CN115712950A - Automatic driving decision-making method for semi-trailer - Google Patents
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Abstract
The invention discloses an automatic driving decision method for a semi-trailer vehicle, which comprises the following steps: acquiring the current motion state of the semi-trailer vehicle, and predicting all motion state spaces of the semi-trailer vehicle based on the dynamic characteristics of the semi-trailer vehicle and the current motion state; narrowing the range of the entire motion state space based on surrounding traffic environment information; calculating the running performance of the semi-trailer vehicle; a future movement state is preferred in the overall movement state space as a future travel target for the semi-trailer vehicle on the basis of the travel performance. The method is used for modeling the semi-trailer in motion prediction, motion stability analysis and driving performance analysis, so that the applicability of the strategy model to the semi-trailer is ensured, discontinuity of multi-target decision results is effectively avoided by reducing the target motion state space layer by layer, and meanwhile, the dependence on the hardware system performance is reduced by adopting a multi-level double-index optimization method.
Description
Technical Field
The invention belongs to the technical field of automatic control of automobiles, and particularly relates to an automatic driving decision method for a semi-trailer automobile.
Background
One of the important directions for the development of the automobile industry is intellectualization, and the industry generally thinks that the automatic driving of commercial vehicles will take the lead to the landing. With the continuous progress of unmanned driving technology, the commercialization of the auxiliary driving technology for basic scenes of the single passenger vehicle has been successful, and due to the more complex motion process and the low driving stability of the trailer type commercial vehicle, the automatic driving technology still needs to explore and overcome some difficult problems. The comprehensive decision of the direction and the speed of the trailer with consideration of the driving stability is one of the difficult problems of the current automatic driving of the trailer.
Regarding decision and control of the unmanned vehicle, the invention patent with the application number of 201110007154.X provides a device and a method for planning a local path of the unmanned vehicle, and the invention refers to a method of a mechanical field diagram to determine a future selectable driving track. The method uniformly considers traffic rules, static objects, dynamic objects and abstract events, improves the complexity of problems and is difficult to obtain a more ideal decision effect.
The invention patent with the application number of 201410221906.6 describes an unmanned automobile control system with social behavior interaction, and the unmanned automobile control system adopts a hidden Markov model to judge the driving intentions of other vehicles and carries out the optimal trajectory decision of the vehicle on the basis. The method needs to establish a hidden Markov model for each adjacent traffic vehicle, and because the adjacent vehicles are difficult to track for a long time in practice, the accuracy of the established model is difficult to ensure.
The invention patent with the application number of 201810007699.2 describes a decision-making system and a decision-making method for unmanned automobile driving tasks, and the decision-making system and the decision-making method for unmanned automobile driving tasks are added to judge the regularity of all tasks in a driving task set and remove driving tasks which are not in accordance with traffic rules, are unsafe and do not conform to the direction of navigation guidance in the driving tasks so as to ensure the safety, legality and high efficiency of vehicle driving. The proposed method does not make a targeted design for large multi-body commercial vehicles, and is only suitable for small single vehicles, i.e. passenger cars.
Disclosure of Invention
The present invention is directed to an automatic driving decision method for a semi-trailer vehicle, which solves the above-mentioned problems of the prior art.
In order to achieve the above object, the present invention provides an automatic driving decision method for a semi-trailer vehicle, comprising:
acquiring the current motion state of a semi-trailer vehicle, and predicting all motion state spaces of the semi-trailer vehicle based on the dynamic characteristics of the semi-trailer vehicle and the current motion state;
narrowing the range of the entire motion state space based on surrounding traffic environment information;
calculating the running performance of the semi-trailer vehicle;
a future movement state is preferred in the overall movement state space as a future travel target for the semi-trailer vehicle on the basis of the travel performance.
