CN114495543B - Method and device for identifying unreasonable lane changing behavior of vehicle and related equipment - Google Patents
Method and device for identifying unreasonable lane changing behavior of vehicle and related equipment Download PDFInfo
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- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
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- G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
- G08G1/096725—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control where the received information generates an automatic action on the vehicle control
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- G—PHYSICS
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
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Abstract
The method comprises the steps of obtaining lane change data, wherein the lane change data comprise data frames when a main vehicle runs from an initial lane change position to a final lane change position, calculating lane change transverse moving completion degree by using lane width in each data frame and position information and state information of the main vehicle, determining lane change comfort degree by using state information of the main vehicle in each data frame, calculating lane change safety degree by using the position information and the state information of the main vehicle in each data frame and the position information and the state information of other vehicles, and identifying unreasonable lane change behaviors of the main vehicle in the lane change data based on the lane change transverse moving completion degree, the lane change comfort degree and the lane change safety degree. According to the lane-changing traversing method and the lane-changing comfort level and the lane-changing safety level of the main car, unreasonable lane-changing behaviors of the main car are identified from three different directions, so that a corresponding lane-changing algorithm is improved.
Description
Technical Field
The application relates to the technical field of automatic driving, in particular to a method and a device for identifying unreasonable lane changing behaviors of a vehicle and related equipment.
Background
With the continuous development of science and technology, the automatic driving technology becomes the key research direction of the automobile industry. The lane change belongs to very important behaviors in the driving process of the automatic driving vehicle, and the automatic driving vehicle can realize the lane change by utilizing a corresponding algorithm in combination with an actual scene in the driving process. At present, in the lane changing process, people are used to simply divide the lane changing result into two situations of lane changing success and lane changing failure. However, even if lane changing succeeds, dangerous behaviors such as emergency lane changing, too close distance to an obstacle during lane changing, or driving of a vehicle close to a sideline after lane changing may exist, and such unreasonable lane changing behaviors may cause safety problems.
Disclosure of Invention
In view of the above, the present application provides a method, an apparatus, a device and a readable storage medium for identifying an unreasonable lane change behavior of a vehicle, so as to identify the unreasonable lane change behavior of the vehicle, thereby improving a corresponding lane change algorithm.
In order to achieve the above object, the following solutions are proposed:
a method for identifying unreasonable lane changing behaviors of a vehicle comprises the following steps:
acquiring lane change data, wherein the lane change data comprises data frames when a main vehicle runs from a lane change initial position to a lane change ending position, and each data frame comprises lane width, position information and state information of the main vehicle and position information and state information of other vehicles;
calculating the lane-changing traversing completion degree of the main vehicle by using the lane width in each data frame and the position information and the state information of the main vehicle;
determining lane-changing comfort of the host vehicle by using the state information of the host vehicle in each data frame;
calculating the lane change safety degree of the host vehicle by utilizing the position information and the state information of the host vehicle in each data frame and the position information and the state information of other vehicles;
and identifying unreasonable lane changing behaviors of the main vehicle in the lane changing data based on the lane changing traversing completion degree, the lane changing comfort degree and the lane changing safety degree.
Optionally, the step of calculating the lane-changing traversing completeness of the host vehicle by using the lane width in each data frame and the position information and the state information of the host vehicle comprises:
calculating the lane changing efficiency and the lane changing sideslip rate of the main vehicle by using the position information of the main vehicle and the lane width in each data frame;
calculating to obtain the deviation rate of the correcting angle of the main vehicle by using the state information of the main vehicle in the last data frame;
and calculating to obtain the lane-changing traversing completeness of the main vehicle based on the lane-changing efficiency, the lane-changing traversing rate and the deviation rate of the correcting angle.
Optionally, the step of calculating the lane change efficiency and the lane change traverse ratio of the host vehicle by using the position information of the host vehicle and the lane width in each data frame includes:
determining the traversing information of the host vehicle in the lane changing process according to the position information of the host vehicle in each data frame;
calculating the lane changing efficiency of the main vehicle by using the transverse moving information;
and calculating the lane-changing traversing rate of the main vehicle by utilizing the traversing information and the lane width.
Optionally, the traversing information and the lane width are used to calculate a lane-changing traversing rate of the host vehicle, including:
determining a theoretical traversing distance of the main vehicle on the center line of the lane where the main vehicle runs from the lane changing initial position to the lane changing ending position according to the lane width;
judging whether the main vehicle has overtaking behavior in the lane changing process;
if so, calculating to obtain the lane-changing traversing rate of the main vehicle by utilizing the traversing information, the theoretical traversing distance and the lane width;
if not, calculating to obtain the lane-changing traversing rate of the main vehicle by utilizing the traversing information and the theoretical traversing distance.
Optionally, the traverse information includes: a positive traverse distance, a negative traverse distance, an absolute traverse distance, and a total traverse distance;
wherein the forward traversing distance is the maximum traversing distance traveled by the host vehicle in the lane change state from the initial lane change position to the next target lane direction;
the negative traversing distance is the maximum traversing distance of the main vehicle running from the lane change initial position to the direction opposite to the next target lane when the main vehicle is in the lane change state;
the absolute transverse moving distance is a transverse moving distance between the initial position of the lane changing of the main vehicle and the ending position of the lane changing when the main vehicle is in the lane changing state;
and the total traversing distance is obtained by accumulating the traversing distances of the main vehicle in the process of driving from the initial lane changing position to the final lane changing position when the main vehicle is in the lane changing state.
Optionally, calculating a yaw angle deviation rate of the host vehicle by using the state information of the host vehicle in the last data frame, including:
determining an actual alignment angle of the host vehicle by using the state information of the host vehicle in the last data frame;
and calculating to obtain the deviation rate of the correcting angle of the main vehicle by utilizing the actual correcting angle and a preset theoretical correcting angle.
