Vehicle Collision Detection Using Multi-Threshold Acceleration Analysis

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Solution Overview

Problem

Existing collision detection systems in autonomous vehicles face challenges in accurately identifying both major and minor collisions due to noise in acceleration data, which can mask minor collisions and make detection difficult.

Innovation Solution

A collision detection system that categorizes occurrences based on unexpected changes in acceleration data, using threshold values and sensor data to differentiate between high-energy and low-energy collisions, and further re-categorizes based on additional sensor data to increase certainty, triggering appropriate responsive actions such as alerts and system adjustments.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If threshold-based collision detection is used, then major collisions can be detected, but minor collisions are masked by noise

Engineering Contradiction:
Improvecollision detection accuracyVSAvoidminor collision detection capability
Core Design Contradiction:
ReliabilityVSMeasurement precision

Solution Approach 1:

The patent segments collision detection into multiple categories (high-energy collisions, low-energy collisions, and indeterminate events) based on acceleration threshold levels. By dividing the detection space into distinct segments with different analysis approaches, the system can accurately detect both major collisions (using high thresholds) and minor collisions (using low thresholds and additional sensor data), thereby resolving the contradiction between reliability and measurement precision.

Inventive Principle:
Principle #1Segmentation

2Measurement precision

If additional sensors are deployed to detect minor collisions, then detection accuracy improves, but system cost increases

Engineering Contradiction:
Improveminor collision detection capabilityVSAvoidsensor system cost
Core Design Contradiction:
Measurement precisionVSDevice complexity

Solution Approach 1:

The patent makes existing vehicle sensors multi-functional by using them for both normal vehicle operation monitoring and collision detection. The acceleration sensors already present in the vehicle are utilized for collision detection across multiple energy levels, eliminating the need for additional dedicated collision sensors and thereby improving measurement precision without increasing device complexity.

Inventive Principle:
Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system uses the vehicle's existing sensor infrastructure to serve the additional function of collision detection. By leveraging data from sensors already deployed for vehicle control and monitoring, the system achieves accurate minor collision detection without requiring external investments in additional sensing equipment.

Inventive Principle:
Principle #25Self-service

3Measurement precision

If acceleration thresholds are lowered to detect minor collisions, then detection sensitivity increases, but false positives from noise increase

Engineering Contradiction:
Improveminor collision detection sensitivityVSAvoidfalse positive rate
Core Design Contradiction:
Measurement precisionVSReliability

Solution Approach 1:

The patent implements dynamic threshold selection and event categorization where the detection criteria adapt based on the magnitude of acceleration changes. The system dynamically adjusts its response based on whether the event falls into high-energy, low-energy, or indeterminate categories, allowing high sensitivity for minor collisions while maintaining reliability through adaptive classification and contextual analysis of sensor data patterns.

Inventive Principle:
Principle #15Dynamics

Data Source

PatentEP3523155B1Method and system for detecting vehicle collisions
Publication Date: 2024.01.24 WAYMO LLC
  • EP3523155B1 patent drawingFigure 1
  • EP3523155B1 patent drawingFigure 2A
  • EP3523155B1 patent drawingFigure 2B~2C

AI summary

The invention relates to a method and a system for detecting vehicle collisions. One or more computing devices may receive acceleration data of a vehicle and the expected acceleration data of the vehicle over a period of time. The one or more computing devices may determine a change in the vehicle's acceleration over the period of time, where the change in the vehicle's acceleration over the period of time is the difference between the expected acceleration data and the acceleration data. The one or more computing devices may detect an occurrence when the change in the vehicle's acceleration is greater than a threshold value and assign the occurrence into a collision category. Based on the assigned collision category, the one or more computing devices may perform a responsive action.