A method, device and equipment for generating a playback video of an abnormal traffic scene event

Abstract

The embodiments of this specification disclose a method, device, and equipment for generating a playback video of an abnormal traffic scene event. The solution may include: obtaining the vehicle operation data of a target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event, so as to determine the target video acquisition time period corresponding to the target intelligent roadside device according to the vehicle operation data, thereby accurately and quickly obtaining the target video data involved in the abnormal traffic scene event from all the video data of the target intelligent roadside device, and further generating the playback video data for the abnormal traffic scene event.

Description

Technical Field

[0001] This specification relates to the technical fields of vehicle networking and intelligent driving, and particularly to a method for generating a playback video of an abnormal traffic scene event. Background Art

[0002] The cloud control platform real-time accesses vehicle bus data, intelligent roadside device perception data, and other intelligent driving data on traffic roads, and uses the intelligent driving data to calculate for abnormal traffic scene events, identify abnormal traffic scene events such as speeding, abnormal low speed, lane change, etc., and at the same time generate collaborative decision-making instructions for guiding and assisting vehicles, and send the collaborative decision-making instructions to vehicles associated with the abnormal traffic scene event. In order to clearly and intuitively display the occurrence process of the abnormal traffic scene event, the occurrence process of the abnormal traffic scene event can be visually displayed, which is called the playback of the abnormal traffic scene event. However, in the function of playing back the abnormal traffic scene event, it is necessary to select the video data of the target intelligent connected vehicle involved in the abnormal traffic scene event from all the video data of the intelligent roadside device. Therefore, how to accurately and quickly select the video data of the vehicle involved in the abnormal traffic scene event from all the data of the intelligent roadside device, so as to generate a playback video for the playback of the abnormal traffic scene event using the selected roadside video has become an urgent technical problem to be solved. Summary of the Invention

[0003] Embodiments of this specification provide a method, device, and equipment for generating a playback video of an abnormal traffic scene event to solve the problem that the prior art cannot efficiently and quickly generate an accurate and complete playback video of an abnormal traffic scene event.

[0004] To solve the above technical problems, the embodiments of this specification are implemented as follows:

[0005] A method for generating a playback video of an abnormal traffic scene event provided by an embodiment of this specification may include:

[0006] Obtain the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event; the target intelligent connected vehicle is an intelligent connected vehicle related to the abnormal traffic scene event;

[0007] Determine the target video acquisition time period corresponding to the target intelligent roadside device according to the vehicle operation data; the target video acquisition time period is the time period during which the target intelligent roadside device acquires video data including the target intelligent connected vehicle during the event occurrence time period;

[0008] Obtain the target video data acquired by the target intelligent roadside device during the target video acquisition time period;

[0009] Generate replay video data for the abnormal traffic scene event according to the target video data;

[0010] Send the replay video data to the target device.

[0011] An apparatus for generating a replay video of an abnormal traffic scene event provided by an embodiment of this specification, the apparatus may include:

[0012] A vehicle operation data acquisition module, configured to acquire vehicle operation data of a target intelligent connected vehicle during the event occurrence time period of an abnormal traffic scene event; the target intelligent connected vehicle is an intelligent connected vehicle related to the abnormal traffic scene event;

[0013] A video acquisition time determination module, configured to determine a target video acquisition time period corresponding to a target intelligent roadside device according to the vehicle operation data; the target video acquisition time period is the time period during which the intelligent roadside device acquires video data including the target intelligent connected vehicle during the event occurrence time period;

[0014] A target video acquisition module, configured to acquire target video data acquired by the target intelligent roadside device during the target video acquisition time period;

[0015] A replay video generation module, configured to generate replay video data for the abnormal traffic scene event according to the target video data;

[0016] A sending module, configured to send the replay video data to the target device.

[0017] An apparatus for generating a replay video of an abnormal traffic scene event provided by an embodiment of this specification, the apparatus may include:

[0018] At least one processor; and,

[0019] A memory communicatively connected to the at least one processor; wherein,

[0020] The memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is enabled to:

[0021] Acquire vehicle operation data of a target intelligent connected vehicle during the event occurrence time period of an abnormal traffic scene event; the target intelligent connected vehicle is an intelligent connected vehicle related to the abnormal traffic scene event;

[0022] Determine a target video acquisition time period corresponding to a target intelligent roadside device according to the vehicle operation data; the target video acquisition time period is the time period during which the target intelligent roadside device acquires video data including the target intelligent connected vehicle within the event occurrence time period;

[0023] Obtain the target video data acquired by the target intelligent roadside device during the target video acquisition time period;

[0024] Generate replay video data for the abnormal traffic scene event according to the target video data;

[0025] Send the replay video data to the target device.

