Contributory factors to the severity of single-vehicle rollover crashes on a mountainous area, generalized additive model

Rezapour, Mahdi; Ksaibati, Khaled

doi:10.1080/17457300.2021.2011927

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…Traffic accidents have a major socio-economic impact as they lead to both the loss of human lives and huge economic costs. According to global statistics, passengers in a rollover accident are 10 times more likely to die than those in a non-rollover accident, and this situation represents 33% of all passenger car crashes [1][2][3]. One line of action to prevent these accidents focuses on research into and the improvement of roll stability control systems, which are relevant for heavy vehicles [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

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

Viadero-Monasterio,

García,

Meléndez-Useros

et al. 2024

Machines

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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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Section: Introductionmentioning

confidence: 99%

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

Viadero-Monasterio,

García,

Meléndez-Useros

et al. 2024

Machines

View full text Add to dashboard Cite

show abstract

“…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.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Controller for Drivers’ Steering-Wheel Operating Behaviour in Haptic Assistive Driving System

Noubissie Tientcheu,

Du,

Djouani

et al. 2024

Electronics

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An advanced driver-assistance system (ADAS) is critical to driver–vehicle-interaction systems. Driving behaviour modelling and control significantly improves the global performance of ADASs. A haptic assistive system assists the driver by providing a specific torque on the steering wheel according to the driving–vehicle–road profile to improve the steering control. However, the main problem is designing a compensator dealing with the high-level uncertainties in different driving scenarios with haptic driver assistance, where different personalities and diverse perceptions of drivers are considered. These differences can lead to poor driving performance if not properly accounted for. This paper focuses on designing a data-driven model-free compensator considering various driving behaviours with a haptic feedback system. A backpropagation neural network (BPNN) models driving behaviour based on real driving data (speed, acceleration, vehicle orientation, and current steering angle). Then, the genetic algorithm (GA) optimises the integral time absolute error (ITEA) function to produce the best multiple PID compensation parameters for various driving behaviours (such as speeding/braking, lane-keeping and turning), which are then utilised by the fuzzy logic to provide different driving commands. An experiment was conducted with five participants in a driving simulator. During the second experiment, seven participants drove in the simulator to evaluate the robustness of the proposed combined GA proportional-integral-derivative (PID) offline, and the fuzzy-PID controller applied online. The third experiment was conducted to validate the proposed data-driven controller. The experiment and simulation results evaluated the ITAE of the lateral displacement and yaw angle during various driving behaviours. The results validated the proposed method by significantly enhancing the driving performance.

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Investigating the spatial heterogeneity of factors influencing speeding-related crash severities using correlated random parameter order models with heterogeneity-in-means

Yuan,

Ding,

Fang

et al. 2023

Transportation Letters

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Contributory factors to the severity of single-vehicle rollover crashes on a mountainous area, generalized additive model

Cited by 4 publications

References 18 publications

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

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

Data-Driven Controller for Drivers’ Steering-Wheel Operating Behaviour in Haptic Assistive Driving System

Investigating the spatial heterogeneity of factors influencing speeding-related crash severities using correlated random parameter order models with heterogeneity-in-means

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