Pre-Crash System for Reliable Automatic Crash Notification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The eCall system fails to perform its intended function if the eCall module in a vehicle experiences a failure, preventing the transmission of critical data during an accident.
Innovation Solution
A method is implemented in user equipment that utilizes a pre-crash system to sense potential accidents, initiating a pre-emergency call procedure, transmitting minimum data to the network, and confirming the occurrence of an accident within a time window.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the eCall module is used for emergency notifications, then the notification function is provided, but the system fails when the eCall module experiences failure
Solution Approach 1:
The patent implements a pre-crash system that performs preliminary actions by detecting potential accidents before they occur and initiating the eCall procedure in advance. The system senses inputs (such as brake pedal pressure, steering angle, airbag deployment status) and predicts collision probability using learning-based models, triggering the emergency call before the actual crash happens. This preliminary action ensures the eCall module is activated and data transmission is prepared before any module failure can occur during the accident.
Solution Approach 2:
The patent introduces an intermediary mechanism that acts as a mediator between the pre-crash sensing system and the eCall module. This intermediary includes a learning-based prediction model that processes sensor inputs, calculates collision probability, and determines whether to trigger the eCall procedure. The intermediary layer ensures reliable data collection and transmission by coordinating between the sensing function, prediction algorithm, and eCall module, thereby maintaining system reliability even if any single component fails.
2Speed
If the pre-crash system transmits data before accident confirmation, then the notification speed is improved, but false transmissions may occur
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors accident status and uses learning-based predictions to adjust the eCall trigger decisions. The learning model processes feedback from sensor inputs (brake pressure, steering angle, airbag status) and updates its collision probability assessment in real-time. This feedback loop allows the system to confirm whether a transmission should be initiated based on the actual accident occurrence, preventing false transmissions while maintaining fast notification speed through continuous monitoring and adaptive decision-making.
Data Source
AI summary
A method and apparatus for triggering advanced automatic collision notification (AACN) using learning-based pre-crash system in a wireless communication system is provided. A user equipment obtains inputs from a pre-crash system (PCS) sensing function (PCSSF) in the user equipment, initiates a pre-emergency call procedure upon receiving, from the PCSSF, a PCS sensing indication informing that an accident has been estimated to happen based on the obtained inputs, transmits, to a network, a minimum set of data (MSD) in the pre-emergency call procedure. The UE checks whether the accident happens for a time window and transmits, to the network, a report based on whether the accident has happened or not.