Optionally, the process of predicting the total motion state space of the semi-trailer vehicle based on the dynamic characteristics of the semi-trailer vehicle and the current motion state comprises:
analyzing a yaw angular speed change range based on a wheel base and a wheel base of the semi-trailer vehicle, and analyzing an acceleration change range based on a power specification of the semi-trailer vehicle;
analyzing the change range of the yaw velocity and the acceleration of the semi-trailer at the next moment based on the current motion state;
and uniformly discretizing the change range of the yaw velocity and the acceleration of the semi-trailer at the next moment, carrying out orthogonal combination on each yaw velocity and each acceleration to obtain a future motion state, and obtaining a whole motion state space based on the future motion state.
Optionally, the process of predicting the total motion state space of the semi-trailer vehicle based on the dynamic characteristics of the semi-trailer vehicle and the current motion state further comprises:
constructing a kinematics model based on the longitudinal acceleration and the yaw angular velocity of the semi-trailer vehicle, and acquiring the motion state of the semi-trailer vehicle based on the kinematics model;
obtaining a future motion state based on the result of the motion state and orthogonal combination, and performing motion failure analysis on the semi-trailer based on the future motion state;
and eliminating future motion states in the overall motion state space which can cause motion failure based on the result of the motion failure analysis.
Optionally, the process of performing a motion failure analysis of the semi-trailer vehicle based on the future motion state comprises:
calculating the transverse load transfer rate of the trailer and the trailer based on the distance between the mass center of the trailer and the trailer shaft and the fifth wheel, the wheel tread, the distance to the roll axis, the trailer spring load mass, the total mass of the trailer, the lateral acceleration and the vehicle body roll angle; judging whether the semi-trailer vehicle is about to turn over or not based on the motion characteristics of the semi-trailer vehicle and the transverse load transfer rate, and acquiring a rollover analysis result;
analyzing the drift and folding problems of the semi-trailer vehicle based on the yaw velocity of the trailer and the yaw velocity of the trailer to obtain a drift folding analysis result;
and obtaining a result of the movement failure analysis based on the rollover analysis result and the swing folding analysis result.
Optionally, the process of narrowing down the range of the entire motion state space based on the surrounding traffic environment information includes:
based on the position and the speed of the vehicle, acquiring the position and the line type of the lane marking, the states of a speed limit sign and a traffic light by adopting environmental perception, and analyzing the illegal problem of the semi-trailer vehicle;
based on the motion state of the vehicle, the environment perception is adopted to obtain the motion states of road boundaries and other traffic participants, and the risk problem of semi-trailer vehicles is analyzed.
Optionally, the process of acquiring the road boundary and the motion state of other traffic participants by using environment perception comprises:
connecting the prediction results of a plurality of adjacent frames of the trailer and the trailer through a polygon to form a vehicle track envelope, acquiring a road boundary based on the vehicle track envelope, and analyzing the vehicle exceeding the road boundary based on the road boundary;
and carrying out circumscribed circle rough collision detection based on the vehicle-shaped circumscribed circle of the semi-trailer vehicle, acquiring the motion states of other traffic participants, and analyzing vehicle collision.
Optionally, the driving performance of the semi-trailer vehicle comprises following performance and driving efficiency, the following performance comprises position following performance and direction following performance, and the driving efficiency comprises efficiency and comfort.
Optionally, the process of calculating the driving performance of the semi-trailer comprises:
acquiring the position following performance based on the distance from the center of mass position corresponding to the tail state of the trailer and the trailer motion track to the recommended path;
acquiring the direction following performance based on the included angle between the direction corresponding to the last state of the motion track of the trailer and the recommended path;
acquiring the effectiveness based on the longitudinal speed of the tail state of the motion trail of the trailer, the recommended vehicle speed, the maximum longitudinal speed and the minimum longitudinal speed;
the comfort is obtained based on the maximum values of the longitudinal acceleration and the yaw velocity of the preview of the trailer, the longitudinal acceleration and the yaw velocity of the trailer at the current moment, and the longitudinal acceleration and the yaw velocity of the preview of the trailer.
