CN111731240A - Emergency brake rationality evaluation method, device, equipment and storage medium - Google Patents
Emergency brake rationality evaluation method, device, equipment and storage medium Download PDFInfo
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- B60—VEHICLES IN GENERAL
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Abstract
The application provides a sudden braking rationality assessment method, a device, equipment and a storage medium, relates to the automatic driving technology, and comprises the following steps: acquiring vehicle running data, and acquiring obstacle information and a vehicle state before sudden braking of the vehicle from the vehicle running data according to the moment when the sudden braking of the vehicle occurs; predicting the motion trail of the vehicle according to the vehicle state; and determining whether the emergency brake is reasonable or not according to the obstacle information and the motion trail. In the scheme that this application provided, can be according to the vehicle state prediction before the emergence emergency brake moment, if not take emergency brake measure, the motion trail of vehicle to according to this motion trail of prediction and the actual barrier information around the vehicle, confirm whether emergency brake is reasonable, for example, if do not take emergency brake can collide with the barrier, then can think that emergency brake is reasonable. The necessity of emergency braking can be quickly and accurately evaluated in such a way, and the way is independent of subjective consciousness of people, so that the evaluation result is more accurate.
Description
Technical Field
The application relates to a data processing technology, in particular to a method, a device, equipment and a storage medium for evaluating the rationality of sudden braking related to automatic driving.
Background
At present, many vehicles are provided with a driving assistance function, and automatic control of the vehicle, such as automatic driving, automatic braking, and the like, can be realized based on the driving assistance function.
In the running process of a vehicle, in order to avoid collision of the vehicle, the vehicle is often controlled to be braked suddenly. However, sudden braking may also present some danger to occupants of the vehicle and an uncomfortable ride for occupants of the vehicle.
Therefore, it is necessary to evaluate whether it is reasonable to control the vehicle to perform sudden braking by the driving assistance function, so as to determine whether it is really necessary to perform a sudden braking operation. How to accurately and efficiently determine whether sudden braking is reasonable is a technical problem which needs to be solved urgently by the technical personnel in the field.
Disclosure of Invention
The application provides a sudden braking rationality evaluation method, device, equipment and storage medium to accurately and efficiently determine whether sudden braking is rational.
According to a first aspect, there is provided a sudden braking rationality assessment method comprising:
acquiring vehicle running data, and acquiring obstacle information and a vehicle state before sudden braking of a vehicle from the vehicle running data according to the moment when the sudden braking of the vehicle occurs;
predicting the motion trail of the vehicle according to the vehicle state;
and determining whether the sudden brake is reasonable or not according to the obstacle information and the motion trail.
According to a second aspect, there is provided a sudden-braking rationality evaluation device including:
the acquisition module is used for acquiring vehicle running data and acquiring barrier information and a vehicle state before sudden braking of the vehicle from the vehicle running data according to the moment when the sudden braking of the vehicle occurs;
the track prediction module is used for predicting the motion track of the vehicle according to the vehicle state;
and the reasonability determining module is used for determining whether the emergency brake is reasonable or not according to the obstacle information and the motion trail.
According to a third aspect, there is provided an electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a sudden brake rationality assessment method according to the first aspect.
According to a fourth aspect, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to execute the sudden brake rationality assessment method according to the first aspect.
According to a fifth aspect, there is provided a sudden braking rationality evaluation method, comprising:
collecting a vehicle state before sudden braking of the vehicle and environmental information around the vehicle;
and evaluating whether the emergency brake is reasonable or not according to the vehicle state and the environmental information.
The application provides a sudden braking rationality evaluation method, a device, equipment and a storage medium, which comprise the following steps: acquiring vehicle running data, and acquiring obstacle information and a vehicle state before sudden braking of the vehicle from the vehicle running data according to the moment when the sudden braking of the vehicle occurs; predicting the motion trail of the vehicle according to the vehicle state; and determining whether the emergency brake is reasonable or not according to the obstacle information and the motion trail. According to the method, the device, the equipment and the storage medium, whether emergency braking measures taken by the vehicle are reasonable or not can be evaluated according to the actual running state of the vehicle and the obstacle information in the running process of the vehicle, the necessity of emergency braking can be evaluated quickly and accurately in such a mode, and the mode does not depend on subjective consciousness of people, so that the evaluation result is more accurate.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not intended to limit the present application. Wherein:
FIG. 1 is a diagram illustrating an application scenario in accordance with an exemplary embodiment of the present application;
FIG. 2 is a flow chart illustrating a sudden brake rationality assessment method according to an exemplary embodiment of the present application;
FIG. 3 is a schematic diagram illustrating a motion profile of a vehicle according to an exemplary embodiment of the present application;
FIG. 4 is a flow chart of a sudden brake rationality assessment method according to another exemplary embodiment of the present application;
FIG. 5 is a schematic diagram of a time-displacement grid graph as shown in an exemplary embodiment of the present application;
FIG. 6 is a block diagram of a sudden braking rationality evaluation device according to an exemplary embodiment of the present application;
FIG. 7 is a block diagram of a sudden braking rationality evaluation device according to another exemplary embodiment of the present application;
FIG. 8 is a flowchart illustrating a sudden brake rationality assessment method according to yet another exemplary embodiment of the present application;
fig. 9 is a block diagram of an electronic device according to an exemplary embodiment of the present application.
