CN115649156A - Method and system for evaluating collision risk of oncoming vehicle - Google Patents
Method and system for evaluating collision risk of oncoming vehicle Download PDFInfo
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Abstract
The invention discloses a collision risk assessment method for oncoming vehicles, which is used for the working condition that a driver deviates from a lane unconsciously and has collision risk, and comprises the following steps: screening out target vehicles meeting specified conditions from all perception targets; selecting a target vehicle with the collision time less than or equal to a time designated threshold, and calculating the predicted collision position variance of the self vehicle and the selected target vehicle in the longitudinal collision time; calculating the maximum value and the minimum value of the transverse distance between the self vehicle and the selected target vehicle during the collision time to obtain a predicted collision position interval; and determining whether the collision risk exists between the self vehicle and the target vehicle according to whether the probability of the predicted collision position in the predicted collision position interval is greater than a probability specified threshold. The invention takes the uncertain introduction of environment perception as a judgment condition on the basis of the prior art, thereby improving the accuracy of the evaluation of the collision risk of oncoming vehicles.
Description
Technical Field
The invention relates to the field of automobiles, in particular to an oncoming vehicle collision risk assessment method and system for an emergency lane keeping system in an intelligent vehicle driving or advanced driving assistance system.
Background
The invention discloses a vehicle emergency lane keeping system, which is used for intervening in lateral control to avoid collision when a driver unconsciously deviates from a lane and has collision risk, mainly comprises 3 scenes of deviating road edges, oncoming vehicle collision and rear vehicle overtaking collision, and relates to oncoming vehicle collision scenes. The collision risk assessment is a core technology of an emergency lane keeping system, and the collision risk of a self vehicle and other vehicles needs to be judged in advance to ensure safety, but the misjudgment cannot generate unnecessary interference to a driver.
For the oncoming vehicle scene, the existing risk assessment methods can be classified into 3 types:
the first method only adopts the longitudinal distance as a judgment condition, namely the collision risk is considered when the longitudinal distance between the opposite vehicle and the self vehicle is smaller than a threshold value.
The second method adopts Time To Collision (TTC) as a judgment condition, that is, a Collision risk is considered when both the longitudinal TTC and the lateral TTC of the oncoming vehicle are smaller than a threshold value.
The third method adopts the distance collision time as a judgment condition, and adopts a scheme of expanding the sizes of the self vehicle and other vehicles in order to cope with the uncertainty of perception, so that although the problem of uncertainty of perception is solved to a certain extent, the misjudgment can be caused due to over conservation.
Disclosure of Invention
In this summary, a series of simplified form concepts are introduced that are simplifications of the prior art in this field, which will be described in further detail in the detailed description. The summary of the invention is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.
The invention aims to provide a method and a system for evaluating collision risks of oncoming vehicles, which take distance collision time as a judgment condition and introduce uncertainty of a perception system into the judgment condition so as to reduce misjudgment.
In order to solve the technical problem, the invention provides an oncoming vehicle collision risk assessment method for an oncoming vehicle under a condition that a driver unintentionally deviates from a lane and has a collision risk, which comprises the following steps:
s1, screening out target vehicles meeting specified conditions from all perception targets;
s2, selecting a target vehicle with the collision time less than or equal to a time designated threshold, and calculating the predicted collision position variance of the self vehicle and the selected target vehicle in the longitudinal collision time;
s3, calculating the maximum value and the minimum value of the transverse distance between the self vehicle and the selected target vehicle during the collision time to obtain a predicted collision position interval;
and S4, determining whether the collision risk exists between the self vehicle and the target vehicle according to whether the probability of the predicted collision position in the predicted collision position interval is greater than a probability specified threshold value.
Optionally, the method for evaluating collision risk of oncoming vehicles is further improved, and the specified conditions include: the target vehicle is in front of the left lane and/or the right lane of the self-vehicle and has the opposite speed to the self-vehicle.
The target sensing process comprises the steps of judging the speed of a target, judging the category of the target and judging the lane to which the target belongs, and the functional requirements can be realized based on the existing environment sensing technology (environment sensing module).