Optionally, the step of calculating the lane change safety degree of the host vehicle by using the position information and the state information of the host vehicle in each data frame and the position information and the state information of other vehicles includes:
calculating a relative distance between the host vehicle and the other vehicles in each data frame using the position information of the host vehicle and the position information of the other vehicles in each data frame;
calculating a relative speed of the host vehicle and the other vehicles in each data frame using the state information of the host vehicle and the state information of the other vehicles in each data frame;
and calculating the lane change safety degree of the host vehicle based on the relative distance and the relative speed between the host vehicle and other vehicles in each data frame.
Optionally, identifying an unreasonable lane change behavior of the host vehicle in the lane change data based on the lane change traverse moving completion degree, the lane change comfort level and the lane change safety degree includes:
assigning respective weight values to the lane-changing traversing completion degree, the lane-changing comfort degree and the lane-changing safety degree to obtain the weighted lane-changing traversing completion degree, the weighted lane-changing comfort degree and the weighted lane-changing safety degree;
and identifying unreasonable lane changing behaviors of the main vehicle in the lane changing data by using the weighted lane changing traversing completion degree, the weighted lane changing comfort degree and the weighted lane changing safety degree.
Optionally, the method further includes:
judging whether unreasonable lane changing behaviors exist in the main vehicle in the lane changing data;
and if so, marking the lane change data so as to remind a user to adjust a related algorithm.
An apparatus for identifying an unreasonable lane change behavior of a vehicle, comprising:
the lane change data acquisition unit is used for acquiring lane change data, wherein the lane change data comprises data frames when a main vehicle runs from a lane change initial position to a lane change ending position, and each data frame comprises lane width, position information and state information of the main vehicle and position information and state information of other vehicles;
the traversing completion degree calculating unit is used for calculating the lane changing traversing completion degree of the main vehicle by utilizing the lane width in each data frame and the position information and the state information of the main vehicle;
the comfort degree calculation unit is used for determining the lane changing comfort degree of the main vehicle by utilizing the state information of the main vehicle in each data frame;
the safety degree calculation unit is used for calculating the lane change safety degree of the main vehicle by utilizing the position information and the state information of the main vehicle in each data frame and the position information and the state information of other vehicles;
and the unreasonable lane changing behavior identification unit is used for identifying unreasonable lane changing behavior of the main vehicle in the lane changing data based on the lane changing traversing completion degree, the lane changing comfort degree and the lane changing safety degree.
An apparatus for identifying an unreasonable lane change behavior of a vehicle, comprising: a memory and a processor;
the memory is used for storing programs;
the processor is used for executing the program to realize the steps of the method for identifying the unreasonable lane change behavior of the vehicle.
A readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method for identifying a lane change behaviour irrational for a vehicle as described in the foregoing.
According to the technical scheme, the method, the device, the equipment and the readable storage medium for identifying the unreasonable lane changing behavior of the vehicle are provided by the embodiment of the application, lane changing data is obtained, the lane changing data comprises data frames when the vehicle runs from an initial lane changing position to a final lane changing position, each data frame comprises lane width, position information and state information of the vehicle and position information and state information of other vehicles, lane changing transverse moving completion degree of the vehicle is obtained by calculation according to the lane width and the position information and the state information of the vehicle in each data frame, the state information of the vehicle in each data frame is used for determining lane changing comfort degree of the vehicle, the lane changing safety degree is obtained by calculation according to the position information and the state information of the vehicle in each data frame and the position information and the state information of other vehicles, and unreasonable lane changing behavior of the vehicle in the lane changing data is identified on the basis of the lane changing completion degree, the lane changing comfort degree and the lane changing safety degree. According to the lane-changing traversing method and the lane-changing comfort level and the lane-changing safety level of the main car, unreasonable lane-changing behaviors of the main car are identified from three different directions, so that a corresponding lane-changing algorithm is improved.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a flowchart of a method for identifying an unreasonable lane change behavior of a vehicle according to an embodiment of the present disclosure;
FIG. 2 is a schematic view illustrating a lane-change driving process of a vehicle according to an embodiment of the present disclosure;
FIG. 3 is a schematic structural diagram of an apparatus for identifying an unreasonable lane change behavior of a vehicle according to an embodiment of the present application;
fig. 4 is a block diagram of a hardware structure of an apparatus for identifying an unreasonable lane change behavior of a vehicle, disclosed in an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Fig. 1 is a flowchart of a method for identifying an unreasonable lane change behavior of a vehicle according to an embodiment of the present application, and referring to fig. 1, the method may include the following steps:
and step S100, lane change data are acquired.
Specifically, the lane change data includes data frames when the host vehicle travels from the initial lane change position to the final lane change position, and each data frame includes lane width, position information and state information of the host vehicle, and position information and state information of other vehicles. In addition, the contour of the host vehicle, the route information around the host vehicle, and the contours of other objects around the host vehicle in each data frame may also be displayed in the lane change data, wherein the contour information of the host vehicle may be represented by a rectangle.
And S101, calculating the lane-changing traversing completion degree of the host vehicle by using the lane width in each data frame and the position information and the state information of the host vehicle.
Specifically, the lane-changing transverse moving finish degree of the main vehicle in the lane-changing driving process can be calculated by using the lane width in each data frame acquired in the steps and the position and state information of the main vehicle.
And step S102, determining the lane change comfort level of the host by using the state information of the host in each data frame.
Specifically, the change situation of the driving state of the host vehicle in the lane-changing driving process can be determined through the state information of the host vehicle in each data frame acquired in the steps, so that the lane-changing comfort level of the host vehicle can be determined. The determination of the lane-changing comfort level of the main vehicle can adopt a pre-trained comfort level determination model, the comfort level score corresponding to each data frame can be obtained by inputting the state information of the main vehicle in each data frame into the comfort level determination model, and the lane-changing comfort level of the whole lane-changing process can be determined in a mean value calculation mode after the corresponding comfort level score in each data frame is obtained.
And step S103, calculating the lane change safety degree of the host vehicle by using the position information and the state information of the host vehicle in each data frame and the position information and the state information of other vehicles.
