A highly integrated system was constructed to assess, and react to, a driver's cognitive load. Sensors embedded throughout the car track a wide variety of driver activities, including driving conditions, driver reactions, control usage, driver reflexes, passenger interaction, and driver attention. The raw sensor readings are compiled and parsed, and used to assess the cognitive and stress load ...

Car-following models, as the most popular microscopic traffic flow modeling, is increasingly being used by transportation experts to evaluate new Intelligent Transportation System (ITS) applications. A number of factors including individual differences of age, gender, and risk-taking behavior, have been found to influence car-following behavior. This paper presents a novel idea to calculate ...

From April 2004 to March 2007, a research project entitled “Situation and Intent Recognition for Risk Finding and Avoidance” was conducted. This project includes the following research topics: (i) estimation of driver’s state, (ii) driver behavior modeling, (iii) intelligent information processing methods for situation recognition and visual enhancement. This paper introduces several researches...

While computational cognitive modeling has made great strides in addressing complex dynamic tasks, the modeling of individual differences in complex tasks remains a largely unexplored area of research. In this paper we present a straightforward approach to modeling individual differences, specifically age-related cognitive differences, in complex tasks, and illustrate the application of this ap...

The recent decades have witnessed a fast rising number of motor vehicles. As a result traffic becomes more congested and streets become more risky. Temptations of widely varied communication and entertainment applications even make drivers more over-burdened and distracted. To relieve the continually increasing stress of drivers and reduce the number of accidents, current intelligent vehicle re...

In contrast to the vast amount of modeling work focused on desktop user interfaces, recent work has increasingly focused on “off-the-desktop” interfaces, one prime example being in-vehicle interfaces used while driving. This paper highlights four recent approaches to predicting driver distraction from in-vehicle interfaces as secondary tasks: hand-crafted modeling with the full-fledged ACT-R ar...