CN111231951B - Blind area detection and vehicle speed control method based on vehicle up-and-down slope - Google Patents

Blind area detection and vehicle speed control method based on vehicle up-and-down slope Download PDF

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CN111231951B
CN111231951B CN202010095837.4A CN202010095837A CN111231951B CN 111231951 B CN111231951 B CN 111231951B CN 202010095837 A CN202010095837 A CN 202010095837A CN 111231951 B CN111231951 B CN 111231951B
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CN111231951A (en
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袁朝春
丁懋
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Jiangsu University
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/095—Predicting travel path or likelihood of collision
    • B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
    • B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
    • B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering

Abstract

The invention discloses a blind area detection and vehicle speed control method based on the up-down slope of an automobile, which comprises the following steps of 1, obtaining the static parameters of a target vehicle; step 2, obtaining external environment information of the target vehicle; step 3, selecting different decisions according to whether the obstacle is detected; step 4, if the obstacle is detected, acquiring dynamic parameters of the current target vehicle and the obstacle, and calculating an actual distance S1 and a safe distance S2; if the obstacle is not detected, judging the position of the blind area according to the static parameters and the dynamic parameters of the target vehicle, and establishing a hypothetical obstacle model; step 5, comparing the actual distance with the safe distance, and controlling the speed of the vehicle; step 6, judging whether the climbing is finished or not; and 7, circulating the steps 1 to 6 until climbing is finished. The invention can actively judge the position of the blind area when the automobile ascends and descends, and calculate the safety distance under different risks through the hypothesis model according to the environment and the dynamic parameters of the automobile, thereby improving the safety when the intelligent driving automobile ascends and descends.

Description

Blind area detection and vehicle speed control method based on vehicle up-and-down slope
Technical Field
The invention relates to the technical field of automatic driving, in particular to a blind area detection and vehicle speed control method based on the up-down slope of an automobile.
Background
With the increasing of the intelligent degree of automobiles, the automatic driving technology at home and abroad is becoming mature, and a plurality of experts also continuously provide more optimized active safety systems. In general, for avoiding and warning an accident of a vehicle in travel in advance and further realizing automatic driving, it is important to recognize the surrounding environment in which an obstacle such as another vehicle exists and to predict the behavior of the obstacle. However, the authors found that in the existing vehicle speed control and following method, a dead zone of detection between the angle of the sensor-mounted position and the changing gradient when the vehicle goes up and down a slope and a deviation of the measured distance due to the gradient are not considered.
In order to solve the problems, the invention provides a blind area detection and vehicle speed control method based on the up-down slope of an automobile. During the process of ascending and descending the automobile, the control method can effectively reduce the deviation of distance measurement between the target vehicle and the front obstacle, and reduce the risk of collision with the obstacle in the blind area caused by overlarge gradient.
Disclosure of Invention
The invention aims to provide a blind area detection and vehicle speed control method based on the up-down slope of an automobile. The method comprises the following steps:
acquiring static parameters of a target vehicle;
(II) acquiring external environment information of the target vehicle;
(III) selecting different decisions according to whether the obstacle is detected;
and (IV) if the obstacle is detected, acquiring the dynamic parameters of the current target vehicle and the obstacle and calculating the actual distance and the safe distance.
If the obstacle cannot be detected, judging the position of the blind area according to the static parameters and the dynamic parameters of the target vehicle, and establishing a hypothetical obstacle model.
Fifthly, controlling the speed of the vehicle by comparing the actual distance with the safe distance;
(VI) judging whether the climbing is finished
And (seventhly), circulating the steps from one to six until the climbing is finished.
Further, the static parameters of the target vehicle (i) include the installation positions of the camera and the millimeter wave radar, and the maximum vertical measurement angle.
And further, the external environment information of the target vehicle in the step (II) comprises gradient and obstacle identification, and is obtained through a camera and a millimeter wave radar.
Further, the dynamic parameters of the target vehicle and the obstacle in (four) include the linear distance between the target vehicle and the obstacle in front and the actual speed of the obstacle, which are acquired by the millimeter wave radar, the current speed of the target vehicle, which is acquired by the wheel speed sensor, and the linear distance between the target vehicle and the start line of the slope in front, the boundary line of the highest slope that can be detected in front and the boundary line of the top of the slope in front, which are acquired by the camera. The actual distance and safe distance between the target vehicle and the obstacle are calculated, the blind area position is calculated, and the assumed obstacle model is established, and the like, the concrete implementation methods are as follows:
condition 1 (target vehicle preparing to go up slope at the bottom of slope):
when the presence of an obstacle on the front ramp is detected:
(1) obtaining the current speed V of the target vehicle through the wheel speed sensor, the millimeter wave radar, the camera and other devices on the target vehicle1Current speed V of obstacle2The distance a between the target vehicle and the starting line of the front slope, the linear distance b between the target vehicle and the detected obstacle in front and the included angle alpha in the directions of the target vehicle and the detected obstacle in front.
