COMPUTATIONALLY EFFICIENT INTERSECTION COLLISION AVOIDANCE SYSTEM

• US 20120330542A1
• Filed: 07/13/2012
• Published: 12/27/2012
• Est. Priority Date: 06/09/2010
• Status: Active Grant

• Current Assignee: Toyota Jidosha Kabushiki Kaisha (Toyota Motor Corporation), Board of Regents of the University of Michigan (University of Michigan)
• Original Assignee: Toyota Motor Engineering & Manufacturing North America Incorporated (Toyota Motor Corporation), Board of Regents of the University of Michigan (University of Michigan)
• Inventors: Caminiti, Lorenzo, Hafner, Michael Robert, Cunningham, Drew, Del Vecchio, Domitilla
• Granted Patent: US 8,965,676 B2
• Time in Patent Office: Days
• US Class Current: 701/301
• CPC Class Codes: G08G 1/163 involving continuous checking

Abstract

A back-propagating intersection collision avoidance system is provided. The system can include a first vehicle and a second vehicle, the first and second vehicles each operable to approach an intersection at a definable velocity and acceleration. In addition, the intersection can have a collision zone in which the first and second vehicles will collide if they are present there at the same time. The first vehicle can have a processing unit with a controller and a microprocessor, the microprocessor having an algorithm with a disturbance model. The processing unit is operable to back-propagate from the collision zone a capture set as a function of a disturbance for the first and second vehicles.

Claims

1. A back propagating intersection collision avoidance system for preventing two vehicles from colliding at an intersection, said system comprising:

a first vehicle and a second vehicle, said first and second vehicle each operable to approach an intersection at a definable velocity and acceleration, said intersection having a collision zone in which said first and second vehicle will collide if present at a same time;

said first vehicle having a processing unit with controller and a microprocessor with an algorithm, said algorithm having a disturbance model and said processing unit operable to back propagate from said collision zone a capture set as a function of a disturbance for said first and second vehicle, determine if said first and second vehicle is within said capture set, and if not, determine if said first and second vehicle will enter said capture set;

said processing unit also operable to instruct said controller to accelerate or de-accelerate said first vehicle in order to prevent said first vehicle from entering said capture set.

2. The system of claim 1, wherein said processing unit with said disturbance model is operable to calculate said disturbance as a function of uncertainty from at least one of:

actuator delays for said first vehicle;

actuator delays far said second vehicle;

discrete time steps used by said microprocessor and said algorithm;

communication time delays;

vehicle dynamics for said first vehicle; and

vehicle dynamics for said second vehicle.

3. The system of claim 2, wherein said processing unit with said disturbance model is operable to calculate a worst case scenario for at least one of said first vehicle and said second vehicle.

4. The system of claim 3, wherein said processing unit with said disturbance model is operable to calculate a disturbance as a function of at least one of:

current dynamics of said first vehicle not known entirely;

current dynamics of said second vehicle not known entirely;

a current state of said first and second vehicle not known due to a communication delay;

a current state of said first and second vehicle not known due to at least one sensor noise; and

a current state of said second vehicle not known due to said second vehicle being a non-communicating vehicle.

5. The system of claim 4, wherein said processing unit with disturbance model are operable to calculate said second vehicle as a complete disturbance when said second vehicle is a non-communicating vehicle.

6. The system of claim 1, wherein said processing unit with said disturbance model is operable to calculate said capture set as a function of a disturbance signal and a time.

7. The system of claim 6, wherein said capture set (C) is:

C;

={xε

X|∀

uε

S(U), ∃

δ

ε

S(Δ

), and ∃

t>

0 such that φ

(t,x,u,δ

)ε

B}

where x is a distance, X is all possible x, u is an input signal, S(U) is the set of all causal input signals, t is time, δ

is a disturbance signal, S(Δ

) is the set of all admissible disturbance signals and B is a bad set.

8. The system of claim 7, wherein said capture set for a fixed input signal is:

where R₊ is all possible positive real numbers.

9. The system of claim 8, wherein dynamics for a fixed input of are:

f(x,ū

)ε

f(x₂);

=[f(x₂,ū

,δ

_L),f(x₂,ū

,δ

_H)]

where is velocity.

10. The system of claim 9, wherein f(x₂, ū

, δ

_L) and f(x₂, ū

, δ

_H) are experimentally determined from data trials using a plurality of initial conditions and taking a worst case performance.