CN112810604B - Intelligent vehicle behavior decision method and system based on parking lot scene - Google Patents

Abstract

The invention discloses an intelligent vehicle decision method and system based on a parking lot scene, wherein the method comprises the following steps: step 1, entering a parking decision system, sensing a driving scene of a self-vehicle, judging whether the self-vehicle is in a parking lot scene S, and if so, entering step 2; if not, entering step 4; step 2, judging whether the self vehicle is in the driving process, if so, entering the step 3; if not, entering step 4; step 3, making a decision on the parking driving behavior E of the self-vehicle according to one or more of the position relation P between the other vehicle and the self-vehicle, the distance relation D between the other vehicle and the self-vehicle, the driving direction relation C between the other vehicle and the self-vehicle, the speed relation V between the other vehicle and the self-vehicle and the parking driving behavior O of the other vehicle; and 4, exiting the parking decision system.

Description

A method and system for intelligent vehicle behavior decision-making based on parking lot scenarios

technical field

The invention relates to the technical field of intelligent vehicle behavior decision-making, in particular to a method and system for intelligent vehicle behavior decision-making based on a parking lot scene.

Background technique

With the continuous development of related technologies such as the Internet of Things and artificial intelligence, automobiles are developing in the direction of unmanned and networked. As an important branch of artificial intelligence in the future, intelligent vehicles can not only improve the efficiency of road traffic, but also improve the safety of vehicles, greatly changing the way people travel. An intelligent vehicle is a system that integrates complex functions such as environmental perception, behavioral decision-making, path planning, and vehicle control. As the "brain" of the unmanned vehicle, the behavior decision module of the intelligent vehicle integrates the surrounding environment and the vehicle's own information through the environment perception system to guide the vehicle to output safe, reliable and reasonable driving actions. At present, the research on the application scenarios of behavioral decision-making of intelligent vehicles mainly includes highways and urban roads, but there is less research on behavioral decision-making of intelligent vehicles in the parking lot scene. In the parking lot scene, the speed of the vehicle is relatively low, And the driving behavior of other vehicles is relatively complex.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a method and system for intelligent vehicle behavior decision-making based on a parking lot scene to overcome or at least alleviate at least one of the above-mentioned defects of the prior art.

In order to achieve the above object, the present invention provides a method for intelligent vehicle decision-making based on a parking lot scene, the method comprising:

Step 1, enter the parking decision system, perceive the driving scene where the vehicle is located, and determine whether it is in the parking lot scene S, if so, go to step 2; if not, go to step 4;

S={s _i |i=1,2,3}

Among them, s ₁ represents a straight lane, s ₂ represents an intersection, and s ₃ represents a parking space;

Step 2, determine whether the vehicle is in the driving process, if so, go to Step 3; if not, go to Step 4;

Step 3: According to the positional relationship P between his car and his own car, the distance relationship D between his car and his own car, the driving direction relationship C between his car and his own car, the speed relationship V between his car and his own car, and the parking distance of his car. One or more of the vehicle driving behaviors O, making decisions on the parking driving behavior E of the own vehicle;

P={pi | _i =1,2,…9}

Among them, p ₁ means that the other car is located in front of the same lane of the own vehicle, p ₂ means that the other car is located in front of the adjacent lane of the own vehicle, p ₃ means that the other car is located in the back of the same lane of the own vehicle, p ₄ means that the other car is located in the own vehicle The rear of the adjacent lane, p ₅ means that the other car is located on the side of the own vehicle, p ₆ means that the other car is located in the parking space in front of the driving lane of the own vehicle, p ₇ means that the other car is located in the parking space behind the driving lane of the own vehicle , p ₈ indicates that his car is located in the adjacent parking space of the own car's parking space, p ₉ indicates that his car is located in the lane in front of the own parking space;

D={d _i |i=1,2}

Among them, d ₁ indicates that the distance between the other vehicle and the own vehicle is greater than or equal to the safety distance, and d ₂ indicates that the distance between the other vehicle and the own vehicle is greater than or equal to the safety distance;

C={ci | _i =1,2,3}

Among them, c ₁ represents the same direction, c ₂ represents the reverse direction, and c ₃ represents the vertical direction;

V={v _i |i=1,2,3}

Among them, v ₁ means that the speed of his car is greater than that of the own car, v ₂ means that the speed of his car is lower than that of the own car, and v ₃ means that the speed of his car is the same as that of the own car;

O={o _i |i=1,2,…,6}

Among them, o ₁ means going straight, o ₂ means changing lanes, o ₃ means turning, o ₄ means parking, o ₅ means driving into the parking space, o ₆ means driving out of the parking space;

Self-vehicle parking and driving behaviors include the following five types:

E={e _i |i=1,2,…5}

Among them, e ₁ represents autonomous cruise, e ₂ represents vehicle following, e ₃ represents parking waiting, e ₄ represents driving into the parking space, and e ₅ represents driving out of the parking space;

Step 4, exit the parking decision system.

Further, the driving environment in which the driving behavior decision of the self _- vehicle is e1 includes:

1. The self-vehicle is in a driving environment where s ₁ , p ₁ , and d ₁ coexist;

2. The self-vehicle is in a driving environment where s ₁ , p ₁ , d ₂ , c ₁ , and v ₁ coexist;

3. The self-vehicle is in a driving environment in which one of p ₂ , p ₃ , p ₄ , p ₅ , and p ₇ coexists with s ₁ ;

4. The self-vehicle is in a driving environment where s ₁ , p ₆ , and d ₁ coexist;

5. The self-vehicle is in a driving environment where s ₂ , p ₂ , c ₂ , and o ₁ coexist;

6. The self-vehicle is in a driving environment in which one of p ₃ , p ₄ and p ₇ coexists with s ₂ .

Further, the driving environment in which the driving behavior decision of the self-vehicle is e ₂ includes:

1. The self-vehicle is in a driving environment where s ₁ , p ₁ , d ₂ , c ₁ , v ₂ or v ₃ , and o ₁ or o ₂ exist simultaneously;

2. The self-vehicle is in a driving environment where s ₂ , p ₁ , and c ₁ coexist.

Further, the driving environment where the driving behavior decision of the self-vehicle is _e3 includes:

