Results 201 to 210 of about 121,839 (252)
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Federated Learning for Driver Status Monitoring
2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021We apply a novel concept for distributed learning to the problem of driver status monitoring. The main benefit is that only local, in-vehicle training data is used, thus privacy sensitive pictures of the driver do not leave the vehicle. We show the challenges of this application, in particular in the distribution of the data and apply different, recent
Atiqa Zafar +2 more
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Driver monitoring for a human-centered driver assistance system
Proceedings of the 1st ACM international workshop on Human-centered multimedia, 2006Driving is a very complex task which, at its core, involves the interaction between the driver and his/her environment. It is therefore extremely important to develop driver assistance systems that are centered around the driver from the ground up. In this paper, we explore one aspect of such a system.
Joel C. McCall, Mohan M. Trivedi
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Adaptation to the driver as part of a driver monitoring and warning system
Accident Analysis & Prevention, 1997A driver monitoring and warning system called DAISY (Driver AssIsting SYstem) is presented, which adapts its warning messages to warning thresholds acceptable to the driver. This is achieved by the use of a model of the individual driving behaviour of the driver actually driving.
R, Onken, J P, Feraric
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Detecting driver inattention in the absence of driver monitoring sensors
2004 International Conference on Machine Learning and Applications, 2004. Proceedings., 2005A classifier was trained to detect driver inattention using output from typical sensors available on modern vehicles equipped with a Collision Avoidance System (CAS). A driving simulator was used to collect driver and vehicle data from ten subjects during normal driving periods and during periods where drivers looked away from their forward view as ...
Kari Torkkola, Noel Massey, Chip Wood
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Driver State Monitoring System
Proceedings of the 4th International Conference on Big Data and Internet of Things, 2019Traffic crashes cause a lot of fatality and injuries every year. Robust and reliable driver monitoring system is an important step toward achieving higher vehicle autonomy level, as well as insuring the road safety and preventing road accidents. Driver states such as distraction and fatigue cause a decrease in driving performance.
Amina Guettas, Soheyb Ayad, Okba Kazar
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Monitoring Driver Behaviour with BackPocketDriver
2019Road safety is an international public health issue with youth drivers being grossly overrepresented in road crash fatalities and injuries. Our work centres on the use of smartphone technology to deliver an intervention that aims to improve driving behaviour. In this paper we describe the technical design of our BackPocketDriver app, which monitors key
Ian Warren +3 more
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A driving simulator with driver monitor system
Systems and Computers in Japan, 2007AbstractThe driving simulators hitherto developed were intended for investigation of active safety techniques, verification of vehicle movement models, etc., without using an actual vehicle. But there subsequently arose a need for a system that could be used to investigate ways of providing driving and safety assistance to drivers in the aging society ...
Kazumasa Adachi +6 more
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Driver Monitoring Systems: Design Considerations for Aging Drivers
AHFE International, 2023A number of automotive manufacturers including General Motors and Tesla offer vehicles with advanced semi-autonomous driving functions that the driver is expected to monitor. Monitoring by the human driver is essential given that these systems are known to have difficulty handling driving situations that human drivers negotiate easily.
Molly C Mersinger +5 more
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Driver State Monitoring with Hierarchical Classification
2018 21st International Conference on Intelligent Transportation Systems (ITSC), 2018While vehicle automation increases in the near future human drivers will still be responsible for monitoring of the driving environment or as a fallback for critical situations. Thus, systems for autonomy levels 2 to 3 require proper knowledge about the driver's state including, for example, the seating position, activity, or hands-on-steering-wheel ...
Patrick Weyers +2 more
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Driver State Monitor from DELPHI
2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005We present an automotive-grade, real-time, vision-based driver state monitor. Upon detecting and tracking the driver's facial features, the system analyzes eye-closures and head pose to infer his/her fatigue or distraction. This information is used to warn the driver and to modulate the actions of other safety systems. The purpose of this monitor is to
N. Edenborough +13 more
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