[0026] At least one embodiment in this specification can achieve the following beneficial effects:

[0027] By obtaining the vehicle operation data of the target intelligent connected vehicle within the event occurrence time period of the abnormal traffic scene event; and determining the target video acquisition time period corresponding to the target intelligent roadside device according to the vehicle operation data, so as to obtain the target video data acquired by the target intelligent roadside device during the target video acquisition time period, and thus generate replay video data for the abnormal traffic scene event according to the target video data; in this solution, since the target video acquisition time period corresponding to the target intelligent roadside device is determined according to the vehicle operation data, the target video data involved in the abnormal traffic scene event can be accurately and quickly obtained from all the video data of the target intelligent roadside device, and then replay video data with better accuracy for the abnormal traffic scene event can be efficiently generated. Description of the Drawings

[0028] In order to more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments recorded in this application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0029] Figure 1 It is a schematic flowchart of a method for generating a replay video of an abnormal traffic scene event provided by an embodiment of this specification;

[0030] Figure 2 It is a schematic structural diagram of a device for generating a replay video of an abnormal traffic scene event provided by an embodiment of this specification;[[ID=2,9]]

[0031] Figure 3 It is a schematic structural diagram of a device for generating a replay video of an abnormal traffic scene event provided by an embodiment of this specification. Detailed implementation manners

[0032] To make the objectives, technical solutions, and advantages of one or more embodiments of this specification clearer, the following will clearly and completely describe the technical solutions of one or more embodiments of this specification in conjunction with the specific embodiments of this specification and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. Based on the embodiments in this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope protected by one or more embodiments of this specification.

[0033] The following will, with reference to the drawings, detail the technical solutions provided in each embodiment of this specification.

[0034] In the prior art, in order to clearly and intuitively display the occurrence process of an abnormal traffic scene event, the occurrence process of the abnormal traffic scene event can be visually displayed, which is called scene event playback. However, in the scene event playback function, it is necessary to select the video data of the vehicles involved in the abnormal traffic scene event from all the video data of the intelligent roadside devices. Therefore, how to accurately and quickly select the video data of the vehicles involved in the abnormal traffic scene event from all the video data of the intelligent roadside devices to generate a playback video for the abnormal traffic scene event using the selected roadside videos has become a technical problem to be solved urgently.

[0035] To solve the defects in the prior art, the following embodiments are given in this solution:

[0036] Figure 1 It is a schematic diagram of the overall solution flow of a method for generating a playback video of an abnormal traffic scene event in an embodiment of this specification. From a program perspective, the execution subject of this process can be a cloud control platform for generating a playback video of an abnormal traffic scene event, such as Figure 1 As shown, this method may include the following steps:

[0037] 102: Obtain the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event; the target intelligent connected vehicle is an intelligent connected vehicle related to the abnormal traffic scene event.

[0038] In the embodiments of this specification, the target intelligent connected vehicle can real-time locate its own vehicle position and upload its own vehicle position to the vehicle bus in real time through the network.

[0039] In practical applications, preferably, the target intelligent connected vehicle may be an intelligent connected vehicle that has encountered an abnormal traffic scenario event, can locate its own vehicle position, and has a data upload function; however, if an intelligent connected vehicle that has encountered an abnormal traffic scenario event does not have a data upload function or cannot locate its own vehicle, then such an intelligent connected vehicle may be prohibited from being determined as the target intelligent connected vehicle. However, by taking the intelligent connected vehicle that is determined to be affected by the abnormal traffic scenario event, can locate its own vehicle position, and has a data upload function as the target intelligent connected vehicle, the Figure 1 normal operation of the method in

[0040] In practical applications, the event occurrence time period of the abnormal traffic scenario event can usually be obtained from the known information of the abnormal traffic scenario event, which will not be elaborated here.

[0041] In the embodiments of this specification, the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scenario event can be obtained from the vehicle bus. The vehicle operation data may include: vehicle unique identifier, vehicle positioning position, and vehicle positioning time corresponding to the vehicle positioning position, etc.

[0042] 104: Determine the target video acquisition time period corresponding to the target intelligent roadside device according to the vehicle operation data; the target video acquisition time period is the time period during which the target intelligent roadside device acquires video data containing the target intelligent connected vehicle during the event occurrence time period.

[0043] In the embodiments of this specification, the intelligent roadside device may include: an intelligent video acquisition unit and a roadside computing unit (Roadside Computing Unit, abbreviated as RCU in English). Among them, the roadside computing unit can obtain the perception data of the perception objects within its perception range and upload the obtained perception data to the cloud control platform.

[0044] In the embodiments of this specification, the intelligent roadside device can obtain the perception data of the perception objects within its perception range. The perception data may include the perception position of the perception object. When it is determined that during the event occurrence time period of the abnormal traffic scenario event, the vehicle positioning position of the target intelligent connected vehicle is within the perception area composed of the perception positions of the perception objects of the intelligent roadside device, the intelligent roadside device can be determined as the target intelligent roadside device.

[0045] In the embodiments of this specification, the target intelligent roadside device is used to obtain the target perception data of the target objects including the target intelligent connected vehicle within its perception range during the event occurrence time period of the abnormal traffic scenario event. The target perception data may include the target object position.

[0046] In the embodiments of this specification, during different time periods within the event occurrence time period of an abnormal traffic scene event, the target intelligent connected vehicle may be within the sensing range of different target intelligent roadside devices. In practical applications, since the vehicle positioning position corresponds to the vehicle positioning moment, the initial moment and the termination moment within the sensing area composed of the target positions of the target objects of the target intelligent roadside devices where the target intelligent connected vehicle is located can be determined based on the vehicle positioning position of the target intelligent connected vehicle, so as to determine the target video acquisition time period corresponding to the target intelligent roadside device.

