Method, device, equipment and medium for processing traffic violation information

Abstract

Embodiments of the present disclosure relate to methods, devices, equipment, and computer-readable storage media for processing traffic violation information. A method for processing traffic violation information includes obtaining traffic violation information of a target user; determining whether the traffic violation indicated by the traffic violation information matches a target trip of the target user; and if it is determined that the traffic violation matches the target trip, providing a processing result for the traffic violation information based on the behavior of the target user during the target trip, the processing result indicating the degree of association between the behavior and the traffic violation. Embodiments of the present disclosure can automatically identify valid parking tickets from the traffic violation information of the target user and determine the degree of association with the target user's personal behavior based on the identification result, thereby improving the efficiency of the taxi-hailing platform in processing traffic violation information.

Description

Technical Field

[0001] Embodiments of the present disclosure generally relate to the field of transportation, and more particularly to methods, devices, equipment, and computer-readable storage media for processing traffic violation information. Background Art

[0002] With the popularization of mobile Internet and smart devices, taxi-hailing platforms are widely used in people's lives. Passengers can use client software installed on user devices (such as mobile phones) to publish taxi information and communicate directly with drivers who accept orders, thereby greatly improving taxi-hailing efficiency.

[0003] The taxi-hailing platform can provide navigation services to drivers. When the driver parks at an illegal location (for example, to pick up or drop off passengers) according to the navigation guidance, the taxi-hailing platform needs to pay the driver the corresponding illegal parking fee. However, if the driver parks illegally while driving or due to personal behavior, the taxi-hailing platform does not need to pay the driver the illegal parking fee or only needs to pay the driver a smaller illegal parking fee. Therefore, it is expected to automatically classify traffic violation information to improve processing efficiency. Summary of the invention

[0004] Embodiments of the present disclosure provide a method, an apparatus, a device, and a computer-readable storage medium for processing traffic violation information.

[0005] In a first aspect of the present disclosure, a method for processing traffic violation information is provided. The method includes obtaining traffic violation information of a target user; determining whether the traffic violation indicated by the traffic violation information matches a target trip of the target user; and if it is determined that the traffic violation matches the target trip, providing a processing result for the traffic violation information based on the behavior of the target user during the target trip, the processing result indicating the degree of association between the behavior and the traffic violation.

[0006] In a second aspect of the present disclosure, a device for processing traffic violation information is provided. The device includes an information acquisition module configured to acquire traffic violation information of a target user; a trip matching module configured to determine whether the traffic violation indicated by the traffic violation information matches a target trip of the target user; and a result providing module configured to provide a processing result for the traffic violation information based on the behavior of the target user during the target trip if it is determined that the traffic violation matches the target trip, the processing result indicating the degree of association between the behavior and the traffic violation.

[0007] In a third aspect of the present disclosure, an electronic device is provided, comprising one or more processors; and a memory for storing one or more programs, which, when executed by one or more processors, enables the electronic device to implement the method described in the first aspect of the present disclosure.

[0008] In a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method described in the first aspect of the present disclosure is implemented.

[0009] In a fifth aspect of the present disclosure, a computer program product is provided, which includes computer executable instructions, wherein the computer executable instructions implement the method described according to the first aspect of the present disclosure when executed by a processor.

[0010] This Summary is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description. This Summary is not intended to identify key features or essential features of the present disclosure, nor is it intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The above and other objects, features and advantages of the present disclosure will become more apparent through a more detailed description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present disclosure.

[0012] Figure 1 A block diagram illustrating an example environment in which embodiments of the present disclosure can be implemented;

[0013] Figure 2 A flowchart showing an example method for processing traffic violation information according to an embodiment of the present disclosure is shown;

[0014] Figure 3 A flowchart showing an example method for determining a time matching result between a traffic violation and a target trip according to an embodiment of the present disclosure is shown;

[0015] Figure 4 A flowchart showing an example method for determining a location matching result of a traffic violation and a target trip according to an embodiment of the present disclosure is shown;

[0016] Figure 5 A flowchart showing another example method for determining a location matching result of a traffic violation and a target trip according to an embodiment of the present disclosure is shown;

[0017] Figure 6 A block diagram showing an example apparatus for processing traffic violation information according to an embodiment of the present disclosure; and

[0018] Figure 7 A block diagram of an example electronic device capable of implementing various embodiments of the present disclosure is shown.