Specifically, the lane change safety of the host vehicle may represent the probability of collision between the host vehicle and other vehicles during the lane change process to some extent. In the lane changing process of the main vehicle, if the probability of collision with other vehicles is high, the lane changing safety degree is relatively low; lane change safety is relatively higher if the probability of a collision with another vehicle is small.
During the process of calculating the lane change safety degree of the main vehicle by using the position information and the state information of the main vehicle in each data frame and the state information of the position information of other vehicles, the safety degree score of the main vehicle can be calculated for each data frame, and then the safety degree scores of all the data frames in the lane change data are used for finally calculating the lane change safety degree of the main vehicle.
And S104, identifying unreasonable lane changing behaviors of the main vehicle in lane changing data based on the lane changing traversing completion degree, the lane changing comfort degree and the lane changing safety degree.
Specifically, when the unreasonable lane changing behavior of the main car in the lane changing data is identified, the lane changing sidesway degree, the lane changing comfort degree and the lane changing safety degree of the main car are utilized for identification, so that the lane changing behavior of the main car is judged only in one aspect, and the lane changing behavior of the main car is comprehensively and objectively evaluated in combination with three aspects, and the unreasonable lane changing behavior of the main car is identified.
In the above embodiment, a method for identifying an unreasonable lane change behavior of a vehicle is provided, by obtaining lane change data, the lane change data including data frames when a host vehicle travels from an initial lane change position to a final lane change position, each data frame including lane width, position information and state information of the host vehicle and position information and state information of other vehicles, calculating lane change traverse movement completion of the host vehicle using the lane width and the position information and the state information of the host vehicle in each data frame, determining lane change comfort of the host vehicle using the state information of the host vehicle in each data frame, calculating lane change safety of the host vehicle using the position information and the state information of the host vehicle in each data frame and the position information and the state information of other vehicles, and identifying an unreasonable lane change behavior of the host vehicle in the lane change data based on the lane change traverse movement completion, the lane change comfort and the lane change safety. According to the lane-changing traversing method and the lane-changing comfort level and the lane-changing safety level of the main car, unreasonable lane-changing behaviors of the main car are identified from three different directions, so that a corresponding lane-changing algorithm is improved.
In some embodiments of the present application, a process of calculating a lane-changing traverse completion of the host vehicle using the lane width and the position information and the state information of the host vehicle in each data frame in step S101 may include:
s11, calculating the lane changing efficiency and the lane changing sideslip rate of the main vehicle by using the position information and the lane width of the main vehicle in each data frame.
Specifically, the lane changing efficiency and the lane changing sideslip rate of the host vehicle in the lane changing process can be calculated by utilizing the position information and the lane width of the host vehicle in each data frame in the lane changing data. The lane changing efficiency can reflect the proportion of the effective movement of the main vehicle in the overall movement of the main vehicle in the lane changing process. The lane-changing sideslip rate can reflect the actual sideslip condition of the main vehicle in the lane-changing process of the main vehicle.
And S12, calculating to obtain the deviation rate of the correcting angle of the main vehicle by using the state information of the main vehicle in the last data frame.
Specifically, in the last data frame, the actual yaw angle of the host vehicle may be determined from the state information of the host vehicle. The actual swing angle may be an included angle between the vehicle and a center line of the lane. After the actual correcting angle of the main vehicle is obtained, the deviation rate of the correcting angle of the main vehicle can be calculated by utilizing the actual correcting angle and a preset theoretical correcting angle. The theoretical correction angle can be determined by collecting a large amount of data of vehicle lane changing, determining the correction angles after all vehicle lane changing is finished, and further determining to obtain the theoretical correction angle by using all determined correction angles.
In the process of calculating the deviation rate of the yaw angle of the main vehicle, the formula can be used: and calculating the actual correction angle/the theoretical correction angle to obtain the deviation rate of the correction angle. In the calculation process, in order to avoid that the calculation result generates larger fluctuation when the actual correcting angle has smaller change, a smoothing factor can be added to the molecule part to balance the change of the molecule.
And S13, calculating to obtain the lane-changing traversing completeness of the main vehicle based on the lane-changing efficiency, the lane-changing traversing rate and the aligning angle deviation rate.
Specifically, the lane-changing traversing rate and the yaw angle deviation rate obtained by the calculation in the steps can be used for calculating the lane-changing traversing completeness of the main vehicle. In calculating the lane-changing traverse completion of the host vehicle, the formula can be used: and calculating the lane changing efficiency, the lane changing sideslip rate- (1-rectification angle deviation rate) and x to obtain the lane changing sideslip completion degree. Wherein x is a constant.
In the above embodiment, the lane-changing traversing rate and the yaw angle deviation rate calculated above are used to calculate the lane-changing traversing completion of the host vehicle, so that the unreasonable lane-changing behavior of the host vehicle is recognized from the moving situation and the completion situation of the host vehicle during the lane-changing process at the angle of the traversing completion.
In some embodiments of the present application, a process of calculating lane change efficiency and lane change lateral movement rate of the host vehicle by using the position information and lane width of the host vehicle in each data frame at S11 may include:
s21, determining the traversing information of the host vehicle in the lane changing process according to the position information of the host vehicle in each data frame.
Specifically, the traverse information may include: positive traverse distance, negative traverse distance, absolute traverse distance, and total traverse distance.
Wherein the negative-direction traversing distance may be a maximum traversing distance traveled by the host vehicle from the lane change initial position to a direction opposite to the next target lane when the host vehicle is in the lane change state. Since the main vehicle may need to traverse in the direction opposite to the next target lane based on actual conditions, such as obstruction of other vehicles or limited lane changing vision, during the lane changing process, so as to facilitate the subsequent lane changing, the present application can be used as reference data for analyzing the lane changing process of the vehicle by recording the negative traverse distance.
The forward traversing distance may be a maximum traversing distance traveled from the lane change initial position to the next target lane direction when the host vehicle is in the lane change state. The absolute traverse distance may be a traverse distance between a lane change initial position and a lane change end position of the host vehicle when the host vehicle is in a lane change state. The total traversing distance may be obtained by accumulating traversing distances of the host vehicle in the process of traveling from the lane change initial position to the lane change end position when the host vehicle is in the lane change state.