[0047] In the embodiments of this specification, the target video acquisition time period corresponding to the target intelligent roadside device is the time period during which the target intelligent roadside device acquires video data including the target intelligent connected vehicle within the event occurrence time period. It can be understood that the target video acquisition time periods corresponding to different target intelligent roadside devices are different.

[0048] 106: Obtain the target video data acquired by the target intelligent roadside device during the target video acquisition time period.

[0049] In the embodiments of this specification, the target video data of the target intelligent roadside device within the corresponding target video acquisition time period can be obtained according to the determined target video acquisition time period, so as to splice the obtained target video data to obtain the playback video data of the abnormal traffic scene event.

[0050] 108: Generate the playback video data for the abnormal traffic scene event according to the target video data.

[0051] In the embodiments of this specification, an existing video splicing processor or video splicing processing technology can be selected to splice the obtained target video data to generate the playback video data for the abnormal traffic scene event. The specific splicing process will not be elaborated here.

[0052] 110: Send the playback video data to the target device.

[0053] In the embodiments of this specification, the target device may be a specific application platform or device that needs to display the playback video, and no specific limitation is made here.

[0054] It should be understood that the order of some steps of the method described in one or more embodiments of this specification can be mutually exchanged according to actual needs, or some of the steps can also be omitted or deleted.

[0055] Figure 1The method in [description] obtains the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event; and determines the target video capture time period corresponding to the target intelligent roadside device according to the vehicle operation data, so as to obtain the target video data captured by the target intelligent roadside device during the target video capture time period, and thus generate the playback video data for the abnormal traffic scene event according to the target video data; in this solution, according to the vehicle operation data, the target intelligent roadside device and the target video capture time period corresponding to the target intelligent roadside device are determined, so that the target intelligent roadside device can be determined, reducing the data processing amount, and at the same time accurately obtaining the target video data involved in the abnormal traffic scene event from all the video data of the target intelligent roadside device, and then generating the playback video data for the abnormal traffic scene event.

[0056] Based on Figure 1 For the method of [description], some specific implementation schemes of this method are also provided in the embodiments of this specification, and the following is an explanation.

[0057] In the embodiments of this specification, the determination of the target intelligent roadside device is specifically as follows:

[0058] Optionally, before determining the target video capture time period corresponding to the target intelligent roadside device according to the vehicle operation data, it may further include:

[0059] Determine the position information of the target object obtained by the specified intelligent roadside device; the target object is an object that appears within the sensing range of the specified intelligent roadside device during the event occurrence time period.

[0060] Determine the effective sensing area of the specified intelligent roadside device according to the position information of the target object.

[0061] Determine the target intelligent roadside device according to the vehicle operation data of the target intelligent connected vehicle and the effective sensing area of the specified intelligent roadside device; the target intelligent connected vehicle is located within the effective sensing area of the target intelligent roadside device during the event occurrence time period.

[0062] In the embodiments of this specification, the specified intelligent roadside device may be determined according to the vehicle positioning position of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event, and includes the intelligent roadside devices within the area range of the area where the abnormal traffic scene event occurs.

[0063] In the embodiments of this specification, the specified intelligent roadside device may obtain the position information of the target object within its sensing range, and determine the area formed by the position information of the target object as the effective sensing area of the specified intelligent roadside device, and the area may be a polygon area.

[0064] In the embodiments of this specification, by determining whether the vehicle positioning position in the vehicle operation data of the target intelligent connected vehicle is within the effective perception area of the specified intelligent roadside device, the target intelligent roadside device is determined. If the judgment result indicates that the vehicle positioning position is within the effective perception area of the specified intelligent roadside device, the specified intelligent roadside device is determined as the target intelligent roadside device.

[0065] In the embodiments of this specification, the specified intelligent roadside device is used to determine the target intelligent roadside device, so as to reduce the data processing amount for determining the target intelligent roadside device using the vehicle operation data, thereby improving the selection efficiency of video data.

[0066] In the embodiments of this specification, since the target intelligent connected vehicle may be within the perception areas of different target intelligent roadside devices at different time periods, it is usually necessary to determine the specific time period when the target intelligent connected vehicle is within the perception area of the target roadside intelligent device.

[0067] Based on this, the vehicle operation data can be used to reflect the moment when the target intelligent connected vehicle is located at the specified position.

[0068] Correspondingly, according to the vehicle operation data, determining the target video acquisition time period corresponding to the target intelligent roadside device may specifically include:

[0069] According to the vehicle operation data of the target intelligent connected vehicle, determine the initial time and the end time when the specified position is within the effective perception area of the target intelligent roadside device.

[0070] Determine the time period between the initial time and the end time as the target video acquisition time period corresponding to the target intelligent roadside device.

[0071] In the embodiments of this specification, the specified position may be the positioning position of the target intelligent connected vehicle at any moment during the event occurrence time period of the abnormal traffic scene event, and the vehicle operation data may further include the vehicle positioning time of the specified position.

