Pedestrian-vehicle relation judgment method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a person-vehicle relationship judgment method, which comprises the following steps of: when a driver is not a vehicle owner of a driving vehicle, acquiring file data of the driver and the vehicle owner; based on the archive data, constructing a first relation graph between the driver and the vehicle owner; determining a first person relationship between the driver and the vehicle owner based on the first relationship graph; and based on the first person relationship, determining a person-vehicle relationship between the driver and the driving vehicle. When it is detected that the driver is not the owner of the driving vehicle, the archive data of the driver and the owner are obtained, and the first relation graph is constructed according to the archive data; therefore, the first person relationship between the driver and the vehicle owner can be accurately determined according to the first relationship map, and the person-vehicle relationship between the driver and the driving vehicle can be accurately determined according to the first person relationship.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a method, device, electronic equipment and storage medium for determining a relationship between a person and a vehicle. Background Art

[0002] With the increasing number of non-owners driving vehicles in daily life, such as car sharing and designated driver services, ensuring the proper relationship between the driver and the vehicle can prevent vehicle theft and other situations. Traditional methods rely on direct document inspection or owner authorization proof, but in actual use, there are still loopholes, such as document forgery, and the accuracy of the judgment of the relationship between the driver and the vehicle is still low. Therefore, how to provide a method for judging the relationship between the driver and the vehicle that can improve the accuracy of the judgment has become an urgent problem to be solved. Summary of the invention

[0003] The embodiment of the present invention provides a method for judging the relationship between a person and a vehicle, aiming to solve the problem of low accuracy in judging the relationship between a person and a vehicle in the prior art. When it is detected that the driver is not the owner of the vehicle being driven, the file data of the driver and the owner are obtained, and a first relationship graph is constructed based on the file data. Since the connection edges in the first relationship graph are determined based on the closeness relationship, the first person relationship between the driver and the owner can be accurately determined based on the first relationship graph, and thus the person-vehicle relationship between the driver and the vehicle being driven can be accurately determined based on the first person relationship.

[0004] In a first aspect, an embodiment of the present invention provides a method for determining a relationship between a person and a vehicle, the method comprising the following steps:

[0005] When the driver is not the owner of the vehicle, obtaining the profile data of the driver and the owner;

[0006] Based on the archive data, a first relationship graph between the driver and the car owner is constructed, wherein the first relationship graph includes at least one associated node and at least one connecting edge, wherein the associated node is an associated person who has a relationship with at least one of the driver and the car owner, and the connecting edge is determined according to the closeness relationship between the associated person and the driver or between the associated person and the car owner;

[0007] Determining a first personnel relationship between the driver and the vehicle owner based on the first relationship map;

[0008] Based on the first personnel relationship, a person-vehicle relationship between the driver and the driving vehicle is determined.

[0009] Optionally, the first relationship map includes the behavior data of the driver and the behavior data of the vehicle owner, and determining the first personnel relationship between the driver and the vehicle owner based on the first relationship map includes:

[0010] In the first relationship graph, traverse the node path between the driver and the car owner to obtain a node path set corresponding to the driver and the car owner;

[0011] The driver's behavior data is matched with the owner's behavior data to obtain a behavior matching result.

[0012] Based on at least one of the node path set and the behavior matching result, a first personnel relationship between the driver and the vehicle owner is determined.

[0013] Optionally, the personnel relationship includes a non-positive relationship, and determining the person-vehicle relationship between the driver and the driving vehicle based on the first personnel relationship includes:

[0014] When the first personnel relationship is the non-positive relationship, obtaining the profile data of the non-driving personnel in the driving vehicle;

[0015] The first relationship map is updated based on the profile data of the non-driving personnel to obtain a second relationship map between the non-driving personnel, the driving personnel, and the vehicle owner;

[0016] Based on the second relationship map, a person-vehicle relationship between the driver and the driving vehicle is determined.

[0017] Optionally, the personnel relationship includes a positive relationship and a non-positive relationship, and determining the person-vehicle relationship between the driver and the driving vehicle based on the second relationship map includes:

[0018] Determining a second personnel relationship between the non-driving person and the vehicle owner based on the second relationship graph;

[0019] When the second person relationship is the positive relationship, determining a third person relationship between the non-driving person and the driving person based on the second relationship map; and determining a person-vehicle relationship between the driving person and the driving vehicle based on the third person relationship;

[0020] When the second person relationship is the non-positive relationship, the travel records of the driver, the vehicle owner and the non-driver are obtained, and based on the travel records, the person-vehicle relationship between the driver and the driving vehicle is determined.

[0021] Optionally, determining the person-vehicle relationship between the driver and the driving vehicle based on the third person relationship includes:

[0022] When the third person relationship is the non-positive relationship, obtaining a driving image in the driving vehicle and a schedule table of the vehicle owner, wherein the driving image includes the driving person and the non-driving person;

[0023] Based on the driving image and the daily planning table, performing intention analysis on the driver to obtain an intention analysis result of the driver;

[0024] Based on the intention analysis result, the person-vehicle relationship between the driver and the driving vehicle is determined.

[0025] Optionally, the travel record includes travel activities, travel trajectories, and travel scenarios, and determining the person-vehicle relationship between the driver and the driving vehicle based on the travel record includes:

[0026] Inferring a fourth person relationship between the driver and the vehicle owner based on the travel activities, travel trajectories, and travel scenarios;

[0027] Based on the fourth personnel relationship, a person-vehicle relationship between the driver and the driving vehicle is determined.

[0028] Optionally, the inferring a fourth person relationship between the driver and the vehicle owner based on the travel activity, travel trajectory, and travel frequency includes:

[0029] Determining common activity data among the driver, the vehicle owner, and the non-driver based on the travel activities of the driver, the vehicle owner, and the non-driver;

[0030] Matching the travel trajectory of the driver with the travel trajectory of the non-driver to obtain a common travel trajectory between the vehicle owner and the driver;

[0031] Determining historical travel scenarios of the driver driving the vehicle based on the driver's travel trajectory and travel frequency;

[0032] Based on at least one of the common activity data, the common travel trajectory and the historical travel scenarios, a fourth person relationship between the driver and the vehicle owner is inferred.

