Real-time Crash Detection and Its Application in Incident Reporting and Accident Reconstruction

2017-01-1419

03/28/2017

Features
Event
WCX™ 17: SAE World Congress Experience
Authors Abstract
Content
Characterizing or reconstructing incidents ranging from light to heavy crashes is one of the enablers for mobility solutions for fleet management, car-sharing, ride-hailing, insurance etc. While crashes involving airbag deployment are noticeable, light crashes without airbag deployment can be hidden and most drivers do not report these incidents. In this paper, we are using vehicle responses together with a dynamics model to trace back if abnormal forces have been applied to a vehicle so as to detect light crashes. The crash location around the perimeter of the vehicle, the direction of the crash force, and the severity of the crashes are all determined in real-time based on on-board sensor measurements which has further application in accident reconstruction. All of this information will be integrated to a feature called “Incident Report”, which enable reporting of minor accidents to the relevant entities such as insurance agencies, fleet managements, etc. The developed algorithms are being pursued for implementation in a wireless on-board-diagnostic (OBD) dongle using the hardware specific Java format. CAN-bus data, accessed through OBD-II port, are from on-board sensors and the information originated from the control functions such as ABS, TCS, ESC, and/or RCM. The impact triggers are first detected and confirmed, the computed variables are then transferred to the cloud. At this moment, the incident report algorithm, has been developed and verified in CARSIM simulation environment, and is implemented in real-time Java environment.
Meta TagsDetails
DOI
https://doi.org/10.4271/2017-01-1419
Pages
15
Citation
Panigrahi, S., Lu, J., and Hong, S., "Real-time Crash Detection and Its Application in Incident Reporting and Accident Reconstruction," SAE Technical Paper 2017-01-1419, 2017, https://doi.org/10.4271/2017-01-1419.
Additional Details
Publisher
Published
Mar 28, 2017
Product Code
2017-01-1419
Content Type
Technical Paper
Language
English