Accident severity estimation system for a vehicle

Patent metadata

Field	Value
Publication number	US-12488637-B2
Application number	US-202318503729-A
Country	US
Kind code	B2
Filing date	Nov 7, 2023
Priority date	Nov 7, 2023
Publication date	Dec 2, 2025
Grant date	Dec 2, 2025

Abstract

An accident severity estimation system for estimating the severity of an accident for a vehicle includes one or more microphones that capture a plurality of audio-based inputs indicative of verbal and non-verbal sounds emitted by one or more occupants of the vehicle. The accident severity estimation system also includes a vision system that captures a plurality of vision-based inputs representing image data indicative of the occupants, a motion-based input system that collects a plurality of motion-based inputs indicative of the motion of the vehicle during the accident, a thermal incident system that collects a plurality of thermal inputs indicative of thermal events within the vehicle, a propulsion system that provides a status-based input of the propulsion system of the vehicle, and one or more controllers.

First claim

What is claimed is:

1 . An accident severity estimation system for estimating the severity of an accident for a vehicle, the accident severity estimation system comprising:
one or more microphones that capture a plurality of audio-based inputs indicative of verbal and non-verbal sounds emitted by one or more occupants of the vehicle; a vision system that captures a plurality of vision-based inputs representing image data indicative of the occupants; a motion-based input system that collects a plurality of motion-based inputs indicative of the motion of the vehicle during the accident; a thermal incident system that collects a plurality of thermal inputs indicative of thermal events within the vehicle; a propulsion system that provides a status-based input of the propulsion system of the vehicle; and one or more controllers in electronic communication with the one or more microphones, the vision system, the motion-based input system, the thermal incident system, and the propulsion system, the one or more controllers executing instructions to:
combine the plurality of audio-based inputs based on at least a 2-value logic system to determine an audio-based indicator, the plurality of vision-based inputs based on the at least 2-value logic system to determine a vision-based indicator, and the plurality of thermal inputs based on the at least 2-value logic system to determine a thermal-based indicator, wherein the 2-value logic system is one of a binary logic system and a ternary logic system;
combine the plurality of motion-based inputs from the motion-based input system based on a weighted sum model to determine a motion-based indicator;
determine a propulsion-based indicator based on the status-based input;
estimate the severity of the accident based on the audio-based indicator, the vision-based indicator, the thermal-based indicator, the motion-based indicator, and the propulsion-based indicator, wherein the severity of the accident is based at least in part on an amount of acceleration the vehicle experiences during the accident;
determine one or more remedial actions based on at least the severity of the accident; and
instruct the vehicle to execute the one or more remedial actions, wherein the one or more remedial actions include one or more of the following: contacting emergency personnel, unlocking doors of the vehicle, lowering windows of the vehicle, sending an SOS signal to one or more vehicles that are located within a predefined radius from the vehicle, and contacting non-emergency personnel.

2 . The accident severity estimation system of claim 1 , wherein the one or more controllers execute instructions to:
estimate the severity of the accident the vehicle undergoes based on comparing values for the audio-based indicator, the vision-based indicator, the motion-based indicator, the thermal-based indicator, and the propulsion-based indicator that are stored in a look-up table.

3 . The accident severity estimation system of claim 1 , wherein the one or more controllers execute instructions to estimate the severity of the accident based on a fuzzy logic severity estimation technique.

4 . The accident severity estimation system of claim 3 , wherein the fuzzy logic severity estimation technique includes:
assigning a corresponding fuzzy value to each indicator based on a membership function; evaluating the corresponding fuzzy value for each of the indicators based on one or more fuzzy logic rules to determine a fuzzified output value, wherein the fuzzified output value indicates the severity of the accident and a truth value corresponding to the severity; and converting the fuzzified output value into the severity of the accident based on the truth value.

5 . The accident severity estimation system of claim 1 , wherein the one or more controllers execute instructions to select one or more remedial actions based on the severity of the accident, a thermal incident indicator, a water incident indicator, and a root cause probability indicator.

6 . The accident severity estimation system of claim 1 , wherein the propulsion system includes a battery pack that provides motive power to one or more electric motors.

7 . The accident severity estimation system of claim 6 , wherein the status-based input is a battery-based input indicating a health of the battery pack.

8 . The accident severity estimation system of claim 1 , wherein the propulsion system includes an internal combustion engine.

9 . The accident severity estimation system of claim 8 , wherein the status-based input includes an engine and location-based status input indicating a status of the internal combustion engine and a location input indicating a location of the vehicle.

10 . The accident severity estimation system of claim 1 , wherein the audio-based inputs include a non-speech-based input and a speech-based input.

11 . The accident severity estimation system of claim 1 , wherein the plurality of vision-based inputs include an in-vehicle input indicative of a visual status of the occupants within an interior cabin of the vehicle and out-vehicle input indicative of a visual status of an exterior of the vehicle and the occupants outside of the vehicle.

12 . The accident severity estimation system of claim 1 , wherein the thermal inputs include an in-cabin thermal input and an engine bay thermal input.

13 . The accident severity estimation system of claim 1 , wherein the plurality of motion-based inputs include one or more of the following: an acceleration and deceleration input, an impact angle input, a roll-over input, and a velocity change input.

14 . The accident severity estimation system of claim 13 , wherein the weighted sum model is expressed as:

I
motion

=

ω

M
⁢
1

×
M
⁢
1

+

ω

M
⁢
2

×
M
⁢
2

+

ω

M
3

×

M
3

+

ω

M
4

×
M
⁢
4

=
1

wherein ω M1 represents a first weighting factor corresponding to the acceleration and deceleration input M1, ω M2 represents a second weighting factor corresponding to the impact angle input M2, ω M3 represents a third weighting factor cor

Assignees

• Gm Global Tech Operations Llc

Inventors

• Khamis Alaa M
• Rafiei Ali
• Lin Chin-Hsu
• Warey Alok

Classifications

• G10L25/33

  using fuzzy logic · CPC title

• G06V20/56

  exterior to a vehicle by using sensors mounted on the vehicle · CPC title

• G06V20/59

  inside of a vehicle, e.g. relating to seat occupancy, driver state or inner lighting conditions · CPC title

• G10L25/51

  for comparison or discrimination · CPC title

• E05Y2900/55

  Windows · CPC title