Optionally, the process of optimizing a future moving state in the total moving state space as a future moving target of the semi-trailer based on the traveling performance comprises:
binary optimization of position following property, direction following property, efficacy and comfort is respectively carried out by adopting a layered two-item optimization method;
combining binary optimization results of position following performance and direction following performance into optimal path following performance, and combining binary optimization results of efficacy and comfort into optimal driving efficiency;
optimizing and combining the optimal path following performance and the optimal running efficiency binary value into optimal performance, and determining a future running target of the semi-trailer based on the optimal performance
The invention has the technical effects that:
1. the method is used for modeling the semi-trailer in motion prediction, motion stability analysis and driving performance analysis, and ensures the applicability of the strategy model to the semi-trailer.
2. The invention adopts a method of reducing the motion state space of the target layer by layer and finally carrying out the optimal decision-making, thereby effectively avoiding the discontinuity of multi-target decision-making results and ensuring the stable running of the vehicle.
3. The invention adopts a multilevel double-index optimization method in the performance analysis optimization: firstly, only one weight is determined in each optimization, so that the technical problem that the weights are difficult to determine in multi-index simultaneous optimization is solved; and secondly, the optimization method of each layer is the same, the purchase and reuse rate is improved, and the dependency of the operation of the method on the performance of a hardware system is reduced.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the application and, together with the description, serve to explain the application and are not intended to limit the application. In the drawings:
FIG. 1 is a flow chart of an automated driving decision method for a semi-trailer vehicle in an embodiment of the present invention;
FIG. 2 is a diagram of a kinematic model of a semi-trailer vehicle in an embodiment of the present invention;
FIG. 3 is a graph illustrating the predicted effect of semi-trailer motion in an embodiment of the present invention;
FIG. 4 is a schematic diagram illustrating a validity determination of an expected travel area according to an embodiment of the present invention;
FIG. 5 is a schematic illustration of a plurality of trailer trajectory envelopes formed by polygon joining in an embodiment of the present invention;
FIG. 6 is a schematic diagram of a rough collision detection of a vehicle-shaped circumcircle in an embodiment of the invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
Example one
As shown in fig. 2 to 6, the present embodiment provides an automatic driving decision method for a semi-trailer vehicle, which includes the following steps:
step one, reachable space analysis: and analyzing all motion state spaces which can be realized by the vehicle in the next decision period, namely the reachable space, according to the dynamic characteristics of the controlled vehicle and the current motion state.
Step two, analysis of a driving space: according to the surrounding traffic environment information, the motion state causing the vehicle to enter the non-driving area is eliminated on the basis of the reachable space, and the motion state space is further reduced.
Step three, analyzing the driving performance: and comprehensively considering the vehicle running performance, preferably deciding a certain motion state in the motion state space, taking the motion state as a future running target of the vehicle, and outputting the motion state from a decision strategy.
In order to realize future driving target decision, the model needs to obtain a macro path and speed distribution scheme planned based on a destination point and arrival time before execution.
In order to realize future driving target decision, in step one, firstly, mobility analysis is carried out, and the method comprises the following steps: firstly, analyzing the change range of the yaw angular velocity according to the wheel base and the wheel base of the vehicle, and analyzing the change range of the acceleration according to the power specification of the vehicle; secondly, analyzing the possible change range of the yaw rate and the acceleration of the vehicle in the next decision period based on the current vehicle motion state; finally, the variation range is evenly discretized, and each yaw rate and each acceleration are orthogonally combined to be used as a motion state of the vehicle, so that an initial motion state space is formed.
