Active Driving AI Assistant

WINLAB Summer Internship 2022

Group Members:

Project Objective

This project study will develop a naturalistic driving monitoring and intervention system. Our interactive system will use multiple in-cabin vehicle sensors to assess driving conditions and performance in real-time and draw a driver’s attention using a voice-based interface to improve their performance. We will use AI-driven techniques to continuously assess the effectiveness of our interventions and make adjustments to maximize driving safety and quality.

Reading material:

• ​Tong Wu, Nikolas Martelaro, Simon Stent, Jorge Ortiz, and Wendy Ju. 2021. Learning When Agents Can Talk to Drivers Using the INAGT Dataset and Multisensor Fusion. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5, 3, Article 133 (Sept 2021), 28 pages.
• ​Tong Wu, Enna Sachdeva, Kumar Akash, Xingwei Wu, Teruhisa Misu, and Jorge Ortiz Toward an Adaptive Situational Awareness Support System for Urban Driving.

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Week 4 Activities