[0019] In the various drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0020] The preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the preferred embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0021] As used herein, the term "including" and its variations mean open inclusion, i.e., "including but not limited to". Unless otherwise stated, the term "or" means "and / or". The term "based on" means "based at least in part on". The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0022] As mentioned above, the taxi platform can provide navigation services to the driver. When the driver parks at an illegal location (for example, to pick up or drop off passengers) according to the navigation guidance, the taxi platform needs to pay the driver the corresponding illegal parking fee. However, if the driver parks illegally while driving or due to personal behavior, the taxi platform does not need to pay the driver the illegal parking fee or only needs to pay the driver a smaller illegal parking fee. Therefore, it is expected to automatically classify traffic violation information to improve processing efficiency.

[0023] The embodiments of the present disclosure propose a solution for processing traffic violation information, which can solve one or more of the above problems and other potential problems. The solution obtains the traffic violation information of the target user and determines whether the traffic violation indicated by the traffic violation information matches the target trip of the target user. In the case of determining that the traffic violation matches the target trip, the solution provides a processing result for the traffic violation information based on the behavior of the target user during the target trip to indicate the degree of association between the behavior of the target user and the traffic violation. In this way, the solution can identify valid parking tickets from the traffic violation information uploaded by the driver, that is, the parking tickets that match the start billing time or the end billing time of the taxi order, match the passenger boarding point or the alighting point, and are not caused by the driver's personal behavior. The solution can determine the degree of association with the driver's personal behavior based on the identification result, so as to facilitate the subsequent determination of whether to provide compensation to the driver and the amount of compensation, thereby improving the efficiency of the taxi platform in processing traffic violation information.

[0024] Hereinafter, embodiments of the present disclosure will be described in further detail with reference to the accompanying drawings. Figure 1 A block diagram of an example environment 100 in which embodiments of the present disclosure can be implemented is shown. Environment 100 may generally include a user device 120 associated with a user 110 and an information processing device 130. It should be understood that the structure and functionality of environment 100 are described for exemplary purposes only and do not imply any limitation on the scope of the present disclosure. Embodiments of the present disclosure may also be applied to environments having different structures and / or functions.

[0025] The user device 120 may be any device with wired or wireless communication capabilities, including but not limited to mobile phones, computers, personal digital assistants, game consoles, wearable devices, vehicle-mounted communication devices, virtual reality devices or augmented reality devices, etc. The user device 120 may be connected to the network, for example, via a network ( Figure 1 The network may be a wired network, a wireless network, or a combination of a wired network and a wireless network, such as but not limited to the Internet, a wide area network, a metropolitan area network, a local area network, a virtual private network (VPN), a wireless communication network, etc. The information processing device 130 may include, for example, but not limited to, any physical computer, a virtual machine, a large computing device provided by a service provider, or other user equipment.

[0026] Taking the taxi service scenario as an example, the user 110 is, for example, a driver, and the user device 120 runs, for example, a driver client software. Figure 1As shown, the user 110 can send traffic violation information 101 to the information processing device 130 via the user device 120. The traffic violation information 101 can be in the format of text or picture, which can, for example, indicate the order number, violation time, violation location, violation type, etc. involved in the traffic violation information 101. The information processing device 130 can receive the traffic violation information 101 and process it. For example, the information processing device 130 can extract the order number, violation time, violation location, violation type, etc. from the traffic violation information 101 through image and / or text recognition. The information processing device 130 can determine whether the traffic violation indicated by the traffic violation information 101 matches the target trip indicated by the order number based on the extracted information. In the case of determining that the traffic violation matches the target trip indicated by the order number, the information processing device 130 can obtain the behavior of the user 110 in the target trip, and determine the processing result 102 for the traffic violation based on the behavior. As Figure 1 As shown, the information processing device 130 can send a message to the user device 120 (or Figure 1 The other devices not shown in the figure) provide a processing result 102 for the traffic violation, which can, for example, indicate the degree of association between the traffic violation and the user's behavior (such as the division of responsibilities between the taxi platform and the user's personal behavior), whether compensation is provided to the user and the specific compensation ratio, etc.