1. The self-vehicle is in a driving environment where s ₁ , p ₁ , d ₂ , c ₁ , v ₂ or v ₃ , and o ₅ or o ₆ exist simultaneously;

2. The self-vehicle is in a driving environment where s ₁ , p ₁ , d ₂ , and c ₂ coexist;

3. The self-vehicle is in a driving environment where s ₁ , p ₆ , and d ₂ coexist;

4. The self-vehicle is in a driving environment where s ₂ , p ₁ , and c ₃ coexist;

5. The self-vehicle is in a driving environment where s ₂ , p ₂ , c ₂ , and o ₃ coexist;

6. The self-vehicle is in a driving environment where s ₂ , p ₂ , and c ₃ coexist;

7. The self-vehicle is in a driving environment where s ₃ , p ₈ , c ₂ , and o ₆ coexist;

8. The driving environment that exists when the ego vehicle is at s ₃ , p ₉ , and d ₂ .

Further, the driving environment in which the driving behavior decision of the self _- vehicle is e4 includes:

1. The self-vehicle is in a driving environment where s ₃ , p ₈ , c ₁ , and o ₅ exist at the same time;

2. The self-vehicle is in a driving environment where s ₃ , p ₈ , c ₁ , and o ₆ coexist;

3. The self-vehicle is in a driving environment where s ₃ , p ₉ , and d ₁ coexist.

Further, the driving environment in which the driving behavior decision of the self _- vehicle is e5 includes:

1. The self-vehicle is in a driving environment where s ₃ , p ₈ , c ₁ , and o ₆ coexist;

2. The self-vehicle is in a driving environment where s ₃ , p ₈ , c ₂ , and o ₅ coexist;

3. The self-vehicle is in a driving environment where s ₃ , p ₉ , and d ₁ coexist.

The present invention also provides an intelligent vehicle decision-making system based on a parking lot scene, the system comprising:

A driving scene judgment unit, which is used to perceive the driving scene in which the vehicle is located after entering the parking decision system, and determine whether it is in the parking lot scene S; if not, go to step 4;

S={s _i |i=1,2,3}

Among them, s ₁ represents a straight lane, s ₂ represents an intersection, and s ₃ represents a parking space;

A driving state judging unit, which is used for judging whether the self-vehicle is in the driving process when the driving scene judging unit determines that the self-vehicle is in the parking lot scene S, and if so, enter step 3; if not, enter step 3 4;

The parking decision-making unit is used for, when the driving state judging unit determines that the own vehicle is in the driving process, according to the positional relationship P between the other vehicle and the own vehicle, the distance relationship D between the other vehicle and the own vehicle, and the distance between the other vehicle and the own vehicle. One or more of the driving direction relationship C of the own vehicle, the speed relationship V between the other vehicle and the own vehicle, and the parking driving behavior O of the other vehicle, to make a decision on the parking driving behavior E of the own vehicle, and use it for Exit when the driving scene determination unit determines that the vehicle is not in the parking lot scene S or the driving state determination unit determines that the vehicle is not in the driving process;

P={pi | _i =1,2,…9}

Among them, p ₁ means that the other car is located in front of the same lane of the own vehicle, p ₂ means that the other car is located in front of the adjacent lane of the own vehicle, p ₃ means that the other car is located in the back of the same lane of the own vehicle, p ₄ means that the other car is located in the own vehicle The rear of the adjacent lane, p ₅ means that the other car is located on the side of the own vehicle, p ₆ means that the other car is located in the parking space in front of the driving lane of the own vehicle, p ₇ means that the other car is located in the parking space behind the driving lane of the own vehicle , p ₈ indicates that his car is located in the adjacent parking space of the own car's parking space, p ₉ indicates that his car is located in the lane in front of the own parking space;

D={d _i |i=1,2}

Among them, d ₁ indicates that the distance between the other vehicle and the own vehicle is greater than or equal to the safety distance, and d ₂ indicates that the distance between the other vehicle and the own vehicle is greater than or equal to the safety distance;

C={ci | _i =1,2,3}

Among them, c ₁ represents the same direction, c ₂ represents the reverse direction, and c ₃ represents the vertical direction;

V={v _i |i=1,2,3}

Among them, v ₁ means that the speed of his car is greater than that of the own car, v ₂ means that the speed of his car is lower than that of the own car, and v ₃ means that the speed of his car is the same as that of the own car;

O={o _i |i=1,2,…,6}

Among them, o ₁ means going straight, o ₂ means changing lanes, o ₃ means turning, o ₄ means parking, o ₅ means driving into the parking space, o ₆ means driving out of the parking space;

Self-vehicle parking and driving behaviors include the following five types:

E={e _i |i=1,2,…5}

Among them, e ₁ represents autonomous cruise, e ₂ represents vehicle following, e ₃ represents parking waiting, e ₄ represents driving into the parking space, and e ₅ represents driving out of the parking space.

Further, the driving environment in which the driving behavior decision of the self _- vehicle is e1 includes:

1. The self-vehicle is in a driving environment where s ₁ , p ₁ , and d ₁ coexist;

2. The self-vehicle is in a driving environment where s ₁ , p ₁ , d ₂ , c ₁ , and v ₁ coexist;

3. The self-vehicle is in a driving environment in which one of p ₂ , p ₃ , p ₄ , p ₅ , and p ₇ coexists with s ₁ ;

4. The self-vehicle is in a driving environment where s ₁ , p ₆ , and d ₁ coexist;

5. The self-vehicle is in a driving environment where s ₂ , p ₂ , c ₂ , and o ₁ coexist;

6. The self-vehicle is in a driving environment in which one of p ₃ , p ₄ and p ₇ coexists with s ₂ .

Further, the driving environment in which the driving behavior decision of the self-vehicle is e ₂ includes:

1. The self-vehicle is in a driving environment where s ₁ , p ₁ , d ₂ , c ₁ , v ₂ or v ₃ , and o ₁ or o ₂ exist simultaneously;

2. The self-vehicle is in a driving environment where s ₂ , p ₁ , and c ₁ coexist.

Further, the driving environment where the driving behavior decision of the self-vehicle is _e3 includes:

