Motivation for continuous haptic gas pedal feedback to support car following

Abstract

The last years, increased effort has been dedicated to the design of systems that assist the driver in car following. The need for assistance systems arises from the fallibility of the visual feedback loop, for example due to inattention. Existing driver assistance systems either automate the car-following task or support drivers with binary warning systems to redirect their attention when necessary. The goal of this paper is to discuss the benefits and limitations of these systems, and to show the possibilities of an alternative design approach. To attain the goal, a theoretic analysis is presented, that views car following as a closed-loop control task that requires sufficient feedback about the separation (relative distance, relative velocity) to a lead vehicle. A task analysis helps to identify the areas where the current systems assist the driver well, and where they do not. The new design approach aims to keep the human in the loop, by supplementing the semi-continuous visual feedback loop with an additional continuous feedback loop, namely haptic feedback applied directly at the gas pedal. Expected benefits compared to existing systems include: better situation awareness (even during periods of visual inattention) and faster responses (the haptic feedback is available directly at the gas pedal, allowing the use of fast reflexes). Several design issues are presented, such as the prevention of nuisance and fatigue, deciding which separation states the feedback is based upon, and challenges in determining the correct characteristics of the haptic signals. The benefits of the approach are illustrated through several examples from literature that describe experimental humanin-the-loop studies with continuous haptic feedback. It is concluded that haptic feedback on the gas pedal is a promising way of supporting drivers.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 53 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.