In recent years, there are many naturalistic driving projects have been conducted, such as the 100-Car Project (Naturalistic Driving study in United State), EuroFOT(European Large-Scale Field Operational Tests on Vehicle Systems), SeMi- FOT(Sweden Michigan Naturalistic Field Operational Test and etc. However, those valuable naturalistic driving data hasn't been applied into Human-machine Intera...

Previous functional neuroimaging studies have identified multiple brain areas associated with distinct aspects of car driving in simulated traffic environments. Few studies, however, have examined brain morphology associated with everyday car-driving experience in real traffic. Thus, the aim of the current study was to identify gray matter volume differences between drivers and non-drivers. We ...

Adaptive Cruise Control Systems (ACC) are becoming essential in developing advanced vehicular applications/services which help to reduce the risk of accidents and offer better conditions for comfort in the driving experience, Hartenstein and Leberteaux (2008). The IDM (Intelligent Driver Model) is a realistic car-following model whose main feature is the use of physical-oriented parameters to e...

This paper introduces a common database and an evaluation framework for connected digit speech recognition in real driving car environments, CENSREC-2, as an outcome of IPSJ-SIG SLP Noisy Speech Recognition Evaluation Working Group. Speech data of CENSREC-2 was collected using two microphones, a close-talking microphone and a hands-free microphone, under three car speeds and four car conditions...

In the current study we examined the relationship between drivers’ eye movement patterns and driving performance in a dual-task driving paradigm. Drivers performed two tasks in a driving simulator. In a car following task, drivers were asked to maintain a constant headway from a leading vehicle as it varied its speed. In the second task (light detection task), drivers tried to detect changes in...

In experimental studies using flight simulations subjects' duration estimates have shown to be an effective indicator of cognitive task demands. In this study we wanted to find out whether subjective time perception could serve as a measure of cognitive workload during simulated car driving. Participants drove on a round course of a driving simulator consisting of three different environments w...

Cognitive dysfunction caused by some neurodegenerative diseases is associated with an increased risk of traffic accidents. Previous studies have reported inconsistent results for prodromal and early stages of dementia. Few studies have directly compared the effects on driving performance of amnestic subtype of mild cognitive impairment (aMCI) with those by normal aging in elderly drivers. The p...

In-car intoxication detection from speech is a highly promising non-intrusive method to reduce the accident risk associated with drunk driving. However, in-car noise significantly influences the recognition performance and needs to be addressed in practical applications. In this paper, we investigate how seriously the intrinsic in-car noise and background music affect the accuracy of intoxicati...

This paper introduces a common database, an evaluation framework, and its baseline recognition results for in-car speech recognition, CENSREC-3, as an outcome of the IPSJ-SIG SLP Noisy Speech Recognition Evaluation Working Group. CENSREC-3, which is a sequel to AURORA-2J, has been designed as the evaluation framework of isolated word recognition in real car-driving environments. Speech data wer...

State is central to understanding objects in the real world a moving car is very di erent from a parked car. Yet most object-oriented languages provide no native support for state or state change. The Plaid language introduces a new object model in which objects are not only instances of a class, but can also be in mutable states. In Plaid, a car object can have one abstract state for driving a...