[0027] Figure 2 FIG. 2 is a flowchart of an exemplary method 200 for processing traffic violation information according to an embodiment of the present disclosure. The method 200 may be performed, for example, in Figure 1 The information processing device 130 shown in FIG. Figure 1 The method 200 is described in detail. It should be understood that the method 200 may also include blocks not shown and / or may omit blocks shown. The scope of the present disclosure is not limited in this respect.

[0028] At box 210, the information processing device 130 obtains the traffic violation information 101 of the target user 110. The traffic violation information 101 may be in the format of text or picture, for example. In some embodiments, the traffic violation information 101 may indicate, for example, the order number, violation time, violation location, and / or violation type involved in the traffic violation information 101. Examples of violation types may include, but are not limited to, illegal parking, speeding, running a red light, etc. In some embodiments, the traffic violation information 101 may not indicate a clear violation type.

[0029] At box 220 , the information processing device 130 determines whether the traffic violation indicated by the traffic violation information 101 matches the target trip of the target user 110 .

[0030] In some embodiments, the information processing device 130 may perform text and / or image recognition on the traffic violation information 101 to extract the order number, violation time, violation location, and / or violation type, etc.

[0031] In some embodiments, the information processing device 130 can determine the target trip corresponding to the order number from multiple historical trips of the target user 110 (for example, the historical trip information can be stored in a local or remote database of the information processing device 130) and obtain information related to the target trip, such as the start time (for example, the order starts billing time), the end time (for example, the order ends billing time), the start location (for example, the passenger boarding point), the end location (for example, the passenger alighting point), trajectory information, etc.

[0032] In some embodiments, the information processing device 130 may only process the violation type of illegal parking. That is, if the extracted violation type is other violation types other than illegal parking, the information processing device 130 may not perform subsequent processing. If the extracted violation type is illegal parking or if the traffic violation information 101 does not indicate a clear violation type, the information processing device 130 may perform subsequent processing.

[0033] In some embodiments, the information processing device 130 may determine a time matching result and a location matching result between the traffic violation and the target trip based on the time of the violation and the location of the violation. The time matching result may indicate whether the time of the violation of the traffic violation matches at least one of the start and end time of the target trip. The location matching result may indicate whether the location of the violation of the traffic violation matches at least one of the start and end locations of the target trip.

[0034] Figure 3 FIG. 3 is a flowchart showing an example method 300 for determining a time match result between a traffic violation and a target trip according to an embodiment of the present disclosure. The method 300 may be implemented, for example, in Figure 1 The method 300 is executed at the information processing device 130 shown. It should be understood that the method 300 may also include blocks not shown and / or may omit the blocks shown. The scope of the present disclosure is not limited in this respect.

[0035] like Figure 3As shown, at box 310, the information processing device 130 determines a first time interval between the violation time and the start time of the target trip, and a second time interval between the violation time and the end time of the target trip. At box 320, the information processing device 130 determines whether one of the first time interval and the second time interval does not exceed a threshold time. The threshold time is, for example, 2 minutes. If so, at box 340, the information processing device 130 determines that the violation time matches at least one of the start time and the end time of the target trip. For example, if the first time interval does not exceed the threshold time, it indicates that the violation time matches the start time of the target trip. If the second time interval does not exceed the threshold time, it indicates that the violation time matches the end time of the target trip. If both the first time interval and the second time interval exceed the threshold time, at box 330, the information processing device 130 determines that the violation time does not match both the start time and the end time of the target trip.

[0036] In this way, the information processing device 130 is able to accurately identify whether the violation time is associated with the start time or end time of the target trip (ie, the order billing start or end time).

[0037] Figure 4 FIG. 4 is a flowchart showing an example method 400 for determining a location match result between a traffic violation and a target trip according to an embodiment of the present disclosure. The method 400 may be performed, for example, in Figure 1 The method 400 is executed at the information processing device 130 shown. It should be understood that the method 400 may also include blocks not shown and / or may omit the blocks shown. The scope of the present disclosure is not limited in this respect.

[0038] like Figure 4 As shown, at box 410, the information processing device 130 obtains a set of stay locations of the target user during the target trip. For example, the information processing device 130 can obtain a set of stay locations of the target user during the target trip from the trajectory information of the target trip.

