main trunk area of the traffic flow can be maximally covered, enhancing the monitoring accuracy and robustness;

[0038] 3) By using the judgment coefficient combining the normal vehicle proportion and the monitoring range radius, the surrounding environment of the vehicle can be measured for obvious differences from its behavior under the premise of a certain number of normal vehicles. This method can effectively identify abnormal requests that suddenly appear in dense normal traffic flow, and can also take into account the actual situation when the vehicle environment is special or dispersed, thereby combining flexibility and accuracy and significantly reducing the risk of misjudgment and false reporting;

[0039] 4) In the execution of safety control and notification, by immediately rejecting the confirmed abnormal request, potential threats can be blocked in the first time to avoid affecting the safety of the vehicle networking system or the vehicle. At the same time, the number of abnormal requests is accumulated and counted within a preset time period, and if it exceeds the threshold, a prompt is sent to the management personnel, forming a closed-loop control of system safety protection, supplemented by post-monitoring on the basis of prevention, thereby further improving the overall safety and reliability of vehicle networking remote control. BRIEF DESCRIPTION OF DRAWINGS

[0040] The present application will be further described below with reference to the accompanying drawings.

[0041] Figure 1is a flowchart of a data security-based remote control method for vehicle networking according to the present application, DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of the present application.

[0043] Please refer to Figure 1 The present application is a data security-based remote control method for vehicle networking, which comprises the following steps:

[0044] The information platform receives the time point of a request sent by a vehicle, the request taking the license plate number of the vehicle as a label, and determines a pending request based on the label and the time point.

[0045] In a preferred embodiment of the present application, determining a pending request based on the label and the time point comprises:

[0046] The request with the same label is obtained and recorded as a target request, and the time point at which the information platform receives the target request is obtained and recorded as a target time point.

[0047] The target time points in a preset collection period are obtained, the end point of the collection period being the current time, the target time points are sorted in chronological order, the time interval between the target time points at two adjacent sorting positions in the sorting is calculated, the time interval is sorted in chronological order, and a first sorting is obtained.

[0048] Starting from the time interval at the n-1th position in the first sorting, n1 time intervals are selected along the reverse chronological order, the mean value t of the selected time intervals is calculated, n represents the total number of time intervals in the first sorting, and n1 is a preset number.

[0049] If the time difference Δt=T-t is greater than Δt1, the last target request in the collection period is recorded as a pending request, and Δt1 represents a preset time difference threshold.

[0050] It can be understood that in this process, a collection period can be set in advance in the information platform, for example, it can be set to twenty minutes or thirty minutes, and if the current time is twelve o'clock, eleven forty or eleven thirty can be taken as the collection period, and the information platform will record the time points of multiple target requests under the same license plate number in the collection period, and arrange them in order, for example, a plurality of time points in order are obtained, then the time interval between adjacent two time points is calculated, and the time interval is arranged in order from early to late, for example, a set of continuous time intervals is obtained, and is recorded as the first order, if the set of time intervals has n, the n-1 time interval in the first order is found, and n1 time intervals are selected in reverse time order, and then the n1 time intervals are averaged, and the average value is recorded as t. T represents the time interval corresponding to the last target request in the collection period, a time difference Δt can be obtained, if the time difference Δt is greater than the pre-set time difference threshold Δt1, it indicates that the occurrence of the last target request and the time sequence distribution before it have significant difference, and the target request is marked as a pending request; in this way, on the one hand, the vehicle request can be quickly analyzed whether it appears abnormal frequency or time sequence distribution mutation in a short time under low calculation amount, and on the other hand, the normal request will not be misjudged as abnormal due to occasional network delay or individual operation of the vehicle, so that the identification accuracy and fault tolerance rate are better balanced. In this way, when the system finally marks a request as a pending request, it can more targetedly enter the next step of monitoring range confirmation and abnormality determination process;

[0051] Obtaining the location information of the vehicle i corresponding to the pending request, determining the monitoring range fi of the vehicle i based on the location information, correcting the monitoring range fi based on the vehicle distribution in the monitoring range fi, and obtaining the monitoring range Fi;

[0052] In a preferred embodiment of the application, obtaining the location information of the vehicle i corresponding to the pending request, determining the monitoring range fi of the vehicle i based on the location information includes:

[0053] Marking the vehicle other than the vehicle corresponding to the pending request as a target vehicle, taking the location of the vehicle i as the center, obtaining the total number C of the target vehicles within the pre-set radius r;

[0054] If the total number C is less than the pre-set number threshold C1, the radius r is increased by the pre-set radius interval Δr, and the total number of the target vehicles corresponding to the radius r is obtained, the above steps are repeated until the radius is R1, and the total number of the target vehicles corresponding to the radius R1 is greater than the number threshold C1, taking the location of the vehicle i as the center, a circle with a radius of R1 is drawn, and it is taken as the monitoring range fi.