[0033] In a second aspect, an embodiment of the present invention further provides a device for determining a relationship between a person and a vehicle, the device comprising:

[0034] A first acquisition module, for acquiring the profile data of the driver and the owner when the driver is not the owner of the vehicle;

[0035] A first construction module is used to construct a first relationship map between the driver and the car owner based on the archive data, wherein the first relationship map includes at least one associated node and at least one connecting edge, wherein the associated node is an associated person who has a relationship with at least one of the driver and the car owner, and the connecting edge is determined according to the closeness relationship between the associated person and the driver or between the associated person and the car owner;

[0036] A first determining module, configured to determine a first personnel relationship between the driver and the vehicle owner based on the first relationship map;

[0037] The second determination module is used to determine the person-vehicle relationship between the driver and the driving vehicle based on the first person relationship.

[0038] In a third aspect, an embodiment of the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for determining a human-vehicle relationship provided in an embodiment of the present invention when executing the computer program.

[0039] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for determining the relationship between a person and a vehicle provided in an embodiment of the invention are implemented.

[0040] In an embodiment of the present invention, when the driver is not the owner of the driving vehicle, the archival data of the driver and the owner are obtained; based on the archival data, a first relationship map between the driver and the owner is constructed, the first relationship map includes at least one association node and at least one connection edge, the association node is an associated person who has a relationship with at least one of the driver and the owner, and the connection edge is determined according to the affinity relationship between the associated person and the driver or the associated person and the owner; in the first relationship map, the first person relationship between the driver and the owner is determined; based on the first person relationship, the person-vehicle relationship between the driver and the driving vehicle is determined. When it is detected that the driver is not the owner of the driving vehicle, the archival data of the driver and the owner are obtained, and the first relationship map is constructed based on the archival data. Since the connection edge in the first relationship map is determined based on the affinity relationship, the first person relationship between the driver and the owner can be accurately determined according to the first relationship map, so that the person-vehicle relationship between the driver and the driving vehicle can be accurately determined according to the first person relationship. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0042] Figure 1 is a flow chart of a method for determining a person-vehicle relationship provided by an embodiment of the present invention;

[0043] Figure 2 is a flow chart of a personnel relationship determination method provided by an embodiment of the present invention;

[0044] Figure 3 is a structural schematic diagram of a human-vehicle relationship determination device provided in an embodiment of the present invention;

[0045] Figure 4 It is a structural schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0047] like Figure 1 As shown, Figure 1 : is a flow chart of a method for determining a person-vehicle relationship provided by an embodiment of the present invention, comprising:

[0048] 101. When the driver is not the owner of the vehicle, obtain the profile data of the driver and the owner.

[0049] In an embodiment of the present invention, the above-mentioned human-vehicle relationship judgment method can be applied to a human-vehicle relationship judgment platform. The above-mentioned human-vehicle relationship judgment platform can be constructed by a server or a server cluster. The above-mentioned server or server cluster can be any electronic device with functions such as data processing, data analysis, data storage, and data transmission.

[0050] The above-mentioned human-vehicle relationship judgment platform can be deployed with a personnel recognition model and a vehicle recognition model. The real-time road image is obtained by the road acquisition camera deployed on the road. By inputting the above-mentioned road image into the above-mentioned personnel recognition model and the vehicle recognition model, the personnel recognition result corresponding to the personnel recognition model and the vehicle recognition result corresponding to the vehicle recognition model can be obtained respectively, wherein the personnel recognition result can be the identity of the person in the vehicle, and the above-mentioned vehicle recognition result can be the license plate number. The owner of the driving vehicle is determined by the above-mentioned license plate number, and whether the above-mentioned driver is the owner of the driving vehicle is determined according to the above-mentioned identity. When the driver is not the owner of the driving vehicle, the driver's file data and the owner's file data are screened out in the personnel archive.

[0051] Among them, the archival data includes but is not limited to the identity information, social account activities, communication records, geographic location data, etc. of the personnel (i.e. the owner or driver or non-driver), and the above archival data can be stored in the above personnel archive in the form of data, and the corresponding archival data can be extracted from the archive when necessary. It should be noted that the above personnel archive can be directly deployed on the above human-vehicle relationship judgment platform, or can be deployed in any electronic device with data transmission function, and the corresponding personnel file is transmitted to the above human-vehicle relationship judgment platform through the data transmission function, so as to implement the human-vehicle relationship judgment method provided in the embodiment of the present invention.

[0052] 102. Based on the archival data, a first relationship map between the driver and the car owner is constructed.

[0053] In an embodiment of the present invention, the first relationship graph includes at least one associated node and at least one connecting edge, the associated node is an associated person who has a relationship with at least one of the driver and the car owner, and the connecting edge is determined based on the closeness of the relationship between the associated person and the driver or between the associated person and the car owner.

[0054] Among them, the driver's relatives, friends, colleagues and other related persons are determined through the identity information, social account activities, communication records and other data in the above-mentioned archive data, and each related person is used as a related node. When the related person has a relationship with the car owner or driver, a connection edge is established between the related person and the car owner or driver. The above-mentioned connection edge corresponds to a connection attribute and a connection weight. The above-mentioned connection attribute can be a relative attribute, a friend attribute, a colleague attribute, etc., which is used to determine the relationship between the two nodes corresponding to the connection edge. The above-mentioned connection weight is determined according to the closeness relationship between the two nodes. For example, under normal circumstances, direct relatives are closer than distant relatives, and the connection weight of the connection edge corresponding to the direct relative is often greater than the connection weight of the connection edge of the distant relative.

[0055] After the corresponding connection edges are established for the associated nodes, the personnel files of each associated person are obtained from the personnel file library, and the above personnel files are stored in the corresponding associated nodes. After the storage is completed, the above first relationship graph is obtained.

[0056] 103. Based on the first relationship map, determine a first personnel relationship between the driver and the vehicle owner.

