Forensic Analysis of Braking Classification Based on Acceleration, Jerk, and Velocity Data

Abstract

Nowadays, four-wheeled vehicles are equipped with an event data recorder (EDR) device to record sensors data. With advances in-memory technology, EDR provides evidence for forensic analysis after an accident happens, that uses information technology to facilitate forensic analysis to provide complete and valuable results using digital investigations. Several types of research have been conducted to reconstruct accidents from forensic data and Fuzzy Logic is an alternative method for classifying crash data taken from the accelerometer due to less complexity of implementation. Vehicle braking data is one of the most important evidence for digital investigation, since braking is a complex process determined by many factors, such as the condition of the vehicle, road construction, and the driver’s physiological condition. However, the existing digital investigation still process vehicle speed, deceleration, and varia- tion time of deceleration (known as a jerk) in separated manner to determine braking distance, driver response time, and braking category. The problem identified in this paper is how to use deceleration, velocity, and jerk to categorize the braking evidence forensic analysis. In this paper, forensic analysis is limited to produce forensic evident of braking events based on the collected data. The contribution of this paper is to propose a braking detection model by combining acceleration, speed, and jerk data into a Fuzzy Inference System. As a result, a forensic analysis of braking data can better understand the braking maneuvers, which can be further developed to identify the cause of the accident and provide recommendations on which actions to include in future analyses.