Affective interaction with a companion robot in an interactive driving assistant system

Abstract

Driving assistant systems are becoming the attractive service tasks in the field of intelligent robotics. Humans meet a variety of situations while driving cars and robotic systems help humans to understand how surrounding situations change and how robot systems are aware of given situations. From the viewpoint of interaction performance, proper situation awareness by a robotic assistant in a car and the relevant determination of corresponding reactions are crucial prerequisites for long term interaction between a human driver and a car's robotic system. In this paper, we focus on preserving human-robot interaction for driving situations, considering how many types of cognitive situation occur and how affective interaction can be designed for the robotic driving assistant. The appropriateness of the driving situation and of the robotic reactions are testified in our experiment system, including the development of a virtual driving environment and tablet-based robotic agent system.

A Design Space for Human Sensor and Actuator Focused In-Vehicle Interaction Based on a Systematic Literature Review

“…Most approaches in our synthesis used screens of various sizes and functions, e.g., [189,193,354,393]. However, we also found different visualization approaches, e.g., head-up displays (HUDs) [331], stereoscopic displays [392], active shutter glasses [49], robotic companion displays [406], projections [257], and shape changing devices [257]. Regarding HUDs, Beck and Park [31] investigated the perceived importance of different HUD information items, and Häuslschmid et al [130] evaluated the recognition of stimuli on a windshield HUD.…”

“…A concept by Broy et al [49] used shutter glasses to visualize a 3D effect on a dashboard display. Yang et al [406] presented a robotic companion display that automatically pans and tilts. Mok et al [257] projected the vehicle's automation status on the steering wheel while also changing its shape to visualize a TOR.…”

Driver Drowsiness Detection and Tracking Based on Yolo with Haar Cascades and ERNN

“…Ho [13] used the Haptic warning signals warning to interrupt driver distraction or redirect the focus on the direction that needs them immediate attention, while Choi et al [14] is about getting the driver characteristics as much as age, gender, driving ability to adjust the interface to the driver and provide cognitive assistance and continual follow-up throughthe camera and DAVIS ( Drive-Adaptive Vehicle Interaction System) that controls the interaction between the vehicle and the driver by monitoring driver's conditions and feedbacks. Yang et al [15] proposes an HMI based on virtual affective agent as an interactive robot system to estimate the driver status through the car operational commands. Park et al [16] suggests an assistant companion for events prediction from the online stream of sensory measurements by providing voice assistance.…”

Feedback-based reasoning process for behavior selection during long-term interaction

“…The affective intelligent driving agent (AIDA) was introduced to approximate human's driving goal on behalf of conventional way point-based navigation [2]. We extended the human-robot interaction technology to the proposed driving assistant system toward an affective companion during long term period [3].…”