[0057] In an embodiment of the present invention, the above-mentioned personnel relationships may include positive relationships and non-positive relationships, wherein positive relationships can be understood as legitimate relationships, that is, legitimate relationships such as relatives, friends, colleagues, etc., and the above-mentioned non-positive relationships can be understood as non-existent legitimate relationships, that is, improper relationships such as strangers, enemies, etc.

[0058] Specifically, the node path between the driver and the car owner can be traversed, and the first personnel relationship between the driver and the car owner can be determined through the above node path. For example, if there is an A1 associated node in the first relationship map, there is an A11 connection edge between the above A1 associated node and the above driver, and there is an A12 connection edge between the above A1 associated node and the above car owner, wherein the connection attribute of the above A11 connection edge is friend, and the connection attribute of the above A12 connection edge is also friend, then it can be determined that the driver and the car owner are in a friend relationship, and the corresponding first personnel relationship can be a positive relationship. Or the connection attribute of the A11 connection edge is friend, and the connection attribute of the A12 connection edge is relative, then it can be determined that the driver and the car owner are in a friend relationship, the associated person and the car owner are relatives, and the driver is a common friend of the associated person and the car owner, and the corresponding first personnel relationship can be a positive relationship. It should be noted that in the first relationship map, the fewer the number of nodes in the node path between the driver and the car owner, the higher the credibility of the determined first personnel relationship, and vice versa, the lower the credibility.

[0059] 104. Based on the first person relationship, determine a person-vehicle relationship between the driver and the driving vehicle.

[0060] In an embodiment of the present invention, the above-mentioned person-vehicle relationship may include a legitimate relationship and an illegitimate relationship. When the above-mentioned first person relationship is a positive relationship, the person-vehicle relationship between the driver and the driving vehicle is a legitimate relationship. When the above-mentioned first person relationship is an illegitimate relationship, the person-vehicle relationship between the driver and the driving vehicle is an illegitimate relationship. When the person-vehicle relationship between the driver and the driving vehicle is an illegitimate relationship, an abnormal warning may be sent to the owner of the driving vehicle and the local traffic management personnel, thereby achieving the purpose of avoiding vehicle theft.

[0061] In an embodiment of the present invention, when the driver is not the owner of the driving vehicle, the archival data of the driver and the owner are obtained; based on the archival data, a first relationship map between the driver and the owner is constructed, the first relationship map includes at least one association node and at least one connection edge, the association node is an associated person who has a relationship with at least one of the driver and the owner, and the connection edge is determined according to the affinity relationship between the associated person and the driver or the associated person and the owner; in the first relationship map, the first person relationship between the driver and the owner is determined; based on the first person relationship, the person-vehicle relationship between the driver and the driving vehicle is determined. When it is detected that the driver is not the owner of the driving vehicle, the archival data of the driver and the owner are obtained, and the first relationship map is constructed based on the archival data. Since the connection edge in the first relationship map is determined based on the affinity relationship, the first person relationship between the driver and the owner can be accurately determined according to the first relationship map, so that the person-vehicle relationship between the driver and the driving vehicle can be accurately determined according to the first person relationship.

[0062] It is understandable that in the specific implementation of this application, it involves archival data, relationship maps, travel records, daily schedules, identity information, social account activities, communication records, geographic location data and other related data. When the embodiments in this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of relevant data and the construction, training and use of related models need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0063] It should be noted that the method for determining the relationship between a person and a vehicle provided in the embodiment of the present invention can be applied to devices such as computers and servers that can determine the relationship between a person and a vehicle.

[0064] Optionally, in the step of determining the first personnel relationship between the driver and the car owner based on the first relationship graph, the node path between the driver and the car owner can also be traversed in the first relationship graph to obtain a node path set corresponding to the driver and the car owner; the driver's behavior data is matched with the car owner's behavior data to obtain a behavior matching result; and the first personnel relationship between the driver and the car owner is determined based on at least one of the node path set and the behavior matching result.

[0065] In an embodiment of the present invention, the first relationship graph includes a driver node corresponding to the driver and a car owner node corresponding to the car owner. The driver's profile data is stored in the driver node, and the car owner's profile data is stored in the car owner node. The driver's profile data includes the driver's behavior data, and the car owner's profile data includes the car owner's behavior data.

[0066] Specifically, the node path between the driver and the car owner can be traversed to obtain a direct relationship path and an indirect relationship path. The direct relationship path can be understood as the number of associated nodes in the node path is only one, and the indirect relationship path can be understood as the number of associated nodes in the node path is only multiple. According to the order of the number of associated nodes in the node path from small to large, the node paths are added one by one to the preset empty set, and the node path set is obtained after the addition is completed.

[0067] Since the fewer the number of nodes in the node path between the driver and the car owner, the higher the credibility of the determined first personnel relationship, and vice versa. Therefore, before adding the node path to the preset empty set, the node path can also be filtered, that is, the node path with a large amount of data of the associated nodes is filtered out, and only the node path with the number of associated nodes less than the preset number threshold is retained, and the retained node paths are added to the preset empty set according to the above number to obtain a node path set, so that relationship reasoning can be performed based on the node paths in the node path set to improve the credibility of the first personnel relationship. The above relationship reasoning can include direct relationship reasoning and indirect relationship reasoning. The above direct relationship reasoning is realized through the above direct relationship path, and the above indirect relationship reasoning is realized through the above indirect relationship path.

[0068] Specifically, if the car owner and the driver are directly connected by only one associated node (such as a common family member, friend, or colleague) in the node path in the first relationship graph, their possible relationship can be directly inferred, such as family members, friends, or colleagues. Alternatively, if the car owner and the driver have multiple associated nodes in the node path in the first relationship graph, their social circles can be analyzed through multi-step connections. For example, the driver may be the car owner's neighbor, a friend of a friend, or a colleague in a different department of the same company.

[0069] Alternatively, the above behavior data may include data such as travel frequency, travel time, travel location, daily activity patterns, etc., and the driver's behavior patterns such as the frequency, time and location of driving the car can be analyzed, combined with the owner's daily activity patterns for matching, and the possible occupational and living habits between the two can be inferred (i.e., behavior matching results), thereby determining the first personnel relationship. It is understandable that the above behavior data is stored in the personnel's files, so the time of adding the above behavior data (i.e., adding it to the corresponding file) is earlier than the current moment.

