Driver monitoring systems (DMS): The future of impaired driving management?

2021 ◽  
pp. 1-9
Author(s):  
Amie C. Hayley ◽  
Brook Shiferaw ◽  
Blair Aitken ◽  
Frederick Vinckenbosch ◽  
Timothy L. Brown ◽  
...  
2017 ◽  
Vol 372 (1734) ◽  
pp. 20160247 ◽  
Author(s):  
Davide M. Dominoni ◽  
Susanne Åkesson ◽  
Raymond Klaassen ◽  
Kamiel Spoelstra ◽  
Martin Bulla

Chronobiological research has seen a continuous development of novel approaches and techniques to measure rhythmicity at different levels of biological organization from locomotor activity (e.g. migratory restlessness) to physiology (e.g. temperature and hormone rhythms, and relatively recently also in genes, proteins and metabolites). However, the methodological advancements in this field have been mostly and sometimes exclusively used only in indoor laboratory settings. In parallel, there has been an unprecedented and rapid improvement in our ability to track animals and their behaviour in the wild. However, while the spatial analysis of tracking data is widespread, its temporal aspect is largely unexplored. Here, we review the tools that are available or have potential to record rhythms in the wild animals with emphasis on currently overlooked approaches and monitoring systems. We then demonstrate, in three question-driven case studies, how the integration of traditional and newer approaches can help answer novel chronobiological questions in free-living animals. Finally, we highlight unresolved issues in field chronobiology that may benefit from technological development in the future. As most of the studies in the field are descriptive, the future challenge lies in applying the diverse technologies to experimental set-ups in the wild. This article is part of the themed issue ‘Wild clocks: integrating chronobiology and ecology to understand timekeeping in free-living animals’.


Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3836
Author(s):  
António Lobo ◽  
Sara Ferreira ◽  
António Couto

Driver inattention is a major contributor to road crashes. The emerging of new driver monitoring systems represents an opportunity for researchers to explore new data sources to understand driver inattention, even if the technology was not developed with this purpose in mind. This study is based on retrospective data obtained from two driver monitoring systems to study distraction and drowsiness risk factors. The data includes information about the trips performed by 330 drivers and corresponding distraction and drowsiness alerts emitted by the systems. The drivers’ historical travel data allowed defining two groups with different mobility patterns (short-distance and long-distance drivers) through a cluster analysis. Then, the impacts of the driver’s profile and trip characteristics (e.g., driving time, average speed, and breaking time and frequency) on inattention were analyzed using ordered probit models. The results show that long-distance drivers, typically associated with professionals, are less prone to distraction and drowsiness than short-distance drivers. The driving time increases the probability of inattention, while the breaking frequency is more important to mitigate inattention than the breaking time. Higher average speeds increase the inattention risk, being associated with road facilities featuring a monotonous driving environment.


Author(s):  
Claudio Alcides Jacoski ◽  
Larissa Saugo

In recent years, concrete structures have started to show increased amounts of degradation or damage. This phenomenon is generally caused by the growth of these constructions, particularly with regard to slenderness. In the quest for new strategies to address this problem and to ensure the safety of structures and their occupants, tools for damage detection and timely analysis distributed within buildings have been developed. These tools are referred to as “Structural Health Monitoring” sensors. It is known that these systems still have high costs, thus this study aims to assess their value through future projections of their costs and utility. This monitoring method, although not widespread, mainly aims to maintain the integrity of major projects; it is not currently focused in small sized works, with the exception of a few structures of historical interest. Therefore, this study proposes the analysis of structural monitoring systems in civil construction, through means of a survey and interviews with experts. The study is aimed at investigating current technologies, planning for implementation, and identifying costs and feasibility of structural monitoring in the future. In conclusion, it was possible to expose that deformation and displacement sensors, along with optical and electrical technologies are the most commonly used types of sensors. Furthermore, it was found that monitoring systems are only feasible for large structures and the estimated time for use in medium-sized buildings is 15 years or more. However, it can be noted that the cost is currently very high, but will likely be reduced in the future.


Author(s):  
Sarah J. Howie ◽  
Vanessa Scherman

2016 ◽  
Vol 4 (3/4) ◽  
pp. 282
Author(s):  
J.M. Cooper ◽  
F. Biondi ◽  
D.L. Strayer ◽  
J.R. Coleman

2017 ◽  
Vol 2017 (19) ◽  
pp. 83-88 ◽  
Author(s):  
Bhawani Shankar ◽  
Dakala Jayachandra ◽  
Kalyan Kumar Hati

Author(s):  
Dary D. Fiorentino ◽  
Zareh Parseghian

In the future, on-board driver monitoring systems could use time-to-collision (TTC) metric algorithms as a real-time measure of driving performance, and alert the driver if performance falls below minimum performance criteria. Such monitoring systems remain years away, but it is currently possible to measure TTC in a simulator. This paper discusses a study to determine whether TTC varies as a function of driver impairment in a simulated driving task. Alcohol was administered to eleven participants, and TTC measures were obtained at 0.00%, 0.04% and 0.08% blood alcohol concentrations (BAC). The results support use of the median TTC, which varied as a function of BAC, as a measure of in-traffic maneuvering performance.


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