[0072] In the embodiments of this specification, the initial time is used to represent the vehicle positioning time when the target intelligent connected vehicle enters the perception range of the target intelligent roadside device; the end time is used to represent the vehicle positioning time when the target intelligent connected vehicle leaves the perception range of the target intelligent roadside device; the target video acquisition time period corresponding to the target intelligent roadside device is the time period between the initial time and the end time.

[0073] In the embodiments of this specification, by determining the specific time periods when the target intelligent connected vehicle is within the sensing areas of different target intelligent roadside devices, it is possible to obtain the corresponding target videos of the target intelligent roadside devices within the specific time periods, and further generate the playback video data for the abnormal traffic scene event.

[0074] In the embodiments of this specification, the designated intelligent roadside device can be first determined from all intelligent roadside devices, so as to determine the target intelligent roadside device according to the designated intelligent roadside device, thereby reducing the data processing amount for determining the target intelligent roadside device using vehicle operation data.

[0075] Based on this, the vehicle operation data can be used to reflect the position where the target intelligent connected vehicle is located.

[0076] Correspondingly, before determining the position information of the target object obtained by the designated intelligent roadside device, it may further include:

[0077] According to the position where the target intelligent connected vehicle is located, a preset area is determined.

[0078] According to the installation position information of the intelligent roadside devices, the designated intelligent roadside device is determined from the candidate intelligent roadside devices installed within the preset area; wherein, the designated intelligent roadside device is used to collect videos of the target intelligent connected vehicle from a preset azimuth.

[0079] In the embodiments of this specification, the vehicle operation data may further include positioning position data for reflecting the position where the target intelligent connected vehicle is located.

[0080] In the embodiments of this specification, the preset area may be determined according to the vehicle positioning position of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event, including the area range of the area where the abnormal traffic scene event occurs. The specific size of the preset area range can be set as needed and will not be specifically limited here.

[0081] In the embodiments of this specification, the installation position information of the intelligent roadside devices may be known information obtained through manual maintenance in advance.

[0082] In the embodiments of this specification, since there are usually obstacles such as trees or light shields in the middle of the road, or the video acquisition angles of the non - same - side roads are relatively biased, some candidate intelligent roadside devices within the preset area (such as the candidate intelligent roadside devices in the oncoming lane of the lane where the target intelligent connected vehicle is located) cannot obtain clear and complete video data of the target intelligent connected vehicle. Therefore, it is necessary to further screen some candidate intelligent roadside devices within the preset area.

[0083] Based on this, determining the specified intelligent roadside device from the candidate intelligent roadside devices installed in the preset area according to the installation position information of the intelligent roadside device may specifically include:

[0084] For any candidate intelligent roadside device installed in the preset area, determine whether the candidate intelligent roadside device and the target intelligent connected vehicle are on the same side of the road, and obtain a first determination result.

[0085] If the first determination result indicates that the candidate intelligent roadside device and the target intelligent connected vehicle are on the same side of the road, then determine the candidate intelligent roadside device as the specified intelligent roadside device.

[0086] Determining whether the candidate intelligent roadside device and the target intelligent connected vehicle are on the same side of the road may specifically include:

[0087] Determine whether the vertical distance between the candidate intelligent roadside device and the road edge of the lane where the target intelligent connected vehicle is located is less than a preset road width, and obtain a second determination result.

[0088] If the second determination result indicates that the vertical distance from the candidate intelligent roadside device to the road edge of the road where the target intelligent connected vehicle is located is less than the road width, then determine that the intelligent roadside device in the area and the target intelligent connected vehicle are on the same side of the road.

[0089] In the embodiments of this specification, the candidate intelligent roadside device may include: a roadside computing unit (Roadside Computing Unit, abbreviated as RCU in English), and an intelligent video acquisition device; the roadside computing unit is used to obtain the perception data of the perception objects within its perception range, and the perception data may include the perception positions of the perception objects; the intelligent video acquisition device is used to perform video acquisition on intelligent connected vehicles.

[0090] In the embodiments of this specification, since the intelligent video acquisition device is usually located in the central area of the road to collect video data of the objects existing on the road, therefore, assuming that the candidate intelligent roadside device and the target intelligent connected vehicle are on the same side of the road, then usually the vertical distance between the candidate intelligent roadside device and the road edge of the lane where the target intelligent connected vehicle is located is less than the preset road width.

[0091] In the embodiments of this specification, it is also possible to determine whether the candidate intelligent roadside device and the target intelligent connected vehicle are on the same side of the road according to the pre-maintained correspondence between the orientation of the intelligent roadside device and the lane driving direction. If the candidate intelligent roadside device has an opposite lane heading angle, it is determined that the candidate intelligent roadside device and the target intelligent connected vehicle are on the same side of the road, and the candidate intelligent roadside device is determined as the designated intelligent roadside device, and the designated intelligent roadside device is used to collect video of the front of the target intelligent connected vehicle.

[0092] In the embodiments of this specification, the roadside computing unit and the intelligent video acquisition device are installed at the same position. Therefore, the designated roadside computing unit can be determined according to the designated intelligent roadside device, so as to determine the designated intelligent roadside device.