[0070] It should be noted that when the above-mentioned behavior data and the node path between the driver and the car owner can be obtained at the same time, the first first-person relationship can be determined through the above-mentioned node path, and the second first-person relationship can be determined through the behavior data. The above-mentioned first first-person relationship and the second first-person relationship are verified. If they are the same, the first-person relationship is determined to be a positive relationship. If they are not the same, the first-person relationship is determined to be a non-positive relationship.

[0071] Alternatively, when only the above-mentioned behavior data or only the node path between the driver and the car owner can be obtained, the above-mentioned first personnel relationship can be determined only through the above-mentioned behavior data or the above-mentioned node path.

[0072] Optionally, in the step of determining the human-vehicle relationship between the driver and the driving vehicle based on the first personnel relationship, when the first personnel relationship is a non-positive relationship, the file data of the non-driver in the driving vehicle can be obtained; based on the driver's file data, the first relationship map is updated to obtain the second relationship map between the non-driver and the driver and the vehicle owner; based on the second relationship map, the human-vehicle relationship between the driver and the driving vehicle is determined.

[0073] In an embodiment of the present invention, the above-mentioned personnel relationship includes a non-positive relationship. When the first personnel relationship is a non-positive relationship, the file data of the non-driving personnel (i.e., the co-driver, or the rear passenger) in the driving vehicle can also be obtained.

[0074] According to the archival data, the associated persons who have a relationship with the non-driver are determined, each associated person is added as an associated node to the first relationship map, and a connection edge is established between each associated node and other nodes with which the relationship exists. After the establishment is completed, the archival data is added to the corresponding associated node, the update of the above-mentioned first relationship map is completed, and the above-mentioned second relationship map is obtained. The node path between the non-driver and the car owner, and the node path between the non-driver and the driver in the second relationship map are traversed. The personnel relationship between the non-driver and the driver, and the personnel relationship between the non-driver and the car owner are determined.

[0075] When the personnel relationship between the non-driver and the driver is a positive relationship, and the personnel relationship between the non-driver and the vehicle owner is also a positive relationship, the person-vehicle relationship between the driver and the driving vehicle is a legitimate relationship. On the contrary, when the personnel relationship between the non-driver and the driver is a non-positive relationship, or the personnel relationship between the non-driver and the vehicle owner is a non-positive relationship, or the personnel relationship between the non-driver, the driver and the vehicle owner are all non-non-positive relationships, the person-vehicle relationship between the driver and the driving vehicle is an illegitimate relationship. At this time, the abnormal warning information can be sent to the vehicle owner and the local traffic management department.

[0076] Optionally, in the step of determining the human-vehicle relationship between the driver and the driving vehicle based on the second relationship map, the second personnel relationship between the non-driver and the vehicle owner can also be determined based on the second relationship map; when the second personnel relationship is a positive relationship, the third personnel relationship between the non-driver and the driver is determined based on the second relationship map; and based on the third personnel relationship, the human-vehicle relationship between the driver and the driving vehicle is determined; when the second personnel relationship is a non-positive relationship, the travel records of the driver, the vehicle owner and the non-driver are obtained, and based on the travel records, the human-vehicle relationship between the driver and the driving vehicle is determined.

[0077] In an embodiment of the present invention, personnel relationships include positive relationships and non-positive relationships. The method for determining the above-mentioned second personnel relationship is consistent with the method for determining the above-mentioned first personnel relationship, that is, in the second relationship graph, the node path between the non-driving personnel and the car owner is traversed to obtain a corresponding node path set, and at the same time, the behavior data of the car owner is extracted from the car owner node and the behavior data of the non-driving personnel is extracted from the non-driving personnel node, so as to determine the behavior matching result corresponding to the car owner and the non-driving personnel based on the behavior data of the car owner and the behavior data of the non-driving personnel, and determine the second personnel relationship based on at least one of the node path set and the behavior matching result between the car owner and the non-driving personnel.

[0078] The method for determining the third personnel relationship mentioned above is consistent with the method for determining the first personnel relationship or the second personnel relationship. It is only necessary to replace the corresponding behavior data or node path, and the effect is the same. In order to avoid repetition and redundancy, it will not be repeated here.

[0079] When the second personnel relationship is a positive relationship, it means that the non-driver and the car owner have a positive relationship. At this time, the non-driver can be used as a relationship bridge to determine the personnel relationship between the driver and the car owner. Specifically, when the second personnel relationship is a positive relationship and the third personnel relationship is also a positive relationship, the personnel relationship between the driver and the car owner is also a positive relationship. On the contrary, if either the second personnel relationship or the third personnel relationship is a non-positive relationship, the personnel relationship between the driver and the car owner is a non-positive relationship.

[0080] When the second person relationship is a non-positive relationship, it means that the non-driver and the car owner have a non-positive relationship. At this time, the non-driver cannot be used as a relationship bridge to determine the personnel relationship between the driver and the car owner. Therefore, the travel records of the driver, the car owner and the non-driver can be obtained, and the personnel relationship between the driver and the car owner can be inferred based on the travel records.

[0081] When the personal relationship between the driver and the car owner is a positive relationship, the person-vehicle relationship between the driver and the driving vehicle is a legitimate relationship. When the personal relationship between the driver and the car owner is a non-positive relationship, the person-vehicle relationship between the driver and the driving vehicle is an improper relationship.

[0082] Optionally, in the step of determining the human-vehicle relationship between the driver and the driving vehicle based on the third-person relationship, when the third-person relationship is a non-positive relationship, the driving image in the driving vehicle and the owner's daily schedule can be obtained; based on the driving image and the daily schedule, the driver's intention is analyzed to obtain the driver's intention analysis result; based on the intention analysis result, the human-vehicle relationship between the driver and the driving vehicle is determined.