Referring to fig. 2, fig. 2 shows the 1 st frame data, the 42 th frame data, the 102 th frame data, and the 131 th frame data in the lane change data, wherein the position of the host vehicle in the 1 st frame data is a lane change initial position, the position of the host vehicle in the 42 th frame data is a farthest position where the host vehicle travels from the lane change initial position in a direction opposite to a next target lane, the position of the host vehicle in the 102 th frame data is a farthest position where the host vehicle travels from the lane change initial position in a direction of the next target lane, and the position of the host vehicle in the 131 th frame data is a lane change ending position. From the position of the host vehicle in the 1 st frame data and the 42 th frame data, the negative-going lateral-movement distance of the host vehicle in the lane-change data can be calculated. From the position of the host vehicle in the 1 st frame data and the 102 th frame data, the forward-traversing distance of the host vehicle in the lane change data can be calculated. From the position of the host vehicle in the 1 st frame data and the 131 st frame data, the absolute lateral-movement distance of the host vehicle in the lane-change data can be calculated.
And S22, calculating the lane changing efficiency of the main vehicle by utilizing the transverse moving information.
Specifically, the lane change efficiency of the host vehicle can be calculated using the lateral movement information determined in the above-described steps. The traverse information may include: the main vehicle can be judged whether overtaking behaviors exist in the lane changing process in the calculation process of the positive traversing distance, the negative traversing distance, the absolute traversing distance and the total traversing distance, wherein overtaking refers to the process that a rear vehicle passes to the rear side of a front vehicle, passes behind the front vehicle and returns to the original lane. If the main vehicle has overtaking behavior in the lane changing process, the lane changing efficiency can be calculated by using the positive traversing distance, the negative traversing distance, the absolute traversing distance and the total traversing distance in the traversing information, and a formula can be used in the calculation process: calculating the lane change efficiency by (positive sidesway distance-negative sidesway distance) alpha + absolute sidesway distance/total sidesway distance; if the main vehicle does not have overtaking behavior in the lane changing process, the lane changing efficiency can be calculated by using the positive traversing distance, the negative traversing distance and the total traversing distance in the traversing information, and the formula can be used in the calculation process: (positive traversing distance-negative traversing distance) alpha/total traversing distance) -1 is calculated to obtain the lane changing efficiency. Wherein α is a constant.
And S23, calculating the lane-changing traversing rate of the main vehicle by using the traversing information and the lane width.
In the embodiment, the traversing information of the host vehicle in the lane changing process can be determined according to the position information of the host vehicle in each data frame, the lane changing efficiency of the host vehicle can be determined by using the traversing information, and the lane changing traversing rate of the host vehicle can be calculated by using the traversing information and the lane width.
In some embodiments of the present application, a process of calculating a lane-changing traverse ratio of the host vehicle by using the traverse information and the lane width at S23 is described, where the process may specifically include:
and S31, determining the theoretical traversing distance of the main vehicle on the center line of the lane from the lane change initial position to the lane change ending position according to the lane width.
Specifically, since the host vehicle generally travels along the center line of the road during traveling, after determining the lane change initial position of the host vehicle and the lane change ending position of the host vehicle, the theoretical traverse distance of the host vehicle on the center line of the lane where the host vehicle travels from the lane change initial position to the lane change ending position can be determined using the determined lane width.
And S32, judging whether the overtaking behavior exists in the lane changing process of the main vehicle.
Specifically, when the lane-changing traversing rate of the host vehicle is calculated, whether the host vehicle has an overtaking behavior in the lane-changing process can be judged, if the host vehicle has the overtaking behavior in the lane-changing process, the step S33 is executed, and if the host vehicle does not have the overtaking behavior in the lane-changing process, the step S34 is executed. The overtaking refers to the process that a rear vehicle merges to the rear side of a front vehicle, crosses behind the front vehicle and merges to return to the original lane.
And S33, calculating the lane-changing traversing rate of the main vehicle by utilizing the traversing information, the theoretical traversing distance and the lane width.
Specifically, the traverse information may include an absolute traverse distance. When the main vehicle has overtaking behavior in the lane changing process, the lane changing traversing rate of the main vehicle can be calculated by utilizing the absolute traversing distance, the theoretical traversing distance and the lane width. In the calculation, the formula can be used: and (1) calculating the lane-changing traversing rate by using the theoretical traversing distance-absolute traversing distance/lane width.
And S34, calculating the lane-changing traversing rate of the main vehicle by utilizing the traversing information and the theoretical traversing distance.
Specifically, the traverse information may include an absolute traverse distance. When the main vehicle does not have overtaking behavior in the lane changing process, the lane changing traversing rate of the main vehicle can be calculated by utilizing the absolute traversing distance and the theoretical traversing distance. In the calculation process, the relation between the absolute traversing distance and the theoretical traversing distance can be judged, and if the absolute traversing distance is larger than the theoretical traversing distance, a formula can be utilized: calculating the theoretical sidesway distance/absolute sidesway distance to obtain the lane-changing sidesway rate of the main vehicle; if the absolute traversing distance is not greater than the theoretical traversing distance, then the formula can be utilized: and calculating the absolute traversing distance/theoretical traversing distance to obtain the lane-changing traversing rate of the main vehicle.
In the above embodiment, the theoretical traverse distance of the host vehicle in the lane change process can be calculated by using the road width, and the lane change traverse ratio when the overtaking behavior of the host vehicle exists in the lane change process and the overtaking behavior of the host vehicle does not exist in the lane change process can be calculated by using different calculation modes.
In some embodiments of the present application, a process of calculating a lane change safety degree of the host vehicle by using the position information and the state information of the host vehicle in each data frame and the position information and the state information of the other vehicles in step S103 may include:
s41, calculating the relative distance between the host vehicle and other vehicles in each data frame by using the position information of the host vehicle and the position information of other vehicles in each data frame.