[0039] At block 420, the information processing device 130 determines whether there is at least one stop location in the set of stop locations whose distance from the start location or the end location of the target trip does not exceed a first threshold distance. For example, the information processing device 130 may determine whether there is at least one stop location in the set of stop locations whose straight-line distance from the start location or the end location of the target trip does not exceed 40 meters.

[0040] If each of the set of stop locations is more than a first threshold distance away from the start and end locations of the target trip, the method 400 proceeds to block 460 , where the information processing device 130 determines that the violation location does not match either the start or end location of the target trip.

[0041] If there is at least one stop location in a group of stop locations whose distance from the start location or the end location of the target trip does not exceed the first threshold distance, then at box 430, the information processing device 130 determines the priority of at least one stop location based on the time interval between the target user's stay time at the at least one stop location and the violation time. In the following, at least one stop location is also referred to as an "effective stop location" or "effective stop point". For example, a higher priority can be assigned to an effective stop location corresponding to a smaller time interval, while a lower priority can be assigned to an effective stop location corresponding to a longer time interval. The range of time intervals corresponding to different priorities can be predetermined.

[0042] At box 440, the information processing device 130 determines whether there is a stop location that exceeds the threshold priority in at least one valid stop location. For example, the threshold priority can be the lowest priority or higher than the lowest priority. If there is a stop location that exceeds the threshold priority in at least one valid stop location (that is, there is a stop location whose stop time is close enough to the violation time), then at box 450, the information processing device 130 determines that the violation location matches at least one of the start location and the end location of the target trip. If there is no stop location that exceeds the threshold priority in at least one stop location (that is, there is no stop location whose stop time is close enough to the violation time), then at box 460, the information processing device 130 determines that the violation location does not match both the start location and the end location of the target trip.

[0043] In this way, the information processing device 130 can accurately identify whether the violation location is associated with the start location or the end location of the target trip (ie, the passenger boarding and alighting location).

[0044] Figure 5 FIG. 5 is a flowchart of another exemplary method 500 for determining a location match result between a traffic violation and a target trip according to an embodiment of the present disclosure. The method 500 may be performed, for example, in Figure 1 The method 500 is executed at the information processing device 130 shown. It should be understood that the method 500 can be used as an alternative to the method 400. Alternatively, the method 500 can be used as a supplement to the method 400. For example, the information processing device 130 can execute the method 500 after executing the method to verify the determined position matching result twice. It should also be understood that the method 500 can also include unshown boxes and / or can omit the shown boxes. The scope of the present disclosure is not limited in this respect.

[0045] like Figure 5As shown, at box 510, the information processing device 130 obtains a set of stay locations of the target user during the target trip. For example, the information processing device 130 can obtain a set of stay locations of the target user during the target trip from the trajectory information of the target trip.

[0046] At block 520, the information processing device 130 determines whether there is at least one stop location in the set of stop locations whose distance from the start location or the end location of the target trip does not exceed a first threshold distance. For example, the information processing device 130 may determine whether there is at least one stop location in the set of stop locations whose straight-line distance from the start location or the end location of the target trip does not exceed 40 meters.

[0047] If each of the set of stop locations is more than a first threshold distance away from both the start and end locations of the target trip, method 500 proceeds to block 550 where telematics device 130 determines that the violation location does not match both the start and end locations of the target trip.

[0048] If there is at least one stop location in the set of stop locations whose distance from the start location or the end location of the target trip does not exceed the first threshold distance, then at box 530, the information processing device 130 further determines whether there is a stop location in the at least one stop location whose distance from the violation location does not exceed the second threshold. If so, at box 540, the information processing device 130 determines that the violation location matches at least one of the start location and the end location of the target trip. Otherwise, the method 500 proceeds to box 550, where the information processing device 130 determines that the violation location does not match either the start location or the end location of the target trip.

[0049] In this way, the information processing device 130 can accurately identify whether the violation location is associated with the start location or the end location of the target trip (ie, the passenger boarding and alighting location).

