Information acquisition method and device, computer equipment and storage medium

Abstract

The invention relates to an information acquisition method and device, computer equipment and a storage medium. The method comprises the steps that the attention duration of a driver of a vehicle for target surrounding vehicles of the vehicle is obtained, the collision time of the target surrounding vehicles of the vehicle is determined, the target surrounding vehicles are any surrounding vehicles of the vehicle, and the target surrounding vehicles are the target surrounding vehicles of the vehicle; the attention duration of the driver for a target surrounding vehicle of the vehicle indicates the duration of the driver paying attention to the target surrounding vehicle, and the attention duration is determined according to the fixation point of the driver; according to the attention duration of the driver for the target surrounding vehicles of the vehicle and the collision time of the target surrounding vehicles of the vehicle, the collision risk level of the target surrounding vehicles of the vehicle is determined.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to an information acquisition method, device, computer equipment and storage medium. Background Art

[0002] Obtaining the collision risk level of vehicles near the vehicle is an important basis for the vehicle's autonomous driving system to make driving decisions, such as lateral and longitudinal control strategies. In related technologies, the collision risk level of vehicles near the vehicle is obtained based on a single factor, namely the parameters of the vehicle, and the accuracy of the obtained collision risk level is low. How to improve the accuracy of the obtained collision risk results has become a problem that needs to be solved. Summary of the invention

[0003] One of the purposes of the present invention is to provide an information acquisition method, apparatus, computer device and storage medium to solve the problem.

[0004] In order to achieve the above object, the technical solution adopted by the present invention is as follows:

[0005] A method for obtaining information, comprising:

[0006] Obtaining the attention time of the driver of the own vehicle to the target surrounding vehicle of the own vehicle, and determining the collision time of the target surrounding vehicle of the own vehicle, wherein the target surrounding vehicle is any surrounding vehicle of the own vehicle, and the attention time of the driver to the target surrounding vehicle of the own vehicle indicates the time the driver pays attention to the target surrounding vehicle, and the attention time is determined according to the gaze point of the driver;

[0007] The collision risk level of the target surrounding vehicle is determined according to the driver's attention duration on the target surrounding vehicle and the collision time of the target surrounding vehicle.

[0008] According to the above technical means, multiple factors, namely, the length of time the driver of the vehicle pays attention to the target surrounding vehicles of the vehicle and the collision time of the target surrounding vehicles of the vehicle, are used to obtain the collision risk level of the target surrounding vehicles of the vehicle. Considering the characteristics of the collision risk level related to the driver of the vehicle, namely, the actions of the surrounding vehicles that the driver of the vehicle pays attention to usually have a greater impact on the actions of the vehicle, the length of time the driver of the vehicle pays attention to the target surrounding vehicles of the vehicle in the information acquisition method provided by the present invention can more accurately quantify the degree of attention of the driver of the vehicle to the surrounding vehicles of the vehicle. The length of time the driver of the vehicle pays attention to the surrounding vehicles has a high correlation with the collision risk level. At the same time, the collision time with a high correlation with the collision risk level and the length of time the driver pays attention to the surrounding vehicles of the vehicle with a high correlation with the collision risk level are used to obtain the collision risk level of the surrounding vehicles of the vehicle, thereby improving the accuracy of the obtained collision risk level.

[0009] Further, determining the collision risk level of the target surrounding vehicle according to the driver's attention duration on the target surrounding vehicle and the collision time of the target surrounding vehicle includes:

[0010] Generate a target of interest judgment result of the target surrounding vehicle according to a comparison result of the driver's attention duration on the target surrounding vehicle and a first attention duration threshold, wherein the target of interest judgment result of the target surrounding vehicle indicates whether the target surrounding vehicle is a target of interest of the driver;

[0011] The collision risk level of the target surrounding vehicle is determined according to the collision time of the target surrounding vehicle and the focus target judgment result of the target surrounding vehicle.

[0012] Further, according to the collision time of the target surrounding vehicle and the judgment result of the target surrounding vehicle, determining the collision risk level of the target surrounding vehicle includes:

[0013] When the target surrounding vehicle's attention target judgment result indicates that the target surrounding vehicle is not the driver's attention target and the target surrounding vehicle has been the driver's attention target within a target previous time period, the automatic driving system collision risk level corresponding to the target surrounding vehicle is determined according to the collision time of the target surrounding vehicle, wherein the target previous time period is a time period having an end time of the current time and a duration of a preset observation time period; the collision risk level of the target surrounding vehicle is determined according to the automatic driving system collision risk level corresponding to the target surrounding vehicle.

[0014] Further, according to the collision risk level of the automatic driving system corresponding to the target surrounding vehicle, determining the collision risk level of the target surrounding vehicle includes:

[0015] The difference between the automatic driving system collision risk level corresponding to the target surrounding vehicle and a preset value is determined as the collision risk level of the target surrounding vehicle.

[0016] Further, according to the collision time of the target surrounding vehicle and the judgment result of the target surrounding vehicle, determining the collision risk level of the target surrounding vehicle includes:

[0017] When the target surrounding vehicle's attention target judgment result indicates that the target surrounding vehicle is the driver's attention target, determining a driver correction level corresponding to the target surrounding vehicle according to the driver's attention duration on the target surrounding vehicle, and determining an automatic driving system collision risk level corresponding to the target surrounding vehicle according to the collision time of the target surrounding vehicle;

[0018] The sum of the driver correction level corresponding to the target surrounding vehicle and the automatic driving system collision risk level corresponding to the target surrounding vehicle is determined as the collision risk level of the target surrounding vehicle.

[0019] Further, according to the driver's attention duration to the target surrounding vehicle, determining the driver correction level corresponding to the target surrounding vehicle includes:

[0020] When the driver's attention time for the target surrounding vehicle is not less than a first attention time threshold and the driver's attention time for the target surrounding vehicle is not greater than a second attention time threshold, determining a first correction level as the driver's correction level corresponding to the target surrounding vehicle, wherein the second attention time threshold is greater than the first attention time threshold;

[0021] When the driver's attention time for the target surrounding vehicle is greater than a second attention time threshold, a second correction level is determined as the driver correction level corresponding to the target surrounding vehicle, and the second correction level is higher than the first correction level.

[0022] Further, determining the collision risk level of the automatic driving system corresponding to the target surrounding vehicle according to the collision time of the target surrounding vehicle includes:

[0023] Determining the type of the target surrounding vehicle related to the collision risk according to the collision time and collision time threshold of the target surrounding vehicle;

[0024] According to the type of the target surrounding vehicle related to the collision risk, the collision risk level of the automatic driving system corresponding to the target surrounding vehicle is determined.

[0025] Further, according to the collision time and the collision time threshold of the target surrounding vehicle, determining the type of the target surrounding vehicle related to the collision risk includes:

[0026] When the collision time of the target surrounding vehicle is greater than a target collision time threshold, determining the no-collision risk type as the type of the target surrounding vehicle associated with the collision risk;

[0027] When the collision time of the target surrounding vehicle is not greater than the target collision time threshold, determining the collision risk type as the type of the target surrounding vehicle related to the collision risk;

[0028] And according to the types of the target surrounding vehicles of the own vehicle related to the collision risk, determining the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle includes:

[0029] When the type of the target surrounding vehicle related to the collision risk is a type without collision risk, determining the preset minimum risk level for determining the collision risk level of the automatic driving system as the collision risk level of the automatic driving system corresponding to the target surrounding vehicle;

[0030] When the type of the target surrounding vehicle associated with the collision risk is a type with collision risk, the collision risk level of the automatic driving system corresponding to the target surrounding vehicle is determined according to the collision time of the target surrounding vehicle, the collision time of the surrounding vehicles and the correlation relationship between the collision risk level of the automatic driving system corresponding to the surrounding vehicles, wherein the preset minimum risk level for determining the collision risk level of the automatic driving system is lower than the collision risk level of the automatic driving system corresponding to the target surrounding vehicle determined when the type of the target surrounding vehicle associated with the collision risk is a type with collision risk.