Optionally, the method for evaluating collision risk of oncoming vehicles is further improved, and the collision time is calculated in the following manner;
in the opposite-direction vehicle target, firstly, longitudinal collision time is calculated, and the self vehicle and the target vehicle are assumed to uniformly accelerate:
according to a one-dimensional quadratic equation, the root formula can be obtained:
if the collision time is larger than the threshold value, no collision risk exists, otherwise, the time TTC of the self vehicle and the target vehicle is calculated long Predicted Impact Location of time (PIL);
Δ x is the longitudinal distance of the target vehicle relative to the own vehicle, Δ v x Is the longitudinal speed, Δ a, of the target vehicle relative to the own vehicle x The longitudinal acceleration of the target vehicle relative to the own vehicle is the required longitudinal collision time.
Optionally, the method for evaluating collision risk of oncoming vehicles is further improved, and the predicted collision position variance is calculated in the following manner;
pil＝Δy+Δvy*TTC long
Var pil ＝Jacobian*diag(Var x ，Var vx ，Var a ，Var y ，Var vy )*Jacobian T
Δ a is an acceleration of the target vehicle with respect to the host vehicle, Δ y is a lateral position of the target vehicle with respect to the host vehicle, and Δ v y Is the lateral velocity of the target vehicle relative to the host vehicle, pil is the time to collision TTC long Predicted collision position of (9), var x Is the measured variance of Δ x, var vx Is Δ v x Measured variance of (Var) a Is the measured variance of Δ a, var y Is the measured variance of Δ y, var vy Is Δ v y Measured variance of (Var) pil Is the variance of the predicted collision location, jacobian is the Jacobian matrix that predicts the collision location;
alternatively, the method for evaluating collision risk of oncoming vehicle may be further improved, the limit situations of collision between the host vehicle and the target vehicle are that the left side of the host vehicle collides with the left side of the target vehicle and the right side of the host vehicle collides with the right side of the target vehicle, and referring to fig. 2, the maximum value of the lateral distance between the host vehicle and the selected target vehicle is the collision time
Minimum value of
L o Is the transverse distance, R, from the center point of the front of the target vehicle to the leftmost side of the lane line o Is the lateral distance from the center point of the front part of the target vehicle to the rightmost side of the lane line, and W is the vehicle width.
Optionally, the method for evaluating the collision risk of the oncoming vehicle is further improved, and the collision risk of the own vehicle and the target vehicle is converted into the prediction of whether the collision position is in the section or not
Within the range;
when step S4 is performed, the mean value is pil and the variance is Var pil Normal distribution of N (pil, var) pil )；
Calculating a predicted collision position section
The integral area within expresses the probability of the predicted collision position within the predicted collision position interval;
and (4) judging that the own vehicle and the target vehicle have collision risks when the probability Prob is greater than the specified threshold value of the probability.
In order to solve the above technical problems, the present invention provides an oncoming vehicle collision risk assessment system for an emergency lane keeping system of a vehicle, wherein the following modules can be implemented based on existing hardware in combination with computer programming technology means, and the system comprises:
the screening module screens out target vehicles which meet specified conditions in all sensing modules;
a selection module that selects a target vehicle whose collision time is equal to or less than a time specified threshold;
a collision position prediction module which calculates a predicted collision position variance of the self vehicle and the selected target vehicle in the longitudinal collision time;
the transverse distance calculation module is used for calculating the maximum value and the minimum value of the transverse distance between the self vehicle and the selected target vehicle during collision time;
and the risk evaluation module calculates a predicted collision position interval and determines whether the collision risk exists between the self vehicle and the target vehicle according to whether the probability of the predicted collision position in the predicted collision position interval is greater than a probability specified threshold value.
Optionally, the system for assessing collision risk of oncoming vehicles is further improved, and the specified conditions include: the target vehicle is in front of the left lane and/or the right lane of the self-vehicle and has the opposite speed to the self-vehicle.