[0050] In some embodiments, the information processing device 130 may determine whether the traffic violation matches the target itinerary based on the determined time matching result and the location matching result. If at least one of the time matching result and the location matching result indicates that the traffic violation does not match the target itinerary, the information processing device 130 may determine that the traffic violation does not match the target itinerary. For example, if the time matching result indicates that the violation time does not match both the start and end time of the target itinerary, the information processing device 130 may determine that the traffic violation does not match the target itinerary. For another example, if the location matching result indicates that the violation location does not match both the start and end locations of the target itinerary, the information processing device 130 may determine that the traffic violation does not match the target itinerary. If both the time matching result and the location matching result indicate that the traffic violation matches the target itinerary, the information processing device 130 may determine that the traffic violation matches the target itinerary. For example, if the time matching result indicates that the violation time matches at least one of the start and end times of the target trip, and the location matching result indicates that the violation location matches at least one of the start and end locations of the target trip, the information processing device 130 can determine that the traffic violation matches the target trip.

[0051] In some embodiments, if the time matching result indicates that the traffic violation time does not match both the start and end time of the target trip, the information processing device 130 may determine that the traffic violation is a violation committed by the target user during driving or is caused by the target user's personal behavior. That is, the target user will bear 100% of the violation responsibility, and the ride-hailing platform will not provide any compensation to the target user.

[0052] Back to Figure 2 At block 230, if it is determined that the traffic violation matches the target trip, the information processing device 130 provides a processing result for the traffic violation information based on the target user's behavior during the target trip. For example, the target user's behavior during the target trip can be obtained from a database local or remote to the information processing device 130. For example, the processing result provided can indicate the degree of association between the target user's behavior and the traffic violation (such as the division of responsibilities between the ride-hailing platform and the user's personal behavior), whether compensation is provided to the target user, and the specific compensation ratio, etc.

[0053] In some embodiments, the information processing device 130 may determine whether a prompt about avoiding the traffic violation has been provided to the target user. For example, the prompt may indicate the maximum stay time at the passenger pick-up point or drop-off point that does not result in illegal parking. If it is determined that the prompt has been provided to the target user, the information processing device 130 may further determine whether the target user's behavior complies with the prompt. For example, the information processing device 130 may further determine whether the target user's stay time at the passenger pick-up point or drop-off point exceeds the maximum stay time prompted. If the target user's behavior complies with the prompt (for example, the stay time does not exceed the maximum stay time), the information processing device 130 may determine the degree of association between the target user's behavior and the traffic violation as a predetermined degree of association. For example, the predetermined degree of association is 50%, indicating that the taxi-hailing platform and the target user's personal behavior each bear 50% responsibility, and the taxi-hailing platform will provide the target user with 50% compensation for the ticket amount. If no prompt has been provided to the target user, or if the target user's behavior does not comply with the prompt, the information processing device 130 can determine whether the target user has attempted actions to avoid the traffic violation, such as negotiating with passengers to change the boarding or alighting point, and further determine the degree of correlation between the target user's behavior and the traffic violation based on the determination result.

[0054] It can be seen from the above description that the embodiments of the present disclosure can identify valid parking tickets from traffic violation information uploaded by drivers, that is, parking tickets that match the start or end billing time of the taxi order, match the passenger boarding point or alighting point, and are not caused by the driver's personal behavior. Based on the identification results, the solution can determine the degree of correlation with the driver's personal behavior, which is convenient for subsequent determination of whether to provide compensation to the driver and the amount of compensation, thereby improving the efficiency of the taxi platform in processing traffic violation information.

[0055] Figure 6 FIG. 6 is a block diagram of an exemplary apparatus 600 for identifying a line of sight direction according to an embodiment of the present disclosure. Figure 6 As shown, the device 600 includes an information acquisition module 610, which is configured to acquire traffic violation information of a target user; a trip matching module 620, which is configured to determine whether the traffic violation indicated by the traffic violation information matches the target trip of the target user; and a result providing module 630, which is configured to provide a processing result for the traffic violation information based on the behavior of the target user during the target trip if it is determined that the traffic violation matches the target trip, and the processing result indicates the degree of association between the behavior and the traffic violation.

[0056] In some embodiments, the trip matching module 620 includes: a first information extraction module, configured to extract the violation time and violation location of the traffic violation from the traffic violation information; a first matching module, configured to determine the time matching result and location matching result between the traffic violation and the target trip based on the violation time and violation location; and a second matching module, configured to determine whether the traffic violation matches the target trip based at least on the time matching result and the location matching result.