[0031] An information acquisition device, the information acquisition device comprising:

[0032] an acquisition unit, used for acquiring a time duration of attention of a driver of the own vehicle to a target surrounding vehicle of the own vehicle, and determining a collision time of the target surrounding vehicle of the own vehicle, wherein the target surrounding vehicle is any surrounding vehicle of the own vehicle, and the time duration of attention of the driver to the target surrounding vehicle of the own vehicle indicates a time duration of attention of the driver to the target surrounding vehicle, and the attention time duration is determined according to a gaze point of the driver;

[0033] The determination unit is used to determine the collision risk level of the target surrounding vehicle according to the driver's attention duration on the target surrounding vehicle and the collision time of the target surrounding vehicle.

[0034] Furthermore, the determination unit is also used to generate an attention target judgment result of the target surrounding vehicle based on a comparison result of the driver's attention time for the target surrounding vehicle and a first attention time threshold, wherein the attention target judgment result of the target surrounding vehicle indicates whether the target surrounding vehicle is the driver's attention target; and determine the collision risk level of the target surrounding vehicle based on the collision time of the target surrounding vehicle and the attention target judgment result of the target surrounding vehicle.

[0035] Furthermore, the determination unit is also used to determine the collision risk level of the automatic driving system corresponding to the target surrounding vehicle according to the collision time of the target surrounding vehicle when the target focus target judgment result of the target surrounding vehicle indicates that the target surrounding vehicle is not the driver's focus target and the target surrounding vehicle has been the driver's focus target within a target previous time period, wherein the target previous time period is a time period having an end time as the current time and a duration as a preset observation time period; determine the collision risk level of the target surrounding vehicle according to the collision risk level of the automatic driving system corresponding to the target surrounding vehicle.

[0036] Furthermore, the determination unit is also used to determine the difference between the automatic driving system collision risk level corresponding to the target surrounding vehicle and a preset value as the collision risk level of the target surrounding vehicle when the focus target judgment result of the target surrounding vehicle indicates that the target surrounding vehicle is not the focus target of the driver and the target surrounding vehicle has been the focus target of the driver within a previous target time period.

[0037] Furthermore, the determination unit is also used to determine the driver correction level corresponding to the target surrounding vehicle according to the driver's attention duration on the target surrounding vehicle when the focus target judgment result of the target surrounding vehicle indicates that the target surrounding vehicle is the driver's focus target, and determine the automatic driving system collision risk level corresponding to the target surrounding vehicle according to the collision time of the target surrounding vehicle; and determine the sum of the driver correction level corresponding to the target surrounding vehicle and the automatic driving system collision risk level corresponding to the target surrounding vehicle as the collision risk level of the target surrounding vehicle.

[0038] Furthermore, the determination unit is also used to determine the first correction level as the driver correction level corresponding to the target surrounding vehicle when the driver's attention time for the target surrounding vehicle is not less than a first attention time threshold and the driver's attention time for the target surrounding vehicle is not greater than a second attention time threshold, wherein the second attention time threshold is greater than the first attention time threshold; when the driver's attention time for the target surrounding vehicle is greater than the second attention time threshold, determine the second correction level as the driver correction level corresponding to the target surrounding vehicle, and the second correction level is higher than the first correction level.

[0039] Furthermore, the determination unit is also used to determine the type of the target surrounding vehicle related to the collision risk based on the collision time and collision time threshold of the target surrounding vehicle; and determine the collision risk level of the automatic driving system corresponding to the target surrounding vehicle based on the type of the target surrounding vehicle related to the collision risk.

[0040] Furthermore, the determination unit is also used to determine the no-collision risk type as the type associated with the collision risk of the target surrounding vehicles when the collision time of the target surrounding vehicles is greater than the target collision time threshold; and to determine the collision risk type as the collision risk type associated with the collision risk of the target surrounding vehicles when the collision time of the target surrounding vehicles is not greater than the target collision time threshold. The determination unit is also used to determine the preset minimum risk level for determining the collision risk level of the automatic driving system as the collision risk level of the automatic driving system corresponding to the target surrounding vehicles when the type associated with the collision risk of the target surrounding vehicles is the no-collision risk type; and when the type associated with the collision risk of the target surrounding vehicles is the collision risk type, determine the collision risk level of the automatic driving system corresponding to the target surrounding vehicles according to the correlation between the collision time of the target surrounding vehicles, the collision time of the surrounding vehicles and the collision risk level of the automatic driving system corresponding to the surrounding vehicles, wherein the preset minimum risk level for determining the collision risk level of the automatic driving system is less than the collision risk level of the automatic driving system corresponding to the target surrounding vehicles determined when the type associated with the collision risk of the target surrounding vehicles is the collision risk type.

[0041] Beneficial effects of the present invention:

[0042] The collision risk level of the target surrounding vehicles of the own vehicle is obtained by using multiple factors, namely, the length of time the driver of the own vehicle pays attention to the target surrounding vehicles of the own vehicle and the collision time of the target surrounding vehicles of the own vehicle. Considering the characteristics of the collision risk level related to the driver of the own vehicle, namely, the actions of the surrounding vehicles that the driver of the own vehicle pays attention to usually have a greater impact on the actions of the own vehicle, the length of time the driver of the own vehicle pays attention to the target surrounding vehicles of the own vehicle in the information acquisition method provided by the present invention can more accurately quantify the degree of attention of the driver of the own vehicle to the surrounding vehicles of the own vehicle. The length of time the driver of the own vehicle pays attention to the surrounding vehicles has a high correlation with the collision risk level. At the same time, the collision time with a high correlation with the collision risk level and the length of time the driver pays attention to the surrounding vehicles of the own vehicle with a high correlation with the collision risk level are used to obtain the collision risk level of the surrounding vehicles of the own vehicle, thereby improving the accuracy of the obtained collision risk level. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A schematic diagram of a flow chart of an information acquisition method provided by an embodiment of the present invention;

[0044] Figure 2 A schematic diagram of a flow chart of another information acquisition method provided by an embodiment of the present invention;

[0045] Figure 3 A flowchart of an example of obtaining collision risk levels of surrounding vehicles of the own vehicle;

[0046] Figure 4 A schematic diagram of the hardware structure of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] The following will describe the embodiments of the present invention with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention, not for limiting the scope of protection of the present invention.

[0048] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0049] refer to Figure 1 , which shows a flow chart of the information acquisition method provided by an embodiment of the present invention. It should be noted that the vehicle can be any vehicle to which the information acquisition method provided by the embodiment of the present invention can be applied. During the driving of the vehicle, the information acquisition method provided by the embodiment of the present invention can be executed periodically according to a preset cycle length. Steps S101-S102 can be periodically executed for each surrounding vehicle of the vehicle. Thus, the collision risk level of each surrounding vehicle of the vehicle is obtained. The information acquisition method provided by an embodiment of the present invention can be executed after determining the authorization of the driver of the vehicle. The driver's perspective image captured by the camera of the device worn by the driver using the information acquisition method provided by the embodiment of the present invention can be used after obtaining the driver's authorization.

[0050] In step S101 , the attention time of the driver of the own vehicle to the target surrounding vehicle of the own vehicle is obtained, and the collision time of the target surrounding vehicle of the own vehicle is determined.

[0051] In the disclosed embodiment, the surrounding vehicles of the own vehicle are vehicles near the own vehicle. The target surrounding vehicle of the own vehicle may be any surrounding vehicle of the own vehicle.

[0052] In a possible implementation, the surrounding vehicles of the own vehicle are vehicles within an area of ​​a preset shape with the current position of the own vehicle as the center point.

[0053] In another possible implementation, the surrounding vehicles of the own vehicle are vehicles whose positions are at a distance less than a distance threshold from the current position of the own vehicle.

[0054] In the embodiment of the present invention, the gaze point can be determined based on an image, and the gaze point is determined according to an environment image captured by a camera of the vehicle or an image of the driver's perspective captured by a camera of a device worn by the driver. For each captured environment image, the driver's gaze point is determined based on the captured environment image.