Specifically, when the relative distance of the host vehicle to the other vehicle in each data frame is calculated, the position information of the host vehicle and the position information of the other vehicle in each data frame may be used. In this case, the calculation process of the relative distance between the host vehicle and the other vehicle can be converted into the calculation process of the relative distance between the two rectangles.
When calculating the relative distance, the symbolic distance can be used for calculation, a plane rectangular coordinate system is established by taking the middle point of the rectangular frame corresponding to the host vehicle as the origin, the x axis and the y axis are perpendicular to or parallel to the sides of the rectangle, the vertex coordinate of the upper right corner of the rectangular frame corresponding to the host vehicle is taken as B (xb, yb), xb is greater than 0 and yb is greater than 0, the rectangular frames corresponding to other vehicles are converted into a new coordinate system and mapped into the first quadrant to obtain the coordinate P (xp, yp) of each point on the rectangular frame corresponding to other vehicles, the coordinate P (xp, yp) of each point on the rectangular frame corresponding to other vehicles and the vertex coordinate of the upper right corner of the rectangular frame corresponding to the host vehicle are B (xb, yb), the vector D (xd, yd) corresponding to each point is obtained by calculation through P-B, the formula norm (D) = sqrt (xd ^ 2) corresponding to other vehicles is calculated by using the symbolic distance calculation formula norm (D) = sqrt (xd 2), and the shortest relative distance between the host vehicle and other vehicles is determined.
When the relative distance between the main vehicle and other vehicles is calculated, the relative position relation between the other vehicles and the main vehicle can be judged, and if the other vehicles are positioned behind the main vehicle, the relative distance between the other vehicles and the main vehicle can be calculated by using a Chebyshev formula; if the other vehicle is not located behind the host vehicle, the relative distance of the other vehicle to the host vehicle may be calculated using Euclidean equations.
And S42, calculating the relative speed of the host vehicle and other vehicles in each data frame by using the state information of the host vehicle and the state information of other vehicles in each data frame.
Specifically, the relative velocity of the host vehicle and the other vehicles in each data frame may be calculated by using the state information of the host vehicle and the state information of the other vehicles in each data frame, wherein in each data frame, the state information of the host vehicle may include the velocity and acceleration information of the host vehicle, and the state information of the other vehicles may include the velocity and acceleration information of the other vehicles.
S43, calculating the lane change safety degree of the host vehicle based on the relative distance and the relative speed between the host vehicle and other vehicles in each data frame.
Specifically, in the above step, after determining the relative distance and the relative speed between the host vehicle and the other vehicles in each data frame, the safety degree corresponding to each data frame may be obtained by calculation according to the preset safety degree calculation rule, and then the safety degrees corresponding to all the data frames in the lane change data are used to determine the lane change safety degree of the host vehicle; the lane-changing safety degree of the host vehicle can also be directly determined by utilizing the relative distance and the relative speed between the host vehicle and other vehicles in each data frame according to a preset safety degree calculation rule.
In the above-described embodiment, by calculating the relative distance and the relative velocity of the host vehicle and the other vehicles in each data frame, the lane change safety degree of the host vehicle can be calculated using the calculated relative distance and the calculated relative velocity, so that the unreasonable lane change behavior of the host vehicle can be recognized from the safety viewpoint.
In some embodiments of the present application, the process of identifying the unreasonable lane change behavior of the host vehicle in the lane change data based on the lane change traverse completion, the lane change comfort level, and the lane change safety level in step S104 is described, and the process may include:
s51, distributing respective weight values to the lane-changing transverse moving completion degree, the lane-changing comfort degree and the lane-changing safety degree to obtain the weighted lane-changing transverse moving completion degree, the weighted lane-changing comfort degree and the weighted lane-changing safety degree.
Specifically, in the above embodiment, the lane changing process of the host vehicle may be analyzed from three different aspects, and the lane changing traverse moving completion degree, the lane changing comfort level, and the lane changing safety degree of the host vehicle in the lane changing process may be calculated. Considering that different users or different scenes may have different requirements on the lane-changing traversing completion degree, the lane-changing comfort degree and the lane-changing safety degree in the actual lane-changing process, respective weight values can be distributed to the lane-changing traversing completion degree, the lane-changing comfort degree and the lane-changing safety degree, so that the weighted lane-changing traversing completion degree, the weighted lane-changing comfort degree and the weighted lane-changing safety degree are obtained.
And S52, identifying unreasonable lane changing behavior of the main vehicle in lane changing data by using the weighted lane changing traversing completion degree, the weighted lane changing comfort degree and the weighted lane changing safety degree.
Specifically, the unreasonable lane changing behavior of the main vehicle in the lane changing data can be identified by using the weighted lane changing traversing completion degree, the lane changing comfort degree and the lane changing safety degree obtained in the steps. In the process of identifying the unreasonable lane changing behavior of the main vehicle in the lane changing data, whether the main vehicle has the overtaking behavior in the lane changing process can be judged, and when the overtaking behavior exists, a formula can be utilized: calculating a lane-changing traversing completion degree a + a comfort degree b + a safety degree c to obtain a lane-changing behavior score, and identifying unreasonable lane-changing behaviors of the main vehicle in the lane-changing data through the score; when there is no overtaking behavior, the formula can be used: and (lane change traversing completion degree d + lane change comfort degree e) lane change safety degree f to obtain a lane change behavior score, and the score can be used for identifying unreasonable lane change behaviors of the main vehicle in the lane change data. Wherein a, b, c, d, e and f are arbitrary constants.
In the above embodiment, the irrational lane-changing behavior of the host vehicle in the lane-changing data is identified by assigning the calculated lane-changing traverse completion degree, the lane-changing comfort degree and the lane-changing safety degree with respective corresponding weight values, and then using the weighted lane-changing traverse completion degree, the weighted lane-changing comfort degree and the weighted lane-changing safety degree, so that the irrational lane-changing behavior identification of the host vehicle can properly adjust the gravity center of the irrational lane-changing behavior identification among the lane-changing traverse completion degree, the lane-changing comfort degree and the lane-changing safety degree according to the actual requirements.