[0057] In some embodiments, the first matching module is configured to: determine that the violation time does not match the start time and the end time if both a first time interval between the violation time and the start time of the target trip and a second time interval between the violation time and the end time of the target trip exceed a threshold time; and determine that the violation time matches at least one of the start time and the end time if at least one of the first time interval and the second time interval does not exceed the threshold time.

[0058] In some embodiments, the first matching module is configured to: obtain a set of stop locations of the target user during the target trip; and if the distance between each stop location in the set of stop locations and the start location and the end location of the target trip exceeds a first threshold distance, determine that the violation location does not match the start location and the end location.

[0059] In some embodiments, the first matching module is further configured to: determine at least one stay location from a group of stay locations whose distance from the start location or the end location does not exceed a first threshold distance; determine the priority of at least one stay location based on the time interval between the stay time of the target user at at least one stay location and the violation time, wherein the stay location corresponding to the smaller time interval has a higher priority; if the priority of one of at least one stay location exceeds the threshold priority, determine that the violation location matches at least one of the start location and the end location; and if the priority of each of the at least one stay location does not exceed the threshold priority, determine that the violation location does not match both the start location and the end location.

[0060] In some embodiments, the first matching module is further configured to: determine at least one stop location from a group of stop locations whose distance from the start location or the end location does not exceed a first threshold distance; determine that the violation location matches at least one of the start location and the end location if the distance between one of the at least one stop location and the violation location does not exceed a second threshold distance; and determine that the violation location does not match both the start location and the end location if the distance between each of the at least one stop location and the violation location exceeds the second threshold distance.

[0061] In some embodiments, the second matching module is configured to: determine that the traffic violation does not match the target trip if at least one of the time matching result and the location matching result indicates that the violation location does not match the target trip; and determine that the traffic violation matches the target trip if both the time matching result and the location matching result indicate that the violation location matches the target trip.

[0062] In some embodiments, the result providing module includes: a prompt determination module, configured to determine whether the target user receives a prompt about avoiding traffic violations; a first association determination module, configured to determine the degree of association between the behavior and the traffic violation based on at least one of the following if it is determined that the target user receives the prompt: the degree of match between the behavior and the prompt; and the actions in the behavior used to avoid traffic violations; a second association determination module, configured to determine the degree of association based on the actions in the behavior used to avoid traffic violations if it is determined that the target user does not receive the prompt; and an indication output module, configured to provide a processing result indicating the degree of association.

[0063] In some embodiments, the apparatus 600 further includes: a second information extraction module configured to extract identification information of the target trip from the traffic violation information; and a trip determination module configured to determine the target trip based on the identification information.

[0064] The modules included in the device 600 can be implemented in various ways, including software, hardware, firmware, or any combination thereof. In some embodiments, one or more units can be implemented using software and / or firmware, such as machine executable instructions stored on a storage medium. In addition to or as an alternative to machine executable instructions, some or all of the modules in the device 600 and / or 700 can be implemented at least in part by one or more hardware logic components. As an example and not limitation, exemplary types of hardware logic components that can be used include field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0065] Figure 7 is a block diagram of an example electronic device 700 capable of implementing various embodiments of the present disclosure. Figure 1 The device 130 shown may be implemented by the device 700. Figure 7As shown, the device 700 includes a central processing unit (CPU) 701, which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) 702 or computer program instructions loaded from a storage unit 708 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0066] A number of components in the device 700 are connected to the I / O interface 705, including: an input unit 706, such as a keyboard, a mouse, etc.; an output unit 707, such as various types of displays, speakers, etc.; a storage unit 708, such as a disk, an optical disk, etc.; and a communication unit 709, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0067] The various processes and processing described above, such as methods 200, 300, 400, and / or 500, may be performed by the processing unit 701. For example, in some embodiments, the methods 200, 300, 400, and / or 500 may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 700 via the ROM 702 and / or the communication unit 709. When the computer program is loaded into the RAM 703 and executed by the CPU 701, one or more actions of the methods 200, 300, 400, and / or 500 described above may be performed.

[0068] The present disclosure may be a method, an apparatus, a system and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing various aspects of the present disclosure.

[0069] Computer readable storage medium can be a tangible device that can hold and store instructions used by an instruction execution device. Computer readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. More specific examples (non-exhaustive list) of computer readable storage medium include: portable computer disk, hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanical encoding device, such as a punch card or a convex structure in a groove on which instructions are stored, and any suitable combination of the above. The computer readable storage medium used here is not interpreted as a transient signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagated by a waveguide or other transmission medium (e.g., a light pulse by an optical fiber cable), or an electrical signal transmitted by a wire.