[0055] Among them, the environmental image collected by the camera of the ego vehicle describes objects such as vehicles, pedestrians, obstacles, etc. in the environment where the ego vehicle is located.

[0056] In one possible implementation, the driver wears an eye tracker. The data obtained by the eye tracker includes: eye movement data, driver's perspective image. Eye movement data includes: fixation point and scan point. Scan point records the process of the driver's viewpoint switching. The driver's scan point is more often caused by the movement of the line of sight. Therefore, it is necessary to extract the fixation point from the eye movement data and filter the scan point. The fixation point of the driver of the vehicle can be extracted by the speed threshold method. The principle of the speed threshold method is to use the driver's viewpoint movement speed to distinguish between fixation and scan. Usually, the fixation point movement speed will be less than 100° / second; the scan point movement speed will be greater than 300° / second. The speed threshold can be set to 100° / second. If the viewpoint movement speed is less than the speed threshold, the viewpoint can be determined as a fixation point. If the viewpoint movement speed is greater than the speed threshold, the viewpoint can be determined as a scan point.

[0057] It should be noted that when the coordinates of the gaze point output by the algorithm for detecting the gaze point are the coordinates of the gaze point in the image coordinate system of the driver's perspective image, it is necessary to convert the coordinates of the gaze point in the image coordinate system of the driver's perspective image into the coordinates of the gaze point in the image coordinate system of the corresponding environment image collected by the camera of the target surrounding vehicle, and obtain the position of the gaze point in the corresponding environment image collected by the camera of the target surrounding vehicle. In this way, it is possible to determine whether the gaze point stays on the surrounding vehicle according to the position of the gaze point in the corresponding environment image collected by the camera of the target surrounding vehicle and the detection frame surrounding the surrounding vehicles in the corresponding environment image. The coordinates in the driver's perspective image can be transformed into the coordinates in the image coordinate system of the environment image according to the transformation relationship between the coordinates of the gaze point in the image coordinate system of the driver's perspective image, the coordinates of the pixel points in the driver's perspective image in the image coordinate system of the driver's perspective image, and the coordinates of the pixel points in the environment image in the image coordinate system of the environment image. In order to obtain the transformation relationship, the environment image whose acquisition time is closest to the acquisition time of the driver's perspective image can be determined as the environment image corresponding to the driver's perspective image. The SURF feature matching method can be applied to the driver's perspective image and the environment image corresponding to the driver's perspective image to obtain the transformation relationship between the coordinates of the pixel points in the driver's perspective image in the image coordinate system of the driver's perspective image and the coordinates of the pixel points in the environment image in the image coordinate system of the environment image.

[0058] In the embodiment of the present invention, for the target surrounding vehicles of the own vehicle, the driver of the own vehicle indicates the attention duration of the target surrounding vehicles of the own vehicle: the duration of the driver of the own vehicle paying attention to the target surrounding vehicles.

[0059] In step S101, for the target surrounding vehicles of the own vehicle, the parameter value of the attention duration parameter of the target surrounding vehicles of the own vehicle can be read, thereby obtaining the attention duration of the driver of the own vehicle to the target surrounding vehicles of the own vehicle.

[0060] The attention duration of the target surrounding vehicle is determined based on the gaze point of the driver of the own vehicle. The gaze point of the driver of the own vehicle is determined based on an image for determining the gaze point of the driver of the own vehicle.

[0061] It should be noted that the parameter value of the attention time parameter of the target surrounding vehicles of the own vehicle is a variable.

[0062] For a target surrounding vehicle of the own vehicle, when the target surrounding vehicle is detected for the first time and before the parameter value of the attention time parameter of the target surrounding vehicle is updated, the parameter value of the attention time parameter of the driver of the own vehicle for the target surrounding vehicle is an initial value, which is 0.

[0063] In an embodiment of the present invention, the parameter value of the attention duration parameter of the target surrounding vehicle of the own vehicle is updated according to whether the gaze point of the driver of the own vehicle determined by the image used to determine the gaze point of the driver of the own vehicle stays on the target surrounding vehicle.

[0064] Whether the gaze point of the driver of the own vehicle determined by the image for determining the gaze point of the driver of the own vehicle stays on the surrounding vehicles can be determined based on the following items: the image for determining the gaze point of the driver of the own vehicle and the environmental image corresponding to the image for determining the gaze point of the driver of the own vehicle.

[0065] The environment image corresponding to the image used to determine the gaze point of the driver of the vehicle may be one of the following: a first environment image, a second environment image, and a third environment image.

[0066] The first environment image is an environment image having a collection time closest to the collection time of the image used to determine the gaze point of the driver of the own vehicle.

[0067] The second environmental image is: an environmental image having a collection time earlier than the collection time of the image used to determine the gaze point of the driver of the vehicle, and an environmental image having a collection time closest to the collection time of the image used to determine the gaze point of the driver of the vehicle.

[0068] The third environmental image is: an environmental image having a collection time later than the collection time of the image used to determine the gaze point of the driver of the vehicle, and having a collection time closest to the collection time of the image used to determine the gaze point of the driver of the vehicle.

[0069] For image j used to determine the gaze point of the driver of the own vehicle and the environmental image k corresponding to image j used to determine the gaze point of the driver of the own vehicle, if the position represented by the coordinates of the gaze point of the driver of the own vehicle determined by image j under the environmental image k is within the detection box of the target surrounding vehicles in the environmental image k, then it can be determined that the gaze point of the driver of the own vehicle determined by image j stays on the target surrounding vehicles.

[0070] The image j used to determine the gaze point of the driver of the own vehicle may be any image used to determine the gaze point of the driver of the own vehicle.

[0071] The updating of the parameter value of the attention time parameter of the driver of the own vehicle to the target surrounding vehicles may include: step S1011 and step S1012. Step S1011 is used to increase the parameter value of the attention time parameter of the driver of the own vehicle to the target surrounding vehicles, and step S1012 is used to clear the parameter value of the attention time parameter of the driver of the own vehicle to the target surrounding vehicles.

[0072] In step S1011, for the target surrounding vehicles of the own vehicle, if it is determined that the gaze point of the driver of the own vehicle determined by the t-1th image for determining the gaze point of the driver of the own vehicle stays on the target surrounding vehicles, and it is determined that the gaze point of the driver of the own vehicle determined by the tth image for determining the gaze point of the driver of the own vehicle stays on the target surrounding vehicles, then the parameter value of the attention time parameter of the driver of the own vehicle for the target surrounding vehicles can be updated, and the parameter value of the attention time parameter of the driver of the own vehicle for the target surrounding vehicles can be updated to: the sum of the current parameter value of the attention time parameter of the target surrounding vehicles and the target time difference.

[0073] The current parameter value of the attention time parameter of the target surrounding vehicle may refer to the parameter value of the attention time parameter of the driver of the own vehicle for the target surrounding vehicle at the time when the update starts.

[0074] The target time difference may be one of the following: a first time interval, a second time interval, or a third time interval.

[0075] The first time interval can be: the time interval between the moment when the gaze point of the driver of the own vehicle determined by the t-1th image for determining the gaze point of the driver of the own vehicle stays on the target surrounding vehicle and the moment when the gaze point of the driver of the own vehicle determined by the tth image for determining the gaze point of the driver of the own vehicle stays on the target surrounding vehicle.

[0076] The second time interval may be: the time interval between the acquisition moments of two adjacent images used to determine the gaze point of the driver of the vehicle.

[0077] The third time interval may be: the time interval between the acquisition moments of two adjacent environment images.

[0078] In a possible implementation of step S1012, for the target surrounding vehicles of the own vehicle, if it is determined that the gaze point of the driver of the own vehicle determined by the t-1th image for determining the gaze point of the driver of the own vehicle stays on the target surrounding vehicles, and it is determined that the gaze point of the driver of the own vehicle determined by the tth image for determining the gaze point of the driver of the own vehicle does not stay on the target surrounding vehicles, then the parameter value of the attention time parameter of the driver of the own vehicle for the target surrounding vehicles can be updated, and the parameter value of the attention time parameter of the driver of the own vehicle for the target surrounding vehicles can be updated to 0.

