Simultaneous Estimation of Vehicle Sideslip and Roll Angles Using an Event-Triggered-Based IoT Architecture

Abstract

In recent years, there has been a significant integration of advanced technology into the automotive industry, aimed primarily at enhancing safety and ride comfort. While a notable proportion of these driver-assist systems focuses on skid prevention, insufficient attention has been paid to addressing other crucial scenarios, such as rollovers. The accurate estimation of slip and roll angles plays a vital role in ensuring vehicle control and safety, making these parameters essential, especially with the rise of modern technologies that incorporate networked communication and distributed computing. Furthermore, there exists a lag in the transmission of information between the various vehicle systems, including sensors, actuators, and controllers. This paper outlines the design of an IoT architecture that accurately estimates the sideslip angle and roll angle of a vehicle, while addressing network transmission delays with a networked control system and an event-triggered communication scheme. Experimental results are presented to validate the performance of the IoT architecture proposed. The event-triggered scheme of the IoT solution is used to decrease data transmission and prevent network overload.

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“…It is also crucial to mention that vehicle rollover and sideslip impact driving behaviour and, therefore, car instability, contributing to a significant number of fatal accidents [40,41]. Fernando et al [42] developed an IoT (Internet of Things) system to estimate the precise vehicle rollover and sideslip angle by taking into account the communication delay, with the aim of improving driving comfort and safety. Arslan et al [43] proposed a non-linear predictive controller that constantly diminishes the tracking error and avoids the vehicle rollover.…”