[0093] In the embodiments of this specification, the designated intelligent roadside device can be selected by determining whether the intelligent video acquisition device in the candidate intelligent roadside device and the target intelligent connected vehicle are on the same side of the road, reducing the data processing amount for determining the target intelligent roadside device using vehicle operation data. At the same time, the video data of the target intelligent connected vehicle on the same side of the road collected by the intelligent video acquisition device is usually not blocked by obstacles, and the video data acquisition angle for the target intelligent connected vehicle meets the requirements of clarity and integrity, thus ensuring the integrity of the target video data.

[0094] In the embodiments of this specification, it is usually necessary to obtain information related to abnormal traffic scene events, so as to obtain target video data related to abnormal traffic scene events according to the relevant information.

[0095] Based on this, before obtaining the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event, it may further include:

[0096] Obtain the event information of the abnormal traffic scene event, where the event information includes the event location information of the abnormal traffic scene event, the event occurrence time period, and the vehicle identification information of the intelligent connected vehicle involved in the abnormal traffic scene event.

[0097] Determine the intelligent connected vehicle with the vehicle identification information as the target intelligent connected vehicle.

[0098] The obtaining of the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event may specifically include:

[0099] Obtain the vehicle operation data reported by the intelligent connected vehicle with the vehicle identification information during the event occurrence time period from the vehicle bus.

[0100] In the embodiments of this specification, the event information of the abnormal traffic scene event is usually generated by the cloud control platform. Therefore, the event information of the abnormal traffic scene event can be directly obtained from the cloud control platform.

[0101] In the embodiments of this specification, preferably, the target intelligent connected vehicle can be an intelligent connected vehicle that has an abnormal traffic scene event, can locate its own vehicle position, and has a data upload function. However, if the intelligent connected vehicle with an abnormal traffic scene event does not have a data upload function or cannot locate its own vehicle, an intelligent connected vehicle that is affected by the abnormal traffic scene event, can locate its own vehicle position, and has a data upload function can be determined as the target intelligent connected vehicle.

[0102] In the embodiments of this specification, by obtaining the vehicle operation data reported in real time by the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event from the vehicle bus, the accuracy and precision of the obtained data are improved, so as to improve the accuracy of the target intelligent roadside device determined according to the vehicle operation data of the target intelligent connected vehicle.

[0103] In the embodiments of this specification, since the target intelligent connected vehicle reports vehicle operation data to the vehicle bus in real time, the density of the vehicle operation data obtained from the vehicle bus is large. Therefore, it is necessary to process the initial vehicle operation data obtained from the vehicle bus to reduce the amount of data processing and improve the data processing efficiency.

[0104] Based on this, obtaining the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event specifically may include:

[0105] Performing thinning processing on the initial vehicle operation data uploaded by the target intelligent connected vehicle during the event occurrence time period to obtain the vehicle operation data.

[0106] In the embodiments of this specification, first, according to the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event, a preset area is determined to determine the candidate intelligent roadside devices. By screening the candidate intelligent roadside devices on the same side of the road as the target intelligent connected vehicle as the specified intelligent roadside devices, then, by determining whether the positioning position in the vehicle operation data is within the effective area of the specified intelligent roadside device to determine the target intelligent roadside device, so as to accurately and quickly determine the target intelligent roadside device from all intelligent roadside devices. Finally, according to the vehicle operation data, the target video acquisition time period corresponding to the target intelligent roadside device is determined, so as to accurately and quickly obtain the target video data related to the abnormal traffic scene event from all the video data of the target intelligent roadside device, and further generate the playback video data for the abnormal traffic scene event.

[0107] Based on the same idea, the embodiments of this specification also provide a device corresponding to the above method. Figure 2 For the embodiment of this specification, it provides a Figure 1 structural schematic diagram of a playback video generation device for an abnormal traffic scene event. As Figure 2 shown, the device may include:

[0108] A vehicle operation data acquisition module 202, configured to acquire vehicle operation data of a target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event; the target intelligent connected vehicle is an intelligent connected vehicle related to the abnormal traffic scene event.

[0109] A video acquisition time determination module 204, configured to determine a target video acquisition time period corresponding to a target intelligent roadside device according to the vehicle operation data; the target video acquisition time period is the time period during which the intelligent roadside device acquires video data including the target intelligent connected vehicle during the event occurrence time period.

[0110] A target video acquisition module 206, configured to acquire target video data acquired by the target intelligent roadside device during the target video acquisition time period.

[0111] A playback video generation module 208, configured to generate playback video data for the abnormal traffic scene event according to the target video data.

[0112] A sending module 201, configured to send the playback video data to a target device.

[0113] Based on the Figure 2 device, the embodiments of this specification also provide some specific implementation schemes of this method, which will be described below.

[0114] Optionally, Figure 2 the device in

[0115] may further include:

[0116] A specified position information determination module, configured to determine the position information of a target object acquired by a specified intelligent roadside device; the target object is an object that appears within the sensing range of the specified intelligent roadside device during the event occurrence time period.

[0117] A target intelligent roadside device determination module, configured to determine the target intelligent roadside device according to the vehicle operation data of the target intelligent connected vehicle and the effective sensing area of the specified intelligent roadside device; the target intelligent connected vehicle is located within the effective sensing area of the target intelligent roadside device during the event occurrence time period.