1. The self-vehicle is in a driving environment where s ₁ , p ₁ , d ₂ , c ₁ , v ₂ or v ₃ , and o ₅ or o ₆ exist simultaneously;

2. The self-vehicle is in a driving environment where s ₁ , p ₁ , d ₂ , and c ₂ coexist;

3. The self-vehicle is in a driving environment where s ₁ , p ₆ , and d ₂ coexist;

4. The self-vehicle is in a driving environment where s ₂ , p ₁ , and c ₃ coexist;

5. The self-vehicle is in a driving environment where s ₂ , p ₂ , c ₂ , and o ₃ coexist;

6. The self-vehicle is in a driving environment where s ₂ , p ₂ , and c ₃ coexist;

7. The self-vehicle is in a driving environment where s ₃ , p ₈ , c ₂ , and o ₆ coexist;

8. The driving environment that exists when the ego vehicle is at s ₃ , p ₉ , and d ₂ .

Further, the driving environment in which the driving behavior decision of the self _- vehicle is e4 includes:

1. The self-vehicle is in a driving environment where s ₃ , p ₈ , c ₁ , and o ₅ exist at the same time;

2. The self-vehicle is in a driving environment where s ₃ , p ₈ , c ₁ , and o ₆ coexist;

3. The self-vehicle is in a driving environment where s ₃ , p ₉ , and d ₁ coexist.

Further, the driving environment in which the driving behavior decision of the self _- vehicle is e5 includes:

1. The self-vehicle is in a driving environment where s ₃ , p ₈ , c ₁ , and o ₆ coexist;

2. The self-vehicle is in a driving environment where s ₃ , p ₈ , c ₂ , and o ₅ coexist;

3. The self-vehicle is in a driving environment where s ₃ , p ₉ , and d ₁ coexist.

The present invention has the following advantages due to taking the above technical solutions:

1. Categorizing driving scenarios can make the behavioral decisions of intelligent vehicles easier.

2. According to the driving behavior of other vehicles in different scenarios, the intelligent vehicle makes the behavior decision of the vehicle more realistic, which can improve the parking efficiency of the parking lot and the safety of the vehicle driving process.

Description of drawings

FIG. 1 is a flowchart of a method for intelligent vehicle behavior decision-making based on a parking lot scene provided by an embodiment of the present invention.

FIG. 2 is a classification diagram for influencing intelligent vehicle behavior decision based on a parking lot scenario provided by an embodiment of the present invention.

FIG. 3 is a behavior decision diagram of an intelligent vehicle in a straight lane scenario provided by an embodiment of the present invention.

FIG. 4 is a behavior decision diagram of an intelligent vehicle in an intersection or T-junction scenario provided by an embodiment of the present invention.

FIG. 5 is a behavior decision diagram in a scenario where an intelligent vehicle enters or leaves a parking space provided by an embodiment of the present invention.

Detailed ways

The present invention will be described in detail below with reference to the accompanying drawings and embodiments.

As shown in FIG. 1, the intelligent vehicle decision-making method based on the parking lot scene provided by the embodiment of the present invention includes:

Step 1, enter the parking decision system, perceive the driving scene where the vehicle is located, and determine whether it is in the parking lot scene S, if so, go to step 2; if not, go to step 4;

S={s _i |i=1,2,3}

Among them, s ₁ represents a straight lane, s ₂ represents an intersection, and s ₃ represents a parking space.

Step 2, determine whether the self-vehicle is in the driving process, if yes, go to Step 3; if not, go to Step 4.

Step 3, according to the parking interaction behavior of the other car and the own car and the parking and driving behavior O of the other car, make a decision on the parking and driving behavior E of the own car. This embodiment classifies the parking interaction behavior of the other vehicle and the own vehicle, the parking and driving behavior of the other vehicle, and the parking and driving behavior E of the own vehicle.

Among them, the parking interaction between the other car and the own car includes the position relationship P between the other car and the own car, the distance relationship D between the other car and the own car, the driving direction relationship C between the other car and the own car, and the relationship between the other car and the own car. The velocity relationship V.

In the parking lot scenario, the positional relationship P between his car and his own car includes the following nine types:

P={pi | _i =1,2,…9}

Among them, p ₁ means that the other car is located in front of the same lane of the own vehicle, p ₂ means that the other car is located in front of the adjacent lane of the own vehicle, p ₃ means that the other car is located in the back of the same lane of the own vehicle, p ₄ means that the other car is located in the own vehicle The rear of the adjacent lane, p ₅ means that the other car is located on the side of the own vehicle (two lanes or more), p ₆ means that the other car is located in the parking space in front of the driving lane of the own vehicle, p ₇ means that the other car is located in the driving lane of the own vehicle In the parking space behind the side, p ₈ indicates that his car is located in the adjacent parking space of the parking space where the vehicle is located, and p ₉ indicates that his car is located in the lane in front of the parking space where the vehicle is located.

In the parking lot scenario, the distance relationship D between his car and his own car includes the following two:

D={d _i |i=1,2}

Among them, d ₁ indicates that the distance between the other vehicle and the own vehicle is greater than or equal to the safety distance d, and d ₂ indicates that the distance between the other vehicle and the own vehicle is greater than or equal to the safety distance d. The specific value of d can be considered to be set according to the vehicle size parameters.

In the parking lot scenario, the relationship C between the driving direction of the other car and the own car includes the following three types:

C={ci | _i =1,2,3}

Among them, c ₁ represents the same direction, c ₂ represents the reverse direction, and c ₃ represents the vertical direction.

In the parking lot scenario, the speed relationship V between the other car and the own car includes the following three types:

V={v _i |i=1,2,3}

Among them, v ₁ means that the speed of his car is greater than that of the own car, v ₂ means that the speed of his car is lower than that of the own car, and v ₃ means that the speed of his car is the same as that of the own car.

In the parking lot scenario, his car's parking driving behavior O includes the following six types:

O={o _i |i=1,2,…,6}

Among them, o ₁ means going straight, o ₂ means changing lanes, o ₃ means turning, o ₄ means parking, o ₅ means driving into the parking space, o ₆ means driving out of the parking space.

