Advances in Human-Machine Systems for In-Vehicle Environments: Noise and Cognitive Stress/Distraction

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