Looking-in and looking-out vision for Urban Intelligent Assistance: Estimation of driver attentive state and dynamic surround for safe merging and braking

Abstract

This paper details the research, development, and demonstrations of real-world systems intended to assist the driver in urban environments, as part of the Urban Intelligent Assist (UIA) research initiative. A 3-year collaboration between Audi AG, Volkswagen Group of America Electronics Research Laboratory, and UC San Diego, the driver assistance portion of the UIA project focuses on two main use cases of vital importance in urban driving. The first, Driver Attention Guard, applies novel computer vision and machine learning research for accurately tracking the driver's head position and rotation using an array of cameras. The system then infers the driver's focus of attention, alerting the driver and engaging safety systems in case of extended driver inattention. The second application, Merge and Lane Change Assist, applies a novel probabilistic compact representation of the on-road environment, fusing data from a variety of sensor modalities. The system then computes safe and low-cost merge and lane-change maneuver recommendations. It communicates desired speeds to the driver via Head-up Display, when the driver touches the blinker, indicating his desired lane. The fully-implemented systems, complete with HMI, were demonstrated to the public and press in San Francisco in January of 2014.