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Driver Modeling and Simulation

UMTRI researchers use computational modeling techniques to describe,explain, predict, and demonstrate driver behavior and performance. Modelingefforts are usually based on data collected in traditional human factorsexperiments in the simulator and on the road. Our models aim to extend thevalue of empirical results by making engineering predictions and attemptingto explain phenomena related to basic driving and to driving in the presenceof ITS systems. Discrete event simulation packages such as ProModel andMicrosaint are used to generate stochastic predictions of driverperformance. Research on the integration of cognitive modeling (QN models)with physical modeling (HUMOSIM) and task analysis (IMPRINT) as well asvehicle dynamics (Matlab) are part of this effort.

Recent Publications

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Effects of task characteristics on unimanual and bimanual movement times.
Divya Srinivasan, Bernard J. Martin, Matthew P. Reed

journal article IN: Ergonomics. Vol. 56, no. 4 (2013), p. 612-622.

Fitts' law cannot be used to predict movement times (MTs) of bimanual tasks since no empirical relationships associating task...

Integration of physical and cognitive human models to simulate driving with a secondary in-vehicle task
Helen J. A. Fuller, Matthew P. Reed, Yili Liu.

journal article IN: IEEE Transactions on Intelligent Transportation Systems. Vol. 13, no. 2 (June 2012), p. 967-972.

Human behavior models give insight into people-s choices and actions and are tools for predicting performance and improving interface...

Integrating physical and cognitive human models to represent driving behavior
Helen J.A. Fuller, Matthew P. Reed, Yili Liu.

conference paper IN: Proceedings of the Human Factors and Ergonomics Society ... Annual Meeting. Vol. 54, no. 13 (2010), p. 1042-1046.

This research addresses the divide between cognitive and physical human models by integrating a cognitive human model with a physical...