Detailed Description
The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application for the understanding of the same, which are to be considered exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In the field of driving assistance, there are cases where sudden braking of a vehicle is controlled in order to avoid a collision of the vehicle. However, sudden braking may bring a bad experience to the user, and in some scenarios, there may be a danger of sudden braking. Therefore, there is a need to assess the rationality of hard braking in order to determine whether a hard braking maneuver is actually necessary.
At present, whether the vehicle has unreasonable sudden braking or not is detected, and at present, a conclusion is given mainly by combining vehicle data and subjective judgment of people. The method mainly comprises the following two steps:
(1) the vehicle data is analyzed. Longitudinal acceleration data of each time point of the vehicle are collected, and if the longitudinal acceleration of a certain time point exceeds a certain threshold value, the vehicle at the time point can be considered to be suddenly braked.
(2) Subjective judgment of a person. And (3) observing the traffic environment where the vehicle is located at the emergency braking time point recorded in the step (1) by human eyes, and judging whether it is reasonable to adopt emergency braking according to the specific traffic environment. For example, the pedestrian passes by in front of the vehicle, and in order to avoid colliding with the pedestrian, the sudden braking of the vehicle is reasonable.
In the above evaluation scheme, subjective judgment of a person needs to be introduced, and the judgment result is inaccurate due to the fact that the judgment mode has high dependence on subjective consciousness of the person.
The application provides an emergency brake rationality evaluation scheme, can go according to the vehicle data automatic determination emergency brake whether reasonable, do not rely on people's subjective judgement to improve the accuracy of assessment result, can also improve aassessment efficiency.
If the emergency brake is not reasonable to evaluate, relevant data can be derived and provided for developers, and the developers optimize the auxiliary driving technology according to the data, so that the provided emergency brake strategy is more reasonable.
Fig. 1 is a diagram illustrating an application scenario according to an exemplary embodiment of the present application.
As shown in fig. 1, the solution provided by the present application can be applied in the application scenario as shown in fig. 1.
Such as the vehicle 11, is traveling on a road based on a driver-assist technique that may provide control strategies for the vehicle, such as lane-changing, braking, etc. The vehicle 11 may be provided with an electronic device 12, and the electronic device 12 may record vehicle driving data generated during the driving of the vehicle, such as vehicle speed, surrounding environment sensed by a sensor, and the like.
In the scheme that this application provided, can estimate the rationality of vehicle emergency brake according to vehicle data of traveling. Specifically, the present invention may be executed by the electronic device 12 provided in the vehicle, or may be executed by another electronic device 13 connected to the electronic device 12. The electronic device 12 and the electronic device 13 may be connected via a network.
FIG. 2 is a flowchart illustrating a sudden braking rationality assessment method according to an exemplary embodiment of the present application.
As shown in fig. 2, the evaluation method for rationality of sudden braking provided by the present application includes:
step 201, obtaining vehicle running data, and obtaining obstacle information and a vehicle state before vehicle sudden braking from the vehicle running data according to the time when the vehicle sudden braking occurs.
The method provided by the present application may be performed by an electronic device with computing capabilities, such as the electronic device 12 or the electronic device 13 shown in fig. 1.
For example, the electronic device 12 may determine that sudden braking of the vehicle occurs according to the vehicle driving data, for example, may determine that sudden braking occurs according to the vehicle speed information. And the rationality of the emergency brake can be evaluated according to the driving data during the emergency brake.
For another example, the electronic device 12 may send the recorded vehicle driving data to the electronic device 13 in real time or at regular time, and the electronic device 13 determines that the vehicle has sudden braking, and evaluates the rationality of the sudden braking.
The electronic device may determine whether sudden braking occurs according to the driving data of the vehicle, for example, if the vehicle speed reduction trend meets the trend of sudden braking, the sudden braking may be considered to occur. For another example, the acceleration of the vehicle may be calculated from the vehicle speed, and if the acceleration satisfies the acceleration at the time of sudden braking, it may be considered that sudden braking has occurred.