Optionally, the collision risk assessment system for the oncoming vehicle is further improved, and the collision time is calculated in the following manner;
Δ x is the longitudinal distance of the target vehicle relative to the own vehicle, Δ v x Is the longitudinal speed, Δ a, of the target vehicle relative to the own vehicle x Is the longitudinal acceleration of the target vehicle relative to the own vehicleDegree, TTC long Is the desired longitudinal collision time.
Optionally, the collision risk assessment system for oncoming vehicles is further improved, and the collision position prediction module calculates the collision position variance in the following manner;
pil＝Δy+Δv y *TTC long
Var pil ＝Jacobian*diag(Var x ，Var vx ，Var a ，Var y ，Var vy )*Jacobian T
Δ a is an acceleration of the target vehicle with respect to the host vehicle, Δ y is a lateral position of the target vehicle with respect to the host vehicle, and Δ v y Is the lateral velocity of the target vehicle relative to the host vehicle, pil is the time to collision TTC long Predicted collision position of (9), var x Is the measured variance of Δ x, var vx Is Δ v x Measured variance of (Var) a Is the measured variance of Δ a, var y Is the measured variance of Δ y, var vy Is Δ v y Measured variance of (Var) pil Is the variance of the predicted collision location, jacobian is the Jacobian matrix of the predicted collision location;
optionally, the collision risk assessment system for the oncoming vehicle is further improved, and the maximum value of the transverse distance between the self vehicle and the selected target vehicle during the collision time is
Minimum value of
L o Is the transverse distance, R, from the center point of the front of the target vehicle to the leftmost side of the lane line o Is the lateral distance from the center point of the front part of the target vehicle to the rightmost side of the lane line, and W is the vehicle width.
Optionally, the collision risk assessment system for the oncoming vehicle is further improvedThe mean value of the risk assessment module is pil, and the variance is Var pil Normal distribution of N (pil, var) pil )；
Calculating a predicted collision position section
The integral area within expresses the probability of the predicted collision position within the predicted collision position interval;
and (4) judging that the own vehicle and the target vehicle have collision risks when the probability Prob is greater than the specified threshold value of the probability.
According to the method, the uncertainty of environment perception is introduced as the judgment condition on the basis of taking the distance collision time as the judgment condition in the prior art, and the perception uncertainty is described by using the variance of the perception state, so that the accuracy of the collision risk assessment of oncoming vehicles is improved. A large amount of road test data show that the method solves the problem of accurate risk assessment under the condition of perception uncertainty and avoids misjudgment.
Drawings
The accompanying drawings, which are included to provide further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention. The drawings are not necessarily to scale, however, and may not be intended to accurately reflect the precise structural or performance characteristics of any given embodiment, and should not be construed as limiting or restricting the scope of values or properties encompassed by exemplary embodiments in accordance with the invention. The invention will be described in further detail with reference to the following detailed description and accompanying drawings:
FIG. 1 is a schematic flow diagram of the present invention.
Fig. 2 is a schematic view of an extreme collision position between the host vehicle and the target vehicle.
FIG. 3 is a schematic diagram of normal distribution computed collision probability.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and technical effects of the present invention will be fully apparent to those skilled in the art from the disclosure in the specification. The invention is capable of other embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the general concept of the invention. It should be noted that the features in the following embodiments and examples may be combined with each other without conflict. The following exemplary embodiments of the present invention may be embodied in many different forms and should not be construed as limited to the specific embodiments set forth herein. It is to be understood that these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the technical solutions of these exemplary embodiments to those skilled in the art.
A first embodiment;
referring to fig. 1, the present invention provides a collision risk assessment method for oncoming vehicles, which is used in a situation where a driver is unintentionally out of a lane and has a collision risk, and comprises the following steps:
s1, screening out target vehicles meeting specified conditions from all perception targets, namely the target vehicles are in front of a left lane and/or a right lane of a vehicle and the speed of the target vehicles is opposite to that of the vehicle;
s2, selecting a target vehicle with the collision time less than or equal to a time designated threshold, and calculating the predicted collision position variance of the self vehicle and the selected target vehicle in the longitudinal collision time;
s3, calculating the maximum value and the minimum value of the transverse distance between the self vehicle and the selected target vehicle during the collision time to obtain a predicted collision position interval;
and S4, determining whether the collision risk exists between the self vehicle and the target vehicle according to whether the probability of the predicted collision position in the predicted collision position interval is greater than a probability specified threshold value.