[0083] In an embodiment of the present invention, the driving image includes a driver and a non-driver. When the second person relationship is a positive relationship, but the third person relationship is a non-positive relationship, the driver's intention analysis can be performed to obtain the intention analysis result, so that when the third person relationship is a non-positive relationship, the person-vehicle relationship between the driver and the driving vehicle can be determined according to the intention analysis result. The above-mentioned driving image can be understood as an image of the interior of the vehicle during driving. It can be understood that the acquisition of the above-mentioned driving image must comply with local laws and regulations and can only be obtained after the permission of users such as the owner.

[0084] Specifically, the driving image may include an image of the driving vehicle at the starting point ready to depart, and in the image at the starting point ready to depart, a situation in which the driver and the non-driver meet is determined. Consider a situation in which a non-driver meets a driver. If the non-driver invites the driver to join the trip, this may imply that the driver is introduced based on trust in the non-driver or some emergency need. At this time, the intention analysis result is that the driver intends to help the non-driver, and the person-vehicle relationship between the driver and the driving vehicle is a legitimate relationship.

[0085] Alternatively, the possible reasons why the owner allowed the driver to drive the vehicle can also be inferred from the above schedule. For example, whether the owner is unable to drive the vehicle himself due to health, legal restrictions (such as drunk driving regulations), time conflicts, etc., and thus entrusts others. If the intention analysis result shows that the driver intends to complete the owner's entrustment, the relationship between the driver and the driving vehicle is a legitimate relationship.

[0086] Alternatively, the above-mentioned schedule may include a historical schedule, and based on the historical schedule, the driver's destination and time of driving the vehicle are evaluated to see whether they are consistent with the owner's daily activities, work needs or personal plans. This can help infer whether there is a business, work cooperation or private assistance relationship between the owner and the driver. If the intention analysis result shows that the driver intends to complete the above relationship and provide assistance to the owner, the person-vehicle relationship between the driver and the driving vehicle is a legitimate relationship.

[0087] Alternatively, the car owner can be judged based on the schedule to determine whether he needs to use the sharing economy platform, that is, whether it is possible to temporarily obtain driving rights through the sharing economy platform (such as car rental services, carpooling services). This indicates that there may be a temporary service usage relationship between the driver and the driver. If the intention analysis result shows that the driver intends to use the above-mentioned car rental services, carpooling services, etc., then the person-vehicle relationship between the driver and the driving vehicle is a legitimate relationship.

[0088] Alternatively, intention analysis can be performed based on the above-mentioned schedule and the above-mentioned driving image at the same time to obtain a first intention analysis result corresponding to the schedule and a second intention analysis result corresponding to the driving image. When the first intention analysis result and the second intention analysis result are both positive intentions, that is, helping the car owner or non-driver, the person-vehicle relationship between the driver and the driving vehicle is a legitimate relationship. On the contrary, if the first intention analysis result or the second intention analysis result is not a positive intention, for example, the intention to steal, then the person-vehicle relationship between the driver and the driving vehicle is an improper relationship.

[0089] Optionally, in the step of determining the person-vehicle relationship between the driver and the driving vehicle based on travel records, a fourth person relationship between the driver and the car owner can also be inferred based on travel activities, travel trajectories and travel scenarios; based on the fourth person relationship, the person-vehicle relationship between the driver and the driving vehicle is determined.

[0090] In an embodiment of the present invention, travel records include travel activities, travel trajectories and travel scenes. Based on the travel activities of drivers, car owners and non-drivers, common activity data between drivers, car owners and non-drivers can be determined, and the travel trajectory of the driver is matched with the travel trajectory of the non-driver to obtain the common travel trajectory between the car owner and the driver. Based on the travel trajectory and travel frequency of the driver, the historical travel scenes of the driver driving the vehicle can be determined.

[0091] When the above common activity data exists between the driver, the car owner and the non-driver, or the driver and the non-driver have a common travel trajectory, or the travel scenario meets the conventional demand or service relationship, such as regular pick-up and drop-off, carpooling services, etc., the fourth person relationship is a positive relationship. Otherwise, the fourth person relationship is a non-positive relationship.

[0092] When the fourth person is in a positive relationship, the relationship between the driver and the vehicle is a legitimate relationship. When the fourth person is in an inappropriate relationship, the relationship between the driver and the vehicle is an inappropriate relationship. At this time, an abnormal warning message can be sent to the vehicle owner and relevant departments such as the local traffic management department.

[0093] Optionally, in the step of inferring the fourth-person relationship between the driver and the car owner based on travel activities, travel trajectory and travel frequency, the common activity data between the driver, the car owner and the non-driver can also be determined based on the travel activities of the driver, the car owner and the non-driver; the travel trajectory of the driver is matched with the travel trajectory of the non-driver to obtain the common travel trajectory between the car owner and the driver; based on the travel trajectory and travel frequency of the driver, the historical travel scenarios of the driver driving the vehicle are determined; based on at least one of the common activity data, the common travel trajectory and the historical travel scenarios, the fourth-person relationship between the driver and the car owner is inferred.

[0094] In an embodiment of the present invention, it is possible to check whether the driver, non-driver and car owner have records of activities they have participated in together, such as family gatherings, company activities or social events. The common activity background can strengthen the rationality of the relationship chain between them. When there is a common activity background (i.e., common activity data), the fourth person relationship is a positive relationship.

[0095] The travel trajectory can be a GPS trajectory, and the parking record data during the trip can be determined based on the GPS trajectory. Using data such as GPS trajectory and parking records, the time and location patterns of drivers and non-drivers when using the vehicle (i.e., common travel trajectories) are analyzed. A consistent common travel trajectory or destination may indicate that the main driver uses the vehicle based on some authorization or habit. When there is a common travel trajectory and the destination is consistent, the fourth person relationship is a positive relationship.

[0096] Based on the above travel scenarios, we can also carefully analyze the specific situations in which the driver uses the vehicle, such as time, location, frequency, etc., to determine whether it can imply some regular demand or service relationship, such as regular pick-up and drop-off, carpooling services, etc. When there is some regular demand or service relationship in the historical travel scenarios, the fourth person relationship is a positive relationship.