Specifically, if it is determined that the vehicle has an abrupt braking condition, the method provided in this embodiment may be executed to evaluate the rationality of the abrupt braking.
Further, the electronic device may obtain vehicle driving data and determine whether an emergency brake condition has occurred based on the data, and if so, the electronic device may obtain data related to the emergency brake condition from the vehicle driving data and perform a rationality evaluation.
In actual application, the moment when the sudden brake occurs can be determined. For example, the time when the vehicle suddenly brakes may be determined based on data such as vehicle speed, vehicle control information, etc. And then acquiring the vehicle state before the emergency brake moment, and the obstacle information before the emergency brake moment or the obstacle information after the emergency brake moment.
In general, the vehicle takes emergency braking measures to avoid an obstacle, for example, if the vehicle runs at the current speed and collides with a pedestrian ahead, the vehicle takes emergency braking measures. Therefore, it is possible to evaluate whether sudden braking is necessary or not this time, based on the state of the vehicle before sudden braking, and the obstacle information in the road at the time of sudden braking.
And step 202, predicting the motion trail of the vehicle according to the vehicle state.
Specifically, in the method provided in this embodiment, the motion trajectory of the vehicle may be predicted according to the vehicle state of the vehicle before sudden braking, that is, the motion trajectory of the vehicle may be predicted if the vehicle does not adopt a sudden braking mode.
Further, it may be determined that the vehicle travels at the current speed without changing the vehicle speed, and the movement locus of the vehicle. The motion trail may include the corresponding positions of the vehicle at various times. For example, when the sudden braking time is t0, it can be predicted that the vehicle will travel in the vehicle state before the sudden braking time, at the position p1 corresponding to the time t1 and at the position p2 corresponding to the time t 2.
Further, the vehicle state may include the speed of the vehicle, the lane in which it is located, and the like. The lane where the vehicle is located can be determined by combining the positioning information of the vehicle, the used high-precision map and other data. It is also possible to assume that the vehicle does not change lane, does not change speed, and thus on the basis thereof, the movement locus of the vehicle in a future period of time is predicted.
In practical application, the specific predicted time period can be set according to requirements, such as the motion track of the vehicle in the future 20 seconds.
Fig. 3 is a schematic diagram illustrating a motion trajectory of a vehicle according to an exemplary embodiment of the present application.
As shown in fig. 3, the motion trajectory of the vehicle during the period t0-tn can be predicted based on the motion state of the vehicle. Within the trajectory, vehicle positions corresponding to respective time points are included, e.g., at time ti, the corresponding vehicle position is pi.
And step 203, determining whether the sudden braking is reasonable or not according to the obstacle information and the motion trail.
In the method provided by this embodiment, it may be determined whether the vehicle may collide with an obstacle in the road or whether the vehicle may be too close to the obstacle in the road according to the predicted movement trajectory, so as to evaluate the rationality of the hard brake.
Specifically, the obstacle information may be acquired by vehicle travel data, which is information of an obstacle actually present. For example, the obstacle information may be collected by a camera of the vehicle, and the obstacle information may also be collected by a radar of the vehicle, without limiting the specific collection method.
Further, the obstacle information after the emergency brake time may be acquired from the vehicle travel data. Since the predicted movement locus is after the sudden braking time, the obstacle information after the sudden braking time can be acquired and the rationality of the sudden braking can be evaluated by using the information.
In practical application, the position of the obstacle in a future period of time can be determined according to the obstacle information. For example, if the obstacle is a stationary obstacle, the position of the obstacle will not change for a period of time in the future, and if the obstacle is a moving obstacle, the position of the obstacle will change for a period of time in the future, and the actual position of the obstacle at each time in the period of time in the future can be determined based on actual vehicle travel data.
Wherein, can be according to the movement track of vehicle, the actual position of barrier, whether the aassessment hard braking is reasonable. For example, if the vehicle position overlaps the obstacle position at the same time, it can be determined that sudden braking is reasonable, and if no sudden braking measure is taken, the vehicle may collide with the obstacle. For another example, if the distance between the vehicle position and the obstacle position is smaller than the safety distance at the same time, the sudden braking may be considered reasonable, and if no sudden braking measure is taken, the distance between the vehicle and the obstacle is too small, which may easily cause an unexpected dangerous situation.
Specifically, whether sudden braking of the vehicle is reasonable or not can be determined according to vehicle running data through the quantification mode, so that the subjective judgment of people is not relied on, and the evaluation result of the rationality of the sudden braking is more accurate.