(2) According to the obtainedDetermining the actual distance S between the target vehicle and the front obstacle by the distance a between the target vehicle and the start line of the front slope, the linear distance b between the target vehicle and the front detected obstacle and the included angle alpha between the target vehicle and the front detected obstacle1The following were used:
S1＝a+sqrt(a2+b2-2abcos(α))
(3) according to the obtained current speed V of the target vehicle1Current speed V of obstacle2Calculating safe distance S based on DRV safe distance model2The following were used:
Figure BDA0002385323350000021
wherein a is1-max,a2-max,TbrFor non-measured data, it is experimentally found that1-max,a2-maxMaximum braking deceleration, usually 3m/s, for the target vehicle and the obstacle, respectively2,TbrFor the target vehicle braking time, take 1.4 s.
When the presence of an obstacle on the front ramp is not detected:
(1) obtaining the current speed V of the target vehicle through the wheel speed sensor, the millimeter wave radar, the camera and other devices on the target vehicle1The distance a between the target vehicle and the starting line of the front slope, the linear distance b' between the target vehicle and the boundary line of the highest slope detected in the front, and the included angle alpha in the directions of the target vehicle and the boundary line of the highest slope.
(2) Determining the position of the blind area and the actual distance S between the target vehicle and the blind area according to the acquired distance a between the target vehicle and the starting line of the front ramp, the linear distance b between the target vehicle and the boundary line of the highest ramp detected in front and the included angle alpha between the target vehicle and the front ramp in the two directions1The specific algorithm is as follows:
S1＝a+sqrt(a2+b2-2abcos(α))
(3) let the velocity of the assumed obstacle in the blind zone be V20, according to V1，V2Calculating a safe distance S 'based on a DRV safe distance model'2. Order toS2＝S’2+S0(ii) a Wherein S0The corresponding threshold values, which are set according to the different grade values and the current speed of the target vehicle, are proportional to the grade values and the current speed of the target vehicle.
Working condition 2 (target vehicle uphill near the top of the hill):
when an obstacle is detected:
(1) obtaining the current speed V of the target vehicle through the wheel speed sensor, the millimeter wave radar, the camera and other devices on the target vehicle1Current speed V of obstacle2A distance a between the target vehicle and a front top boundary line, a linear distance b between the target vehicle and a detected obstacle ahead, and a gradient β.
(2) According to the obtained current speed V of the target vehicle1Determining the actual distance S between the target vehicle and the obstacle ahead1The following were used:
S1＝a+(b-a)*cos(β)
(3) according to the obtained current speed V of the target vehicle1Current speed V of obstacle2Calculating safe distance S based on DRV safe distance model2The following were used:
Figure BDA0002385323350000031
wherein a is1-max,a2-max,TbrFor non-measured data, it is experimentally found that1-max,a2-maxMaximum braking deceleration, usually 3m/s, for the target vehicle and the obstacle, respectively2,TbrFor the target vehicle braking time, take 1.4 s.
When no obstacle is detected:
(1) the distance a of the target vehicle from the slope top boundary line is obtained through a camera on the target vehicle and a millimeter wave radar together, and a height value h is preset0If a first speed exists at the boundary line c from the top of the slope in the blind zoneDegree of V20 height h0And the distance of the target vehicle from the obstacle is S1Wherein
c＝h0/tan(β)
S1＝a+c
Wherein: h is0Can be determined according to the height of the common car or the acceptable safety factor of different drivers, h0Inversely proportional to the safety factor acceptable to the driver.
(2) Obtaining the current speed V of the target vehicle through a wheel speed sensor1According to V1，V2Calculating a safe distance S 'based on a DRV safe distance model'2Let S2＝S’2+S0In which S is0The corresponding threshold values, which are set according to the different grade values and the current speed of the target vehicle, are proportional to the grade values and the current speed of the target vehicle.
Similarly, the target vehicle may refer to condition 1 when located on a downhill section and may refer to condition 2 when located on the top of a hill to prepare for downhill.
The invention has the beneficial effects that:
1. the accuracy of the distance calculation of the front obstacle when the automobile goes up and down the slope is improved.