In order to realize future driving objective decision, in step one, on the basis of the initial motion state space, motion states which may cause vehicle motion failure (such as rollover, tail flicking and folding) need to be excluded, and the method comprises the following steps:
first, a kinematic model (fig. 2) of the vehicle (semi-trailer) is created, as shown by the following equation, with the input of the model being the longitudinal acceleration a of the trailer h And yaw angular velocity ω h And the output is the hinge point position x of the trailer and the trailer h ,y h Speed v of trailer h Course angle of trailer
Central point x of trailer rear axle t ,y t Course angle of trailer
Collectively referred to as vehicle motion states
Secondly, each acceleration and yaw rate combination in the initial motion state space is substituted into the formula, and the future vehicle motion state is calculated
Referring to fig. 3, and performing the vehicle motion failure analysis according to the calculation result, the method is as follows:
for vehicle rollover problem analysis, the lateral load transfer rate R of the trailer and the trailer is calculated as follows 1 And R 2 If R is determined according to the motion characteristics of the semi-trailer 1 > 0.6 or R 2 If the vehicle speed is more than 0.7, the vehicle is judged to be in rollover failure. Wherein d and e are the distances between the center of mass of the trailer and the trailer axle and the fifth wheel respectivelyAnd g is gravity acceleration. T is 1 And T 2 The track width of the trailer and the trailer, respectively. h is 1 And h 2 The trailer and the trailer's distance to the roll axis, respectively. m is 1s Is the sprung mass of the trailer, m 2 Is the total mass of the trailer. a is ym1 And a ym2 For lateral accelerations of the trailer and the trailer respectively,
and
the roll angle of the trailer and the body of the trailer is shown.
For the analysis of the vehicle drift and folding problems, the drift can be regarded as the trailer slipping outward with respect to the steering center, and the folding can be regarded as the trailer slipping inward with respect to the steering center, so that both are analyzed by the following formula. Wherein
Is a constraint on the absolute value of the articulation angle. Limiting the articulation angle between the trailer and the trailer indirectly prevents mechanical collisions between the two structural units during movement.
Is the yaw rate of the trailer,
is the yaw rate of the trailer,
is a constraint on the absolute value of the yaw rate of the articulation angle. Twin mopLimiting the difference in articulation angular velocities between the vehicle and the trailer reduces the probability of saturation of the lateral forces on the axles of the trailer or the tires of the trailer, thereby reducing the likelihood of collapse and whiplash instability.
Finally, the spatial positions x corresponding to all motion states in the motion state space after the motion state possibly causing the failure is eliminated h ,y h ,x t ,y t And aggregating as reachable space.
In order to realize future driving objective decision, in the second step, for each position point in the reachable space, the illegal and illegal judgment needs to be carried out and eliminated at the same time, so as to form a feasible space, thereby ensuring that the vehicle can safely and legally drive. The method comprises the following steps:
aiming at the analysis of the vehicle illegal problems, the main illegal forms are lane crossing illegal and overspeed illegal, and the lane marking position and line type, speed limit signs and traffic light states obtained by sensing the position and speed of the vehicle and the environment are respectively compared and determined. It is characterized in that: the lane markings are described in the form of the following polynomial, and the host vehicle is described using double rectangular bounding boxes to reduce the amount of computation. The validity judgment is shown in fig. 4.
y＝A 3 x 3 +A 2 x 2 +A 1 x+A 0
Aiming at the analysis of the vehicle danger problem, two danger forms of exceeding a road boundary and colliding with other traffic participants are mainly adopted, and the road boundary and the motion states of the other traffic participants obtained through the motion state of the vehicle and the environmental perception are respectively compared and determined. In order to further ensure the safety, the road boundary and the motion state of other traffic participants are analyzed after being multiplied by a safety factor. It is characterized in that: in order to further reduce the calculated amount, the predicted results of a plurality of adjacent frames of the trailer and the trailer are connected through a polygon to form a vehicle track envelope, namely, the whole vehicle track consists of a plurality of sections of track envelopes, and road boundary crossing analysis is carried out as shown in figure 5; the rough collision detection is carried out through the vehicle shape circumscribed circle, the circumscribed circle rough collision detection firstly respectively takes the front left and right corners of the tail frame vehicle and the rear left and right corners of the head frame vehicle from the envelope of the two vehicle tracks needing to be calculated to form a rectangle, as the rectangle is long and narrow, the rectangle needs to be surrounded by a plurality of circles, as shown in figure 6, then the sum of the distance of the circle center and the corresponding radius is respectively calculated, if the former is larger than the latter, the track envelope does not collide in the period of time, otherwise, the collision occurs.