[0055] wherein, when R1≥Rmax, R1=Rmax, Rmax represents a preset maximum radius;

[0056] If the total number C>C1, the radius r is reduced by the radius interval Δr, and the total number of corresponding target vehicles is obtained, and the above steps are repeated until the radius is r1, and the total number of corresponding target vehicles is less than the number threshold C1, and the position of the vehicle i is taken as the center to draw a circle with a radius R2=r1+Δr, which is taken as the monitoring range fi;

[0057] It can be understood that an initial radius r is first set, for example, fifty meters, and then the total number C of target vehicles within a range of fifty meters is counted with the current coordinates of the vehicle i as the center. If the counting result C is lower than the number threshold C1, for example, C1 can be set to ten, it is indicated that the expected number cannot be reached within a range of fifty meters, and the radius r is increased by the interval Δr (for example, twenty meters or thirty meters) at this time, and the total number of target vehicles within the range is counted again. If the radius is continuously increased, and the total number C is greater than or equal to C1 at a certain time, the radius at this time is recorded as R1, which is regarded as a suitable monitoring range. If the R1 exceeds the maximum radius Rmax set in advance, the R1 is set to Rmax. In this way, in the scenario of sparse vehicles, the coverage range can be gradually expanded, and unnecessary calculation pressure caused by setting the radius too large at one time is avoided;

[0058] On the contrary, if the total number C of target vehicles within the initial radius r is already greater than C1, it is indicated that the vehicles are distributed relatively densely, and the radius can be appropriately reduced, and the radius is gradually reduced in the interval Δr until the counting result C is less than C1 at a certain time, and the radius r1 at this time is taken plus Δr to obtain R2, which is taken as the final monitoring range Fi. In this way, the risk of misjudgment can be reduced by preventing the monitoring range from being too large due to too dense distribution. Through the process of adaptively increasing and reducing the radius, the coverage radius around the vehicle i can be more accurate on the premise of retaining a sufficient number of target vehicles, and more representative environmental information for subsequent identification of abnormal requests is provided;

[0059] In a preferred case of the embodiment, the monitoring range fi is corrected based on the distribution of vehicles in the monitoring range fi to obtain the monitoring range Fi, which includes:

[0060] A target direction is obtained when the distance between the theoretical gravity center of the monitoring range fi and the vehicle i is greater than a preset distance threshold, and the target direction is from the position of the vehicle i to the theoretical gravity center;

[0061] A circle with a radius of r is constructed with the position of the vehicle i as the center, denoted as an initial circle, the initial circle is moved along the target line in the target direction at a preset speed, and the total number of target vehicles in the initial circle is recorded in real time, denoted as a to-be-determined number, the target line is a line connecting the vehicle i and the theoretical gravity center;

[0062] The center j of the initial circle where the maximum to-be-determined number corresponds is obtained, the position of the vehicle i is determined as the center j of the initial circle, and the monitoring range Fi is determined;

[0063] It should be noted that the theoretical gravity center formed by the distribution of the target vehicles is calculated in the monitoring range fi obtained in the previous step, and if the distance between the theoretical gravity center and the position of the vehicle i exceeds a preset threshold, it indicates that the vehicle i may not be in the main traffic flow concentrated area. For example, if most of the target vehicles on a certain road are concentrated in a certain range in front of the vehicle i, and the vehicle i is just at the edge of this vehicle dense area, the position of the vehicle i needs to be further corrected to ensure that the monitoring range can accurately cover the main traffic flow. To this end, an initial circle can be constructed with the position of the vehicle i as the center, and the initial circle is translated on the target line connecting the vehicle i and the theoretical gravity center at a preset speed, and the number of target vehicles in the initial circle is continuously counted while moving. When the number of target vehicles in the initial circle at a certain position reaches the maximum, it indicates that this position best represents the concentrated distribution of the target vehicles, and the center j of this position is recorded as the center of the initial circle. After the position of the vehicle i is replaced by the center j, the monitoring range Fi is redrawn, and a monitoring range that is closer to the main traffic flow area can be obtained. The monitoring range Fi is drawn in the same way as fi.