[0079] In another possible implementation of step S1012, for the target surrounding vehicle of the own vehicle, if it is determined that the gaze point of the driver of the own vehicle determined by the t-1th image for determining the gaze point of the driver of the own vehicle stays on the target surrounding vehicle, and it is determined that each gaze point of the driver of the own vehicle determined by the tth image for determining the gaze point of the driver of the own vehicle ... the t+kth image for determining the gaze point of the driver of the own vehicle does not stay on the target surrounding vehicle, then the parameter value of the attention time parameter of the driver of the own vehicle for the target surrounding vehicle can be updated, and the parameter value of the attention time parameter of the driver of the own vehicle for the target surrounding vehicle can be updated to 0. Wherein, k is preset.

[0080] It should be noted that the order of images used to determine the gaze point of the driver of the own vehicle refers to the order obtained by sorting the images used to determine the gaze point of the driver of the own vehicle from the earliest to the latest according to the acquisition time of the images used to determine the gaze point of the driver of the own vehicle. The earlier the acquisition time of the images used to determine the gaze point of the driver of the own vehicle, the earlier the position of the images used to determine the gaze point of the driver of the own vehicle in the order.

[0081] In one possible implementation, for a target surrounding vehicle of the self-vehicle, the collision time of the target surrounding vehicle indicates how long it will take for the target surrounding vehicle to collide with the self-vehicle from the current moment. Any existing method for predicting the collision time of a vehicle can be used to predict how long it will take for the target surrounding vehicle to collide with the self-vehicle from the current moment.

[0082] In another possible implementation, for the target surrounding vehicles of the self-vehicle, the collision time of the target surrounding vehicles indicates: how long will it take for the target surrounding vehicles to enter the safety area of ​​the self-vehicle from the current moment. The module for predicting the vehicle trajectory of the self-vehicle predicts the trajectory of the self-vehicle and the trajectory of the target surrounding vehicles. For example, assuming that the self-vehicle is traveling at a constant speed according to the planned driving trajectory of the vehicle at the current speed, and the target surrounding vehicles of the self-vehicle are traveling at a constant acceleration according to their predicted trajectories at the current acceleration and speed, the trajectory of the self-vehicle within a certain time, such as 20 seconds, from the current moment is predicted, and the trajectory of the target surrounding vehicles of the self-vehicle within a certain time, such as 20 seconds, from the current moment is predicted. According to the trajectory of the self-vehicle, the position of the self-vehicle after a certain time, such as 20 seconds, from the current moment is determined. The rectangular area with the center point being the position of the self-vehicle after a certain time from the current moment is taken as the safety area of ​​the self-vehicle. Among them, the length of the safety area of ​​the self-vehicle can be the sum of the length of the self-vehicle and the preset length. As an example, the preset length is 2 meters. The width of the safety area of ​​the self-vehicle can be called the safe driving channel width. The width of the safety zone of the ego vehicle can be preset, and the width of the safety zone of the ego vehicle can also be determined based on the speed and acceleration of the ego vehicle after a certain period of time from the current moment. Based on the trajectory of the target surrounding vehicles of the ego vehicle, it is predicted whether the target surrounding vehicles will enter the safety zone of the ego vehicle within a certain period of time from the current moment. If the ego vehicle predicts that the target surrounding vehicles will enter the safety zone of the ego vehicle within a certain period of time from the current moment, the collision time of the target surrounding vehicles is predicted, and the collision time of the target surrounding vehicles indicates how long it will take for the target surrounding vehicles of the ego vehicle to enter the safety zone of the ego vehicle from the current moment.

[0083] In step S102 , the collision risk level of the target surrounding vehicle of the own vehicle is determined according to the attention time of the driver of the own vehicle to the target surrounding vehicle of the own vehicle and the collision time of the target surrounding vehicle.

[0084] In step S102, the attention time of the driver of the vehicle to each surrounding vehicle of the vehicle can be normalized to obtain the normalized value of the attention time of the driver of the vehicle to each surrounding vehicle of the vehicle. The collision time of each surrounding vehicle of the vehicle can be normalized to obtain the normalized value of the collision time of each surrounding vehicle of the vehicle. Determine the average value of the normalized value of the attention time of the driver of the vehicle to the target surrounding vehicles of the vehicle and the normalized value of the collision time of the target surrounding vehicles, that is, the sum of the normalized value of the attention time of the target surrounding vehicles of the vehicle and the normalized value of the collision time of the target surrounding vehicles divided by 2, and use the average value as the collision risk level of the target surrounding vehicles of the vehicle.

[0085] In an embodiment of the present invention, a plurality of collision risk level intervals may be pre-set. Each collision risk level interval corresponds to a control strategy. After determining the collision risk level of the target surrounding vehicles of the own vehicle, the collision risk level interval in which the collision risk of the target surrounding vehicles of the own vehicle is located may be determined, and the control strategy corresponding to the collision risk level interval in which the collision risk of the target surrounding vehicles is located may be determined as the control strategy for the target surrounding vehicles of the own vehicle. The greater the collision risk level of the target surrounding vehicles of the own vehicle, the higher the priority of the driving decision for the target surrounding vehicles of the own vehicle.

[0086] As an example, a first collision risk level interval, a second collision risk level interval, and a third collision risk level interval are pre-set. The left endpoint of the first collision risk level interval is 6, and the right endpoint is a value much greater than 6, such as positive infinity. The left endpoint of the second collision risk level interval is 3, and the right endpoint of the second collision risk level interval is 5. The left endpoint of the third collision risk level interval is a value much less than 2, such as negative infinity, and the right endpoint of the third collision risk level interval is 2. If the collision risk level of the target surrounding vehicles is greater than 6, the strategy for the target surrounding vehicles is to slow down the vehicle or evade laterally, thereby reducing or avoiding the collision risk. If the collision risk level of the target surrounding vehicles is less than 2, it can be considered that the collision risk of the vehicle is very small, and the driving decision for the target surrounding vehicles can be that the vehicle temporarily does not take corresponding actions against the target surrounding vehicles. If the collision risk level of the target surrounding vehicles is greater than 3 and less than 5, it can be considered that the collision risk of the target surrounding vehicles is small, and the strategy for the target surrounding vehicles can be to reduce the throttle and slow down the vehicle.

[0087] refer to Figure 2 , which shows a flow chart of another information acquisition method provided by an embodiment of the present invention.

[0088] In step S201, the attention time of the driver of the own vehicle to the target surrounding vehicle of the own vehicle is obtained, and the collision time of the target surrounding vehicle of the own vehicle is determined.

[0089] Step S202 includes: S2021-S2022. Step S202 considers whether the target surrounding vehicle is the target of attention of the driver of the own vehicle, and obtains the collision risk level of the target surrounding vehicle of the own vehicle under the condition that whether the target surrounding vehicle of the own vehicle is the target of attention of the driver of the own vehicle, thereby improving the accuracy of the obtained collision risk level of the target surrounding vehicle of the own vehicle.

[0090] In S2021, based on the comparison result of the driver's attention time on the target surrounding vehicles of the own vehicle and the first attention time threshold, a target attention target judgment result of the target surrounding vehicles is generated, wherein the target attention target judgment result of the target surrounding vehicles indicates whether the target surrounding vehicles of the own vehicle are the attention targets of the driver of the own vehicle.

[0091] As an example, the first attention duration threshold is 0.5 seconds.

[0092] In a possible implementation, in step S2021, based on the comparison result of the driver's attention time to the target surrounding vehicle of the own vehicle and the first attention time threshold, generating the attention target judgment result of the target surrounding vehicle includes: if the driver's attention time to the target surrounding vehicle of the own vehicle is less than the first attention time threshold, then the attention target judgment result indicating that the target surrounding vehicle is not the driver's attention target surrounding vehicle can be generated. If the driver's attention time to the target surrounding vehicle of the own vehicle is not less than the first attention time threshold, then the attention target judgment result indicating that the target surrounding vehicle is the driver's attention target surrounding vehicle can be generated.