In the third step, all the positions in the feasible space are evaluated according to the following indexes, and the optimal value is selected as a target position-motion state. The first level index is following performance and driving efficiency:
the following performance includes two sub-performances, which are respectively position following performance and direction following performance:
the position followability embodies the degree of position coincidence of the estimated position-motion state with the pre-planned macro path:
in the formula (d) h,ep Distance of the center of mass position of the trailer vehicle corresponding to the end-of-track state to the recommended path, d t,ep And the distance from the center of mass position of the trailer vehicle corresponding to the tail state of the track to the recommended path. min and max represent taking the maximum and minimum values, respectively.
The direction followability embodies the degree of conformity of the estimated position-motion state with the tangential direction of the pre-planned macroscopic path:
in the formula, theta h Is the angle theta between the trailer vehicle direction corresponding to the end-of-track condition and the recommended path t The included angle between the direction of the trailer vehicle corresponding to the end state of the track and the recommended path is shown. min and max represent taking the maximum and minimum values, respectively.
The driving efficiency includes two sub-properties, respectively efficacy and comfort:
the efficacy embodies how fast the estimated position-motion state enables the driving task to be completed, and mainly considers the balance capability between the expected vehicle speed and the road speed limit:
in the formula u p Longitudinal speed of trailer, u, corresponding to end-of-track condition ep To recommend a vehicle speed, u p,max ，u p,min Respectively representing the maximum and minimum longitudinal speed of the trailer in the track cluster end state.
The comfort level represents the physical and psychological comfort level of people in the vehicle caused by the estimated position-motion state, and mainly takes the ratio of the acceleration of the vehicle to the variation of the yaw angular velocity to the human bearing capacity into consideration.
In the formula, J h,lon For the evaluation index of longitudinal comfort, a x,p For pre-aiming longitudinal acceleration of the trailer, a x Longitudinal acceleration of the trailer at the present moment, a x,pmax The maximum value of the longitudinal acceleration of the trailer is predicted; j. the design is a square h,lat As an index for evaluating the lateral comfort hp For pre-aiming the trailer yaw rate, r h Yaw rate, r, of the trailer at the present moment h,pmax The maximum value of the predicted yaw rate of the trailer is obtained.
Adopting a layering two-item optimization method, and carrying out optimization layer by layer: the first layer is used for respectively carrying out binary optimization of position following property, direction following property, efficacy and comfort; the second layer is used for merging the position and speed following binary optimization into optimal path following performance and merging the efficacy and comfort binary optimization into optimal driving efficiency; and in the third layer, the path following performance and the driving efficiency binary value are optimized and combined into the optimal performance, and finally, the future driving target is preferably determined. The binary optimization method is characterized in that: only one weight is determined by each binary comparison, so that the condition that multiple weights are determined simultaneously without method support is avoided; and the same method is adopted for optimizing multiple layers, so that the stability of the method is ensured, the code reuse rate is improved, and the dependence on hardware calculation and storage units is reduced. The binary optimization method is shown as the following formula, X * And (3) outputting a final output result for the model, wherein the final output result is used for guiding a vehicle motion control unit to work so as to realize an automatic driving function:
x * ＝argmin(J)＝argmin[λ·J 1 +(1-λ)·J 2 ]
the model adopts the strategy of reducing the target motion state space layer by layer through reachable space analysis and travelable space analysis, and finally optimizing and deciding the future motion state through travel performance analysis, thereby realizing the motion decision function in the automatic driving system. The motion prediction is more accurate by introducing a semi-trailer kinematic model, and the motion stability is ensured by analyzing typical motion failure modes of the semi-trailer, such as rollover, drift, folding and the like. The behaviors of the trailer and the trailer are considered simultaneously in the performance analysis, the following performance and the running efficiency are comprehensively evaluated, and the automobile is reasonably driven while the macro planning target is achieved.