[0097] Alternatively, at least one of the above-mentioned common activity data, common travel trajectory and historical travel scenes (or understood as any combination) can be comprehensively considered. For example, when there is a common activity background (i.e., common activity data), and there is a common travel trajectory with the same destination, and there is a certain routine demand or service relationship in the historical travel scene, the fourth person relationship is a positive relationship. In any case, if there is no common travel trajectory or no common activity data or no routine demand or service relationship in the common activity data, common travel trajectory and historical travel scenes, the fourth person relationship is a non-positive relationship. It can be understood that after comprehensively considering the three types of data, namely, common activity data, common travel trajectory and historical travel scenes as the basis for determining the fourth person relationship, the accuracy of determining the fourth person relationship can be improved, thereby improving the accuracy of judging the person-vehicle relationship.

[0098] like Figure 2 FIG. 1 is a flowchart of a method for determining a personnel relationship provided by an embodiment of the present invention, comprising the following steps:

[0099] Step 1: Data collection step, collecting the personal information of the main driver (i.e. the driver), the co-driver (i.e. the non-driver) and the owner through the data collection module;

[0100] Step 2: Perform data cleaning and normalization on the personal information of the main driver (i.e., the driver), the co-driver (i.e., the non-driver), and the owner to obtain the profile data of the main driver, the co-driver, and the owner;

[0101] Step 3: construct a relationship graph (i.e., the second relationship graph) based on the archival data of the driver, the co-driver, and the owner;

[0102] Step 4: Analyze the relationship between the driver and the car owner (i.e., the first person relationship) based on the relationship graph to determine whether there is a legitimate relationship between the driver and the car owner (i.e., determine whether the first person relationship is a positive relationship or a negative relationship). If so, the first person relationship between the driver and the car owner is a positive relationship.

[0103] Step 5: If there is no legitimate relationship between the main driver and the car owner (i.e., the first personnel relationship is a non-positive relationship), then the relationship between the co-driver and the car owner (i.e., the second personnel relationship) is analyzed based on the relationship graph;

[0104] Step 6: If the co-driver and the car owner have a legitimate relationship (i.e., the second person relationship is a positive relationship), then based on the relationship graph, analyze whether the co-driver and the car owner have a legitimate relationship (i.e., the third person relationship);

[0105] Step 7: If there is a legitimate relationship between the main driver and the co-driver (i.e. the third person relationship is a positive relationship), the co-driver is used as a medium (or understood as a bridge between the main driver and the car owner) to determine that there is a legitimate relationship between the main driver and the car owner;

[0106] Step 8: If there is no legitimate relationship between the main driver and the co-driver (i.e., the third person relationship is a non-positive relationship), the scene of the encounter between the main driver and the co-driver and the intention of the main driver are analyzed to determine whether there is a legitimate relationship between the main driver and the car owner (i.e., the fourth person relationship. It can be understood that the fourth person relationship is obtained based on the intention analysis, and the first person relationship is obtained based on the relationship map);

[0107] Step 9: If there is no legitimate relationship between the passenger and the car owner, it is possible to infer whether there is a legitimate relationship between the driver and the car owner through indirect methods (i.e. based on travel activities, travel trajectories and travel scenarios).

[0108] It can be understood that after the personnel relationship between the main driver (i.e., the driver) and the car owner is determined through the above-mentioned personnel relationship judgment method, the person-vehicle relationship between the driver and the driving vehicle can be determined through the personnel relationship between the driver and the car owner. Then, when the person-vehicle relationship is an improper relationship, an abnormal alarm information can be sent to the car owner and relevant departments such as the local traffic management department to avoid vehicle theft.

[0109] like Figure 3 As shown, an embodiment of the present invention further provides a device for determining a relationship between a person and a vehicle, comprising:

[0110] The first acquisition module 301 is used to acquire the profile data of the driver and the owner when the driver is not the owner of the vehicle;

[0111] A first construction module 302 is used to construct a first relationship graph between the driver and the car owner based on the archive data, wherein the first relationship graph includes at least one associated node and at least one connecting edge, wherein the associated node is an associated person who has a relationship with at least one of the driver and the car owner, and the connecting edge is determined according to the closeness relationship between the associated person and the driver or between the associated person and the car owner;

[0112] A first determining module 303, configured to determine a first personnel relationship between the driver and the vehicle owner based on the first relationship map;

[0113] The second determination module 304 is used to determine the person-vehicle relationship between the driver and the driving vehicle based on the first person relationship.

[0114] Optionally, the first relationship graph includes the behavior data of the driver and the behavior data of the vehicle owner, and the first determination module 303 includes:

[0115] A first traversal submodule, configured to traverse the node path between the driver and the car owner in the first relationship graph to obtain a node path set corresponding to the driver and the car owner;

[0116] The first matching submodule is used to match the driver's behavior data with the owner's behavior data to obtain a behavior matching result.

[0117] The first determination submodule is used to determine a first personnel relationship between the driver and the vehicle owner based on at least one of the node path set and the behavior matching result.

[0118] Optionally, the personnel relationship includes a non-positive relationship, and the second determining module 304 includes:

[0119] A first acquisition submodule, configured to acquire file data of a non-driving person in the driving vehicle when the first personnel relationship is the non-positive relationship;

[0120] A first updating submodule, configured to update the first relationship map based on the profile data of the non-driving personnel, and obtain a second relationship map between the non-driving personnel, the driving personnel, and the vehicle owner;

[0121] The second determination submodule is used to determine the person-vehicle relationship between the driver and the driving vehicle based on the second relationship map.

[0122] Optionally, the personnel relationship includes a positive relationship and a negative relationship, and the second determining submodule includes:

[0123] A first determining unit, configured to determine a second personnel relationship between the non-driving person and the vehicle owner based on the second relationship map;

[0124] a second determining unit, configured to determine, when the second person relationship is the positive relationship, a third person relationship between the non-driving person and the driving person based on the second relationship map; and determine a person-vehicle relationship between the driving person and the driving vehicle based on the third person relationship;

[0125] The third determination unit is used to obtain the travel records of the driver, the vehicle owner and the non-driver when the second personnel relationship is the non-positive relationship, and determine the person-vehicle relationship between the driver and the driving vehicle based on the travel records.

