CN117970933B - Vehicle self-positioning correction method used in low-speed parking straight driving scene - Google Patents
Vehicle self-positioning correction method used in low-speed parking straight driving scene Download PDFInfo
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Abstract
The invention provides a vehicle self-positioning correction method used in a low-speed parking straight driving scene, which can improve the parking positioning precision based on lower cost. Firstly judging whether the vehicle to be parked is in a low-speed running state and spans the scene of an obstacle, if the vehicle to be parked is in the low-speed running state and spans road protrusions such as a deceleration strip, replacing the wheel speed pulse increment of the wheel running on the plane road section with the wheel speed pulse increment of the wheel to be observed, avoiding unnecessary wheel speed pulse increment caused by the road section protrusion, and further achieving the purpose of plane positioning correction.
Description
Technical Field
The invention relates to the technical field of intelligent parking systems, in particular to a vehicle self-positioning correction method used in a low-speed parking straight-line driving scene.
Background
In an intelligent parking system, comprising: sensing, positioning, planning, controlling and other main functions. The vehicle positioning algorithm is one of the core algorithms of the intelligent parking function. And (3) obtaining positioning information of the vehicle based on a vehicle positioning algorithm, feeding back the positioning information to perception for obstacle tracking and obstacle positioning, feeding back the positioning information to a planning layer for path planning and dynamic adjustment, feeding back the positioning information to a control layer for path offset correction and track tracking control.
Because the parking location is calculated based on a two-dimensional plane, the position coordinates X, Y of the object (vehicle, obstacle or parking space, etc.) and the angle between the object and the X-axis under the two-dimensional plane coordinate system are output in real time, and most of the current location algorithms calculate the driving distance according to the wheel speed pulse, and the algorithm is simple and practical. The method comprises the following steps:
single wheel travel distance = unit wheel speed pulse distance x wheel speed pulse change value,
Vehicle travel distance = average of 4 wheel travel distances.
The pulse distance of the unit wheel speed is the driving distance of the wheel corresponding to each pulse output by the wheel speed sensor.
However, when the vehicle passes through a road section with a bulge, such as a deceleration strip, the driving distance is increased due to the three-dimensional road surface factors of the bulge, but the plane relative position is unchanged. In the scenario shown in fig. 1, after the vehicle 1 enters the parking lot, the vehicle travels at a lower speed (1-5 km/h) into the automatic parking process after the automatic parking system takes over control of the vehicle. When the vehicle 1 passes through the speed reducing zone 2, the front wheel 1-1 and the rear wheel 1-2 need to sequentially travel over the speed reducing zone 2, and compared with the running on a flat road, the wheel speed pulse change values of the front wheel 1-1 and the rear wheel 1-2 are increased, and compared with the complete plane running distance, the actual running distance of the vehicle is increased.
In the existing method for calculating the vehicle running distance based on the two-dimensional plane to perform positioning calculation, the parking positioning only considers the position output under the two-dimensional plane coordinate system, and the three-dimensional space change of the road surface caused by the convex objects actually causes the vehicle running distance to be longer because the plane distance is unchanged, so that the positioning precision of the vehicle on the two-dimensional plane is affected, and in order to improve the positioning precision, the sensors are added to assist in measurement in the prior art, but the cost of the intelligent parking system is increased.
Disclosure of Invention
In order to solve the problem of insufficient calculation accuracy of the existing parking positioning in a low-speed parking straight-line driving scene, the invention provides a vehicle self-positioning correction method for the low-speed parking straight-line driving scene, which can improve the parking positioning accuracy based on lower cost.