Example two
As shown in fig. 1, an example of an application of the automatic driving decision method for a semi-trailer vehicle is provided in this embodiment, and includes:
Step 1, analyzing original maneuverability: and analyzing the appropriate acceleration, deceleration and yaw rate change range of the vehicle based on the wheel track, the wheel base and the power specification of the vehicle.
Step 2, analyzing the current maneuvering capacity: and analyzing the variation range of the addition, deceleration and yaw rate which are possible in one control period in the future based on the current vehicle motion state fed back in real time 0, performing equally-spaced dispersion on the variation range, and orthogonally combining each addition/deceleration and yaw rate to form an original motion state space.
And 3, establishing a semi-trailer vehicle kinematic model, predicting the future track and posture of each group of motion states in the original motion state space, respectively judging the motion failure modes of side turning, tail flicking, folding and the like, and eliminating the motion states which possibly cause failure to form an reachable space.
And 4, respectively carrying out illegal judgment and danger judgment on each group of motion states in the reachable space, wherein the illegal judgment comprises the violation of the lane marking caused by the position and the overspeed violation caused by the speed, and the danger comprises the danger of exceeding the physical boundary of the road and the collision danger with other traffic participants, and eliminating the motion states which possibly cause the violation and the danger, thereby reducing the reachable space and forming the reachable space.
And 5, respectively evaluating the driving performance of each group of motion states in the drivable space, wherein the evaluation is carried out in three levels: the first level is respectively carried out the position evaluation of the proximity degree of the trailer and the trailer position and the macroscopic path, the direction evaluation of the tangential consistency degree of the trailer and the trailer course and the macroscopic path, the comprehensive efficacy evaluation of the consistency of the speed and the expected speed and the consistency of the speed and the regulation speed limit, and the comfort evaluation of the consistency of the acceleration and the yaw angular speed and the bearing capacity of drivers and passengers; the second level carries out the following performance evaluation of comprehensive position and direction, and the driving efficiency evaluation of comprehensive efficacy and comfort; the third level is the running performance evaluation of the comprehensive following performance and running efficiency.
And 6, selecting the optimal motion state and the corresponding position and posture thereof as the target motion state output by comparing the driving performance of each group of motion states in the drivable space, and finishing the work of the decision model.
The above description is only for the preferred embodiment of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (9)
1. An automatic driving decision method for a semi-trailer vehicle, comprising the steps of:
acquiring the current motion state of a semi-trailer vehicle, and predicting all motion state spaces of the semi-trailer vehicle based on the dynamic characteristics of the semi-trailer vehicle and the current motion state;
narrowing the range of the entire motion state space based on surrounding traffic environment information;
calculating the running performance of the semi-trailer vehicle;
a future movement state is preferred in the overall movement state space as a future travel target for the semi-trailer vehicle on the basis of the travel performance.
2. The automated driving decision method for a semi-trailer vehicle of claim 1, wherein predicting the overall motion state space of the semi-trailer vehicle based on the dynamics of the semi-trailer vehicle and the current motion state comprises:
analyzing a yaw angular speed change range based on the wheel base and the wheel base of the semi-trailer vehicle, and analyzing an acceleration change range based on the power specification of the semi-trailer vehicle;
analyzing the change range of the yaw velocity and the acceleration of the semi-trailer at the next moment based on the current motion state;
and carrying out uniform discretization on the change range of the yaw velocity and the acceleration of the semi-trailer at the next moment, carrying out orthogonal combination on each yaw velocity and each acceleration to obtain a future motion state, and obtaining all motion state spaces based on the future motion states.
3. The automated driving decision method for a semi-trailer vehicle of claim 2, wherein predicting the overall motion state space of the semi-trailer vehicle based on the dynamics of the semi-trailer vehicle and the current motion state further comprises:
constructing a kinematics model based on the longitudinal acceleration and the yaw angular velocity of the semi-trailer vehicle, and acquiring the motion state of the semi-trailer vehicle based on the kinematics model;
obtaining a future motion state based on the result of the motion state and orthogonal combination, and performing motion failure analysis on the semi-trailer based on the future motion state;
and eliminating future motion states in the overall motion state space which can cause motion failure based on the result of the motion failure analysis.