[0126] Optionally, the second determining unit includes:

[0127] A first acquisition subunit is used for acquiring a driving image in the driving vehicle and a schedule of the vehicle owner when the third person relationship is the non-positive relationship, wherein the driving image includes the driving person and the non-driving person;

[0128] A first analysis subunit is used to perform intention analysis on the driver based on the driving image and the daily planning table to obtain an intention analysis result of the driver;

[0129] The first determination subunit is used to determine the person-vehicle relationship between the driver and the driving vehicle based on the intention analysis result.

[0130] Optionally, the travel record includes travel activities, travel tracks and travel scenes, and the third determining unit includes:

[0131] A first inference subunit, configured to infer a fourth person relationship between the driver and the vehicle owner based on the travel activity, travel trajectory, and travel scene;

[0132] The second determining subunit is used to determine the person-vehicle relationship between the driver and the driving vehicle based on the fourth person relationship.

[0133] Optionally, the first inference subunit includes:

[0134] a third determining subunit, configured to determine common activity data among the driver, the vehicle owner and the non-driver based on the travel activities of the driver, the vehicle owner and the non-driver;

[0135] A first matching subunit is used to match the travel trajectory of the driver with the travel trajectory of the non-driver to obtain a common travel trajectory between the vehicle owner and the driver;

[0136] A fourth determining subunit, configured to determine a historical travel scenario of the driver driving the vehicle based on the driver's travel trajectory and travel frequency;

[0137] The second inference subunit is used to infer a fourth person relationship between the driver and the car owner based on at least one of the common activity data, the common travel trajectory and the historical travel scenes.

[0138] like Figure 4 As shown, an embodiment of the present invention further provides an electronic device, characterized in that it includes a processor, and the processor can execute any one of the above-mentioned methods for determining the relationship between a person and a vehicle.

[0139] Specifically, it includes a processor 401 and a memory 402, and a computer program for executing a method for determining a person-vehicle relationship, which is stored in the memory 402 and can be run on the processor 401, wherein:

[0140] The processor 401 runs the computer program of the vehicle-person relationship determination method stored in the memory 402 to perform the following steps:

[0141] When the driver is not the owner of the vehicle, obtaining the profile data of the driver and the owner;

[0142] Based on the archive data, a first relationship graph between the driver and the car owner is constructed, wherein the first relationship graph includes at least one associated node and at least one connecting edge, wherein the associated node is an associated person who has a relationship with at least one of the driver and the car owner, and the connecting edge is determined according to the closeness relationship between the associated person and the driver or between the associated person and the car owner;

[0143] Determining a first personnel relationship between the driver and the vehicle owner based on the first relationship map;

[0144] Based on the first personnel relationship, a person-vehicle relationship between the driver and the driving vehicle is determined.

[0145] Optionally, the first relationship map includes the behavior data of the driver and the behavior data of the vehicle owner, and the processor 401 determines the first personnel relationship between the driver and the vehicle owner based on the first relationship map, including:

[0146] In the first relationship graph, traverse the node path between the driver and the car owner to obtain a node path set corresponding to the driver and the car owner;

[0147] The driver's behavior data is matched with the owner's behavior data to obtain a behavior matching result.

[0148] Based on at least one of the node path set and the behavior matching result, a first personnel relationship between the driver and the vehicle owner is determined.

[0149] Optionally, the personnel relationship includes a non-positive relationship, and the processor 401 determines the person-vehicle relationship between the driver and the driving vehicle based on the first personnel relationship, including:

[0150] When the first personnel relationship is the non-positive relationship, obtaining the profile data of the non-driving personnel in the driving vehicle;

[0151] The first relationship map is updated based on the profile data of the non-driving personnel to obtain a second relationship map between the non-driving personnel, the driving personnel, and the vehicle owner;

[0152] Based on the second relationship map, a person-vehicle relationship between the driver and the driving vehicle is determined.

[0153] Optionally, the personnel relationship includes a positive relationship and a non-positive relationship, and the processor 401 determines the person-vehicle relationship between the driver and the driving vehicle based on the second relationship map, including:

[0154] Determining a second personnel relationship between the non-driving person and the vehicle owner based on the second relationship graph;

[0155] When the second person relationship is the positive relationship, determining a third person relationship between the non-driving person and the driving person based on the second relationship map; and determining a person-vehicle relationship between the driving person and the driving vehicle based on the third person relationship;

[0156] When the second person relationship is the non-positive relationship, the travel records of the driver, the vehicle owner and the non-driver are obtained, and based on the travel records, the person-vehicle relationship between the driver and the driving vehicle is determined.

[0157] Optionally, the determining of the person-vehicle relationship between the driver and the driving vehicle based on the third person relationship performed by the processor 401 includes:

[0158] When the third person relationship is the non-positive relationship, obtaining a driving image in the driving vehicle and a schedule table of the vehicle owner, wherein the driving image includes the driving person and the non-driving person;

[0159] Based on the driving image and the daily planning table, performing intention analysis on the driver to obtain an intention analysis result of the driver;

[0160] Based on the intention analysis result, the person-vehicle relationship between the driver and the driving vehicle is determined.

[0161] Optionally, the travel record includes travel activities, travel trajectories, and travel scenarios, and the processor 401 determines the person-vehicle relationship between the driver and the driving vehicle based on the travel record, including:

[0162] Inferring a fourth person relationship between the driver and the vehicle owner based on the travel activities, travel trajectories, and travel scenarios;

[0163] Based on the fourth personnel relationship, a person-vehicle relationship between the driver and the driving vehicle is determined.

