Eventos Anais de eventos
COBEM 2023
27th International Congress of Mechanical Engineering
Implementation of a vehicle dynamics data acquisition system on a scale prototype to detect dangerous driving patterns
Submission Author:
Vinicius Marini , RS
Co-Authors:
Caio Gabriel Vicentin, Julia Kerkoff Ladeira, Kays Abur, Valdemo Vilino Kahl Junior, Luciano de Souza Oliveira, André Costa, Nathan Pereira, Álisson Henrique Kolling, Matheus João Silva de Almeida, Marcia Pasin, Vinicius Marini
Presenter: André Costa
doi://10.26678/ABCM.COBEM2023.COB2023-0237
Abstract
A stronger demand for mobility causes increased risks to the lives of occupants inside vehicles, and pedestrians, so there is a need to monitor the dynamic parameters regarding driving behaviour that risks the integrity of the vehicle and its occupants. In this context, the aim of this paper is to demonstrate the modelling and implementation of a vehicle dynamics data acquisition system based on a scale vehicle prototype, whose design intent is the recognition of dangerous driving patterns. While currently available vehicle dynamics control systems involve the necessary sensing resources, there is still a need to recognize driving hazards and thus improve the ability to mitigate them. The article begins with reviewing the state-of-the-art in vehicle sensing technologies and driving behavior recognition, and proceeds with the methodology about selecting the scale vehicle platform, followed by the installation of the respective devices and the data processing technique. This enables the implementation of the vehicle dynamics data acquisition system on a scale vehicle prototype for collecting dynamic data. While monitoring requirements were captured based on the recognition of current technologies, the team kept in mind the implementation of a vehicle system at scale. The data acquisition system consists of in-vehicle ordinary sensors, capable of collecting dynamic data. Data collection on the dynamic behaviour of the vehicle is done successfully, with prospects to improve data accuracy at scale and route implementation in real vehicles. There is, however, in future works, the need of establish dynamic patterns representing dangerous driving circumstances, and required processing systems dedicated to the recognition and communication of such data, internally and externally to the vehicle.
Keywords
Vehicle Dynamics, Data acquisition, Dangerous Driving, Pattern analysis