2. The position of the blind area during ascending and descending can be actively judged, the safety distance calculation under different risks is carried out through the hypothesis model according to the environment and the dynamic parameters of the self, and the safety during ascending and descending of the intelligent driving automobile is improved.
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FIG. 1 is a basic flow diagram of the process of the present invention
FIG. 2 is a schematic diagram of two operating conditions, wherein (a) indicates that an uphill road segment is detected and no known obstacle exists, (b) indicates that an uphill road segment is detected and a known obstacle exists, (c) indicates that a top of slope is detected and a known obstacle exists, and (d) indicates that a top of slope is detected and no known obstacle exists
Detailed Description
The invention will be further explained with reference to the drawings. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention provides a blind area detection and vehicle speed control method based on up and down slopes of an automobile, which comprises the following specific steps as shown in figure 1:
the method comprises the following steps: acquiring the static parameters of a target vehicle;
the installation positions of the camera and the millimeter wave radar, the maximum vertical measurement angle and the like can be obtained according to the factory setting of the vehicle and different parameters corresponding to different models.
Step two: acquiring external environment information of a target vehicle;
during the running process of a target vehicle, the camera detects a road ahead, when a slope is detected, the camera and the millimeter wave radar work in a matched mode, and according to the horizontal position difference X and the vertical height difference Y of a far point and a near point on the same central line, an arc tangent formula is utilized
Figure BDA0002385323350000041
And calculating the slope gradient. And the millimeter wave radar is used for detecting the obstacle, and whether the obstacle exists in the front is judged.
Step three: selecting different decisions according to whether an obstacle is detected;
step four: and if the obstacle is detected, acquiring dynamic parameters of the current target vehicle and the obstacle and calculating an actual distance and a safe distance.
If the obstacle cannot be detected, judging the position of the blind area according to the static parameters and the dynamic parameters of the target vehicle, and establishing a hypothetical obstacle model.
FIG. 2 is an example of two common operating conditions:
the working condition I is as follows: as shown in fig. 2 a and b, when the vehicle detects that the front part belongs to an uphill road section, the blind zone detection and speed control strategy is started.
The method comprises the steps of firstly identifying the gradient beta of a front ramp through a gradient sensor, and detecting the front road condition environment through a camera, a laser radar, a millimeter wave radar and the like. It is determined whether there are other vehicles, pedestrians, or obstacles.
When other vehicles, pedestrians or obstacles exist at the front, vehicle-mounted devices such as millimeter wave radars and vehicle speed sensors start to acquire the distance and the angle between the target vehicle and the starting line of the ramp and the front obstacle as well as the speed of the target vehicle and the obstacle.
The controller (comprising a storage module and a calculation module) is used for:
S1＝a+sqrt(a2+b2-2abcos(α))
calculating the actual distance S between the target vehicle and the front obstacle1. Where α is an angle between the target vehicle and a slope starting line and an obstacle ahead as shown in fig. 2 (a), b is a distance between the target vehicle and the obstacle ahead, and a is a distance between the target vehicle and the slope starting line.
Calculating a safe distance S based on a DRV safe distance model according to the current speed of the target vehicle and the speed of the obstacle2By comparison of S1、S2To control the speed of the vehicle, and the process is circulated until the hill climbing is finished.
When the front side can not detect other vehicles, pedestrians or obstacles, vehicle-mounted devices such as a millimeter wave radar and a vehicle speed sensor start to collect the distance between the target vehicle and a slope starting line and the distance between the target vehicle and the highest slope boundary line which can be detected in front of the slope starting line, namely the blind area, and the current vehicle speed of the target vehicle.
The controller (comprising a storage module and a calculation module) is used for:
S1＝a+sqrt(a2+b2-2abcos(α))
calculating the actual distance S between the target vehicle and the blind area1Where α is an angle between the target vehicle and the slope starting line and the blind spot as shown in fig. 2 (b), b is a distance between the target vehicle and the blind spot, and a is a distance between the target vehicle and the slope starting line.
Calculating a safe distance S based on the DRV safe distance model and a preset threshold according to the current speed of the target vehicle and the speed of the obstacle in the assumed blind area2。
Working conditions are as follows: as shown in fig. 2 c and d, when the vehicle detects that the front of the vehicle is about to reach the top of the slope, the blind zone detection and speed control strategy is started.
The method comprises the following steps of firstly detecting the front road condition environment through a camera, a laser radar, a millimeter wave radar and the like. It is determined whether other vehicles, pedestrians, or obstacles are detected.