[0064] Through this moving correction step, the matching degree of the monitoring range and the real vehicle distribution can be further improved, the monitoring accuracy can be prevented from being reduced due to the fact that the vehicle i deviates from the main traffic flow, the judgment of the subsequent abnormal request is more representative, and thus the risk of missing detection is effectively reduced and the overall monitoring accuracy is improved;

[0065] Based on the monitoring range Fi, it is determined whether the to-be-determined request is an abnormal request, and the information platform rejects the abnormal request;

[0066] In another preferred condition of the embodiment, determining whether the to-be-determined request is an abnormal request based on the monitoring range Fi includes:

[0067] The proportion c of the number of target vehicles in the monitoring range Fi to the total number of vehicles is obtained, and a judgment coefficient K is calculated , RR represents the radius of the monitoring range Fi, and η is a preset empirical coefficient;

[0068] If the judgment coefficient K > K1, it is determined that the to-be-determined request is an abnormal request, and K1 represents a preset judgment coefficient threshold.

[0069] In a preferred embodiment of the present application, the position information of the vehicle i is obtained based on GPS or Beidou.

[0070] In another preferred embodiment of the present application, after the information platform rejects the abnormal request, the method further comprises the following steps:

[0071] The number of abnormal requests in a preset time period is counted, and if the number exceeds a preset threshold, a prompt information is sent to a preset manager.

[0072] A vehicle networking remote control system based on data security comprises:

[0073] A collection module: obtaining the time point at which the information platform receives a request sent by a vehicle, the request taking the license plate number of the vehicle as a tag, and determining a pending request based on the tag and the time point;

[0074] A correction module: obtaining the position information of the vehicle i corresponding to the pending request, determining the monitoring range fi of the vehicle i based on the position information, correcting the monitoring range fi based on the distribution of vehicles in the monitoring range fi, and obtaining the monitoring range Fi.

[0075] A control module: determining whether the pending request is an abnormal request based on the monitoring range Fi, and rejecting the abnormal request by the information platform.

[0076] The above describes one embodiment of the present application in detail, but the content is only a preferred embodiment of the present application and cannot be considered as limiting the scope of the present application. Any equivalent changes and improvements made in the scope of the present application should still belong to the scope of the present application.

Claims

1. A data security-based remote control method for a vehicle-to-everything network, characterized by, The method comprises the following steps: The information platform receives the time point of the request sent by the vehicle, the request taking the license plate number of the vehicle as a label, and determines a pending request based on the label and the time point; Obtain the location information of vehicle i corresponding to the pending request, determine the monitoring range fi of vehicle i based on the location information, correct the monitoring range fi based on the distribution of vehicles within the monitoring range fi, and obtain the monitoring range Fi; Determine whether the pending request is an abnormal request based on the monitoring range Fi, and the information platform rejects the abnormal request; Determination of a pending request based on the label and the time point comprises: Obtain the request with the same label, denoted as a target request, obtain the time point at which the information platform receives the target request, denoted as a target time point; Obtain the target time points within a preset collection period, the end of the collection period being the current time, sort the target time points in chronological order, calculate the time interval between the target time points at adjacent sorting positions in the sorting, sort the time intervals in chronological order, and obtain a first sorting; From the (n-1)th time interval in the first sorting, select n1 time intervals along the reverse chronological order, calculate the mean value t of the selected time intervals, n represents the total number of time intervals in the first sorting, and n1 is a preset number; If the time difference value Δt=T-t>Δt1, the last target request in the collection period is recorded as a pending request, and Δt1 represents a preset time difference value threshold; Correcting the monitoring range fi based on the distribution of vehicles within the monitoring range fi to obtain the monitoring range Fi comprises: Mark vehicles other than the vehicle corresponding to the pending request as target vehicles, obtain the theoretical center of gravity of the monitoring range fi, and when the distance between the theoretical center of gravity and the vehicle i is greater than a preset distance threshold, obtain a target direction, the target direction being directed from the position of the vehicle i to the theoretical center of gravity; Take the position of the vehicle i as the center of a circle with a radius of r, denoted as an initial circle, move the initial circle along the target direction on a target line at a preset speed, and record the total number of target vehicles within the initial circle in real time, denoted as a pending number, the target line being a line connecting the vehicle i and the theoretical center of gravity; Obtain the center j of the position of the initial circle corresponding to the maximum pending number, take the center j as the position of the vehicle i, and determine the monitoring range Fi; Determination of whether the pending request is an abnormal request based on the monitoring range Fi comprises: Obtaining the proportion c of the number of target vehicles in the monitoring range Fi to all vehicles, and calculating a judgment coefficient , RR represents the radius of the monitoring range Fi, and η is a preset empirical coefficient. If the judgment coefficient K>K1, the pending request is determined to be an abnormal request, and K1 represents a preset judgment coefficient threshold. 2.The data security based remote control method for vehicle networking according to claim 1, wherein, Obtaining the location information of vehicle i corresponding to the pending request based on the location information to determine the monitoring range fi of vehicle i comprises: Take the position of the vehicle i as the center of a circle, and obtain the total number C of target vehicles within a preset radius r. If the total number C is less than a preset number threshold C1, the radius r is increased by a preset radius interval Δr, and the total number of corresponding target vehicles is obtained. The above steps are repeated until the radius is R1, and the total number of corresponding target vehicles is greater than the number threshold C1. The position of the vehicle i is taken as the center, and a circle with a radius of R1 is drawn as the monitoring range fi. Wherein, when R1≥Rmax, let R1=Rmax, and Rmax represents a preset maximum radius. If the total number C is greater than C1, the radius r is decreased by the radius interval Δr, and the total number of corresponding target vehicles is obtained. The above steps are repeated until the radius is r1, and the total number of corresponding target vehicles is less than the number threshold C1. The position of the vehicle i is taken as the center, and a circle with a radius of R2=r1+Δr is drawn as the monitoring range fi. 3.The data security based remote control method for vehicle networking according to claim 1, wherein, The position information of the vehicle i is obtained based on GPS or Beidou. 4.The data security based remote control method for vehicle networking according to claim 1, wherein, After the information platform rejects the abnormal request, the following steps are further included: The number of abnormal requests within a preset time period is counted. If the number exceeds a preset threshold, a prompt message is sent to a preset manager.