A second embodiment;
the invention provides an oncoming vehicle collision risk assessment method, which is further improved based on the first embodiment, and the same parts are not repeated; the following calculation methods are the most preferable calculation methods provided by the present invention, and should not be construed as limitations on the calculation methods;
the collision time is calculated in the following manner;
Δ x is the longitudinal distance of the target vehicle relative to the own vehicle, Δ v x Is the longitudinal speed, Δ a, of the target vehicle relative to the own vehicle x Is the longitudinal acceleration, TTC, of the target vehicle relative to the host vehicle long Is the longitudinal collision time to be solved;
the predicted collision location variance is calculated in the following manner;
pil＝Δy+Δv y *TTC long
Var pil ＝Jacobian*diag(Var x ，Var vx ，Var a ，Var y ，Var vy )*Jacobian T
Δ a is an acceleration of the target vehicle with respect to the host vehicle, Δ y is a lateral position of the target vehicle with respect to the host vehicle, and Δ v y Is the lateral velocity of the target vehicle relative to the host vehicle, pil is the time to collision TTC long Predicted collision position of (9), var x Is the measured variance of Δ x, V α r vx Is Δ v x Measured variance of (Var) a Is the measured variance of Δ a, var y Is the measured variance of Δ y, var vy Is Δ v y Measured variance of (3), var pil Is the variance of the predicted collision location, jacobian is the Jacobian matrix of the predicted collision location;
the maximum value of the transverse distance between the self vehicle and the selected target vehicle during the collision time is
Minimum value of
L o Is the transverse distance, R, from the center point of the front of the target vehicle to the leftmost side of the lane line o The transverse distance from the center point of the front part of the target vehicle to the rightmost side of the lane line, and W is the width of the vehicle;
referring to FIG. 3, the mean is constructed as pil with variance as Var pil Normal distribution of N (pil, var) pil )；
Calculating a predicted collision position section
The integral area within expresses the probability of the predicted collision position within the predicted collision position interval;
and (4) judging that the own vehicle and the target vehicle have collision risks when the probability Prob is greater than the specified threshold value of the probability.
A third embodiment;
the invention provides an oncoming vehicle collision risk assessment system, which is used for a vehicle emergency lane keeping system, and comprises:
the screening module screens out target vehicles which meet specified conditions in all the sensing targets sensed by the sensing modules;
a selection module that selects a target vehicle whose collision time is equal to or less than a time specified threshold;
a collision position prediction module which calculates a predicted collision position variance of the self vehicle and the selected target vehicle in the longitudinal collision time;
the transverse distance calculation module is used for calculating the maximum value and the minimum value of the transverse distance between the self vehicle and the selected target vehicle during collision time;
and the risk evaluation module calculates a predicted collision position interval and determines whether the collision risk exists between the self vehicle and the target vehicle according to whether the probability of the predicted collision position in the predicted collision position interval is greater than a probability specified threshold value.
A fourth embodiment;
the invention provides an oncoming vehicle collision risk assessment system, which is further improved based on the basis of the fourth embodiment, and the same parts are not repeated; the following calculation methods are the most preferable calculation methods provided by the present invention, and should not be construed as limiting the calculation methods;
the specified conditions include: the target vehicle is in front of the left lane and/or the right lane of the self-vehicle and has the opposite speed to the self-vehicle.