By the embodiment, the unreasonable lane changing behavior of the main vehicle in the lane changing data can be identified, and whether the unreasonable lane changing behavior exists in the main vehicle in the lane changing data can be judged by utilizing the identification result of the unreasonable lane changing behavior obtained in the embodiment, so that whether the lane changing behavior in the lane changing data meets the requirement of a user is determined. Based on this, in some embodiments of the application, the lane change data with the unreasonable lane change behavior can be regarded as abnormal data by judging whether the main vehicle has the unreasonable lane change behavior in the lane change data, so as to remind a user to perform optimization adjustment on an algorithm corresponding to the abnormal data.
Specifically, whether unreasonable lane changing behaviors exist in the main vehicle in the lane changing data can be judged, if yes, the lane changing data can be marked, and therefore a user is reminded to adjust an algorithm corresponding to the lane changing data. The unreasonable lane changing behavior of the main vehicle in the lane changing data can be identified independently according to the lane changing traversing completion degree, the lane changing comfort degree or the lane changing safety degree, so that the unreasonable lane changing behavior of the main vehicle can be more accurately positioned, and a user can conveniently improve an algorithm.
In the embodiment, the lane change data with the unreasonable lane change behavior of the main vehicle can be selected by judging whether the unreasonable lane change behavior exists in the lane change data of the main vehicle, so that a user is reminded to improve an algorithm corresponding to the lane change data with the unreasonable lane change behavior of the main vehicle.
The following describes a method for identifying a vehicle lane change unreasonable behavior provided by an embodiment of the present application, and the method for identifying a vehicle lane change unreasonable behavior described below and the device for identifying a vehicle lane change unreasonable behavior described above may be referred to correspondingly.
Fig. 3 is a schematic structural diagram of an apparatus for identifying a vehicle lane change unreasonable behavior according to an embodiment of the present application, where the apparatus for identifying a vehicle lane change unreasonable behavior may include:
a lane change data acquisition unit 10 for acquiring lane change data including data frames when the host vehicle travels from a lane change initial position to a lane change end position, each data frame including a lane width, position information and state information of the host vehicle, and position information and state information of other vehicles;
a traversing completion degree calculating unit 20, configured to calculate a lane-changing traversing completion degree of the host vehicle by using the lane width in each data frame and the position information and state information of the host vehicle;
a comfort level calculation unit 30 for determining a lane change comfort level of the host vehicle using the state information of the host vehicle in each data frame;
a safety degree calculation unit 40, configured to calculate a lane change safety degree of the host vehicle by using the position information and the state information of the host vehicle in each data frame and the position information and the state information of other vehicles;
an unreasonable lane change behavior recognition unit 50, configured to recognize an unreasonable lane change behavior of the host vehicle in the lane change data based on the lane change traverse moving completion degree, the lane change comfort degree, and the lane change safety degree.
In the above embodiment, there is provided an apparatus for recognizing an unreasonable lane change behavior of a vehicle, lane change data including data frames when a host vehicle travels from an initial lane change position to a final lane change position is acquired by a lane change data acquiring unit 10, each data frame includes lane width, position information and state information of the host vehicle and position information and state information of other vehicles, a traverse completion calculating unit 20 calculates a lane change traverse completion of the host vehicle using the lane width and the position information and state information of the host vehicle in each data frame, a comfort calculating unit 30 determines a lane change comfort of the host vehicle using the state information of the host vehicle in each data frame, a safety calculating unit 40 calculates a lane change safety of the host vehicle using the position information and state information of the host vehicle in each data frame and the position information and state information of other vehicles, and an unreasonable lane change behavior recognizing an unreasonable lane change behavior of the host vehicle in the lane change data based on the lane change completion, the lane change safety and the lane change safety. According to the lane-changing traversing method and the lane-changing comfort level and the lane-changing safety level of the main car, unreasonable lane-changing behaviors of the main car are identified from three different directions, so that a corresponding lane-changing algorithm is improved.
Alternatively, the traversing completion calculating unit 20 may perform a process of calculating the lane-changing traversing completion of the host vehicle using the lane width and the position information and the state information of the host vehicle in each data frame, and may include:
calculating the lane changing efficiency and the lane changing sideslip rate of the main vehicle by using the position information of the main vehicle and the lane width in each data frame;
calculating to obtain the deviation rate of the correcting angle of the main vehicle by using the state information of the main vehicle in the last data frame;
and calculating to obtain the lane-changing traversing completeness of the main vehicle based on the lane-changing efficiency, the lane-changing traversing rate and the deviation rate of the correcting angle.
Alternatively, the traversing completion calculating unit 20 may perform a process of calculating the lane change efficiency and the lane change traversing rate of the host vehicle by using the position information of the host vehicle and the lane width in each data frame, and may include:
determining the traversing information of the host vehicle in the lane changing process according to the position information of the host vehicle in each data frame;
calculating the lane changing efficiency of the main vehicle by using the transverse moving information;
and calculating the lane-changing traversing rate of the main vehicle by utilizing the traversing information and the lane width.
Alternatively, the traversing completion calculating unit 20 may perform a process of calculating the lane-changing traversing rate of the host vehicle by using the traversing information and the lane width, and the process may include:
determining a theoretical traversing distance of the main vehicle on the center line of the lane where the main vehicle runs from the lane changing initial position to the lane changing ending position according to the lane width;
judging whether the main vehicle has overtaking behavior in the lane changing process;
if so, calculating to obtain the lane-changing traversing rate of the main vehicle by utilizing the traversing information, the theoretical traversing distance and the lane width;
if not, calculating to obtain the lane-changing traversing rate of the main vehicle by utilizing the traversing information and the theoretical traversing distance.
Alternatively, the traversing completion calculating unit 20 may perform a process of calculating the yaw angle deviation ratio of the host vehicle using the state information of the host vehicle in the last data frame, and may include:
determining an actual alignment angle of the host vehicle by using the state information of the host vehicle in the last data frame;
and calculating to obtain the deviation rate of the correcting angle of the main vehicle by utilizing the actual correcting angle and a preset theoretical correcting angle.