[0164] Optionally, the processor 401 performs the inferring of a fourth person relationship between the driver and the vehicle owner based on the travel activity, travel trajectory, and travel frequency, including:

[0165] Determining common activity data among the driver, the vehicle owner, and the non-driver based on the travel activities of the driver, the vehicle owner, and the non-driver;

[0166] Matching the travel trajectory of the driver with the travel trajectory of the non-driver to obtain a common travel trajectory between the vehicle owner and the driver;

[0167] Determining historical travel scenarios of the driver driving the vehicle based on the driver's travel trajectory and travel frequency;

[0168] Based on at least one of the common activity data, the common travel trajectory and the historical travel scenarios, a fourth person relationship between the driver and the vehicle owner is inferred.

[0169] An embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the computer program implements the various processes of the human-vehicle relationship judgment method or the application-side human-vehicle relationship judgment method provided in the embodiment of the present invention, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0170] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the above-mentioned computer program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the above-mentioned computer-readable storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0171] The above disclosure is only the preferred embodiment of the present invention, which certainly cannot be used to limit the scope of the present invention. Therefore, equivalent changes made according to the claims of the present invention are still within the scope of the present invention.

Claims

1. A method for determining a relationship between a person and a vehicle, characterized in that: The method comprises the following steps: When the driver is not the owner of the vehicle, obtaining the profile data of the driver and the owner; Based on the archive data, a first relationship graph between the driver and the car owner is constructed, wherein the first relationship graph includes at least one associated node and at least one connecting edge, wherein the associated node is an associated person who has a relationship with at least one of the driver and the car owner, and the connecting edge is determined according to the closeness relationship between the associated person and the driver or between the associated person and the car owner; Determining a first personnel relationship between the driver and the vehicle owner based on the first relationship map; Based on the first personnel relationship, a person-vehicle relationship between the driver and the driving vehicle is determined.

2. The method for determining the relationship between a person and a vehicle according to claim 1, wherein: The first relationship map includes the behavior data of the driver and the behavior data of the vehicle owner. The determining of the first personnel relationship between the driver and the vehicle owner based on the first relationship map includes: In the first relationship graph, traverse the node path between the driver and the car owner to obtain a node path set corresponding to the driver and the car owner; The driver's behavior data is matched with the owner's behavior data to obtain a behavior matching result. Based on at least one of the node path set and the behavior matching result, a first personnel relationship between the driver and the vehicle owner is determined.

3. The method for determining the relationship between a person and a vehicle according to claim 1, wherein: The personnel relationship includes a non-positive relationship, and determining the person-vehicle relationship between the driver and the driving vehicle based on the first personnel relationship includes: When the first personnel relationship is the non-positive relationship, obtaining the profile data of the non-driving personnel in the driving vehicle; The first relationship map is updated based on the profile data of the non-driving personnel to obtain a second relationship map between the non-driving personnel, the driving personnel, and the vehicle owner; Based on the second relationship map, a person-vehicle relationship between the driver and the driving vehicle is determined.

4. The method for determining the relationship between a person and a vehicle as claimed in claim 3, characterized in that: The personnel relationship includes a positive relationship and a negative relationship, and the determining of the person-vehicle relationship between the driver and the driving vehicle based on the second relationship map includes: Determining a second personnel relationship between the non-driving person and the vehicle owner based on the second relationship graph; When the second person relationship is the positive relationship, determining a third person relationship between the non-driving person and the driving person based on the second relationship map; and determining a person-vehicle relationship between the driving person and the driving vehicle based on the third person relationship; When the second person relationship is the non-positive relationship, the travel records of the driver, the vehicle owner and the non-driver are obtained, and based on the travel records, the person-vehicle relationship between the driver and the driving vehicle is determined.

5. The method for determining the relationship between a person and a vehicle as claimed in claim 4, characterized in that: The determining, based on the third person relationship, a person-vehicle relationship between the driver and the driving vehicle includes: When the third person relationship is the non-positive relationship, obtaining a driving image in the driving vehicle and a schedule table of the vehicle owner, wherein the driving image includes the driving person and the non-driving person; Based on the driving image and the daily planning table, performing intention analysis on the driver to obtain an intention analysis result of the driver; Based on the intention analysis result, the person-vehicle relationship between the driver and the driving vehicle is determined.

6. The method for determining the relationship between a person and a vehicle as claimed in claim 4, characterized in that: The travel record includes travel activities, travel trajectories, and travel scenarios. The determining of the person-vehicle relationship between the driver and the driving vehicle based on the travel record includes: Inferring a fourth person relationship between the driver and the vehicle owner based on the travel activities, travel trajectories, and travel scenarios; Based on the fourth personnel relationship, a person-vehicle relationship between the driver and the driving vehicle is determined.

7. The method for determining the relationship between a person and a vehicle as claimed in claim 6, characterized in that: The inferring a fourth person relationship between the driver and the vehicle owner based on the travel activity, travel trajectory, and travel frequency includes: Determining common activity data among the driver, the vehicle owner, and the non-driver based on the travel activities of the driver, the vehicle owner, and the non-driver; Matching the travel trajectory of the driver with the travel trajectory of the non-driver to obtain a common travel trajectory between the vehicle owner and the driver; Determining historical travel scenarios of the driver driving the vehicle based on the driver's travel trajectory and travel frequency; Based on at least one of the common activity data, the common travel trajectory and the historical travel scenarios, a fourth person relationship between the driver and the vehicle owner is inferred.

8. A device for determining the relationship between a person and a vehicle, characterized in that: The human-vehicle relationship determination device comprises: A first acquisition module, for acquiring the profile data of the driver and the owner when the driver is not the owner of the vehicle; A first construction module is used to construct a first relationship map between the driver and the car owner based on the archive data, wherein the first relationship map includes at least one associated node and at least one connecting edge, wherein the associated node is an associated person who has a relationship with at least one of the driver and the car owner, and the connecting edge is determined according to the closeness relationship between the associated person and the driver or between the associated person and the car owner; A first determining module, configured to determine a first personnel relationship between the driver and the vehicle owner based on the first relationship map; The second determination module is used to determine the person-vehicle relationship between the driver and the driving vehicle based on the first person relationship.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps in the method for determining a human-vehicle relationship as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the method for determining a human-vehicle relationship as claimed in any one of claims 1 to 7 are implemented.

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