The collision time is calculated in the following manner;
Δ x is the longitudinal distance of the target vehicle relative to the own vehicle, Δ v x Is the longitudinal speed, Δ a, of the target vehicle relative to the own vehicle x Is the longitudinal acceleration, TTC, of the target vehicle relative to the own vehicle long Is the longitudinal collision time to be solved;
the collision position prediction module calculates a collision position variance in the following manner;
pil＝Δy+Δv y *TTC long
Var pil ＝Jacobian*diag(Var x ，Var vx ，Var a ，Var y ，Var vy )*Jacobian T
Δ a is an acceleration of the target vehicle with respect to the host vehicle, Δ y is a lateral position of the target vehicle with respect to the host vehicle, and Δ v y Is the lateral velocity of the target vehicle relative to the host vehicle, pil is the time to collision TTC long Predicted collision position of (9), var x Is the measured variance of Δ x, var vx Is Δ v x Measured variance of (Var) a Is the measured variance of Δ a, var y Is the measured variance of Δ y, var vy Is Δ v y Measured variance of (Var) pil Is the variance of the predicted collision location, jacobian is the Jacobian matrix of the predicted collision location;
the maximum value of the transverse distance between the self vehicle and the selected target vehicle during the collision time is
Minimum value of
L o Is the transverse distance, R, from the center point of the front of the target vehicle to the leftmost side of the lane line o Is the lateral distance from the center point of the front part of the target vehicle to the rightmost side of the lane line, and W is the vehicle width.
The risk assessment module constructs the mean value pil and the variance Var pil Normal distribution of N (pil, var) pil )；
Calculating a predicted collision position section
The integral area within expresses the probability of the predicted collision position within the predicted collision position interval;
and (4) judging that the own vehicle and the target vehicle have collision risks when the probability Prob is greater than the specified threshold value of the probability.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The present invention has been described in detail with reference to the specific embodiments and examples, but these are not to be construed as limiting the invention. Many variations and modifications may be made by one of ordinary skill in the art without departing from the principles of the present invention, which should also be considered as within the scope of the present invention.
Claims (12)
1. An oncoming vehicle collision risk assessment method for an operating condition in which a driver is unintentionally out of a lane and there is a collision risk, comprising the steps of:
s1, screening out target vehicles meeting specified conditions from all perception targets;
s2, selecting a target vehicle with the collision time less than or equal to a time designated threshold, and calculating the predicted collision position variance of the self vehicle and the selected target vehicle in the longitudinal collision time;
s3, calculating the maximum value and the minimum value of the transverse distance between the self vehicle and the selected target vehicle during the collision time to obtain a predicted collision position interval;
and S4, determining whether the collision risk exists between the self vehicle and the target vehicle according to whether the probability of the predicted collision position in the predicted collision position interval is greater than a probability specified threshold value.
2. The oncoming vehicle collision risk assessment method according to claim 1, wherein the specified conditions include: the target vehicle is in front of the left lane and/or the right lane of the self-vehicle and has the opposite speed to the self-vehicle.
3. The oncoming vehicle collision risk assessment method according to claim 1, wherein the collision time is calculated in the following manner;
Δ x is the longitudinal distance of the target vehicle relative to the own vehicle, Δ v x Is the longitudinal speed, Δ a, of the target vehicle relative to the own vehicle x Is the longitudinal acceleration, TTC, of the target vehicle relative to the host vehicle long Is the desired longitudinal collision time.
4. The oncoming vehicle collision risk assessment method according to claim 3, wherein the predicted collision location variance is calculated in the following manner;
pil＝Δy+Δv y *TTC long
Var pil ＝Jacobian*diag(Var x ，Var vx ，Var a ，Var y ，Var vy )*Jacobian T
Δ a is the acceleration of the target vehicle relative to the host vehicle, Δ y is the lateral position of the target vehicle relative to the host vehicle, Δ v y Is the lateral velocity of the target vehicle relative to the host vehicle, pil is the time to collision TTC long Predicted collision position of (9), var x Is the measured variance of Δ x, var vx Is Δ v x Measured variance of (Var) a Is the measured variance of Δ a, var y Is the measured variance of Δ y, var vy Is Δ v y Measured variance of (Var) pil Is the variance of the predicted collision location and Jacobian is the Jacobian matrix of the predicted collision location.