[0070] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0071] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0072] Various aspects of the present disclosure are described herein with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present disclosure. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer-readable program instructions.

[0073] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processing unit of the computer or other programmable data processing device, a device that implements the functions / actions specified in one or more boxes in the flowchart and / or block diagram is generated. These computer-readable program instructions can also be stored in a computer-readable storage medium, and these instructions cause the computer, programmable data processing device, and / or other equipment to work in a specific manner, so that the computer-readable medium storing the instructions includes a manufactured product, which includes instructions for implementing various aspects of the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0074] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operating steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more boxes in the flowchart and / or block diagram.

[0075] The flow chart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to multiple embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a part of a module, program segment or instruction, and a part of the module, program segment or instruction includes one or more executable instructions for realizing the specified logical function. In some alternative implementations, the function marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two continuous square boxes can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or action, or can be implemented with a combination of special hardware and computer instructions.

[0076] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method for processing traffic violation information, comprising: Obtaining traffic violation information of a target user, wherein the traffic violation information includes the time and location of the traffic violation; determining whether the traffic violation indicated by the traffic violation information matches the target itinerary of the target user; as well as If it is determined that the traffic violation matches the target trip, providing a processing result for the traffic violation information based on the degree of association between the target user's behavior during the target trip and the traffic violation; The processing result provided includes: determining whether the target user receives a prompt for avoiding the traffic violation; If it is determined that the target user receives the prompt, the degree of association between the behavior and the traffic violation is determined based on at least one of the following: how closely the behavior matches the prompt; and Actions in the behavior used to avoid the traffic violation; If it is determined that the target user has not received the prompt, determining the degree of association based on the action in the behavior for avoiding the traffic violation; and A result of the processing is provided that indicates the degree of association.

2. The method according to claim 1, wherein determining whether the traffic violation matches the target trip comprises: Extracting the violation time and violation location of the traffic violation from the traffic violation information; Determine a time matching result and a location matching result between the traffic violation and the target trip based on the violation time and the violation location; as well as Based at least on the time matching result and the location matching result, it is determined whether the traffic violation matches the target trip.

3. The method according to claim 2, wherein determining the time matching result comprises: Determining a first time interval between the violation time and the start time of the target trip and a second time interval between the violation time and the end time of the target trip; If both the first time interval and the second time interval exceed a threshold time, determining that the violation time does not match the start time and the end time; as well as If at least one of the first time interval and the second time interval does not exceed the threshold time, it is determined that the violation time matches at least one of the start time and the end time.

4. The method according to claim 2, wherein determining the location matching result comprises: Obtaining a set of stay locations of the target user during the target trip; as well as If the distance between each of the group of stop locations and the start location and the end location of the target trip exceeds a first threshold distance, it is determined that the violation location does not match the start location and the end location.

5. The method according to claim 4, wherein determining the location matching result further comprises: Determine at least one stop position from the set of stop positions, the distance from the start position or the end position not exceeding the first threshold distance; Determining the priority of the at least one stop location based on the time interval between the stay time of the target user at the at least one stop location and the violation time, wherein a stop location corresponding to a smaller time interval has a higher priority; determining that the violation location matches at least one of the start location and the end location if the priority of one of the at least one stay location exceeds a threshold priority; as well as If the priority of each of the at least one stop location does not exceed the threshold priority, it is determined that the violation location does not match both the start location and the end location.

6. The method according to claim 4, wherein determining the location matching result further comprises: Determine at least one stop position from the set of stop positions, the distance from the start position or the end position not exceeding the first threshold distance; If the distance between one of the at least one stay location and the violation location does not exceed a second threshold distance, determining that the violation location matches at least one of the start location and the end location; as well as If the distance between each of the at least one stop location and the violation location exceeds the second threshold distance, it is determined that the violation location does not match both the start location and the end location.

7. The method of claim 2, wherein determining whether the traffic violation matches the target trip comprises: If at least one of the time matching result and the location matching result indicates that the traffic violation does not match the target trip, determining that the traffic violation does not match the target trip; as well as If both the time matching result and the location matching result indicate that the traffic violation matches the target trip, it is determined that the traffic violation matches the target trip.