When other vehicles, pedestrians or obstacles exist in the front, vehicle-mounted devices such as millimeter wave radars and vehicle speed sensors start to acquire the distance and the angle between the target vehicle and the slope top boundary line and the front obstacle as well as the speed of the target vehicle and the obstacle.
The controller (comprising a storage module and a calculation module) is used for:
S1＝a+(b-a)*cos(β)
calculating the actual distance S between the target vehicle and the front obstacle1Where β is a gradient value as shown in fig. 2 (c), b is a distance between the target vehicle and the obstacle, and a is a distance between the target vehicle and the top boundary line.
Calculating a safe distance S based on a DRV safe distance model according to the current speed of the target vehicle and the speed of the obstacle2By comparison of S1、S2To control the speed of the vehicle, and the process is circulated until the hill climbing is finished.
When the front side can not detect other vehicles, pedestrians or obstacles, vehicle-mounted devices such as a millimeter wave radar and a vehicle speed sensor start to acquire the distance between the target vehicle and the slope top boundary line and the current vehicle speed of the target vehicle.
The controller (comprising a storage module and a calculation module) is used for:
c＝h0/tan(β)
S1＝a+c
calculating the distance S between the target vehicle and the assumed obstacle in the blind zone1Wherein h is0As shown in fig. 2(d), the height of the assumed obstacle, which is preset, can be taken as the height of a normal car or determined according to a safety factor acceptable to different drivers, h0Inversely proportional to the safety factor acceptable to the driver. Beta is gradientThe value, c, is the distance of the assumed obstacle from the top boundary line, and a is the distance of the target vehicle from the top boundary line.
Based on the DRV safe distance model and the preset threshold value S according to the current speed of the target vehicle and the speed of the assumed obstacle (normally set to 0)0Calculating the safety distance S2，
Step five: controlling the speed of the vehicle by comparing the actual distance with the safe distance;
if S1>S2The controller outputs an acceleration or constant speed maintaining signal to the actuator; if S1<S2The controller outputs a deceleration signal to the actuator.
Step six: judging whether the gradient is 0 or whether the climbing is finished
Step seven: and (5) circulating the steps from one step to six until the gradient is 0 or the climbing is finished.
The above-listed detailed description is only a specific description of a possible embodiment of the present invention, and they are not intended to limit the scope of the present invention, and equivalent embodiments or modifications made without departing from the technical spirit of the present invention should be included in the scope of the present invention.

Claims (7)

1. A blind area detection and vehicle speed control method based on vehicle uphill and downhill is characterized by comprising the following steps:
step 1, obtaining static parameters of a target vehicle;
step 2, obtaining external environment information of the target vehicle;
step 3, selecting different decisions according to whether the obstacle is detected;
step 4, if the obstacle is detected, acquiring dynamic parameters of the current target vehicle and the obstacle, and calculating an actual distance S1 and a safe distance S2;
if the obstacle cannot be detected, judging the position of the blind area according to the static parameters and the dynamic parameters of the target vehicle, and establishing a hypothetical obstacle model;
step 5, controlling the speed of the vehicle by comparing the actual distance with the safe distance;
step 6, judging whether the climbing is finished or not; if not, executing step 7;
step 7, the steps 1 to 6 are circulated until climbing is finished;
in the step 1, the static parameters of the target vehicle comprise the installation positions of the camera and the millimeter wave radar and the maximum vertical measurement angle;
in step 2, the target vehicle external environment information includes: gradient and obstacle information, which is obtained by a camera and a millimeter wave radar;
in step 4, the dynamic parameters of the target vehicle and the obstacle include: the linear distance between the target vehicle and the front obstacle and the actual speed of the obstacle are acquired by the millimeter wave radar, the current speed of the target vehicle is acquired by the wheel speed sensor, and the linear distances between the target vehicle and the front slope starting line, the front detectable highest slope boundary line and the front slope top boundary line are acquired by the camera.
2. The method according to claim 1, wherein in step 4, the actual distance, the safe distance and the blind area position between the target vehicle and the obstacle are obtained, and the specific implementation method for establishing the assumed obstacle model corresponds to the following two working conditions:
working condition 1: when the target vehicle is preparing to ascend at the bottom of a slope; and
working condition 2: the target vehicle ascends the slope close to the top of the slope.