5. The oncoming vehicle collision risk assessment method according to claim 4, characterized in that:
the maximum value of the transverse distance between the self vehicle and the selected target vehicle is
Minimum value of
L o Is the transverse distance, R, from the center point of the front of the target vehicle to the leftmost side of the lane line o Is the lateral distance from the center point of the front part of the target vehicle to the rightmost side of the lane line, and W is the vehicle width.
6. The oncoming vehicle collision risk assessment method according to claim 5, characterized in that:
when step S4 is performed, the mean value is pil and the variance is Var pil Normal distribution of N (pil, var) pil )；
Calculating a predicted collision position section
The integral area within expresses the probability of the predicted collision position within the predicted collision position interval;
and (4) judging that the own vehicle and the target vehicle have collision risks when the probability Prob is greater than the specified threshold value of the probability.
7. An oncoming vehicle collision risk assessment system for a vehicle emergency lane keeping system, comprising:
the screening module screens out target vehicles which meet specified conditions in all sensing modules;
a selection module that selects a target vehicle whose collision time is equal to or less than a time specified threshold;
a collision position prediction module which calculates a predicted collision position variance of the own vehicle and the selected target vehicle in the longitudinal collision time;
the transverse distance calculation module is used for calculating the maximum value and the minimum value of the transverse distance between the self vehicle and the selected target vehicle during collision time;
and the risk evaluation module calculates a predicted collision position interval and determines whether the collision risk exists between the self vehicle and the target vehicle according to whether the probability of the predicted collision position in the predicted collision position interval is greater than a probability specified threshold value.
8. The oncoming vehicle collision risk assessment system according to claim 7, wherein the specified conditions include: the target vehicle is in front of the left lane and/or the right lane of the self-vehicle and has the opposite speed to the self-vehicle.
9. The oncoming vehicle collision risk assessment system according to claim 7, wherein the collision time is calculated in the following manner;
Δ x is the longitudinal distance of the target vehicle relative to the own vehicle, Δ v x Is the longitudinal direction of the target vehicle relative to the self vehicleSpeed, Δ a x Is the longitudinal acceleration, TTC, of the target vehicle relative to the host vehicle long Is the desired longitudinal collision time.
10. The oncoming vehicle collision risk assessment system according to claim 9, wherein the collision location prediction module calculates a collision location variance in the following manner;
pil＝Δy+Δv y *TTC long
Var pil ＝Jacobian*diag(Var x ，Var vx ，Var a ，Var y ，Var vy )*Jacobian T
Δ a is an acceleration of the target vehicle with respect to the host vehicle, Δ y is a lateral position of the target vehicle with respect to the host vehicle, and Δ v y Is the lateral velocity of the target vehicle relative to the host vehicle, pil is the time to collision TTC long Predicted collision position of (3), var x Is the measured variance of Δ x, var vx Is Δ v x Measured variance of (3), var a Is the measured variance of Δ a, var y Is the measured variance of Δ y, var vy Is Δ v y Measured variance of (Var) pil Is the variance of the predicted collision location and Jacobian is the Jacobian matrix of the predicted collision location.
11. The oncoming vehicle collision risk assessment system according to claim 10, characterized in that: the maximum value of the transverse distance between the self vehicle and the selected target vehicle during the collision time is
Minimum value of
L o Is the transverse distance, R, from the center point of the front of the target vehicle to the leftmost side of the lane line o Is the lateral distance from the center point of the front part of the target vehicle to the rightmost side of the lane line, and W is the vehicle width.
12. The oncoming vehicle collision risk assessment system according to claim 11, characterized in that:
the risk assessment module constructs the mean value pil and the variance Var pil Normal distribution of N (pil, var) pil )；
Calculating a predicted collision position section
The integral area within expresses the probability of the predicted collision position within the predicted collision position interval;
and (4) judging that the own vehicle and the target vehicle have collision risks when the probability Prob is greater than the specified threshold value of the probability.
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