In the parking lot scenario, the parking driving behavior E of the self-vehicle includes the following five types:

E={e _i |i=1,2,…5}

Among them, e ₁ represents autonomous cruise, e ₂ represents vehicle following, e ₃ represents parking waiting, e ₄ represents driving into the parking space, and e ₅ represents driving out of the parking space.

This step is based on the positional relationship P between the other vehicle and the own vehicle, the distance relationship D between the other vehicle and the own vehicle, the driving direction relationship C between the other vehicle and the own vehicle, the speed relationship V between the other vehicle and the own vehicle, and the parking of the other vehicle. One or more of the driving behaviors O to make decisions on the parking driving behavior E of the self-vehicle.

Step 4: Exit the parking decision system: When the self-vehicle is not in the driving process in the parking lot scene, that is, the self-vehicle has entered the parking space or has exited the parking lot, this decision-making behavior ends.

The embodiment of the present invention not only classifies the parking lot scenes, which can make the behavior decision of the intelligent vehicle easier, but also makes the self-vehicle behavior decision more realistic according to the driving behavior of other vehicles in different scenarios, which can improve the behavior of the parking lot. Parking efficiency and safety during vehicle travel.

In one embodiment, as shown in Figures 3-5, the behavioral decisions of the self-vehicle in different driving environments in step 3 are specifically described as:

( ₁ ) The driving environment in which the driving behavior decision of the self-vehicle is e1 includes:

1. When the self-vehicle is in a driving environment in which s ₁ , p ₁ , and d ₁ coexist, since the two vehicles are at a safe distance, the driving behavior of the other vehicle will not affect the self-vehicle, then the self-vehicle at this time The driving behavior decision is e ₁ .

2. In the driving environment where s ₁ , p ₁ , d ₂ , c ₁ , and v ₁ coexist, although the two cars are within a safe distance, the speed of the other car is greater than the one The distance between them is getting larger, then the driving behavior decision of the self-vehicle at this time is e ₁ .

3. When the own car is in a driving environment in which one of p ₂ , p ₃ , p ₄ , p ₅ , and p ₇ coexists with s ₁ , because in these interactive relationships, the driving behavior of the other car If the driving behavior of the self-vehicle is not affected, the driving behavior decision of the self-vehicle at this time is e ₁ .

4. Under the circumstance that the own car is in a driving environment where s ₁ , p ₆ , and d ₁ exist at the same time, since the two cars are at a safe distance, the driving behavior of the other car will not affect the driving behavior of the own car, then this The driving behavior decision of the ego vehicle is e ₁ .

5. When the self-vehicle is in a driving environment where s ₂ , p ₂ , c ₂ , and o ₁ coexist, since the trajectories of the two vehicles do not intersect, the self-vehicle's driving behavior decision at this time is e ₁ .

6. In a situation where the ego car is in a driving environment in which one of p ₃ , p ₄ and p ₇ coexists with s ₂ , because in these interaction relationships, the driving behavior of the ego car will not affect the ego car's driving. If the behavior affects, then the driving behavior decision of the ego vehicle at this time is e ₁ .

( ₂ ) The driving environment in which the driving behavior decision of the self-vehicle is e2 includes:

1. When the self-vehicle is in a driving environment where s ₁ , p ₁ , d ₂ , c ₁ , v ₂ or v ₃ , and o ₁ or o ₂ exist at the same time, since the two vehicles are within a safe distance, and at this time The distance is decreasing or unchanged, and the driving behavior of the other car will affect the speed of the own car, then the driving behavior decision of the own car at this time is e ₂ . Among them, "v ₂ or v ₃ " can be understood as an alternative choice, and "o ₁ or o ₂ " can be understood as an alternative choice.

2. When the ego car is in a driving environment where s ₂ , p ₁ , and c ₁ exist at the same time, since the other car is located in front of the ego car, the driving behavior of the ego car will affect the speed of the ego car, then the ego car is The driving behavior decision of the car is e ₂ .

( ₃ ) The driving environment where the driving behavior decision of the self-vehicle is e3 includes:

1. When the self-vehicle is in a driving environment in which s ₁ , p ₁ , d ₂ , c ₁ , v ₂ or v ₃ , and o ₅ or o ₆ exist at the same time, since the two vehicles are within a safe distance, the other vehicle is driving. The driving behavior of entering/exiting the parking space will affect the driving behavior of the self-vehicle, and the driving behavior decision of the self-vehicle at this time is e ₃ . Among them, "or" means to choose one.

2. When the own vehicle is in a driving environment where s ₁ , p ₁ , d ₂ , and c ₂ exist at the same time, since the two vehicles are within a safe distance and drive in the opposite direction in the same lane, the driving behavior of the other vehicle will affect the driving behavior of the other vehicle. If the driving behavior of the ego car affects, then the driving behavior decision of the ego car at this time is e ₃ .

3. When the own vehicle is in a driving environment where s ₁ , p ₆ , and d ₂ exist at the same time, since the two vehicles are within a safe distance and the other vehicle is in the parking space in front of the own vehicle, the driving behavior of the other vehicle will be affected. If the driving behavior of the own vehicle is affected, the driving behavior decision of the own vehicle at this time is e ₃ .

4. When the own vehicle is in a driving environment where s ₂ , p ₁ , and c ₃ coexist, since the other vehicle is in front of the own vehicle and the driving direction is vertical, the own vehicle needs to wait for the other vehicle to pass first, then this The driving behavior decision of the ego vehicle is e ₃ .

5. When the self-vehicle is in a driving environment where s ₂ , p ₂ , c ₂ , and o ₃ exist at the same time, since the trajectories of the two vehicles will intersect, the self-vehicle needs to wait for the other vehicle to pass first. The driving behavior decision is e ₃ .

6. When the self-vehicle is in the driving environment where s ₂ , p ₂ , and c ₃ exist at the same time, since the trajectories of the two vehicles will intersect, the self-vehicle needs to wait for the other vehicle to pass by first. At this time, the self-vehicle's driving behavior decision is: e ₃ .

7. When the own car is in a driving environment where s ₃ , p ₈ , c ₂ , and o ₆ exist at the same time, since the driving behavior of other cars will have an impact on the driving behavior of the own car, the driving behavior of the own car is decided at this time is e ₃ .