Alternatively, the safety degree calculation unit 40 may perform a process of calculating the lane change safety degree of the host vehicle using the position information and the state information of the host vehicle and the position information and the state information of the other vehicles in each data frame, and may include:
calculating a relative distance between the host vehicle and the other vehicles in each data frame using the position information of the host vehicle and the position information of the other vehicles in each data frame;
calculating a relative velocity of the host vehicle and the other vehicles in each data frame using the state information of the host vehicle and the state information of the other vehicles in each data frame;
and calculating the lane change safety degree of the host vehicle based on the relative distance and the relative speed between the host vehicle and other vehicles in each data frame.
Alternatively, the unreasonable lane change behavior recognition unit 50 may perform a process of recognizing the unreasonable lane change behavior of the host vehicle in the lane change data based on the lane change traverse completion degree, the lane change comfort degree, and the lane change safety degree, and may include:
assigning respective weight values to the lane-changing traversing completion degree, the lane-changing comfort degree and the lane-changing safety degree to obtain the weighted lane-changing traversing completion degree, the weighted lane-changing comfort degree and the weighted lane-changing safety degree;
and identifying unreasonable lane changing behaviors of the main vehicle in the lane changing data by using the weighted lane changing traversing completion degree, the weighted lane changing comfort degree and the weighted lane changing safety degree.
Optionally, the device for identifying the unreasonable lane change behavior of the vehicle may further include:
the judging unit is used for judging whether the main vehicle has unreasonable lane changing behavior in the lane changing data;
and the marking reminding unit is used for marking the lane change data when unreasonable lane change behaviors exist in the main vehicle in the lane change data so as to remind a user of adjusting a related algorithm.
The embodiment of the present application further provides a device for identifying a vehicle unreasonable lane change behavior, fig. 4 shows a block diagram of a hardware structure of the device for identifying a vehicle unreasonable lane change behavior, and referring to fig. 4, a hardware structure of the device for identifying a vehicle unreasonable lane change behavior may include: at least one processor 1, at least one communication interface 2, at least one memory 3 and at least one communication bus 4;
in the embodiment of the application, the number of the processor 1, the communication interface 2, the memory 3 and the communication bus 4 is at least one, and the processor 1, the communication interface 2 and the memory 3 complete mutual communication through the communication bus 4;
the processor 1 may be a central processing unit CPU, or an Application Specific Integrated Circuit ASIC (Application Specific Integrated Circuit), or one or more Integrated circuits configured to implement embodiments of the present invention, etc.;
the memory 3 may include a high-speed RAM memory, and may further include a non-volatile memory (non-volatile memory) or the like, such as at least one disk memory;
wherein the memory stores a program and the processor can call the program stored in the memory, the program for: and realizing each processing flow in the identification method for the unreasonable lane changing behavior of the vehicle.
Embodiments of the present application further provide a storage medium, where a program suitable for execution by a processor may be stored, where the program is configured to: and realizing each processing flow in the method for identifying the unreasonable lane change behavior of the vehicle.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, the embodiments can be combined with each other, and the same and similar parts can be referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (11)
1. A method for identifying unreasonable lane changing behaviors of a vehicle is characterized by comprising the following steps:
acquiring lane change data, wherein the lane change data comprises data frames when a host vehicle runs from a lane change initial position to a lane change ending position, and each data frame comprises lane width, position information and state information of the host vehicle and position information and state information of other vehicles;
calculating the lane-changing traversing completion degree of the main vehicle by using the lane width in each data frame and the position information and the state information of the main vehicle;
determining lane-changing comfort of the host vehicle by using the state information of the host vehicle in each data frame;
calculating the lane-changing safety degree of the host vehicle by utilizing the position information and the state information of the host vehicle in each data frame and the position information and the state information of other vehicles;
identifying unreasonable lane changing behaviors of the main vehicle in the lane changing data based on the lane changing traversing completion degree, the lane changing comfort degree and the lane changing safety degree;
the method comprises the following steps of calculating the lane-changing transverse moving completion degree of the main vehicle by using the lane width in each data frame and the position information and the state information of the main vehicle, wherein the method comprises the following steps:
calculating the lane changing efficiency and the lane changing sideslip rate of the main vehicle by using the position information of the main vehicle and the lane width in each data frame;
calculating to obtain the deviation rate of the correcting angle of the main vehicle by using the state information of the main vehicle in the last data frame;
calculating to obtain the lane-changing traversing completion degree of the main vehicle based on the lane-changing efficiency, the lane-changing traversing rate and the deviation rate of the correcting angle;
the calculation formula of the lane-changing transverse moving completion degree of the main truck is as follows: lane change efficiency, lane change sideslip rate- (1-yaw angular deviation rate) ×, where x is a constant.
2. The method of claim 1, wherein calculating a lane-change efficiency and a lane-change lateral-movement rate of the host vehicle using the position information of the host vehicle and the lane width in each data frame comprises:
determining the traversing information of the host vehicle in the lane changing process according to the position information of the host vehicle in each data frame;
calculating the lane changing efficiency of the main vehicle by using the transverse moving information;
and calculating the lane-changing traversing rate of the main vehicle by utilizing the traversing information and the lane width.
3. The method of claim 2, wherein calculating a lane-change traverse rate of the host vehicle using the traverse information and the lane width comprises:
determining a theoretical traversing distance of the main vehicle on the center line of the lane where the main vehicle runs from the lane changing initial position to the lane changing ending position according to the lane width;
judging whether the main vehicle has overtaking behavior in the lane changing process;
if so, calculating to obtain the lane-changing traversing rate of the main vehicle by utilizing the traversing information, the theoretical traversing distance and the lane width;
if not, calculating to obtain the lane-changing traversing rate of the main vehicle by utilizing the traversing information and the theoretical traversing distance.