Further, if the evaluation result is that the sudden braking is not reasonable, data related to the sudden braking at this time, such as logic for formulating a sudden braking strategy, a motion state of the vehicle before the sudden braking, obstacle information around the vehicle during the sudden braking, and the like, can be derived. The auxiliary driving technology can be optimized by utilizing the data, so that the emergency braking strategy is more and more reasonable, and the frequency of unreasonable emergency braking conditions is less and less.
The method provided by the embodiment is used for evaluating the rationality of sudden braking, and is executed by a device provided with the method provided by the embodiment, and the device is generally implemented in a hardware and/or software mode.
The application provides an emergency brake rationality evaluation method, including: acquiring vehicle running data, and acquiring obstacle information and a vehicle state before sudden braking of the vehicle from the vehicle running data according to the moment when the sudden braking of the vehicle occurs; predicting the motion trail of the vehicle according to the vehicle state; and determining whether the emergency brake is reasonable or not according to the obstacle information and the motion trail. In the method provided by the application, if emergency braking measures are not taken according to the vehicle state of the vehicle before the emergency braking moment, the motion track of the vehicle can be predicted, and whether emergency braking is reasonable or not can be determined according to the predicted motion track and the actual obstacle information around the vehicle, for example, if the vehicle and the obstacle collide without emergency braking, the emergency braking can be considered to be reasonable. The necessity of emergency braking can be quickly and accurately evaluated in such a way, and the way is independent of subjective consciousness of people, so that the evaluation result is more accurate.
FIG. 4 is a flowchart illustrating a sudden brake rationality assessment method according to another exemplary embodiment of the present application.
As shown in fig. 4, the evaluation method for rationality of sudden braking provided by the present application includes:
The method provided by the present application may be performed by an electronic device with computing capabilities, such as the electronic device 12 or the electronic device 13 shown in fig. 1.
For example, the electronic device 12 may determine that sudden braking of the vehicle occurs according to the vehicle driving data, for example, may determine that sudden braking occurs according to the vehicle speed information. And the rationality of the emergency brake can be evaluated according to the driving data during the emergency brake.
For another example, the electronic device 12 may send the recorded vehicle driving data to the electronic device 13 in real time or at regular time, and the electronic device 13 determines that the vehicle has sudden braking, and evaluates the rationality of the sudden braking.
The electronic equipment can acquire vehicle running data and determine the emergency brake moment according to the vehicle running data. For example, the vehicle driving data includes collected longitudinal acceleration data of the vehicle at each time point, and if the longitudinal acceleration at a certain time point exceeds a certain threshold, it can be determined that the vehicle has sudden braking at the time point.
In one embodiment, if an emergency brake occurs, the electronic device may acquire a vehicle driving state before the instant of the emergency brake. For example, the vehicle state is collected every Δ t, and if the vehicle takes a sudden braking measure at time t, the vehicle state at (t- Δ t) may be used as the vehicle state before sudden braking.
A vehicle state comprising any one of:
vehicle speed, vehicle acceleration, and vehicle direction of travel.
Further, the vehicle state may be read by the electronic device from a sensor provided in the vehicle, or may be calculated based on the read data. The motion trail of the vehicle can be predicted by the data if the vehicle does not take the sudden braking, so that whether a sudden braking measure is necessary or not is evaluated based on the motion trail.
In practical application, the obstacle information in the vehicle driving data within a period of time after the moment of emergency braking can be acquired. For example, when the sudden braking time is T, the obstacle information can be acquired from the vehicle travel data during the period from T to (T + T).
Wherein, the value of T can be set according to requirements.
The specific obstacle information may include, for example, a movement state, a position, and the like of the obstacle.
Further, the obstacle information acquired at this time may be actual obstacle information, that is, information of each obstacle after occurrence of sudden braking. For example, the position of the obstacle a at each time in the period of T to (T + T), and the position of the obstacle B at each time in the period of T to (T + T).
In actual application, the position of the vehicle at each moment can be predicted to be still kept in the current vehicle state running in the future preset time period if the vehicle does not take emergency braking measures.
The positions of a plurality of vehicles are connected, and a predicted vehicle motion track can be obtained.
In one embodiment, the positions of the vehicles at different times can be determined, i.e. predicted, based on the current driving speed and acceleration, assuming that the vehicle keeps the current driving direction unchanged.
Further, the position of the vehicle at each moment determined in the step is the motion track of the predicted vehicle under the condition that the vehicle does not take emergency braking measures. In actual conditions, the vehicle takes emergency braking measures, and the motion track after the emergency braking measures are taken is different from the currently predicted motion track.