8. When the self-vehicle is in the driving environment that exists when s ₃ , p ₉ , and d ₂ , since the two vehicles are within a safe distance and there is a possibility of collision, the driving behavior decision of the self-vehicle at this time is e ₃ .

( ₄ ) The driving environment in which the driving behavior decision of the self-vehicle is e4 includes:

1. When the own car is in a driving environment where s ₃ , p ₈ , c ₁ , and o ₅ exist at the same time, since the behavior of other cars will not affect the own car's driving into the parking space, the driving behavior of the own car is decided at this time is e ₄ .

2. When the own car is in the driving environment where s ₃ , p ₈ , c ₁ , and o ₆ exist at the same time, since the driving behavior of other cars has no influence on the driving behavior of the own car, the driving behavior decision of the own car at this time is: e ₄ .

3. When the own car is in the driving environment where s ₃ , p ₉ , and d ₁ exist at the same time, since the driving behavior of other cars will not affect the driving behavior of the own car, the driving behavior decision of the own car at this time is e ₄ .

In one embodiment, the driving environment where the driving behavior decision of the self _- vehicle is e5 includes:

1. When the own car is in the driving environment where s ₃ , p ₈ , c ₁ , and o ₆ exist at the same time, since the driving behavior of other cars has no influence on the driving behavior of the own car, the driving behavior decision of the own car at this time is: e ₅ .

2. The self-vehicle is in a driving environment where s ₃ , p ₈ , c ₂ , and o ₅ exist at the same time. Since the driving behavior of other vehicles will not affect the self-vehicle's driving out of the parking space, the driving behavior decision of the self-vehicle at this time is e ₅ .

3. When the own car is in the driving environment where s ₃ , p ₉ , and d ₁ exist at the same time, since the driving behavior of other cars will not affect the driving behavior of the own car, the driving behavior decision of the own car at this time is e ₅ .

The embodiment of the present invention also provides an intelligent vehicle decision system based on a parking lot scene, which includes a driving scene judgment unit, a driving state judgment unit, and a parking decision unit.

The driving scene judgment unit is used to perceive the driving scene where the vehicle is located after entering the parking decision system, and determine whether it is in the parking lot scene S:

S={s _i |i=1,2,3}

Among them, s ₁ represents a straight lane, s ₂ represents an intersection, and s ₃ represents a parking space.

The driving state judging unit is configured to judge whether the self-vehicle is in the driving process when the driving scene judging unit determines that the self-vehicle is in the parking lot scene S.

The parking decision unit is used to determine the position relationship P between the other car and the own vehicle, the distance relationship D between the other vehicle and the own vehicle, and the One or more of the driving direction relationship C, the speed relationship V between the other car and the own car, and the parking driving behavior O of the other car, make decisions on the parking driving behavior E of the own car, and use it in all The driving scene determination unit determines that the vehicle is not in the parking lot scene S or the driving state determination unit determines that the vehicle is not in the driving process to exit.

In the parking lot scenario, the positional relationship P between his car and his own car includes the following nine types:

P={pi | _i =1,2,…9}

Among them, p ₁ means that the other car is located in front of the same lane of the own vehicle, p ₂ means that the other car is located in front of the adjacent lane of the own vehicle, p ₃ means that the other car is located in the back of the same lane of the own vehicle, p ₄ means that the other car is located in the own vehicle The rear of the adjacent lane, p ₅ means that the other car is located on the side of the own vehicle, p ₆ means that the other car is located in the parking space in front of the driving lane of the own vehicle, p ₇ means that the other car is located in the parking space behind the driving lane of the own vehicle , p ₈ means that his car is located in the adjacent parking space of the own car's parking space, p ₉ means that his car is in the lane in front of the own car's parking space.

In the parking lot scenario, the distance relationship D between his car and his own car includes the following two:

D={d _i |i=1,2}

Among them, d ₁ indicates that the distance between the other vehicle and the own vehicle is greater than or equal to the safety distance d, and d ₂ indicates that the distance between the other vehicle and the own vehicle is greater than or equal to the safety distance d. The specific value of d can be considered to be set according to the vehicle size parameters.

In the parking lot scenario, the relationship C between the driving direction of the other car and the own car includes the following three types:

C={ci | _i =1,2,3}

Among them, c ₁ represents the same direction, c ₂ represents the reverse direction, and c ₃ represents the vertical direction.

In the parking lot scenario, the speed relationship V between the other car and the own car includes the following three types:

V={v _i |i=1,2,3}

Among them, v ₁ means that the speed of his car is greater than that of the own car, v ₂ means that the speed of his car is lower than that of the own car, and v ₃ means that the speed of his car is the same as that of the own car.

In the parking lot scenario, his car's parking driving behavior O includes the following six types:

O={o _i |i=1,2,…,6}

Among them, o ₁ means going straight, o ₂ means changing lanes, o ₃ means turning, o ₄ means parking, o ₅ means driving into the parking space, o ₆ means driving out of the parking space.

In the parking lot scenario, the parking driving behavior E of the self-vehicle includes the following five types:

E={e _i |i=1,2,…5}

Among them, e ₁ represents autonomous cruise, e ₂ represents vehicle following, e ₃ represents parking waiting, e ₄ represents driving into the parking space, and e ₅ represents driving out of the parking space.

The embodiment of the present invention not only classifies the parking lot scenes, which can make the behavior decision of the intelligent vehicle easier, but also makes the self-vehicle behavior decision more realistic according to the driving behavior of other vehicles in different scenarios, which can improve the behavior of the parking lot. Parking efficiency and safety during vehicle travel.

In _one embodiment, the driving environment where the driving behavior decision of the self-vehicle is e1 includes:

1. When the self-vehicle is in a driving environment in which s ₁ , p ₁ , and d ₁ coexist, since the two vehicles are at a safe distance, the driving behavior of the other vehicle will not affect the self-vehicle, then the self-vehicle at this time The driving behavior decision is e ₁ .

2. When the own vehicle is in the driving environment where s ₁ , p ₁ , d ₂ , c ₁ , and v ₁ exist at the same time, although the two vehicles are within a safe distance, the speed of the other vehicle is greater than that of the own vehicle, and the speed of the other vehicle is greater than that of the own vehicle. The distance between them is getting larger, then the driving behavior decision of the self-vehicle at this time is e ₁ .

