As computing technology advances, the ability to integrate a wider range of personal
services for in-vehicle environments increases. These technologies include hands-free wireless
communications, video/data/internet within the vehicle, route planning and navigation, access to
music and information download, command and control of vehicle instrumentation, as well as
inter-vehicle communications. While these advances offer a diverse range of entertainment and
information access opportunities, they generally are introduced into the vehicle with limited
understanding of their impact to driver distraction and cognitive stress load. As the diversity of
speech, video, biometric, and vehicle signals increases, improved corpora and system
formulation are needed. In this study, we consider recent advances for in-vehicle humanmachine
systems for route navigation, noise suppression for robust speech recognition, and
driver behavior modeling. Multi-microphone array processing based on combined fixedadaptive
beamforming is developed for noise suppression for hands-free communications as
well as improved automatic speech recognition for route dialog interaction. Next, advances in
modeling driver behavior are considered in the UT-Drive project, which is focused on
advancing smart vehicle technologies for improved safety while driving. Finally, a general
discussion considers next generation advances for in-vehicle environments which sense driver
cognitive stress/distraction to adapt interactive systems to improve safety.
Keywords: robust speech recognition, environmental sniffing, array processing, stress detection, in-vehicle dialog
systems, UT-Drive, in-vehicle route navigation, driver behavior model