[0118] Optionally, the vehicle operation data is used to reflect the moment when the target intelligent connected vehicle is located at a specified position.

[0119] The video acquisition time determination module 204 may specifically be configured to:

[0120] According to the vehicle operation data of the target intelligent connected vehicle, determine the initial time and the end time when the specified position is within the effective sensing area of the target intelligent roadside device.

[0121] Determine the time period between the initial time and the end time as the target video acquisition time period corresponding to the target intelligent roadside device.

[0122] Optionally, the vehicle operation data is used to reflect the position where the target intelligent connected vehicle is located;

[0123] Optionally, Figure 2 the device in [[ ]] may further include:

[0124] A preset area determination module, configured to determine a preset area according to the position where the target intelligent connected vehicle is located.

[0125] A specified intelligent roadside device determination module, configured to determine the specified intelligent roadside device from the candidate intelligent roadside devices installed in the preset area according to the installation position information of the intelligent roadside device; wherein, the specified intelligent roadside device is used to perform video acquisition on the target intelligent connected vehicle from a preset orientation.

[0126] Optionally, the specified intelligent roadside device determination module may specifically include:

[0127] A first judgment unit, configured to, for any candidate intelligent roadside device installed in the preset area, judge whether the candidate intelligent roadside device and the target intelligent connected vehicle are on the same side of the road, and obtain a first judgment result.

[0128] A first judgment result determination unit, configured to, if the first judgment result indicates that the candidate intelligent roadside device and the target intelligent connected vehicle are on the same side of the road, determine the candidate intelligent roadside device as the specified intelligent roadside device.

[0129] Optionally, the first judgment unit may specifically be configured to:

[0130] Determine whether the vertical distance between the candidate intelligent roadside device in the preset area and the road edge of the lane where the target intelligent connected vehicle is located is less than the preset road width, and obtain a second determination result.

[0131] If the second determination result indicates that the vertical distance from the intelligent roadside device in the area to the road edge of the lane where the target intelligent connected vehicle is located is less than the road width, it is determined that the intelligent roadside device in the area and the target intelligent connected vehicle are on the same side of the road.

[0132] Optionally, Figure 2 The device in

[0133] An abnormal traffic scene event information acquisition module, configured to acquire the event information of the abnormal traffic scene event, where the event information includes the event location information of the abnormal traffic scene event, the event occurrence time period, and the vehicle identification information of the intelligent connected vehicle involved in the abnormal traffic scene event.

[0134] A target intelligent connected vehicle determination module, configured to determine the intelligent connected vehicle with the vehicle identification information as the target intelligent connected vehicle.

[0135] Optionally, the vehicle operation data acquisition module 202 may specifically be configured to:

[0136] Acquire the vehicle operation data reported by the intelligent connected vehicle with the vehicle identification information during the event occurrence time period from the vehicle bus.

[0137] Optionally, the vehicle operation data acquisition module 202 may specifically be configured to:

[0138] Perform thinning processing on the initial vehicle operation data uploaded by the target intelligent connected vehicle during the event occurrence time period to obtain the vehicle operation data.

[0139] First, according to the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event, determine a preset area to determine candidate intelligent roadside devices, so as to screen the candidate intelligent roadside devices on the same side of the road as the target intelligent connected vehicle as the specified intelligent roadside devices. Then, determine the target intelligent roadside device by judging whether the positioning position in the vehicle operation data is within the effective area of the specified intelligent roadside device, so as to accurately and quickly determine the target intelligent roadside device from all intelligent roadside devices. Finally, according to the vehicle operation data, determine the target video acquisition time period corresponding to the target intelligent roadside device, so as to accurately and quickly obtain the target video data related to the abnormal traffic scene event from all the video data of the target intelligent roadside device, and further generate the playback video data for the abnormal traffic scene event.

[0140] Based on the same idea, the embodiments of this specification also provide a device corresponding to the above method.

[0141] Figure 3 For the Figure 1 abnormal traffic scene event provided by the embodiments of this specification, a schematic structural diagram of a playback video generation device is shown in Figure 3 the following figure. As

[0142] shown, the device 300 may include:

[0143] at least one processor 310; and,

[0144] a memory 330 communicatively connected to the at least one processor; wherein,

[0145] the memory 330 stores instructions 320 executable by the at least one processor 310, and when the instructions are executed by the at least one processor 310, the at least one processor 310 is enabled to:

[0146] obtain the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event; the target intelligent connected vehicle is an intelligent connected vehicle related to the abnormal traffic scene event;

[0147] determine the target video acquisition time period corresponding to the target intelligent roadside device according to the vehicle operation data; the target video acquisition time period is the time period during which the target intelligent roadside device acquires video data including the target intelligent connected vehicle during the event occurrence time period;

[0148] obtain the target video data acquired by the target intelligent roadside device during the target video acquisition time period;

[0149] generate playback video data for the abnormal traffic scene event according to the target video data;

[0150] The embodiments in this specification are all described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for Figure 3 the playback video generation device for the abnormal traffic scene event shown in the following figure, since it is basically similar to the method embodiment, the description is relatively simple, and for the related parts, reference can be made to the partial description of the method embodiment.