3. When the own car is in a driving environment in which one of p ₂ , p ₃ , p ₄ , p ₅ , and p ₇ coexists with s ₁ , because in these interactive relationships, the driving behavior of the other car If the driving behavior of the self-vehicle is not affected, the driving behavior decision of the self-vehicle at this time is e ₁ .

4. Under the circumstance that the own car is in a driving environment where s ₁ , p ₆ , and d ₁ exist at the same time, since the two cars are at a safe distance, the driving behavior of the other car will not affect the driving behavior of the own car, then this The driving behavior decision of the ego vehicle is e ₁ .

5. When the self-vehicle is in a driving environment where s ₂ , p ₂ , c ₂ , and o ₁ coexist, since the trajectories of the two vehicles do not intersect, the self-vehicle's driving behavior decision at this time is e ₁ .

6. In a situation where the ego car is in a driving environment in which one of p ₃ , p ₄ and p ₇ coexists with s ₂ , because in these interaction relationships, the driving behavior of the ego car will not affect the ego car's driving. If the behavior affects, then the driving behavior decision of the ego vehicle at this time is e ₁ .

In one embodiment, the driving environment where the driving behavior decision of the self-vehicle is e ₂ includes:

1. When the self-vehicle is in a driving environment where s ₁ , p ₁ , d ₂ , c ₁ , v ₂ or v ₃ , and o ₁ or o ₂ exist at the same time, since the two vehicles are within a safe distance, and at this time The distance is decreasing or unchanged, and the driving behavior of the other car will affect the speed of the own car, then the driving behavior decision of the own car at this time is e ₂ . Among them, "v ₂ or v ₃ " can be understood as an alternative choice, and "o ₁ or o ₂ " can be understood as an alternative choice.

2. When the ego car is in a driving environment where s ₂ , p ₁ , and c ₁ exist at the same time, since the other car is located in front of the ego car, the driving behavior of the ego car will affect the speed of the ego car, then the ego car is The driving behavior decision of the car is e ₂ .

In one embodiment, the driving environment where the driving behavior decision of the self-vehicle is _e3 includes:

1. When the self-vehicle is in a driving environment where s ₁ , p ₁ , d ₂ , c ₁ , v ₂ or v ₃ , and o ₅ or o ₆ exist at the same time, since the two vehicles are within a safe distance, the other vehicle is driving. The driving behavior of entering/exiting the parking space will affect the driving behavior of the self-vehicle, and the driving behavior decision of the self-vehicle at this time is e ₃ . Among them, "or" means to choose one.

2. When the own vehicle is in a driving environment where s ₁ , p ₁ , d ₂ , and c ₂ exist at the same time, since the two vehicles are within a safe distance and drive in the opposite direction in the same lane, the driving behavior of the other vehicle will affect the driving behavior of the other vehicle. If the driving behavior of the ego car affects, then the driving behavior decision of the ego car at this time is e ₃ .

3. When the own vehicle is in a driving environment where s ₁ , p ₆ , and d ₂ exist at the same time, since the two vehicles are within a safe distance and the other vehicle is in the parking space in front of the own vehicle, the driving behavior of the other vehicle will be affected. If the driving behavior of the own vehicle is affected, the driving behavior decision of the own vehicle at this time is e ₃ .

4. When the own vehicle is in a driving environment where s ₂ , p ₁ , and c ₃ coexist, since the other vehicle is in front of the own vehicle and the driving direction is vertical, the own vehicle needs to wait for the other vehicle to pass first, then this The driving behavior decision of the ego vehicle is e ₃ .

5. When the self-vehicle is in a driving environment where s ₂ , p ₂ , c ₂ , and o ₃ exist at the same time, since the trajectories of the two vehicles will intersect, the self-vehicle needs to wait for the other vehicle to pass first. The driving behavior decision is e ₃ .

6. When the self-vehicle is in the driving environment where s ₂ , p ₂ , and c ₃ exist at the same time, since the trajectories of the two vehicles will intersect, the self-vehicle needs to wait for the other vehicle to pass by first. At this time, the self-vehicle's driving behavior decision is: e ₃ .

7. When the own car is in a driving environment where s ₃ , p ₈ , c ₂ , and o ₆ exist at the same time, since the driving behavior of other cars will have an impact on the driving behavior of the own car, the driving behavior of the own car is decided at this time is e ₃ .

8. When the self-vehicle is in the driving environment that exists when s ₃ , p ₉ , and d ₂ , since the two vehicles are within a safe distance and there is a possibility of collision, the driving behavior decision of the self-vehicle at this time is e ₃ .

In one embodiment, the driving environment where the driving behavior decision of the self _- vehicle is e4 includes:

1. When the own car is in a driving environment where s ₃ , p ₈ , c ₁ , and o ₅ exist at the same time, since the behavior of other cars will not affect the own car's driving into the parking space, the driving behavior of the own car is decided at this time is e ₄ .

2. When the own car is in the driving environment where s ₃ , p ₈ , c ₁ , and o ₆ exist at the same time, since the driving behavior of other cars has no influence on the driving behavior of the own car, the driving behavior decision of the own car at this time is: e ₄ .

3. When the own car is in the driving environment where s ₃ , p ₉ , and d ₁ exist at the same time, since the driving behavior of other cars will not affect the driving behavior of the own car, the driving behavior decision of the own car at this time is e ₄ .

In one embodiment, the driving environment where the driving behavior decision of the self _- vehicle is e5 includes:

1. When the own car is in the driving environment where s ₃ , p ₈ , c ₁ , and o ₆ exist at the same time, since the driving behavior of other cars has no influence on the driving behavior of the own car, the driving behavior decision of the own car at this time is: e ₅ .

2. The self-vehicle is in a driving environment where s ₃ , p ₈ , c ₂ , and o ₅ exist at the same time. Since the driving behavior of other vehicles will not affect the self-vehicle's driving out of the parking space, the driving behavior decision of the self-vehicle at this time is e ₅ .

3. When the own car is in the driving environment where s ₃ , p ₉ , and d ₁ exist at the same time, since the driving behavior of other cars will not affect the driving behavior of the own car, the driving behavior decision of the own car at this time is e ₅ .