During actual application, the quantitative prediction of the vehicle motion track is more accurate than the manual observation of whether traffic accidents occur or not if the vehicle does not adopt emergency braking.
And step 403, determining whether the vehicle collides with the obstacle or not according to the obstacle information and the motion trail.
In practical application, whether the vehicle runs along the determined motion track and collides with the obstacle or not can be judged according to the obstacle information if the vehicle does not take emergency braking measures.
The obstacles may include stationary obstacles as well as moving obstacles. If the vehicle is a static obstacle, whether the motion track passes through the position of the static obstacle or not can be judged, and if the vehicle is not braked suddenly, the vehicle can collide with the static obstacle in a future preset time period. If the vehicle is moving obstacle, whether the position of the vehicle and the position of the obstacle overlap at the same moment can be judged, if so, the vehicle does not brake suddenly, and the vehicle can collide with the static obstacle in a future preset time period.
Specifically, the obstacle moving trajectory may be determined based on the obstacle information. An obstacle recognition algorithm may be provided in the electronic device, for example, an image captured by a camera of the vehicle may be input into a neural network, and the position, the category, and the like of an obstacle in the image may be output through the neural network, where the category is, for example, a stationary obstacle or a moving obstacle.
Further, if the vehicle is a moving obstacle, the position of the moving obstacle at each moment in a future period of time can be obtained according to the vehicle driving data. If the obstacle is a static obstacle, the current position of the obstacle can be determined as the position of the obstacle at each moment in a future period of time. In this way, the moving track of the obstacle can be determined.
In practical applications, the moving obstacle refers to an obstacle that can move, such as a pedestrian, a vehicle, and the like. A stationary obstacle is an obstacle that generally does not move, such as a barricade, a mound of earth, etc.
The moving track of the static barrier in a future period can be rapidly determined by distinguishing the type of the barrier and then determining the track of the barrier, so that the evaluation speed is increased.
Specifically, in an alternative embodiment, the determined obstacle movement trajectory and the determined movement trajectory may be plotted in a preset time-displacement grid diagram. And if the moving track of the obstacle and the moving track of the obstacle have the overlapped part at the same moment, determining that the vehicle collides with the obstacle.
Further, if the movement locus of the obstacle and the movement locus of the vehicle coincide with each other at the same time, it means that the obstacle and the vehicle are in the same position at the time, that is, the obstacle and the vehicle collide with each other. By the method, whether the vehicle collides with the obstacle or not can be accurately predicted if the vehicle does not take emergency braking measures.
The preset time-displacement grid map may include a horizontal axis and a vertical axis, where the horizontal axis is time information and the vertical axis is displacement information. Further, the origin in the grid map may represent the location of the vehicle at the instant of emergency brake.
The determined obstacle movement trajectory, the movement trajectory of the vehicle, may be marked in the grid. In this way, the positions of the vehicle and the obstacle at various moments in time can be directly reflected in the future period of time.
If the grids occupied by the obstacles and the grids occupied by the vehicles have the overlapped parts, the overlapped parts of the movement tracks and the movement tracks of the obstacles are determined to exist at the same moment, and then the vehicles can collide with the obstacles if the vehicles do not take emergency braking measures. Through the mode, the position relation between the vehicle and the obstacle can be more intuitively embodied, and the electronic equipment can conveniently and rapidly determine whether the vehicle and the obstacle collide or not.
FIG. 5 is a schematic diagram of a time-displacement grid diagram shown in an exemplary embodiment of the present application.
As shown in fig. 5, in the time-displacement grid diagram, a movement locus 51 of the vehicle, and a movement locus 52 of the obstacle may be plotted. As shown, the obstacle is a stationary obstacle and thus changes its position with time.
Here, t0 is a portion where the motion trajectory 51 and the movement trajectory 52 overlap during a time period t1-t2 when the vehicle takes the sudden braking, and it can be considered that the vehicle still travels in a state at time t0 when the vehicle does not take the sudden braking measure, and the vehicle collides with an obstacle during a time period t1-t 2.
Specifically, in the preset time-displacement grid diagram, each cell may be set as a grid representing a unit time length and a unit displacement, for example, each grid spans time as a unit time, and spans distance as a unit distance.
And step 404A, if the vehicle is determined to collide with the obstacle, determining that sudden braking is reasonable.
In one embodiment, if it is determined that the vehicle will collide with an obstacle, i.e., the vehicle will collide with an obstacle without taking emergency braking action, then it may be determined that emergency braking is necessary and reasonable.
In step 404B, if it is determined that the vehicle does not collide with the obstacle, it is determined that sudden braking is not reasonable.
