Driving Skill Modeling Using Neural Networks for Performance-based Haptic Assistance

TL;DR

This paper presents a neural network-based framework for modeling expert driving skills to enhance performance-based haptic assistance, improving steering performance in novice drivers through data-driven feedback.

Contribution

It introduces a neural network model trained on expert data to provide optimized haptic feedback for driving skill improvement.

Findings

The skill model accurately captures expert steering and pedaling skills.

Haptic assistance improves steering performance of novices to expert levels.

Assistance effectively enhances steering but less so for pedaling.

Abstract

This paper addresses a data-driven framework, modeling expert driving skills for performance-based haptic assistance using neural networks (NNs). We have built a haptic driving training simulator to collect expert driving data and to provide proper haptic feedback. We establish an expert driving skill model by training NNs with the collected data. Then, the skill model is applied to performance-based haptic assistance to provide optimized references of the steering/pedaling movements. We evaluate the skill model and its application to performance-based haptic assistance in two user experiments. The results of the first experiment demonstrate that our skill model has appropriately captured experts' steering/pedaling skills. The results of the second experiment show that our performance-based haptic assistance can help novice drivers perform steering as expert drivers, but cannot assist their pedaling performance.