The technical scheme of the invention is as follows: a vehicle self-positioning correction method for a low-speed parking straight driving scene, comprising the following steps:
S1: the intelligent parking system is started to control the parking process of the vehicle to be parked;
The method is characterized by further comprising the following steps:
S2: initializing a preset correction Flag to 0;
s3, recording the gradient value of the current road surface in real time, and collecting the wheel speed pulse value and the running direction parameter of the vehicle to be parked;
s4: the wheel that encounters an obstacle is denoted as: a wheel to be observed;
when the wheel to be observed which advances at a low speed contacts with the raised barrier, the barrier can give an upward vertical force to the front end of the wheel, so that a moment opposite to the rolling direction of the wheel is formed; because the initial automatic parking is lower in vehicle speed and small in engine torque, the wheels to be observed slide backward, the running direction parameters jump, the jump of the running direction parameters of the wheels to be observed at the moment is recorded as the first change, and the recording time is t1;
The intelligent parking system controls the engine to increase torque and cross the convex obstacle, the running direction parameter of the wheel to be observed jumps again, the change of the running direction parameter at the moment is recorded as a second change, and the recording time is t2;
s5: calculating the relation between the time difference of T2 and T1 and a preset obstacle crossing time constant T1;
if (T2-T1) < T1, determining that the running direction of the wheel to be observed is changed continuously twice within the preset time T1, and executing step S6;
Otherwise, executing the step S3;
S6: setting the correction Flag to 1, which indicates that the wheel to be observed starts to cross an obstacle;
Recording the gradient value of the road surface recorded before the first change of the running direction parameter as: θ 0;
s7: after the correction Flag is set to 1, it is confirmed whether the following two conditions are simultaneously satisfied:
Condition 1: θ - 0 < C1;
condition 2: d1< D2;
wherein θ is the gradient value of the current road surface acquired in real time, and C1 is a constant value calibrated in advance;
d1 is the wheel travel distance of the vehicle to be parked during the period from the gradient value theta 0 to the gradient value theta; d2 is the wheelbase between the two sets of wheels of the vehicle to be parked;
d1 Mean value of 4 wheel travel distances;
Single wheel travel distance = unit wheel speed pulse distance x wheel speed pulse change value;
If the conditions 1 and 2 are satisfied at the same time, setting the Flag for correction to 2, which indicates that the wheels to be observed of the vehicle to be parked have completed crossing the obstacle, but the other group of wheels have not contacted the obstacle, which is the target of the correction, and executing step S9;
Otherwise, executing step S8;
s8: circularly executing the steps S2-S7;
s9: calculating a wheel speed pulse change value delta Wx of the wheel to be observed and a wheel speed pulse change value delta Wrear of the other group of wheels;
△Wx = Wx2- Wx1，
△Wrear = Wrear2- Wrear1；
Wherein Wx1 is the wheel speed pulse value of the wheel to be observed at the moment of Flag setting 1, and Wx2 is the wheel speed pulse value of the wheel to be observed at the moment of Flag setting 2; wrear1 is the wheel speed pulse value of the other group of wheels at the moment of Flag setting 1, wrear is the wheel speed pulse value of the other group of wheels at the moment of Flag setting 2, deltaWx is the wheel speed pulse increment of the wheel to be observed, delta Wrear is the wheel speed pulse increment of the other group of wheels;
S10: comparing the sizes of Δwx and Δ Wrear;
If ΔWx > - Δ Wrear, the value of Δ Wrear is used to replace ΔWx, and the individual wheel travel distances of the wheels to be observed are calculated.
It is further characterized by:
Before step S9 is performed, the following steps are performed;
Comparing the relation between the time difference of T2 and T1 and a preset timeout threshold T2:
If (T2-T1) > T2, judging that an abnormal condition occurs and calculating is abnormal, and executing steps S2-S9 in a circulating way;
otherwise, (T2-T1) is less than or equal to T2, if the situation is judged to be normal, the steps S7-S9 are circularly executed;
The calculating method of the gradient value comprises the following steps:
θ=tan(ɑ) * 100；
wherein alpha represents the slope angle of the road on which the vehicle is located;
ɑ＝arcsin( (A–dV) / g)；
A is a horizontal component of acceleration in a vehicle traveling direction, dV represents a rate of change of vehicle speed, and g represents gravitational acceleration of the vehicle;
before the step S2 is executed, the following steps are executed:
Judging whether the vehicle to be parked is in a straight running state, if so, executing the steps S2-S10, otherwise, stopping the correction;
The straight running state judging method comprises the following steps:
The steering wheel angle is within +/-5 degrees;
The wheel to be observed comprises: front wheels or rear wheels.
