2023
DOI: 10.3390/s23020814
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Vehicle and Driver Monitoring System Using On-Board and Remote Sensors

Abstract: This paper presents an integrated monitoring system for the driver and the vehicle in a single case of study easy to configure and replicate. On-board vehicle sensors and remote sensors are combined to model algorithms for estimating polluting emissions, fuel consumption, driving style and driver’s health. The main contribution of this paper is the analysis of interactions among the above monitored features highlighting the influence of the driver in the vehicle performance and vice versa. This analysis was ca… Show more

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Cited by 11 publications
(4 citation statements)
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References 69 publications
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“…Deep learning framework that analyze CAN-BUS data have been successful in identifying different driving behaviors [9]. Monitoring systems in vehicles that utilize principal component analysis can track fuel consumption, emissions, driving style, and driver health in real-time effectively [10]. Additionally, energy efficiency in rail vehicles is being optimized by detecting energy losses [11].…”
Section: Introductionmentioning
confidence: 99%
“…Deep learning framework that analyze CAN-BUS data have been successful in identifying different driving behaviors [9]. Monitoring systems in vehicles that utilize principal component analysis can track fuel consumption, emissions, driving style, and driver health in real-time effectively [10]. Additionally, energy efficiency in rail vehicles is being optimized by detecting energy losses [11].…”
Section: Introductionmentioning
confidence: 99%
“…Among others, a method has been developed to detect driving habits using single turn vehicle sensor data (Hallac et al 2016). Human-vehicle interaction analysis systems can monitor fuel consumption, CO 2 emissions, driving style and driver health in real-time with high predictive reliability (Campos-Ferreira et al 2023). Several behavioural analyses, mainly using the Driver Behaviour Questionnaire, have shown that professional drivers engage in less risky behaviour than non-professional drivers, but are more likely to be involved in traffic accidents due to longer driving time (Maslać et al 2018).…”
Section: Introductionmentioning
confidence: 99%
“…In the realm of vehicle technologies research, the focus has been on developing smart systems to enhance vehicle efficiency and driver experience. Recent studies have leveraged smartphones for robust data collection, marking a shift towards comprehensive assessments of vehicle performance and driver behavior [4]. Hence, researchers and transportation experts strive to enhance road safety and reduce accidents.…”
mentioning
confidence: 99%