Further, if it is determined that the vehicle does not collide with the obstacle, that is, the vehicle does not collide with the obstacle without taking the emergency braking measure, it is determined that the emergency braking is not necessary, and the vehicle is an unreasonable killing measure.
In practical application, under the condition, the data related to the emergency brake can be exported and provided for developers, so that the developers can optimize the driving assistance function.
In the method provided by the embodiment, the situation that the vehicle can occur if emergency braking measures are not taken can be predicted according to the predicted vehicle motion track and the actual obstacle information, so that whether killing measures are necessary or not can be accurately determined, artificial participation is not needed, and the accuracy and the efficiency of the determination result can be improved.
Fig. 6 is a block diagram of a sudden braking rationality evaluation device according to an exemplary embodiment of the present application.
As shown in fig. 6, the present application provides a sudden braking rationality evaluation device, including:
the acquisition module 61 is used for acquiring vehicle running data and acquiring obstacle information and a vehicle state before sudden braking of the vehicle from the vehicle running data according to the time when the sudden braking of the vehicle occurs;
a trajectory prediction module 62 for predicting a motion trajectory of the vehicle according to the vehicle state;
and the reasonability determining module 63 is used for determining whether the emergency brake is reasonable according to the obstacle information and the motion trail.
The sudden braking rationality evaluation device that this embodiment provided includes: the acquisition module is used for acquiring vehicle running data and acquiring barrier information and a vehicle state before sudden braking of the vehicle from the vehicle running data according to the moment when the sudden braking of the vehicle occurs; the track prediction module is used for predicting the motion track of the vehicle according to the vehicle state; and the reasonability determining module is used for determining whether the emergency brake is reasonable or not according to the obstacle information and the motion trail. In the apparatus provided in this embodiment, the movement trajectory of the vehicle can be predicted from the vehicle state before the instant when the sudden braking occurs, and whether the sudden braking is reasonable or not can be determined from the predicted movement trajectory and the actual obstacle information around the vehicle. The necessity of emergency braking can be quickly and accurately evaluated in such a way, and the way is independent of subjective consciousness of people, so that the evaluation result is more accurate.
The specific principle and implementation of the sudden braking rationality evaluation device provided by this embodiment are similar to those of the embodiment shown in fig. 2, and are not described herein again.
Fig. 7 is a block diagram of a sudden braking rationality evaluation device according to another exemplary embodiment of the present application.
As shown in fig. 7, on the basis of the foregoing embodiment, in the sudden braking rationality evaluation apparatus provided in this embodiment, optionally, the trajectory prediction module 62 is specifically configured to:
predicting the position of the vehicle at each moment when the vehicle keeps the vehicle state in a future preset time period.
Optionally, the rationality determining module 63 includes:
a collision determination unit 631 for determining whether the vehicle will collide with an obstacle based on the obstacle information and the motion trajectory;
a rationality determining unit 632 for:
if the vehicle is determined to collide with the obstacle, determining that the emergency brake is reasonable;
and if the vehicle is determined not to collide with the obstacle, determining that the hard brake is unreasonable.
Optionally, the collision determination unit 631 is specifically configured to:
determining the movement track of the obstacle according to the obstacle information;
and if the moving track of the obstacle and the moving track have the overlapped part at the same moment, determining that the vehicle collides with the obstacle.
Optionally, the rationality determining module 63 further comprises a drawing unit 633 for:
drawing the movement track and the motion track of the obstacle in a preset time-displacement grid diagram;
and if the grids occupied by the obstacles and the grids occupied by the vehicles have overlapped parts, determining that the moving track of the obstacles and the moving track have overlapped parts at the same moment.
Optionally, the collision determination unit 631 is specifically configured to:
identifying whether the obstacle is a static obstacle or a moving obstacle to obtain an identification result;
and determining the movement track of the obstacle according to the recognition result.
Optionally, the vehicle state includes any one of:
vehicle speed, vehicle acceleration, and vehicle direction of travel.
Optionally, in the preset time-displacement grid map, a horizontal axis direction is time information, and a vertical axis direction is displacement information.
The specific principle and implementation of the sudden braking rationality evaluation device provided by this embodiment are similar to those of the embodiment shown in fig. 4, and are not described herein again.
FIG. 8 is a flowchart illustrating a sudden brake rationality assessment method according to yet another exemplary embodiment of the present application.
As shown in fig. 8, the evaluation method for rationality of sudden braking provided by the present application includes:
The method provided by the present application may be performed by an electronic device with computing capabilities, such as the electronic device 12 or the electronic device 13 shown in fig. 1.
For example, the electronic device 12 may determine that sudden braking of the vehicle occurs according to the vehicle driving data, for example, may determine that sudden braking occurs according to the vehicle speed information. And the rationality of the emergency brake can be evaluated according to the driving data during the emergency brake.