[0093] In S2022, the collision risk level of the target surrounding vehicles of the own vehicle is determined according to the collision time of the target surrounding vehicles of the own vehicle and the focus target judgment result of the target surrounding vehicles of the own vehicle.

[0094] In a possible implementation of step S2022, the attention time of the driver of the vehicle to each surrounding vehicle of the vehicle can be normalized to obtain a normalized value of the attention time of the driver of the vehicle to each surrounding vehicle of the vehicle. The collision time of each surrounding vehicle of the vehicle can be normalized to obtain a normalized value of the collision time of each surrounding vehicle of the vehicle. Determine the average value of the attention time of the driver of the vehicle to the target surrounding vehicles of the vehicle and the collision time of the target surrounding vehicles, and use the average value as the basic value for calculating the collision risk level of the target surrounding vehicles of the vehicle. If the target surrounding vehicles of the vehicle are not the attention targets of the driver of the vehicle, the basic value used to calculate the collision risk level of the target surrounding vehicles of the vehicle can be subtracted from the preset reduction value to obtain a difference, and use the difference as the collision risk level of the target surrounding vehicles of the vehicle. If the target surrounding vehicles of the own vehicle are the targets of attention of the driver of the own vehicle, the basic value used to calculate the collision risk level of the target surrounding vehicles of the own vehicle can be added to the preset increased value to obtain the sum of the basic value used to calculate the collision risk level of the target surrounding vehicles of the own vehicle and the preset increased value, and the sum can be used as the collision risk level of the target surrounding vehicles of the own vehicle.

[0095] In another possible implementation of step S3022, when the focus target judgment result of the target surrounding vehicles of the own vehicle indicates that the target surrounding vehicles of the own vehicle are the focus targets of the driver of the own vehicle, the driver correction level corresponding to the target surrounding vehicles of the own vehicle is determined according to the attention duration of the driver of the own vehicle on the target surrounding vehicles of the own vehicle, and the automatic driving system collision risk level corresponding to the target surrounding vehicles of the own vehicle is determined according to the collision time of the target surrounding vehicles of the own vehicle; the collision risk level of the target surrounding vehicles of the own vehicle is determined by the sum of the driver correction level corresponding to the target surrounding vehicles of the own vehicle and the automatic driving system collision risk level corresponding to the target surrounding vehicles of the own vehicle.

[0096] In a possible implementation, when determining the driver correction level corresponding to the target surrounding vehicles of the own vehicle according to the attention time of the driver of the own vehicle to the target surrounding vehicles of the own vehicle, the driver correction level corresponding to the target surrounding vehicles of the own vehicle can be determined according to the attention time of the driver of the own vehicle to the target surrounding vehicles of the own vehicle, the association between the attention time of the driver of the own vehicle to the surrounding vehicles and the driver correction level corresponding to the surrounding vehicles. Among them, the association between the attention time of the driver of the own vehicle to the surrounding vehicles and the driver correction level corresponding to the surrounding vehicles is preset, and the association between the attention time of the driver of the own vehicle to the surrounding vehicles and the driver correction level corresponding to the surrounding vehicles can be represented by a function. The collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle can be determined according to the collision time of the target surrounding vehicles of the own vehicle, the collision time of the surrounding vehicles and the collision risk level of the automatic driving system corresponding to the surrounding vehicles. Among them, the association between the collision time of the surrounding vehicles and the collision risk level of the automatic driving system corresponding to the surrounding vehicles is preset, and the association between the collision time of the surrounding vehicles and the collision risk level of the automatic driving system corresponding to the surrounding vehicles can be represented by a function.

[0097] In the disclosed embodiment, the driver correction level corresponding to the target surrounding vehicles of the self-vehicle and the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the self-vehicle are determined, and the collision risk level of the target surrounding vehicles of the self-vehicle is determined by summing the driver correction level corresponding to the target surrounding vehicles of the self-vehicle and the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the self-vehicle. This is because: if the collision risk level of the target surrounding vehicles of the self-vehicle is obtained by directly calculating the attention time of the driver of the self-vehicle to the target surrounding vehicles of the self-vehicle and the collision time of the target surrounding vehicles of the self-vehicle, the accuracy of the collision risk level of the target surrounding vehicles of the self-vehicle may be reduced in some cases. For example, in some cases, the attention time of the driver of the self-vehicle to the target surrounding vehicles of the self-vehicle is long, the collision time of the target surrounding vehicles of the self-vehicle is long, the attention time of the driver of the self-vehicle to the target surrounding vehicles of the self-vehicle is positively correlated with the collision risk level of the target surrounding vehicles of the self-vehicle, the collision time of the target surrounding vehicles of the self-vehicle is negatively correlated with the collision risk level of the target surrounding vehicles of the self-vehicle, and the actual collision risk level of the target surrounding vehicles of the self-vehicle should be small, but the calculated collision risk level of the target surrounding vehicles of the self-vehicle is large due to the long attention time of the driver of the self-vehicle to the target surrounding vehicles of the self-vehicle. For example, since the target surrounding vehicles of the own vehicle are far away from the own vehicle, the collision time of the target surrounding vehicles of the own vehicle is long. At the same time, the driver of the own vehicle pays attention to the target surrounding vehicles of the own vehicle for a long time. Since the target surrounding vehicles of the own vehicle are far away from the own vehicle, the collision risk level of the target surrounding vehicles of the own vehicle should actually be small. However, the calculated collision risk level of the target surrounding vehicles of the own vehicle is large.

[0098] Therefore, based on the attention time of the driver of the vehicle to the target surrounding vehicles of the vehicle and the collision time of the target surrounding vehicles of the vehicle, the attention time of the driver of the vehicle to the target surrounding vehicles of the vehicle is quantified as the driver correction level corresponding to the target surrounding vehicles of the vehicle, and the collision time of the target surrounding vehicles of the vehicle. Therefore, even if the attention time of the driver of the vehicle to the target surrounding vehicles of the vehicle is large, it will be limited to the highest collision risk level of the automatic driving system set in advance. Therefore, in some cases, the attention time of the driver of the vehicle to the target surrounding vehicles of the vehicle is positively correlated with the collision risk level of the target surrounding vehicles of the vehicle, and the collision time of the target surrounding vehicles of the vehicle is negatively correlated with the collision risk level of the target surrounding vehicles of the vehicle. The actual collision risk level of the target surrounding vehicles of the vehicle should be small, but the calculated collision risk level of the target surrounding vehicles of the vehicle is large due to the long attention time of the driver of the vehicle to the target surrounding vehicles of the vehicle. Improve the accuracy of the collision risk level of the target surrounding vehicles of the vehicle.

[0099] In a possible implementation, when determining the driver correction level corresponding to the target surrounding vehicles of the own vehicle according to the attention time of the driver of the own vehicle to the target surrounding vehicles of the own vehicle, the collision risk level of the automatic driving system of the target surrounding vehicles of the own vehicle is calculated according to the collision time of the target surrounding vehicles of the own vehicle, and the automatic driving system collision risk coefficient of the target surrounding vehicles of the own vehicle is determined according to the inverse proportional function in accordance with the principle that the smaller the collision time of the target surrounding vehicles of the own vehicle, the greater the collision risk level of the automatic driving system of the target surrounding vehicles of the own vehicle. According to the comparison result of the automatic driving system collision risk coefficient and the automatic driving system collision risk coefficient threshold, the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle is determined.

[0100] The collision risk coefficient of the automatic driving system of the target surrounding vehicles determined by the inverse proportional function can be expressed as:

[0101]

[0102] Among them, E S represents the collision risk coefficient of the autonomous driving system of the target surrounding vehicles of the own vehicle, and t represents the collision time of the target surrounding vehicles of the own vehicle.