The application provides a vehicle self-positioning correction method used in a low-speed parking straight-line driving scene, which comprises the steps of firstly judging whether a vehicle to be parked is in a low-speed driving state and spans a scene of an obstacle, and if the vehicle to be parked is in the low-speed driving state and spans road surface protrusions such as a deceleration strip, replacing the wheel speed pulse increment of a wheel which is still driving on a plane road section with the wheel speed pulse increment of a wheel to be observed, avoiding unnecessary wheel speed pulse increment caused by the road section protrusions, and further achieving the purpose of plane positioning correction. The whole process does not need to add any extra sensor, the wheel speed pulse increment of the wheel when the wheel passes through a bumpy road section can be corrected based on the calculation of the inherent running parameters of the intelligent vehicle system, and the method ensures that the parking positioning accuracy can be improved based on lower cost.
Drawings
FIG. 1 is an embodiment of a vehicle over-deceleration strip in a low-speed park straight travel scenario;
FIG. 2 is an embodiment of a wheel contacting a deceleration strip in a low-speed park straight travel scenario;
Fig. 3 is a flow chart of a method for correcting the self-positioning of a vehicle in a low-speed parking straight driving scene according to the method.
Detailed Description
As shown in fig. 3, the present application includes a vehicle self-positioning correction method for a low-speed parking straight traveling scene, which includes the following steps.
S1: and starting the intelligent parking system, and controlling the parking process of the vehicle to be parked.
Before the step S2 is executed, the following steps are executed:
Judging whether the vehicle to be parked is in a straight running state, if so, executing the steps S2-S10, otherwise, stopping the correction;
the straight running state judging method comprises the following steps:
the steering wheel angle is within + -5 degrees.
In the method, whether the vehicle is in a straight running state or not is judged based on the steering wheel rotation angle, and if the vehicle is in a non-straight running state, other factors need to be considered, so that the vehicle is not in the range of the method.
S2: the preset correction Flag is initialized to 0.
And S3, recording the gradient value of the current road surface in real time, and collecting the wheel speed pulse value and the running direction parameters of the vehicle to be parked.
S4: the wheel that encounters an obstacle is denoted as: a wheel to be observed; the wheel to be observed comprises: front or rear wheels;
The method can be used for self-positioning correction no matter when the front wheel first encounters an obstacle such as a deceleration strip during the forward movement of the wheel or when the rear wheel spans a road surface protrusion such as the deceleration strip during the linear backward movement of the vehicle. The wheel speed pulse increment of the wheel running on the plane road section is replaced by the wheel speed pulse increment of the wheel to be observed, so that unnecessary wheel speed pulse increment caused by the protrusion of the road section is avoided, and the purpose of plane positioning correction is achieved.
As shown in fig. 2, when the wheel to be observed, which is advancing at a low speed, contacts the protruding obstacle, the obstacle gives an upward vertical force to the front end of the wheel, thereby forming a moment M opposite to the rolling direction of the wheel. Because the initial automatic parking is lower in vehicle speed and small in engine torque, the wheels to be observed slide backward, the running direction parameters jump, the jump of the running direction parameters of the wheels to be observed at the moment is recorded as the first change, and the recording time is t1;
The intelligent parking system can control the engine to increase torque and cross the convex obstacle, so that the running direction parameter of the wheel to be observed jumps again, the change of the running direction parameter at the moment is recorded as a second change, and the recording time is t2.
Since the design of the parking algorithm will seek to enable the vehicle to clear such obstacles, the engine will be controlled to build up torque as the vehicle is rolling back to clear the raised obstacle, with a second change in the direction of travel of the wheels.
S5: calculating the relation between the time difference of T2 and T1 and a preset obstacle crossing time constant T1;
if (T2-T1) < T1, judging that the running direction of the wheel to be observed is changed continuously twice within the preset T1 time, and executing the step S6;
Otherwise, judging that the road is not a scene of the processing object of the method, executing the step S3, monitoring the conditions of the road and the obstacle in real time, and waiting for the next calculation.