For another example, the electronic device 12 may send the recorded vehicle driving data to the electronic device 13 in real time or at regular time, and the electronic device 13 determines that the vehicle has sudden braking, and evaluates the rationality of the sudden braking.
The electronic device may determine whether sudden braking occurs according to the driving data of the vehicle, for example, if the vehicle speed reduction trend meets the trend of sudden braking, the sudden braking may be considered to occur. For another example, the acceleration of the vehicle may be calculated from the vehicle speed, and if the acceleration satisfies the acceleration at the time of sudden braking, it may be considered that sudden braking has occurred.
Specifically, if it is determined that the vehicle has an abrupt braking condition, the method provided in this embodiment may be executed to evaluate the rationality of the abrupt braking.
Further, the electronic device can acquire the vehicle state before the vehicle is suddenly braked and the environmental information around the vehicle.
In actual application, the moment when the sudden brake occurs can be determined. For example, the time when the vehicle suddenly brakes may be determined based on data such as vehicle speed, vehicle control information, etc. And then the vehicle state before the instant brake is acquired.
The electronic device can also acquire environmental information around the vehicle, and specifically can acquire the environmental information before the emergency brake moment of the vehicle, or after the emergency brake moment, or before and after the emergency brake moment.
In particular, the environmental information is environmental data collected by sensors on the vehicle, such as data collected by sensors such as radar, cameras, etc., which may be stored in the electronic device.
In general, the vehicle takes emergency braking measures only in response to the current surrounding environment of the vehicle, for example, the vehicle takes emergency braking measures in order to avoid pedestrians in front. Therefore, it is possible to evaluate whether sudden braking is necessary or not this time, based on the state of the vehicle before sudden braking, and the environmental information around the vehicle.
And step 802, evaluating whether sudden braking is reasonable or not according to the vehicle state and the environmental information.
Specifically, it is possible to determine whether this braking measure is necessary or not, based on the environmental information around the vehicle. For example, it is possible to predict whether the vehicle will collide with other objects without taking braking measures.
In one embodiment, the position of the obstacle at each time may be determined based on the environmental information. For example, at time t1, the obstacle is at position p 1. The time t2 when the vehicle is at p1 can be determined from the vehicle state, and if t1 and t2 coincide, it can be considered that the vehicle will collide with the obstacle.
In another embodiment, the movement track of the vehicle can be predicted according to the vehicle state if the vehicle does not take braking measures, and the movement track of each obstacle can be determined according to the surrounding environment information. If the movement locus of the vehicle and the movement locus of the obstacle coincide with each other at the same time, it is said that the vehicle and the obstacle collide with each other.
Further, if the vehicle does not take a sudden braking measure and collides with an obstacle, the sudden braking is considered to be reasonable and necessary. Otherwise, an unreasonable hard braking measure can be considered.
According to an embodiment of the present application, an electronic device and a readable storage medium are also provided.
As shown in fig. 9, is a block diagram of an electronic device according to an embodiment of the application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.
As shown in fig. 9, the electronic apparatus includes: one or more processors 901, memory 902, and interfaces for connecting the various components, including a high-speed interface and a low-speed interface. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device, including instructions stored in or on the memory to display graphical information of a GUI on an external input/output apparatus (such as a display device coupled to the interface). In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple electronic devices may be connected, with each device providing portions of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). Fig. 9 illustrates an example of a processor 901.
The memory 902, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules (e.g., the obtaining module 61, the trajectory prediction module 62, and the rationality determination module 63 shown in fig. 6) corresponding to the sudden-braking rationality assessment method in the embodiment of the present application. The processor 901 executes various functional applications and data processing of the server by running non-transitory software programs, instructions and modules stored in the memory 902, so as to implement the sudden braking rationality assessment method in the above method embodiment.
The memory 902 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the electronic device, and the like. Further, the memory 902 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 902 may optionally include memory located remotely from the processor 901, which may be connected to the electronic device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device may further include: an input device 903 and an output device 904. The processor 901, the memory 902, the input device 903 and the output device 904 may be connected by a bus or other means, and fig. 9 illustrates the connection by a bus as an example.
The input device 903 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device, such as an input device like a touch screen, a keypad, a mouse, a track pad, a touch pad, a pointing stick, one or more mouse buttons, a track ball, a joystick, etc. The output devices 904 may include a display device, auxiliary lighting devices (e.g., LEDs), tactile feedback devices (e.g., vibrating motors), and the like. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device can be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, and the present invention is not limited thereto as long as the desired results of the technical solutions disclosed in the present application can be achieved.