[0151] In the 1990s, it was obvious to distinguish whether an improvement to a technology was an improvement in hardware (e.g., improvement to the circuit structure of diodes, transistors, switches, etc.) or an improvement in software (improvement to the method flow). However, with the development of technology, many improvements to method flows today can be regarded as direct improvements to the hardware circuit structure. Almost all designers obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that an improvement to a method flow cannot be implemented with a hardware entity module. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logical function is determined by the user programming the device. The designer can program by himself to "integrate" a digital character system on a piece of PLD without asking the chip manufacturer to design and fabricate a dedicated integrated circuit chip. Moreover, nowadays, instead of manually fabricating integrated circuit chips, this programming is mostly implemented using "logic compiler" software, which is similar to the software compiler used in program development and writing. The original code before compilation also has to be written in a specific programming language, which is called Hardware Description Language (HDL). And there is not only one kind of HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones currently are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also be clear that as long as the method flow is slightly logically programmed with the above-mentioned several hardware description languages and programmed into the integrated circuit, it is easy to obtain the hardware circuit that implements the logical method flow.

[0152] The controller can be implemented in any suitable manner. For example, the controller can take the form of, for example, a microprocessor or a processor and a computer-readable medium storing computer-readable program code (such as software or firmware) executable by the (micro)processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of the controller include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that, in addition to implementing the controller in the form of pure computer-readable program code, it is entirely possible to make the controller implement the same function in the form of logic gates, switches, ASICs, programmable logic controllers, embedded microcontrollers, etc. by logically programming the method steps. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be regarded as the structures within the hardware component. Or even, the devices for implementing various functions can be regarded as either software modules for implementing the method or structures within the hardware component.

[0153] The systems, devices, modules, or units illustrated in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0154] For the convenience of description, the above devices are described by dividing them into various units according to functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0155] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0156] The present invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each flow and / or block of the flowchart illustrations and / or block diagrams, and combinations of flows and / or blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing apparatus create means for implementing the functions specified in the flowchart Figure 1 for one or more flows and / or blocks Figure 1 for one or more blocks.

[0157] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means that implement the functions specified in the flowchart Figure 1 for one or more flows and / or blocks Figure 1 for one or more blocks.

[0158] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart Figure 1 for one or more flows and / or blocks Figure 1 for one or more blocks.

[0159] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and memory.

[0160] The memory may include non-permanent memory in the form of computer-readable media, random access memory (RAM), and / or non-volatile memory, such as read-only memory (ROM) or flash memory (flash RAM). The memory is an example of computer-readable media.

[0161] Computer-readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0162] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0163] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0164] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0165] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for generating a playback video of an abnormal traffic scene event, characterized in that, The method includes: Obtaining vehicle operation data of a target intelligent connected vehicle during the event occurrence time period of an abnormal traffic scene event; the target intelligent connected vehicle is an intelligent connected vehicle related to the abnormal traffic scene event; Determining a target video capture time period corresponding to a target intelligent roadside device according to the vehicle operation data; the target video capture time period is the time period during which the target intelligent roadside device captures video data including the target intelligent connected vehicle during the event occurrence time period; Obtaining target video data captured by the target intelligent roadside device during the target video capture time period; Generating replay video data for the abnormal traffic scene event according to the target video data; Sending the replay video data to a target device; The vehicle operation data is used to reflect the moment when the target intelligent connected vehicle is located at a specified position; The determining the target video capture time period corresponding to the target intelligent roadside device according to the vehicle operation data specifically includes: Determining an initial moment and a termination moment when the specified position is within the effective sensing area of the target intelligent roadside device according to the vehicle operation data of the target intelligent connected vehicle; Determining the time period between the initial moment and the termination moment as the target video capture time period corresponding to the target intelligent roadside device; Before the determining the target video capture time period corresponding to the target intelligent roadside device according to the vehicle operation data, it further includes: Determining the position information of a target object obtained by a specified intelligent roadside device; the target object is an object that appears within the sensing range of the specified intelligent roadside device during the event occurrence time period; Determining the effective sensing area of the specified intelligent roadside device according to the position information of the target object; Determining the target intelligent roadside device according to the vehicle operation data of the target intelligent connected vehicle and the effective sensing area of the specified intelligent roadside device; the target intelligent connected vehicle is within the effective sensing area of the target intelligent roadside device during the event occurrence time period.

2. The method according to claim 1, characterized in that, The vehicle operation data is used to reflect the position where the target intelligent connected vehicle is located; Before the determining the position information of the target object obtained by the specified intelligent roadside device, it further includes: Determining a preset area according to the position where the target intelligent connected vehicle is located; Determining the specified intelligent roadside device from the candidate intelligent roadside devices installed in the preset area according to the installation position information of the intelligent roadside device; wherein, the specified intelligent roadside device is used to capture video of the target intelligent connected vehicle from a preset orientation.