8. The method according to claim 1, further comprising: Extracting identification information of the target trip from the traffic violation information; as well as Based on the identification information, the target trip is determined.

9. A device for processing traffic violation information, comprising: An information acquisition module is configured to acquire traffic violation information of a target user, wherein the traffic violation information includes a time and location of the traffic violation; a trip matching module configured to determine whether the traffic violation indicated by the traffic violation information matches the target trip of the target user; and A result providing module, configured to provide a processing result for the traffic violation information based on the degree of association between the behavior of the target user during the target trip and the traffic violation if it is determined that the traffic violation matches the target trip; The result providing module comprises: a prompt determination module, configured to determine whether the target user receives a prompt for avoiding the traffic violation; The first association determination module is configured to determine the association degree between the behavior and the traffic violation based on at least one of the following if it is determined that the target user receives the prompt: how closely the behavior matches the prompt; and Actions in the behavior used to avoid the traffic violation; A second association determination module is configured to determine the association degree based on the action in the behavior for avoiding the traffic violation if it is determined that the target user has not received the prompt; and The indication output module is configured to provide the processing result indicating the association degree.

10. The device according to claim 9, wherein the trip matching module comprises: A first information extraction module is configured to extract the violation time and violation location of the traffic violation from the traffic violation information; A first matching module is configured to determine a time matching result and a location matching result between the traffic violation and the target trip based on the violation time and the violation location; as well as The second matching module is configured to determine whether the traffic violation matches the target trip based at least on the time matching result and the location matching result.

11. The apparatus according to claim 10, wherein the first matching module is configured to: Determining a first time interval between the violation time and the start time of the target trip and a second time interval between the violation time and the end time of the target trip; If both the first time interval and the second time interval exceed a threshold time, determining that the violation time does not match the start time and the end time; as well as If at least one of the first time interval and the second time interval does not exceed the threshold time, it is determined that the violation time matches at least one of the start time and the end time.

12. The apparatus according to claim 10, wherein the first matching module is configured to: Obtaining a set of stay locations of the target user during the target trip; and If the distance between each of the group of stop locations and the start location and the end location of the target trip exceeds a first threshold distance, it is determined that the violation location does not match the start location and the end location.

13. The apparatus according to claim 12, wherein the first matching module is further configured to: Determine at least one stop position from the set of stop positions, the distance from the start position or the end position not exceeding the first threshold distance; Determining the priority of the at least one stop location based on the time interval between the stay time of the target user at the at least one stop location and the violation time, wherein a stop location corresponding to a smaller time interval has a higher priority; determining that the violation location matches at least one of the start location and the end location if the priority of one of the at least one stay location exceeds a threshold priority; as well as If the priority of each of the at least one stop location does not exceed the threshold priority, it is determined that the violation location does not match both the start location and the end location.

14. The apparatus according to claim 12, wherein the first matching module is further configured to: Determine at least one stop position from the set of stop positions, the distance from the start position or the end position not exceeding the first threshold distance; If the distance between one of the at least one stay location and the violation location does not exceed a second threshold distance, determining that the violation location matches at least one of the start location and the end location; as well as If the distance between each of the at least one stop location and the violation location exceeds the second threshold distance, it is determined that the violation location does not match both the start location and the end location.

15. The apparatus according to claim 10, wherein the second matching module is configured to: If at least one of the time matching result and the location matching result indicates that the traffic violation does not match the target trip, determining that the traffic violation does not match the target trip; and If both the time matching result and the location matching result indicate that the traffic violation matches the target trip, it is determined that the traffic violation matches the target trip.

16. The apparatus according to claim 9, further comprising: A second information extraction module is configured to extract identification information of the target trip from the traffic violation information; as well as The itinerary determination module is configured to determine the target itinerary based on the identification information.

17. An electronic device comprising: one or more processors; as well as A memory for storing one or more programs, which, when executed by the one or more processors, enables the electronic device to implement the method according to any one of claims 1 to 8.

18. A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method according to any one of claims 1 to 8.

19. A computer program product comprising computer executable instructions, wherein the computer executable instructions, when executed by a processor, implement the method according to any one of claims 1 to 8.

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