The above-described embodiments should not be construed as limiting the scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (19)
1. A sudden braking rationality assessment method is characterized by comprising the following steps:
acquiring vehicle running data, and acquiring obstacle information and a vehicle state before sudden braking of a vehicle from the vehicle running data according to the moment when the sudden braking of the vehicle occurs;
predicting the motion trail of the vehicle according to the vehicle state;
and determining whether the sudden brake is reasonable or not according to the obstacle information and the motion trail.
2. The method of claim 1, wherein predicting the motion profile of the vehicle based on the vehicle state comprises:
predicting the position of the vehicle at each moment when the vehicle keeps the vehicle state in a future preset time period.
3. The method of claim 1, wherein determining whether the hard brake is rational based on the obstacle information and the motion trajectory comprises:
determining whether the vehicle collides with an obstacle or not according to the obstacle information and the motion trail;
if the vehicle is determined to collide with the obstacle, determining that the emergency brake is reasonable;
and if the vehicle is determined not to collide with the obstacle, determining that the hard brake is unreasonable.
4. The method of claim 3, wherein the determining whether the vehicle will collide with an obstacle comprises:
determining the movement track of the obstacle according to the obstacle information;
and if the moving track of the obstacle and the moving track have the overlapped part at the same moment, determining that the vehicle collides with the obstacle.
5. The method of claim 4, further comprising:
drawing the movement track and the motion track of the obstacle in a preset time-displacement grid diagram;
and if the grids occupied by the obstacles and the grids occupied by the vehicles have overlapped parts, determining that the moving track of the obstacles and the moving track have overlapped parts at the same moment.
6. The method of claim 4, wherein determining an obstacle movement trajectory from the obstacle information comprises:
identifying whether the obstacle is a static obstacle or a moving obstacle to obtain an identification result;
and determining the movement track of the obstacle according to the recognition result.
7. The method according to any one of claims 1-6, wherein the vehicle state comprises any one of:
vehicle speed, vehicle acceleration, and vehicle direction of travel.
8. The method according to claim 5, wherein the predetermined time-displacement grid map has time information in a horizontal axis direction and displacement information in a vertical axis direction.
9. An emergency brake rationality evaluation device, comprising:
the acquisition module is used for acquiring vehicle running data and acquiring barrier information and a vehicle state before sudden braking of the vehicle from the vehicle running data according to the moment when the sudden braking of the vehicle occurs;
the track prediction module is used for predicting the motion track of the vehicle according to the vehicle state;
and the reasonability determining module is used for determining whether the emergency brake is reasonable or not according to the obstacle information and the motion trail.
10. The apparatus of claim 9, wherein the trajectory prediction module is specifically configured to:
predicting the position of the vehicle at each moment when the vehicle keeps the vehicle state in a future preset time period.
11. The apparatus of claim 9, wherein the rationality determining module comprises:
the collision determining unit is used for determining whether the vehicle collides with an obstacle according to the obstacle information and the motion trail;
a rationality determining unit for:
if the vehicle is determined to collide with the obstacle, determining that the emergency brake is reasonable;
and if the vehicle is determined not to collide with the obstacle, determining that the hard brake is unreasonable.
12. The apparatus according to claim 11, wherein the collision determination unit is specifically configured to:
determining the movement track of the obstacle according to the obstacle information;
and if the moving track of the obstacle and the moving track have the overlapped part at the same moment, determining that the vehicle collides with the obstacle.
13. The apparatus according to claim 12, characterized in that the rationality determining module further comprises a rendering unit for:
drawing the movement track and the motion track of the obstacle in a preset time-displacement grid diagram;
and if the grids occupied by the obstacles and the grids occupied by the vehicles have overlapped parts, determining that the moving track of the obstacles and the moving track have overlapped parts at the same moment.
14. The apparatus according to claim 12, wherein the collision determination unit is specifically configured to:
identifying whether the obstacle is a static obstacle or a moving obstacle to obtain an identification result;
and determining the movement track of the obstacle according to the recognition result.
15. The apparatus according to any one of claims 9-14, wherein the vehicle state comprises any one of:
vehicle speed, vehicle acceleration, vehicle direction of travel.
16. The apparatus of claim 13, wherein the predetermined time-displacement grid map has time information in a horizontal axis direction and displacement information in a vertical axis direction.
17. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.
18. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-8.
19. A sudden braking rationality assessment method is characterized by comprising the following steps:
collecting a vehicle state before sudden braking of the vehicle and environmental information around the vehicle;
and evaluating whether the sudden brake is reasonable or not according to the vehicle state and the environmental information.
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