[0103] In an embodiment of the present invention, if the collision risk coefficient of the autonomous driving system of the target surrounding vehicles of the ego vehicle is greater than the highest collision risk coefficient threshold of the autonomous driving system, the collision risk level of the autonomous driving system corresponding to the target surrounding vehicles of the ego vehicle is the highest collision risk level of the autonomous driving system, such as the collision risk level of the level 8 autonomous driving system. If the collision risk coefficient of the autonomous driving system of the target surrounding vehicles of the ego vehicle is less than the lowest collision risk coefficient threshold of the autonomous driving system, the collision risk level of the autonomous driving system corresponding to the target surrounding vehicles of the ego vehicle is the lowest collision risk level of the autonomous driving system, such as the collision risk level of the level 1 autonomous driving system.

[0104] Table 1 shows the collision risk coefficient E of the autonomous driving system for the target surrounding vehicles of the ego vehicle. S The collision risk level P of the autonomous driving system corresponding to the target surrounding vehicles of the self-driving car S An example of the value relationship of E S The unit is seconds. 0.5, 1, 1.5, 2, 3, 5, and 10 are all collision risk coefficient thresholds of the autonomous driving system.

[0105] Table 1

[0106]

[0107]

[0108] In one possible implementation, determining the driver correction level corresponding to the target surrounding vehicles of the own vehicle based on the length of time the driver of the own vehicle pays attention to the target surrounding vehicles of the own vehicle includes: when the length of time the driver of the own vehicle pays attention to the target surrounding vehicles of the own vehicle is not less than a first attention length threshold and the length of time the driver of the own vehicle pays attention to the target surrounding vehicles of the own vehicle is not greater than a second attention length threshold, determining the first correction level as the driver correction level corresponding to the target surrounding vehicles of the own vehicle, wherein the second attention length threshold is greater than the first attention length threshold; when the driver of the own vehicle pays attention to the target surrounding vehicles of the own vehicle greater than the second attention length threshold, determining the second correction level as the driver correction level corresponding to the target surrounding vehicles of the own vehicle, and the second correction level is higher than the first correction level.

[0109] As an example, the first attention duration threshold is 0.5s, the second attention duration threshold is 1.5s, the first correction level is the Level 1 driver correction level, and the second correction level is the Level 2 driver correction level. If the driver of the own vehicle pays attention to the target surrounding vehicle for a duration between 0.5s and 1.5s, the first correction level is determined as the driver correction level corresponding to the target surrounding vehicle of the own vehicle, that is, P d =1, if the driver of the vehicle pays attention to the target surrounding vehicle of the vehicle for more than 1.5 seconds, the second correction level is determined as the driver correction level corresponding to the target surrounding vehicle of the vehicle, P d =2. It should be noted that if the driver of the vehicle pays attention to the target surrounding vehicle for less than 0.5s, it can be regarded as the driver correction level P corresponding to the target surrounding vehicle of the vehicle. d =0.

[0110] In one possible implementation, determining the collision risk level of the target surrounding vehicles of the own vehicle according to the collision time of the target surrounding vehicles of the own vehicle and the focus target judgment result of the target surrounding vehicles of the own vehicle includes: when the focus target judgment result of the target surrounding vehicles of the own vehicle indicates that the target surrounding vehicles of the own vehicle are not the focus target of the driver of the own vehicle and the target surrounding vehicles of the own vehicle have been the focus target of the driver of the own vehicle within the target previous time period, determining the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle according to the collision time of the target surrounding vehicles of the own vehicle, wherein the target previous time period is a time period having an end time of the current time and a duration of a preset observation duration; determining the collision risk level of the target surrounding vehicles of the own vehicle according to the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle. When determining the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle based on the collision time of the target surrounding vehicles of the own vehicle, the normalized value of the collision time of the target surrounding vehicles of the own vehicle obtained by normalizing the collision time of each surrounding vehicle of the own vehicle can be determined as the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle, or the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle can be determined based on the correlation between the collision time of the target surrounding vehicles of the own vehicle, the collision time of the surrounding vehicles and the collision risk level of the automatic driving system corresponding to the surrounding vehicles. When determining the collision risk level of the target surrounding vehicles of the own vehicle based on the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle, the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle can be determined as the collision risk level of the target surrounding vehicles of the own vehicle.

[0111] As an example, the preset observation time may be 1.5 seconds.

[0112] It should be noted that the preset observation time may be the second attention time threshold mentioned above.

[0113] In the embodiment of the present disclosure, when the target surrounding vehicle of the own vehicle's target attention target judgment result indicates that the target surrounding vehicle of the own vehicle is not the target of attention of the driver of the own vehicle and has been regarded as a target of attention in the previous time period of the target, the collision risk level of the automatic driving system corresponding to the target surrounding vehicle of the own vehicle is determined according to the collision time of the target surrounding vehicle of the own vehicle. This is because: if the target surrounding vehicle of the own vehicle is not the target of attention of the driver at present, and the target surrounding vehicle has been regarded as the target of attention of the driver of the own vehicle in the previous time period of the target, it can be reflected that: the target surrounding vehicle is not the target of attention of the driver of the own vehicle at present, and the target surrounding vehicle has paid attention to the target surrounding vehicle in the previous time period of the target, and the driver of the own vehicle judges that in the short term

[0114] The target surrounding vehicles will not have a collision risk and will move away. Therefore, the driver of the vehicle may not participate in the acquisition of the collision risk level of the vehicle, thereby improving the accuracy of the acquired collision risk level of the target surrounding vehicles of the vehicle.

[0115] In one possible implementation, when the target surrounding vehicles of the own vehicle's target attention target judgment result indicates that the target surrounding vehicles of the own vehicle are not the target of attention of the driver of the own vehicle and the target surrounding vehicles of the own vehicle have been the target of attention of the driver of the own vehicle within the target previous time period, determining the collision risk level of the target surrounding vehicles of the own vehicle according to the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle includes: determining the difference between the collision risk level of the automatic driving system corresponding to the target surrounding vehicles and a preset value as the collision risk level of the target surrounding vehicles.

[0116] The difference between the collision risk level of the automatic driving system corresponding to the target surrounding vehicles and the preset value is: the collision risk level of the automatic driving system corresponding to the target surrounding vehicles minus the preset value.

[0117] Among them, the preset value is a positive number.

[0118] As an example, when the target surrounding vehicle of the own vehicle's attention target judgment result indicates that the target surrounding vehicle of the own vehicle is not the target of attention of the driver of the own vehicle and the target surrounding vehicle of the own vehicle has been the target of attention of the driver of the own vehicle in the target previous time period, the collision risk level of the target surrounding vehicle of the own vehicle can be determined by the following formula:

[0119]

[0120] Wherein, P represents the collision risk level of the target surrounding vehicles of the own vehicle, t represents the collision time of the target surrounding vehicles of the own vehicle, and the preset value is 1.

[0121] The difference between the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the ego vehicle and the preset value is determined as the collision risk level of the target surrounding vehicles. It can be ensured that the collision risk level of the target surrounding vehicles of the ego vehicle obtained is small.

[0122] In one possible implementation, determining the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle based on the collision time of the target surrounding vehicles of the own vehicle includes: determining the type of the target surrounding vehicles of the own vehicle related to the collision risk based on the collision time of the target surrounding vehicles of the own vehicle and the collision time threshold; determining the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle based on the type of the target surrounding vehicles of the own vehicle related to the collision risk.

[0123] As an example, the types related to collision risk are divided into: a type with collision risk, a type with possible collision risk, and a type without collision risk. A plurality of collision risk level intervals may be preset.

[0124] Multiple collision risk level intervals can be pre-set. The left endpoint and the right endpoint of the collision risk level interval are both collision time thresholds. Each collision risk level interval in the multiple collision risk level intervals corresponds to a different type related to collision risk. Each type related to collision risk corresponds to different parameters. The collision risk level interval where the collision risk of the target surrounding vehicles of the vehicle is located can be determined, and the type corresponding to the collision risk level interval where the collision risk of the target surrounding vehicles is located is determined as the type related to the collision risk of the target surrounding vehicles. The parameter corresponding to the type related to the collision risk of the target surrounding vehicles is determined as the collision risk level of the automatic driving system corresponding to the target surrounding vehicles.