3. The method according to claim 2, characterized in that, The determining the specified intelligent roadside device from the candidate intelligent roadside devices installed in the preset area according to the installation position information of the intelligent roadside device specifically includes: For any candidate intelligent roadside device installed in the preset area, determining whether the candidate intelligent roadside device and the target intelligent connected vehicle are on the same side of the road, and obtaining a first judgment result; If the first judgment result indicates that the candidate intelligent roadside device and the target intelligent connected vehicle are on the same side of the road, then determine the candidate intelligent roadside device as the specified intelligent roadside device.

4. The method according to claim 3, wherein The judgment of whether the candidate intelligent roadside device and the target intelligent connected vehicle are on the same side of the road specifically includes: Judging whether the vertical distance between the candidate intelligent roadside device and the road edge line of the lane where the target intelligent connected vehicle is located is less than a preset road width to obtain a second judgment result; If the second judgment result indicates that the vertical distance from the candidate intelligent roadside device to the road edge line of the road in the lane where the target intelligent connected vehicle is located is less than the preset road width, then determine that the candidate intelligent roadside device and the target intelligent connected vehicle are on the same side of the road.

5. The method according to claim 1, characterized in that, Before obtaining the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event, it further includes: Obtaining the event information of the abnormal traffic scene event, where the event information includes the event location information of the abnormal traffic scene event, the event occurrence time period, and the vehicle identification information of the intelligent connected vehicle involved in the abnormal traffic scene event; Determining the intelligent connected vehicle with the vehicle identification information as the target intelligent connected vehicle; The obtaining of the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event specifically includes: Obtaining the vehicle operation data reported by the intelligent connected vehicle with the vehicle identification information at the vehicle bus during the event occurrence time period.

6. The method according to any one of claims 1 to 5, characterized in that, The obtaining of the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event specifically includes: Performing downsampling processing on the initial vehicle operation data uploaded by the target intelligent connected vehicle during the event occurrence time period to obtain the vehicle operation data.

7. A playback video generation device for abnormal traffic scene events, characterized in that, The device includes: A vehicle operation data acquisition module, configured to acquire the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event; the target intelligent connected vehicle is an intelligent connected vehicle related to the abnormal traffic scene event; A video acquisition time determination module, configured to determine a target video acquisition time period corresponding to the target intelligent roadside device according to the vehicle operation data; the target video acquisition time period is the time period during which the intelligent roadside device acquires video data including the target intelligent connected vehicle during the event occurrence time period; A target video acquisition module, configured to acquire the target video data acquired by the target intelligent roadside device during the target video acquisition time period; A playback video generation module, configured to generate playback video data for the abnormal traffic scene event according to the target video data; A sending module, configured to send the playback video data to a target device; Wherein, the vehicle operation data is used to reflect the moment when the target intelligent connected vehicle is located at a specified position; The determining of the target video acquisition time period corresponding to the target intelligent roadside device according to the vehicle operation data specifically includes: Determine the initial time and the end time when the specified location is within the effective sensing area of the target intelligent roadside device according to the vehicle operation data of the target intelligent connected vehicle; Determine the time period between the initial time and the end time as the target video acquisition time period corresponding to the target intelligent roadside device; The vehicle operation data is used to reflect the location of the target intelligent connected vehicle; Before determining the location information of the target object obtained by the specified intelligent roadside device, it further includes: Determine a preset area according to the location of the target intelligent connected vehicle; Determine the specified intelligent roadside device from the candidate intelligent roadside devices installed in the preset area according to the installation location information of the intelligent roadside device; wherein, the specified intelligent roadside device is used to perform video acquisition on the target intelligent connected vehicle from a preset direction.

8. A playback video generation device for abnormal traffic scene events, characterized in that, The device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is capable of: Obtain the vehicle operation data of the target intelligent connected vehicle during the event occurrence time period of the abnormal traffic scene event; the target intelligent connected vehicle is an intelligent connected vehicle related to the abnormal traffic scene event; Determine the target video acquisition time period corresponding to the target intelligent roadside device according to the vehicle operation data; the target video acquisition time period is the time period during which the intelligent roadside device acquires video data including the target intelligent connected vehicle during the event occurrence time period; Obtain the target video data acquired by the target intelligent roadside device during the target video acquisition time period; Generate replay video data for the abnormal traffic scene event according to the target video data; Send the replay video data to the target device; The vehicle operation data is used to reflect the time when the target intelligent connected vehicle is located at the specified location; The determining the target video acquisition time period corresponding to the target intelligent roadside device according to the vehicle operation data specifically includes: Determine the initial time and the end time when the specified location is within the effective sensing area of the target intelligent roadside device according to the vehicle operation data of the target intelligent connected vehicle; Determine the time period between the initial time and the end time as the target video acquisition time period corresponding to the target intelligent roadside device; Before determining the target video acquisition time period corresponding to the target intelligent roadside device according to the vehicle operation data, it further includes: Determine the location information of the target object obtained by the specified intelligent roadside device; the target object is an object that appears within the sensing range of the specified intelligent roadside device during the event occurrence time period; Determine the effective sensing area of the specified intelligent roadside device according to the location information of the target object; Determine the target intelligent roadside device according to the vehicle operation data of the target intelligent connected vehicle and the effective sensing area of the specified intelligent roadside device; the target intelligent connected vehicle is located within the effective sensing area of the target intelligent roadside device during the event occurrence time period.

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