4. The method of claim 2, wherein the traversing information comprises: a positive traverse distance, a negative traverse distance, an absolute traverse distance, and a total traverse distance;
wherein the forward traversing distance is the maximum traversing distance traveled by the host vehicle in the lane change state from the initial lane change position to the next target lane direction;
the negative traversing distance is the maximum traversing distance of the main vehicle running from the lane change initial position to the direction opposite to the next target lane when the main vehicle is in the lane change state;
the absolute transverse moving distance is a transverse moving distance between the initial position of the lane changing of the main vehicle and the ending position of the lane changing when the main vehicle is in the lane changing state;
and the total traversing distance is obtained by accumulating the traversing distances of the main vehicle in the process of driving from the initial lane changing position to the final lane changing position when the main vehicle is in the lane changing state.
5. The method of claim 1, wherein calculating a yaw angle deviation ratio for the host vehicle using the state information for the host vehicle in a last data frame comprises:
determining an actual alignment angle of the host vehicle by using the state information of the host vehicle in the last data frame;
and calculating to obtain the deviation rate of the correcting angle of the main vehicle by utilizing the actual correcting angle and a preset theoretical correcting angle.
6. The method of claim 1, wherein calculating a lane-change safety of the host vehicle using the position information and the state information of the host vehicle and the position information and the state information of other vehicles in each data frame comprises:
calculating a relative distance between the host vehicle and the other vehicles in each data frame using the position information of the host vehicle and the position information of the other vehicles in each data frame;
calculating a relative velocity of the host vehicle and the other vehicles in each data frame using the state information of the host vehicle and the state information of the other vehicles in each data frame;
and calculating the lane change safety degree of the host vehicle based on the relative distance and the relative speed between the host vehicle and other vehicles in each data frame.
7. The method of claim 1, wherein identifying unreasonable lane change behavior of the host vehicle in the lane change data based on the lane change traverse completion, the lane change comfort, and the lane change safety comprises:
assigning respective weight values to the lane-changing traversing completion degree, the lane-changing comfort degree and the lane-changing safety degree to obtain the weighted lane-changing traversing completion degree, the weighted lane-changing comfort degree and the weighted lane-changing safety degree;
and identifying unreasonable lane changing behaviors of the main vehicle in the lane changing data by using the weighted lane changing traversing completion degree, the weighted lane changing comfort degree and the weighted lane changing safety degree.
8. The method of any one of claims 1-7, further comprising:
judging whether unreasonable lane changing behaviors exist in the main vehicle in the lane changing data;
and if so, marking the lane change data so as to remind a user to adjust a related algorithm.
9. An apparatus for recognizing an unreasonable lane change behavior of a vehicle, comprising:
the lane change data acquisition unit is used for acquiring lane change data, wherein the lane change data comprises data frames when a main vehicle runs from a lane change initial position to a lane change ending position, and each data frame comprises lane width, position information and state information of the main vehicle and position information and state information of other vehicles;
the traversing completion degree calculating unit is used for calculating the lane changing traversing completion degree of the main vehicle by utilizing the lane width in each data frame and the position information and the state information of the main vehicle;
the comfort degree calculation unit is used for determining the lane changing comfort degree of the main vehicle by utilizing the state information of the main vehicle in each data frame;
the safety degree calculation unit is used for calculating the lane change safety degree of the main vehicle by utilizing the position information and the state information of the main vehicle in each data frame and the position information and the state information of other vehicles;
an unreasonable lane change behavior identification unit, which is used for identifying unreasonable lane change behavior of the main vehicle in the lane change data based on the lane change traversing completion degree, the lane change comfort degree and the lane change safety degree;
the method comprises the following steps of calculating the lane-changing transverse moving completion degree of the main vehicle by using the lane width in each data frame and the position information and the state information of the main vehicle, wherein the method comprises the following steps:
calculating the lane changing efficiency and the lane changing sideslip rate of the main vehicle by using the position information of the main vehicle and the lane width in each data frame;
calculating to obtain the deviation rate of the correcting angle of the main vehicle by using the state information of the main vehicle in the last data frame;
calculating to obtain the lane-changing traversing completion degree of the main vehicle based on the lane-changing efficiency, the lane-changing traversing rate and the deviation rate of the correcting angle;
the calculation formula of the lane-changing transverse moving completion degree of the main truck is as follows: lane change efficiency, lane change sideslip rate- (1-yaw angular deviation rate) ×, where x is a constant.
10. An apparatus for identifying an unreasonable lane change behavior of a vehicle, comprising: a memory and a processor;
the memory is used for storing programs;
the processor, which is used for executing the program, realizes the steps of the method for identifying the unreasonable lane changing behavior of the vehicle according to any one of claims 1-8.
11. A readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method for identifying a lane change irrational behavior of a vehicle according to any one of claims 1 to 8.
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| CN102609765A (en) * | 2012-03-22 | 2012-07-25 | 北京工业大学 | Intelligent vehicle lane change path planning method based on polynomial and radial basis function (RBF) neural network |
| CN103496366B (en) * | 2013-09-09 | 2016-02-24 | 北京航空航天大学 | A kind of initiative lane change collision avoidance control method based on collaborative truck and device |
| CN105480229B (en) * | 2015-11-24 | 2018-01-16 | 大连楼兰科技股份有限公司 | A kind of intelligent lane change householder method based on information fusion |
| CN107323450B (en) * | 2017-06-08 | 2019-08-13 | 广州汽车集团股份有限公司 | The control method and device of vehicle lane change, storage medium |
| CN110533958A (en) * | 2018-05-24 | 2019-12-03 | 上海博泰悦臻电子设备制造有限公司 | Vehicle lane change based reminding method and system |
| CN111439263B (en) * | 2018-12-29 | 2022-05-20 | 沈阳美行科技股份有限公司 | Vehicle lane change recognition method and device, electronic equipment and storage medium |
| CN109910792B (en) * | 2019-03-08 | 2022-04-22 | 苏州工业园区职业技术学院 | High-speed lane-changing control system of automatic driving electric vehicle |
| CN111783536A (en) * | 2020-05-29 | 2020-10-16 | 北京百度网讯科技有限公司 | Method, device and equipment for evaluating lane change reasonability and storage medium |
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