Method for automated reconstruction of a car's path during crash from GPS/INS data using a Kalman filter. (January 2018)

• Record Type: Journal Article
• Authors: Aldimirov, Marin; Arnaudov, Rumen
• Is Part Of: Advances in engineering software. Volume 115(2018)
• Page Start: 386
• Page End: 390
• Publication Date: 2018-01
• Subjects: Kalman filter -- Path reconstruction -- Accident investigation -- Inertial navigation -- Event data recorder; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2017.10.009
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights: A method for automated reconstruction of a car's path during crash is proposed. Reconstruction is made from EDR data by loosely-coupled Kalman filter in direct form. EDR data is preprocessed before being fed to the filter. The method can be used for remote reconstruction of accidents. The reconstructed path can help crash investigators for their expert reports. Abstract: This article presents a method for automated reconstruction of a car's path during crash. Unlike conventional methods, which rely on indirect measurements like tire marks, property damage, etc. and on human intervention, the presented method uses only data from direct measurements, made by an EDR device. The method is compatible with devices built with low cost MEMS sensors. The path reconstruction is done fully automated, using a Kalman filter, similar to the ones used in inertial navigation. The test results show that the method has practical value as a source of information for the final expert report in a car crash investigation. It can also be used to perform a remote crash reconstruction if the data is sent over e.g. mobile network, thus being of benefit even to emergency call center operators.