Finally, it should be pointed out that the above embodiments are only used to illustrate the technical solutions of the present invention, but not to limit them. It should be understood by those of ordinary skill in the art that the technical solutions described in the foregoing embodiments can be modified, or some of the technical features thereof can be equivalently replaced; these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the various aspects of the present invention. The spirit and scope of the technical solutions of the embodiments.

Claims (12)

1. An intelligent vehicle decision-making method based on a parking lot scene is characterized by comprising the following steps:

step 1, entering a parking decision system, sensing a driving scene of a self-vehicle, judging whether the self-vehicle is in a parking lot scene S, and if so, entering step 2; if not, entering step 4;

S＝{s_i|i＝1，2，3}

wherein s is₁Indicating a straight-through lane, s₂Indicates a crossroad, s₃Representing a parking space;

step 2, judging whether the self vehicle is in the driving process, if so, entering the step 3; if not, entering step 4;

step 3, making a decision on the parking driving behavior E of the self-vehicle according to one or more of the position relation P between the other vehicle and the self-vehicle, the distance relation D between the other vehicle and the self-vehicle, the driving direction relation C between the other vehicle and the self-vehicle, the speed relation V between the other vehicle and the self-vehicle and the parking driving behavior O of the other vehicle;

P＝{p_i|i＝1，2，…9}

wherein p is₁Indicating that the other vehicle is located in front of the same lane as the own vehicle, p₂Indicating that the other vehicle is located in front of the adjacent lane of the own vehicle, p₃Indicating that the other vehicle is located behind the same lane as the own vehicle, p₄Indicating that the other vehicle is located behind the adjacent lane of the own vehicle, p₅Indicating that he is parked on his side of the vehicle, p₆Indicating that his car is in a parking space in front of the side of the lane on which the car is driving, p₇Indicating that other vehicle is located in a parking space laterally behind the driving lane of the host vehicle, p₈Indicating that his car is located in a parking space adjacent to the parking space in which the own car is located, p₉Indicating that the other vehicle is positioned on the lane in front of the parking space of the own vehicle;

D＝{d_i|i＝1，2}

wherein d is₁Indicating that the distance between the other vehicle and the own vehicle is less than the safety distance, d₂The distance between the other vehicle and the self vehicle is larger than or equal to the safe distance;

C＝{c_i|i＝1，2，3}

wherein, c₁Denotes the same direction, c₂Denotes the reverse direction, c₃Represents a vertical direction;

V＝{v_i|i＝1，2，3}

wherein v is₁Indicating that the speed of other vehicle is greater than that of own vehicle, v₂Indicating that the speed of other vehicle is less than that of own vehicle, v₃Indicating that the speed of other vehicles is the same as that of the own vehicle;

O＝{o_i|i＝1，2，…，6}

wherein o is₁Denotes straight going, o₂Indicates a lane change, o₃Indicates a turn o₄Indicating parking, o₅Indicating entry into a parking space, o₆Indicating exiting the parking space;

the parking driving behaviors of the own vehicle include the following five behaviors:

E＝{e_i|i＝1，2，…5}

wherein e is₁Indicating autonomous cruising, e₂Indicating vehicle following, e₃Indicating a parking wait, e₄Indicating entry into a parking space, e₅Indicating exiting the parking space;

and 4, exiting the parking decision system.

2. The intelligent vehicle decision-making method based on parking lot scene as claimed in claim 1, wherein the driving behavior decision of the self vehicle is e₁The driving environment of (a) includes:

a1. the bicycle is at s₁、p₁And d₁Simultaneous driving environment;

a2. the bicycle is at s₁、p₁、d₂、c₁And v₁Simultaneous driving environment;

a3. the bicycle is at p₂、p₃、p₄、p₅And p₇And s₁Simultaneous driving environment;

a4. the bicycle is at s₁、p₆And d₁Simultaneous driving environment;

a5. the bicycle is at s₂、p₂、c₂And o₁Simultaneous driving environment;

a6. the bicycle is at p₃、p₄And p₇And s₂Simultaneous driving environment.

3. The intelligent vehicle decision-making method based on parking lot scene as claimed in claim 1, wherein the driving behavior decision of the self vehicle is e₂The driving environment of (a) includes:

b1. the bicycle is at s₁、p₁、d₂、c₁、v₂Or v₃And o₁Or o₂Simultaneous driving environment;

b2. the bicycle is at s₂、p₁And c₁Simultaneous driving environment.

4. The intelligent vehicle decision method based on parking lot scene as claimed in any one of claims 1 to 3, characterized in that the driving behavior decision of the vehicle is e₃The driving environment of (a) includes:

c1. the bicycle is at s₁、p₁、d₂、c₁、v₂Or v₃And o₅Or o₆Simultaneous driving environment;

c2. the bicycle is at s₁、p₁、d₂And c₂Simultaneous driving environment;

c3. the bicycle is at s₁、p₆And d₂Simultaneous driving environment;

c4. the bicycle is at s₂、p₁And c₃Simultaneous driving environment;

c5. the bicycle is at s₂、p₂、c₂And o₃Simultaneous driving environment;

c6. the bicycle is at s₂、p₂And c₃Simultaneous driving environment;

c7. the bicycle is at s₃、p₈、c₂And o₆Simultaneous driving environment;

c8. the bicycle is at s₃、p₉And d₂The driving environment that exists.

5. The intelligent vehicle decision-making method based on parking lot scene as claimed in claim 4, wherein the driving behavior decision of the self vehicle is e₄The driving environment of (a) includes:

d1. the bicycle is at s₃、p₈、c₁And o₅Simultaneous driving environment;

d2. the bicycle is at s₃、p₈、c₁And o₆Simultaneous driving environment;

d3. the bicycle is at s₃、p₉And d₁Simultaneous driving environment.

6. The intelligent vehicle decision-making method based on parking lot scene as claimed in claim 4, wherein the driving behavior decision of the self vehicle is e₅The driving environment of (a) includes:

f1. the bicycle is at s₃、p₈、c₁And o₆Simultaneous driving environment;

f2. the bicycle is at s₃、p₈、c₂And o₅Simultaneous driving environment;

f3. the bicycle is at s₃、p₉And d₁Simultaneous driving environment.