In the embodiment shown in fig. 1, when a vehicle advances through a road surface protrusion such as a deceleration strip, the front part of the vehicle firstly contacts the deceleration strip, so that the vehicle can bear an upward vertical force, and has a certain offset distance from the center of the vehicle, further, a torque opposite to the running direction of the vehicle is formed, the vehicle fails to run across the obstacle for the first time due to the fact that the vehicle speed of initial automatic parking is low and the torque of the engine is small, and the vehicle is particularly characterized in that the running direction parameter of the vehicle jumps, and the first change of the running direction of the vehicle is recorded at the moment;
In the method, whether the wheel spans a convex obstacle is judged by identifying whether the running direction of the wheel of the vehicle continuously changes twice in the time T1, and the Flag bit Flag is set to be 1 from 0 when the running direction of the wheel continuously changes twice. Taking 5 cars as an example in fig. 1, the running speed of the car is 1-5km/h when the car is parked automatically, and the time T1 can be set to 3s.
S6: setting the correction Flag to 1, indicating that the wheel to be observed starts to cross the obstacle;
Recording the gradient value of the road surface recorded before the first change of the running direction parameter as: θ 0.
S7: after the correction Flag is set to 1, it is confirmed whether the following two conditions are simultaneously satisfied:
Condition 1: θ - 0 < C1;
condition 2: d1< D2;
wherein θ is the gradient value of the current road surface acquired in real time, and C1 is a constant value calibrated in advance;
d1 is the wheel travel distance of the vehicle to be parked during the period from the gradient value theta 0 to the gradient value theta; d2 is the wheelbase between the two sets of wheels of the vehicle to be parked;
d1 Mean value of 4 wheel travel distances;
Single wheel travel distance = unit wheel speed pulse distance x wheel speed pulse change value;
If the conditions 1 and 2 are satisfied at the same time, setting the Flag for correction to 2, which indicates that the wheels to be observed of the vehicle to be parked have completed crossing the obstacle, but the other group of wheels have not contacted the obstacle, which is the target of the correction, and executing step S9;
Otherwise, step S8 is performed.
After the correction Flag is set to 1, comparing the gradient value theta of the current road surface acquired in real time with theta 0;
when θ satisfies the following condition, it means that the road surface on which the wheel to be observed is running is restored to the road surface angle before the wheel to be observed crosses the obstacle;
The value of the absolute value theta-theta 0 is smaller than C1, wherein C1 is a constant value calibrated in advance; the specific value of C1 is calibrated in advance according to different vehicle types, and in the embodiment, the C1 for 5 cars is set to be 1%;
D1 Not less than D2, indicating that the length of the obstacle is greater than the wheelbase of the vehicle to be parked, and indicating that the obstacle is not the target of the correction method;
otherwise, if D1< D2, it indicates that the wheels to be observed of the vehicle to be parked have completed crossing the obstacle, but the other set of wheels has not yet contacted the obstacle, which is the target of the current correction.
In the embodiment shown in fig. 1 and 2, the road gradient value θ is calculated in real time during automatic parking, the gradient value θ 0 of the wheel traveling direction at the previous time is recorded at the time when Flag is set to 1, when the subsequent gradient value is restored to the vicinity of θ 0, i.e., |θ - θ 0 | < C1, if the vehicle traveling distance is smaller than the vehicle wheelbase length at this time, the front wheel of the vehicle is considered to have completed the process of crossing the short-distance raised obstacle, the rear wheel has not been in contact with the raised obstacle, and the Flag bit Flag is set to 2 from 1 at this time.
S8: and (5) circularly executing the steps S2-S7.
Before step S9 is executed, the following redundant abnormality determination step is executed;
Comparing the relation between the time difference of T2 and T1 and a preset timeout threshold T2:
If (T2-T1) > T2, judging that an abnormal condition occurs and calculating is abnormal, and executing steps S2-S9 in a circulating way;
Otherwise, (T2-T1) is less than or equal to T2, if the condition is judged to be normal, steps S7-S9 are circularly executed, and the waiting is continued until the condition (|theta-theta 0 | < C1& D1< D2) is met in the period of time.