[0125] In one possible implementation, the types associated with collision risk are divided into: types with collision risk and types without collision risk. Determining the types associated with collision risk of the target surrounding vehicles of the own vehicle based on the collision time and collision time threshold of the target surrounding vehicles of the own vehicle includes: when the collision time of the target surrounding vehicles of the own vehicle is greater than the target collision time threshold, determining the type with no collision risk as the type associated with collision risk of the target surrounding vehicles; when the collision time of the target surrounding vehicles of the own vehicle is not greater than the target collision time threshold, determining the type with collision risk as the type associated with collision risk of the target surrounding vehicles; and determining the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle based on the types associated with collision risk of the target surrounding vehicles of the own vehicle includes: when the type associated with collision risk of the target surrounding vehicles of the own vehicle is the type without collision risk. , the preset minimum risk level for determining the collision risk level of the automatic driving system is determined as the collision risk level of the automatic driving system corresponding to the target surrounding vehicles; when the type of the target surrounding vehicles of the own vehicle that is associated with the collision risk is a type with collision risk, the collision risk level of the automatic driving system corresponding to the target surrounding vehicles of the own vehicle is determined according to the correlation between the collision time of the target surrounding vehicles of the own vehicle, the collision time of the surrounding vehicles and the collision risk level of the automatic driving system corresponding to the surrounding vehicles, wherein the preset minimum risk level for determining the collision risk level of the automatic driving system is less than the collision risk level of the automatic driving system corresponding to the target surrounding vehicles determined when the type of the target surrounding vehicles that is associated with the collision risk is a type with collision risk.

[0126] It should be noted that the target collision time threshold is a collision time threshold used to determine whether the target surrounding vehicle of the own vehicle is a type related to the collision risk.

[0127] In one possible implementation, the preset minimum risk level for determining the collision risk level of the autonomous driving system is 0.

[0128] refer to Figure 3 , which shows a flowchart of an example of obtaining the collision risk level of the surrounding vehicles of the own vehicle.

[0129] In this example, for the target surrounding vehicles of the own vehicle, the parameter value of the attention time parameter of the target surrounding vehicles can be read, thereby, the attention time of the driver of the own vehicle to the target surrounding vehicles of the own vehicle. In this example, for the target surrounding vehicles of the own vehicle, the collision time of the target surrounding vehicles indicates how long it will take for the target surrounding vehicles of the own vehicle to enter the safety area of ​​the own vehicle from the current moment. It is predicted how long it will take for the target surrounding vehicles to enter the safety area of ​​the own vehicle from the current moment, thereby obtaining the collision time of the target surrounding vehicles. According to the attention time of the driver of the own vehicle to the target surrounding vehicles of the own vehicle and the collision time of the target surrounding vehicles, the collision risk level of the target surrounding vehicles of the own vehicle is determined. According to the collision risk level of the target surrounding vehicles of the own vehicle, the driving decision for the target surrounding vehicles is determined.

[0130] An information acquisition device is also provided in the embodiment of the present invention, and the device is used to implement the above-mentioned method embodiment and preferred implementation mode, which have been described and will not be repeated here. As used below, the term "unit" can implement a combination of software and / or hardware of a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware is also possible and conceived. The device in the embodiment of the present invention is presented in the form of a functional unit, where the functional unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above-mentioned functions.

[0131] The information acquisition device comprises:

[0132] an acquisition unit, used for acquiring a time duration of attention of a driver of the own vehicle to a target surrounding vehicle of the own vehicle, and determining a collision time of the target surrounding vehicle of the own vehicle, wherein the target surrounding vehicle is any surrounding vehicle of the own vehicle, and the time duration of attention of the driver to the target surrounding vehicle of the own vehicle indicates a time duration of attention of the driver to the target surrounding vehicle, and the attention time duration is determined according to a gaze point of the driver;

[0133] The determination unit is used to determine the collision risk level of the target surrounding vehicle according to the driver's attention duration on the target surrounding vehicle and the collision time of the target surrounding vehicle.

[0134] In one possible implementation, the determination unit is also used to generate a focus target judgment result of the target surrounding vehicle based on a comparison result of the driver's attention time for the target surrounding vehicle and an attention time threshold, wherein the focus target judgment result of the target surrounding vehicle indicates whether the target surrounding vehicle is the driver's focus target; and determine the collision risk level of the target surrounding vehicle based on the collision time of the target surrounding vehicle and the focus target judgment result of the target surrounding vehicle.

[0135] In one possible implementation, the determination unit is also used to determine the collision risk level of the automatic driving system corresponding to the target surrounding vehicle according to the collision time of the target surrounding vehicle when the target focus target judgment result of the target surrounding vehicle indicates that the target surrounding vehicle is not the driver's focus target and the target surrounding vehicle has been the driver's focus target within a target previous time period, wherein the target previous time period is a time period having an end time as the current time and a duration as a preset observation time period; determine the collision risk level of the target surrounding vehicle according to the collision risk level of the automatic driving system corresponding to the target surrounding vehicle.

[0136] In one possible implementation, the determination unit is also used to determine the difference between the automatic driving system collision risk level corresponding to the target surrounding vehicle and a preset value as the collision risk level of the target surrounding vehicle when the focus target judgment result of the target surrounding vehicle indicates that the target surrounding vehicle is not the focus target of the driver and the target surrounding vehicle has been the focus target of the driver within a previous target time period.

[0137] In one possible implementation, the determination unit is also used to determine the driver correction level corresponding to the target surrounding vehicle according to the driver's attention duration on the target surrounding vehicle when the focus target judgment result of the target surrounding vehicle indicates that the target surrounding vehicle is the driver's focus target, and determine the automatic driving system collision risk level corresponding to the target surrounding vehicle according to the collision time of the target surrounding vehicle; and determine the sum of the driver correction level corresponding to the target surrounding vehicle and the automatic driving system collision risk level corresponding to the target surrounding vehicle as the collision risk level of the target surrounding vehicle.

[0138] In one possible implementation, the determination unit is also used to determine the first correction level as the driver correction level corresponding to the target surrounding vehicle when the driver's attention time for the target surrounding vehicle is not less than a first attention time threshold and the driver's attention time for the target surrounding vehicle is not greater than a second attention time threshold, wherein the second attention time threshold is greater than the first attention time threshold; when the driver's attention time for the target surrounding vehicle is greater than the second attention time threshold, determine the second correction level as the driver correction level corresponding to the target surrounding vehicle, and the second correction level is higher than the first correction level.

[0139] In one possible implementation, the determination unit is also used to determine the type of the target surrounding vehicle related to the collision risk based on the collision time and collision time threshold of the target surrounding vehicle; and determine the collision risk level of the automatic driving system corresponding to the target surrounding vehicle based on the type of the target surrounding vehicle related to the collision risk.

[0140] In a possible implementation, the determination unit is further configured to, when the collision time of the target surrounding vehicle is greater than a target collision time threshold, determine the no-collision risk type as the type associated with the collision risk of the target surrounding vehicle; when the collision time of the target surrounding vehicle is not greater than the target collision time threshold, determine the collision risk type as the type associated with the collision risk of the target surrounding vehicle; the determination unit is further configured to, when the type associated with the collision risk of the target surrounding vehicle is the no-collision risk type, determine the preset minimum risk level for determining the collision risk level of the automatic driving system as the collision risk level of the automatic driving system corresponding to the target surrounding vehicle; when the type associated with the collision risk of the target surrounding vehicle is the collision risk type, determine the collision risk level of the automatic driving system corresponding to the target surrounding vehicle according to the correlation between the collision time of the target surrounding vehicle, the collision time of the surrounding vehicles and the collision risk level of the automatic driving system corresponding to the surrounding vehicles, wherein the preset minimum risk level for determining the collision risk level of the automatic driving system is less than the collision risk level of the automatic driving system corresponding to the target surrounding vehicle determined when the type associated with the collision risk of the target surrounding vehicle is the collision risk type.