7. The utility model provides an intelligent vehicle decision-making system based on parking area scene, its characterized in that includes:

the driving scene judging unit is used for sensing a driving scene where the self-vehicle is located after entering the parking decision system and judging whether the self-vehicle is located in a parking lot scene S; if not, entering step 4;

S＝{s_i|i＝1，2，3}

wherein s is₁Indicating a straight-through lane, s₂Indicates a crossroad, s₃Representing a parking space;

a driving state judgment unit for judging whether the vehicle is in the driving process or not under the condition that the driving scene judgment unit judges that the vehicle is in the parking lot scene S, and if so, entering the step 3; if not, entering step 4;

a parking decision unit for deciding a parking driving behavior E of the own vehicle according to one or more of a positional relationship P between the own vehicle and the own vehicle, a distance relationship D between the own vehicle and the own vehicle, a driving direction relationship C between the own vehicle and the own vehicle, a speed relationship V between the own vehicle and the own vehicle, and a parking driving behavior O of the own vehicle in a case where the driving state determination unit determines that the own vehicle is in the driving process, and for exiting in a case where the driving scene determination unit determines that the own vehicle is not in the parking lot scene S or in a case where the driving state determination unit determines that the own vehicle is not in the driving process;

P＝{p_i|i＝1，2，…9}

wherein p is₁Indicating that the other vehicle is located in front of the same lane as the own vehicle, p₂Indicating that the other vehicle is located in front of the adjacent lane of the own vehicle, p₃Indicating that the other vehicle is located behind the same lane as the own vehicle, p₄Indicating that the other vehicle is located behind the adjacent lane of the own vehicle, p₅Indicating that he is parked on his side of the vehicle, p₆Indicating that his car is in a parking space in front of the side of the lane on which the car is driving, p₇Indicating that other vehicle is located in a parking space laterally behind the driving lane of the host vehicle, p₈Indicating that his car is located in a parking space adjacent to the parking space in which the own car is located, p₉Indicating that the other vehicle is positioned on the lane in front of the parking space of the own vehicle;

D＝{d_i|i＝1，2}

wherein d is₁Indicating that the distance between the other vehicle and the own vehicle is greater than or equal to the safety distance, d₂The distance between the other vehicle and the self vehicle is larger than or equal to the safe distance;

C＝{c_i|i＝1，2，3}

wherein, c₁Denotes the same direction, c₂Denotes the reverse direction, c₃Represents a vertical direction;

V＝{v_i|i＝1，2，3}

wherein v is₁Indicating that the speed of other vehicle is greater than that of own vehicle, v₂Indicating that the speed of other vehicle is less than that of own vehicle, v₃Indicating that the speed of other vehicles is the same as that of the own vehicle;

O＝{o_i|i＝1，2，…，6}

wherein o is₁Denotes straight going, o₂Indicates a lane change, o₃Indicates a turn o₄Indicating parking, o₅Indicating entry into a parking space, o₆Indicating exiting the parking space;

the parking driving behaviors of the own vehicle include the following five behaviors:

E＝{e_i|i＝1，2，…5}

wherein e is₁Indicating autonomous cruising, e₂Indicating vehicle following, e₃Indicating a parking wait, e₄Indicating entry into a parking space, e₅Indicating exiting the parking space.

8. The intelligent vehicle decision making system based on parking lot scene as claimed in claim 7, wherein the driving behavior decision of the self vehicle is e₁The driving environment of (a) includes:

a1. the bicycle is at s₁、p₁And d₁Simultaneous driving environment;

a2. the bicycle is at s₁、p₁、d₂、c₁And v₁Simultaneous driving environment;

a3. the bicycle is at p₂、p₃、p₄、p₅And p₇And s₁Simultaneous driving environment;

a4. the bicycle is at s₁、p₆And d₁Simultaneous driving environment;

a5. the bicycle is at s₂、p₂、c₂And o₁Simultaneous driving environment;

a6. the bicycle is at p₃、p₄And p₇And s₂Simultaneous driving environment.

9. The intelligent vehicle decision making system based on parking lot scene as claimed in claim 8, wherein the driving behavior decision of the self vehicle is e₂The driving environment of (a) includes:

b1. the bicycle is at s₁、p₁、d₂、c₁、v₂Or v₃And o₁Or o₂Simultaneous driving environment;

b2. the bicycle is at s₂、p₁And c₁Simultaneous driving environment.

10. The intelligent vehicle decision making system based on parking lot scene as claimed in any one of claims 7 to 9, wherein the driving behavior decision of the vehicle is e₃The driving environment of (a) includes:

c1. the bicycle is at s₁、p₁、d₂、c₁、v₂Or v₃And o₅Or o₆Simultaneous driving environment;

c2. the bicycle is at s₁、p₁、d₂And c₂Simultaneous driving environment;

c3. the bicycle is at s₁、p₆And d₂Simultaneous driving environment;

c4. the bicycle is at s₂、p₁And c₃Simultaneous driving environment;

c5. the bicycle is at s₂、p₂、c₂And o₃Simultaneous driving environment;

c6. the bicycle is at s₂、p₂And c₃Simultaneous driving environment;

c7. the bicycle is at s₃、p₈、c₂And o₆Simultaneous driving environment;

c8. the bicycle is at s₃、p₉And d₂The driving environment that exists.

11. The intelligent vehicle decision making system based on parking lot scene as claimed in claim 10, wherein the driving behavior decision of the own vehicle is e₄The driving environment of (a) includes:

d1. the bicycle is at s₃、p₈、c₁And o₅Simultaneous driving environment;

d2. the bicycle is at s₃、p₈、c₁And o₆Simultaneous driving environment;

d3. the bicycle is at s₃、p₉And d₁Simultaneous driving environment.

12. The intelligent vehicle decision making system based on parking lot scene as claimed in claim 10, wherein the driving behavior decision of the own vehicle is e₅The driving environment of (a) includes:

f1. the bicycle is at s₃、p₈、c₁And o₆Simultaneous driving environment;

f2. the bicycle is at s₃、p₈、c₂And o₅Simultaneous driving environment;

f3. the bicycle is at s₃、p₉And d₁Simultaneous driving environment.

Images