When the obstacle is not a narrower object such as a deceleration strip, but a longer object and the length exceeds the wheelbase of the vehicle, other factors need to be considered for correcting the positioning of the vehicle, and the method is not in the discussion range of the technical scheme of the application, so that in the method, the situation that the vehicle is in the overlong obstacle is eliminated by firstly judging the vehicle to pass through the distance limitation based on the comparison of D1 and D1, and the situation that the front wheel does not pass over the obstacle and the rear wheel also runs onto the obstacle is avoided, and the distance limitation value is the wheelbase length D2 of the vehicle. Meanwhile, in order to avoid errors in calculation results caused by data acquisition errors in the intelligent vehicle system, a redundancy abnormality judging step is further set in the method, a time limit value is set, overlong obstacles are eliminated in a time range, and in the embodiment, an empirical value of 10s can be taken as T2.
S9: calculating a wheel speed pulse change value delta Wx of a wheel to be observed and a wheel speed pulse change value delta Wrear of another group of wheels;
△Wx = Wx2- Wx1，
△Wrear = Wrear2- Wrear1；
Wherein Wx1 is the wheel speed pulse value of the wheel to be observed at the moment of Flag setting 1, and Wx2 is the wheel speed pulse value of the wheel to be observed at the moment of Flag setting 2; wrear1 is the wheel speed pulse value of the other group of wheels at the moment of Flag setting 1, wrear is the wheel speed pulse value of the other group of wheels at the moment of Flag setting 2, deltaWx is the wheel speed pulse increment of the wheel to be observed, delta Wrear is the wheel speed pulse increment of the other group of wheels;
S10: comparing the sizes of Δwx and Δ Wrear;
If ΔWx > - Δ Wrear, the value of Δ Wrear is used to replace ΔWx, and the individual wheel travel distances of the wheels to be observed are calculated.
It is further characterized by:
the gradient value calculating method comprises the following steps:
θ=tan(ɑ) * 100；
wherein alpha represents the slope angle of the vehicle on the road;
ɑ＝arcsin( (A–dV) / g)；
a is a horizontal component of acceleration in the vehicle traveling direction, dV represents a rate of change of the vehicle speed, and g represents gravitational acceleration of the vehicle.
The intelligent vehicle is provided with equipment such as an acceleration sensor, and the horizontal component A of the acceleration in the vehicle travelling direction can be directly collected from a control system of the intelligent vehicle based on a can bus during specific calculation. The change rate dV of the vehicle speed is obtained by the difference value of the acquired real-time running speed of the vehicle, the g value is constant 9.8m/s 2, and no additional sensor auxiliary calculation is needed.
After the technical scheme of the application is used, aiming at the situation that the actual running distance of the vehicle is increased and the plane relative position is unchanged when the wheel passes through the raised road section, the positioning accuracy of the vehicle based on the plane coordinate system is corrected by correcting the wheel speed pulse increment of the wheel when the wheel passes through the bumpy road section, so that the parking positioning accuracy is improved.