3. The vehicle up-down slope-based blind area detection and vehicle speed control method according to claim 2, characterized in that under condition 1:
if an obstacle is detected on the front ramp:
(1) obtaining the current speed V of the target vehicle through a wheel speed sensor, a millimeter wave radar and a camera on the target vehicle1Current speed V of obstacle2Distance a between target vehicle and front slope starting line, and targetThe straight line distance b between the vehicle and the detected obstacle in front and the included angle alpha in the directions of the vehicle and the detected obstacle;
(2) determining the actual distance S between the target vehicle and the front obstacle according to the acquired distance a between the target vehicle and the starting line of the front slope, the linear distance b between the target vehicle and the front detected obstacle and the included angle alpha between the target vehicle and the front detected obstacle1The following were used:
S1＝a+sqrt(a2+b2-2abcos(α))
(3) according to the obtained current speed V of the target vehicle1Current speed V of obstacle2Calculating safe distance S based on DRV safe distance model2；
If no obstacle on the front ramp is detected:
(1) obtaining the current speed V of the target vehicle through a wheel speed sensor, a millimeter wave radar, a camera and other devices on the target vehicle1The distance a between the target vehicle and the starting line of the front ramp, the linear distance b' between the target vehicle and the boundary line of the highest ramp detected in front and the included angle alpha in the directions of the target vehicle and the boundary line of the highest ramp are obtained;
(2) determining the position of the blind area and the actual distance S between the target vehicle and the blind area according to the acquired distance a between the target vehicle and the starting line of the front ramp, the linear distance b between the target vehicle and the boundary line of the highest ramp detected in front and the included angle alpha between the target vehicle and the front ramp in the two directions1The specific algorithm is as follows:
S1＝a+sqrt(a2+b2-2abcos(α))
(3) let the velocity of the assumed obstacle in the blind zone be V20, according to V1，V2Calculating a safe distance S 'based on a DRV safe distance model'2Then the safe distance S at this time2＝S’2+S0In which S is0The corresponding threshold values, which are set according to the different grade values and the current speed of the target vehicle, are proportional to the grade values and the current speed of the target vehicle.
4. The vehicle up-down slope-based blind area detection and vehicle speed control method according to claim 2, characterized in that under condition 2:
if an obstacle is detected:
(1) obtaining the current speed V of the target vehicle through the wheel speed sensor, the millimeter wave radar and the camera on the target vehicle1Current speed V of obstacle2A distance a between the target vehicle and a front top boundary line, a linear distance b between the target vehicle and a detected obstacle ahead, and a gradient β.
(2) According to the obtained current speed V of the target vehicle1Determining the actual distance S between the target vehicle and the obstacle ahead1The following were used:
S1＝a+(b-a)*cos(β)
(3) according to the obtained current speed V of the target vehicle1Current speed V of obstacle2Calculating safe distance S based on DRV safe distance model2：
Figure FDA0002982347340000031
If no obstacle is detected:
(1) the distance a of the target vehicle from the slope top boundary line is obtained through a camera on the target vehicle and a millimeter wave radar together, and a height value h is preset0If a velocity V exists at the boundary line c between the distance and the top of the slope in the blind zone20 height h0And the distance of the target vehicle from the obstacle is S1Wherein
c＝h0/tan(β)
S1＝a+c
Wherein: h is0Can be determined according to the height of the common car or the acceptable safety factor of different drivers, h0Inversely proportional to the safety factor acceptable to the driver;
(2) obtaining the current speed V of the target vehicle through a wheel speed sensor1According to V1，V2Calculating DRV-based securitySafe distance S 'from model'2Then a safe distance S2＝S’2+S0In which S is0The corresponding threshold values, which are set according to the different grade values and the current speed of the target vehicle, are proportional to the grade values and the current speed of the target vehicle.
5. The vehicle up-down slope-based blind area detection and vehicle speed control method according to claim 2, characterized by further comprising working condition 3: when the target vehicle is located on a downhill section, the actual distance, the safe distance and the blind area position between the target vehicle and the obstacle corresponding to the working condition 3 are the same as those of the working condition 1.
6. The vehicle up-down slope-based blind area detection and vehicle speed control method according to claim 2, characterized by further comprising working condition 4: when the target vehicle is positioned at the top of a slope and ready to go downhill, the actual distance, the safe distance and the blind area position between the target vehicle and the obstacle corresponding to the working condition 4 and the method for establishing the assumed obstacle model are the same as those of the working condition 2.
7. The method for detecting the blind area and controlling the vehicle speed based on the up-and-down slope of the automobile according to the claim 1, characterized in that the step 5 is realized by the following steps:
if S1>S2The controller outputs an acceleration or constant speed maintaining signal to the actuator; if S1<S2The controller outputs a deceleration signal to the actuator.
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