5. A remote control party system for a vehicle-to-everything based on data security, characterized in that, It includes: The acquisition module obtains the time point at which the information platform receives the request sent by the vehicle. The request uses the license plate number of the vehicle as a tag. Based on the tag and the time point, the pending request is determined. The correction module obtains the position information of the vehicle i corresponding to the pending request, determines the monitoring range fi of the vehicle i based on the position information, corrects the monitoring range fi based on the vehicle distribution within the monitoring range fi, and obtains the monitoring range Fi. The control module determines whether the pending request is an abnormal request based on the monitoring range Fi, and the information platform rejects the abnormal request. Based on the tag and the time point, the pending request is determined, which includes: The same tag is obtained as the request, which is recorded as a target request. The time point at which the information platform receives the target request is recorded as a target time point. The target time points within a preset acquisition period are obtained. The end of the acquisition period is the current time. The target time points are sorted in chronological order. The time interval between the target time points at adjacent sorting positions in the sorting is calculated. The time interval is sorted in chronological order to obtain a first sorting. From the time interval at the n-1th position in the first sorting, n1 time intervals are selected along the reverse chronological order. The mean value t of the selected time intervals is calculated. n represents the total number of time intervals in the first sorting, and n1 is a preset number. If the time difference Δt=T-t>Δt1, the last target request in the acquisition period is recorded as a pending request, and Δt1 represents a preset time difference threshold. Based on the vehicle distribution within the monitoring range fi, the monitoring range fi is corrected to obtain the monitoring range Fi, which includes: marking the vehicle not corresponding to the pending request as a target vehicle, obtaining a theoretical gravity center of the monitoring range fi, and obtaining a target direction when a distance between the theoretical gravity center and the vehicle i is greater than a preset distance threshold; constructing a circle with a radius r and a center at the position of the vehicle i, denoted as an initial circle, moving the initial circle along the target direction on a target line at a preset speed, the target line being a line connecting the vehicle i and the theoretical gravity center, and recording a total number of target vehicles in the initial circle in real time, denoted as a pending number; obtaining a center j of a position of an initial circle corresponding to a maximum pending number, determining a monitoring range Fi with the center j as the position of the vehicle i; determining whether the pending request is an abnormal request based on the monitoring range Fi includes: acquiring a proportion c of the number of target vehicles in the monitoring range Fi to all vehicles, and calculating a judgment coefficient , RR represents the radius of the monitoring range Fi, and η is a preset empirical coefficient. if the judgment coefficient K > K1, determining that the pending request is an abnormal request, K1 representing a preset judgment coefficient threshold.

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