Claims (5)
1. A vehicle self-positioning correction method for a low-speed parking straight driving scene, comprising the following steps:
S1: the intelligent parking system is started to control the parking process of the vehicle to be parked;
The method is characterized by further comprising the following steps:
S2: initializing a preset correction Flag to 0;
s3, recording the gradient value of the current road surface in real time, and collecting the wheel speed pulse value and the running direction parameter of the vehicle to be parked;
s4: the wheel that encounters an obstacle is denoted as: a wheel to be observed;
when the wheel to be observed which advances at a low speed contacts with the raised barrier, the barrier can give an upward vertical force to the front end of the wheel, so that a moment opposite to the rolling direction of the wheel is formed; because the initial automatic parking is lower in vehicle speed and small in engine torque, the wheels to be observed slide backward, the running direction parameters jump, the jump of the running direction parameters of the wheels to be observed at the moment is recorded as the first change, and the recording time is t1;
The intelligent parking system controls the engine to increase torque and cross the convex obstacle, the running direction parameter of the wheel to be observed jumps again, the change of the running direction parameter at the moment is recorded as a second change, and the recording time is t2;
s5: calculating the relation between the time difference of T2 and T1 and a preset obstacle crossing time constant T1;
if (T2-T1) < T1, determining that the running direction of the wheel to be observed is changed continuously twice within the preset time T1, and executing step S6;
Otherwise, executing the step S3;
S6: setting the correction Flag to 1, which indicates that the wheel to be observed starts to cross an obstacle;
Recording the gradient value of the road surface recorded before the first change of the running direction parameter as: θ 0;
s7: after the correction Flag is set to 1, it is confirmed whether the following two conditions are simultaneously satisfied:
Condition 1: θ - 0 < C1;
Condition 2: d1< D2;
wherein θ is the gradient value of the current road surface acquired in real time, and C1 is a constant value calibrated in advance;
d1 is the wheel travel distance of the vehicle to be parked during the period from the gradient value theta 0 to the gradient value theta; d2 is the wheelbase between the two sets of wheels of the vehicle to be parked;
d1 Mean value of 4 wheel travel distances;
Single wheel travel distance = unit wheel speed pulse distance x wheel speed pulse change value;
If the conditions 1 and 2 are satisfied at the same time, setting the Flag for correction to 2, which indicates that the wheels to be observed of the vehicle to be parked have completed crossing the obstacle, but the other group of wheels have not contacted the obstacle, which is the target of the correction, and executing step S9;
Otherwise, executing step S8;
s8: circularly executing the steps S2-S7;
s9: calculating a wheel speed pulse change value delta Wx of the wheel to be observed and a wheel speed pulse change value delta Wrear of the other group of wheels;
△Wx = Wx2- Wx1，
△Wrear = Wrear2- Wrear1；
Wherein Wx1 is the wheel speed pulse value of the wheel to be observed at the moment of Flag setting 1, and Wx2 is the wheel speed pulse value of the wheel to be observed at the moment of Flag setting 2; wrear1 is the wheel speed pulse value of the other group of wheels at the moment of Flag setting 1, wrear is the wheel speed pulse value of the other group of wheels at the moment of Flag setting 2, deltaWx is the wheel speed pulse increment of the wheel to be observed, delta Wrear is the wheel speed pulse increment of the other group of wheels;
S10: comparing the sizes of Δwx and Δ Wrear;
If ΔWx > - Δ Wrear, the value of Δ Wrear is used to replace ΔWx, and the individual wheel travel distances of the wheels to be observed are calculated.
2. The vehicle self-positioning correction method for a low-speed parking straight line driving scene according to claim 1, wherein: before step S9 is performed, the following steps are performed;
Comparing the relation between the time difference of T2 and T1 and a preset timeout threshold T2:
If (T2-T1) > T2, judging that an abnormal condition occurs and calculating is abnormal, and executing steps S2-S9 in a circulating way;
Otherwise, (T2-T1) is less than or equal to T2, if the situation is judged to be normal, the steps S7-S9 are circularly executed.
3. The vehicle self-positioning correction method for a low-speed parking straight line driving scene according to claim 1, wherein: the calculating method of the gradient value comprises the following steps:
θ=tan(ɑ) * 100；
wherein alpha represents the slope angle of the road on which the vehicle is located;
ɑ＝arcsin( (A–dV) / g)；
a is a horizontal component of acceleration in the vehicle traveling direction, dV represents a rate of change of the vehicle speed, and g represents gravitational acceleration of the vehicle.
4. The vehicle self-positioning correction method for a low-speed parking straight line driving scene according to claim 1, wherein: before the step S2 is executed, the following steps are executed:
Judging whether the vehicle to be parked is in a straight running state, if so, executing the steps S2-S10, otherwise, stopping the correction;
The straight running state judging method comprises the following steps:
the steering wheel angle is within + -5 degrees.
5. The vehicle self-positioning correction method for a low-speed parking straight line driving scene according to claim 1, wherein: the wheel to be observed comprises: front wheels or rear wheels.
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