[0141] refer to Figure 4 , Figure 41 is a schematic diagram of the hardware structure of a computer device provided by an embodiment of the present invention. The computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. The various components are connected to each other using different buses for communication, and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used with multiple memories and multiple memories. Similarly, multiple vehicles can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). The processor 10 can be a central processing unit, a network processor, or a combination thereof. Among them, the processor 10 can further include a hardware chip. The above-mentioned hardware chip can be a dedicated integrated circuit, a programmable logic device, or a combination thereof. The above-mentioned programmable logic device can be a complex programmable logic device, a field programmable gate array, a general array logic, or any combination thereof. The memory 20 stores instructions executable by at least one processor 10 so that the at least one processor 10 executes the method shown in the above embodiment. The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required by at least one function; the data storage area may store data created according to the use of the vehicle, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage devices. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof. The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state hard disk; the memory 20 may also include a combination of the above-mentioned types of memory. The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30, and the output device 40 may be connected via a bus or in other ways. The input device 30 can receive input digital or character information, and generate key signal input related to the user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touch pad, an indicator stick, one or more mouse buttons, a trackball, a joystick, etc.The output device 40 may include a display device, an auxiliary lighting device (e.g., LED), a tactile feedback device (e.g., a vibration motor), etc. The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display, and a plasma display. In some optional embodiments, the display device may be a touch screen.

[0142] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0143] A portion of the embodiments of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of computer program instructions in a computer-readable medium includes, but is not limited to, source files, executable files, installation package files, etc., and accordingly, the way in which the computer program instructions are executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0144] The above embodiments are only preferred embodiments for fully illustrating the present invention, and the protection scope of the present invention is not limited thereto. Any equivalent substitution or change made by a person skilled in the art based on the present invention is within the protection scope of the present invention.

Claims

1. A method for obtaining information, characterized in that: The method comprises: Obtaining the attention time of the driver of the own vehicle to the target surrounding vehicle of the own vehicle, and determining the collision time of the target surrounding vehicle of the own vehicle, wherein the target surrounding vehicle is any surrounding vehicle of the own vehicle, and the attention time of the driver to the target surrounding vehicle indicates the time the driver pays attention to the target surrounding vehicle, and the attention time is determined according to the gaze point of the driver; The collision risk level of the target surrounding vehicle is determined according to the driver's attention duration on the target surrounding vehicle and the collision time of the target surrounding vehicle.

2. The method according to claim 1, characterized in that: Determining the collision risk level of the target surrounding vehicle according to the driver's attention duration on the target surrounding vehicle and the collision time of the target surrounding vehicle includes: Generate a target of interest judgment result of the target surrounding vehicle according to a comparison result of the driver's attention duration on the target surrounding vehicle and a first attention duration threshold, wherein the target of interest judgment result of the target surrounding vehicle indicates whether the target surrounding vehicle is a target of interest of the driver; The collision risk level of the target surrounding vehicle is determined according to the collision time of the target surrounding vehicle and the focus target judgment result of the target surrounding vehicle.

3. The method according to claim 2, characterized in that: Determining the collision risk level of the target surrounding vehicle according to the collision time of the target surrounding vehicle and the target of interest judgment result of the target surrounding vehicle includes: When the target surrounding vehicle's attention target judgment result indicates that the target surrounding vehicle is not the driver's attention target and the target surrounding vehicle has been the driver's attention target within a target previous time period, the automatic driving system collision risk level corresponding to the target surrounding vehicle is determined according to the collision time of the target surrounding vehicle, wherein the target previous time period is a time period having an end time of the current time and a duration of a preset observation time period; the collision risk level of the target surrounding vehicle is determined according to the automatic driving system collision risk level corresponding to the target surrounding vehicle.

4. The method according to claim 3, characterized in that: Determining the collision risk level of the target surrounding vehicle according to the collision risk level of the automatic driving system corresponding to the target surrounding vehicle includes: The difference between the automatic driving system collision risk level corresponding to the target surrounding vehicle and a preset value is determined as the collision risk level of the target surrounding vehicle.

5. The method according to claim 2, characterized in that: Determining the collision risk level of the target surrounding vehicle according to the collision time of the target surrounding vehicle and the target of interest judgment result of the target surrounding vehicle includes: When the target surrounding vehicle's attention target judgment result indicates that the target surrounding vehicle is the driver's attention target, determining a driver correction level corresponding to the target surrounding vehicle according to the driver's attention duration on the target surrounding vehicle, and determining an automatic driving system collision risk level corresponding to the target surrounding vehicle according to the collision time of the target surrounding vehicle; The sum of the driver correction level corresponding to the target surrounding vehicle and the automatic driving system collision risk level corresponding to the target surrounding vehicle is determined as the collision risk level of the target surrounding vehicle.

6. The method according to claim 5, characterized in that: Determining the driver correction level corresponding to the target surrounding vehicle according to the driver's attention duration on the target surrounding vehicle includes: When the driver's attention time for the target surrounding vehicle is not less than a first attention time threshold and the driver's attention time for the target surrounding vehicle is not greater than a second attention time threshold, determining a first correction level as the driver's correction level corresponding to the target surrounding vehicle, wherein the second attention time threshold is greater than the first attention time threshold; When the driver's attention time for the target surrounding vehicle is greater than a second attention time threshold, a second correction level is determined as the driver correction level corresponding to the target surrounding vehicle, and the second correction level is higher than the first correction level.

7. The method according to any one of claims 3 to 6, characterized in that: Determining the collision risk level of the automatic driving system corresponding to the target surrounding vehicle according to the collision time of the target surrounding vehicle includes: Determining the type of the target surrounding vehicle related to the collision risk according to the collision time and collision time threshold of the target surrounding vehicle; According to the type of the target surrounding vehicle related to the collision risk, the collision risk level of the automatic driving system corresponding to the target surrounding vehicle is determined.

8. The method according to claim 7, characterized in that: Determining the type of the target surrounding vehicle related to the collision risk according to the collision time and the collision time threshold of the target surrounding vehicle includes: When the collision time of the target surrounding vehicle is greater than a target collision time threshold, determining the no-collision risk type as the type of the target surrounding vehicle associated with the collision risk; When the collision time of the target surrounding vehicle is not greater than the target collision time threshold, determining the collision risk type as the type of the target surrounding vehicle related to the collision risk; And determining the collision risk level of the automatic driving system corresponding to the target surrounding vehicle according to the type of the target surrounding vehicle related to the collision risk includes: When the type of the target surrounding vehicle related to the collision risk is a type without collision risk, determining the preset minimum risk level for determining the collision risk level of the automatic driving system as the collision risk level of the automatic driving system corresponding to the target surrounding vehicle; When the type of the target surrounding vehicle associated with the collision risk is a type with collision risk, the collision risk level of the automatic driving system corresponding to the target surrounding vehicle is determined according to the collision time of the target surrounding vehicle, the collision time of the surrounding vehicles and the collision risk level of the automatic driving system corresponding to the surrounding vehicles, wherein the preset minimum risk level for determining the collision risk level of the automatic driving system is lower than the collision risk level of the automatic driving system corresponding to the target surrounding vehicle determined when the type of the target surrounding vehicle associated with the collision risk is a type with collision risk.

9. An information acquisition device, characterized in that: The device comprises: an acquisition unit, used for acquiring a driver's attention duration of the own vehicle to a target surrounding vehicle of the own vehicle, and determining a collision time of the target surrounding vehicle of the own vehicle, wherein the target surrounding vehicle is any surrounding vehicle of the own vehicle, and the driver's attention duration for the target surrounding vehicle indicates a duration of the driver's attention to the target surrounding vehicle, and the attention duration is determined according to the driver's gaze point; The determination unit is used to determine the collision risk level of the target surrounding vehicle according to the driver's attention duration on the target surrounding vehicle and the collision time of the target surrounding vehicle.

10. A computer device installed in a vehicle, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 8 by executing the computer instructions.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 8.

12. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the method according to any one of claims 1 to 8.

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