4. The automated driving decision method for a semi-trailer vehicle of claim 3, wherein the process of performing a kinematic failure analysis of the semi-trailer vehicle based on the future kinematic state comprises:
calculating the transverse load transfer rate of the trailer and the trailer based on the distance between the center of mass of the trailer and the trailer shaft and the fifth wheel, the wheel tread, the distance to a roll axis, the trailer spring load mass, the total mass of the trailer, the lateral acceleration and the vehicle body roll angle; judging whether the semi-trailer vehicle is about to turn over or not based on the motion characteristics of the semi-trailer vehicle and the transverse load transfer rate, and acquiring a rollover analysis result;
analyzing the drift and folding problems of the semi-trailer vehicle based on the yaw velocity of the trailer and the yaw velocity of the trailer to obtain a drift folding analysis result;
and obtaining a result of the movement failure analysis based on the rollover analysis result and the swing folding analysis result.
5. The automated driving decision method for a semi-trailer according to claim 1, wherein narrowing the entire motion state space based on ambient traffic environment information comprises:
based on the position and the speed of the vehicle, acquiring the position and the line type of a lane marking, the states of a speed limit sign and a traffic light by adopting environmental perception, and analyzing the illegal problem of the semi-trailer;
based on the motion state of the vehicle, the environment perception is adopted to obtain the motion states of road boundaries and other traffic participants, and the risk problem of semi-trailer vehicles is analyzed.
6. The automated driving decision method for semi-trailer vehicles according to claim 5, wherein the process of obtaining road boundaries and other traffic participant motion states using environmental awareness comprises:
connecting the prediction results of a plurality of adjacent frames of the trailer and the trailer through a polygon to form a vehicle track envelope, acquiring a road boundary based on the vehicle track envelope, and analyzing the vehicle exceeding the road boundary based on the road boundary;
and carrying out circumscribed circle rough collision detection based on the vehicle-shaped circumscribed circle of the semi-trailer vehicle, acquiring the motion states of other traffic participants, and analyzing vehicle collision.
7. The automated driving decision method for a semi-trailer vehicle of claim 1, wherein the driving performance of the semi-trailer vehicle comprises following performance and driving efficiency, the following performance comprises position following performance and direction following performance, and the driving efficiency comprises efficiency and comfort.
8. The automated driving decision method for semi-trailer vehicles of claim 7, wherein calculating the driving performance of the semi-trailer vehicle comprises:
acquiring the position following performance based on the distance from the center of mass position corresponding to the tail state of the trailer and the trailer motion track to the recommended path;
acquiring the direction following performance based on an included angle between the direction corresponding to the end state of the motion track of the trailer and the recommended path;
acquiring the effectiveness based on the longitudinal speed of the tail state of the motion trail of the trailer, the recommended vehicle speed, the maximum longitudinal speed and the minimum longitudinal speed;
the comfort is obtained based on the maximum values of the longitudinal acceleration and the yaw velocity of the preview of the trailer, the longitudinal acceleration and the yaw velocity of the trailer at the current moment, and the longitudinal acceleration and the yaw velocity of the preview of the trailer.
9. The automated driving decision method for a semi-trailer according to claim 1, wherein the process of preferring a future moving state in the total moving state space as a future driving target of the semi-trailer based on the driving performance comprises:
binary optimization of position following property, direction following property, efficacy and comfort is respectively carried out by adopting a layered two-item optimization method;
combining binary optimization results of position following performance and direction following performance into optimal path following performance, and combining binary optimization results of efficacy and comfort into optimal driving efficiency;
and optimizing and combining the optimal path following performance and the optimal running efficiency binary value into optimal performance, and determining a future running target of the semi-trailer based on the optimal performance.
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