Design and implementation of driver coach application for pilot assist: A first validation study
Journal article, 2024

This article discusses the importance of driver understanding and trust in Advanced Driver-Assistance Systems (ADAS) and proposes a framework for a personalized driver coaching system called Driver Coach, focusing on the Volvo Pilot Assist (PA) function. Despite the widespread adoption of ADAS, research indicates that many drivers have limited comprehension of ADAS functionality and limitations. Moreover, feedback-related factors play a crucial role in determining drivers’ proper use of ADAS. The article emphasizes the need for appropriate, continual feedback to enhance driver interaction with ADAS. Traditional methods, such as user manuals or supervised test drives, have limitations in effectively conveying critical information and facilitating driver adaptation. To address these challenges, the proposed Driver Coach app provides personalized, real-time recommendations to drivers based on their individual needs and understanding of both the system and driving context. The app was tested in a field trial involving 17 drivers over a four-month period, and the results regarding the logic design verification and the impact of the Driver Coach app on PA usage are presented. The findings highlight the potential of personalized, context-aware coaching systems to improve driver understanding and usage of ADAS.

Real-time driver support

Driver Coach app

Data-driven design

Vehicle data

Driver Coaching

Personalised Assistant

ADAS

Real-time personalised Assistance

ADAS personalization

Function personalization

Driver behavior assessment

Author

Julia Orlovska

Chalmers, Industrial and Materials Science, Product Development

Casper Wickman

Volvo Group

Chalmers, Industrial and Materials Science, Product Development

Rikard Söderberg

Chalmers, Industrial and Materials Science, Product Development

Daniel Bark

Volvo Group

Christoffer Carlsson

Volvo Group

Pär Gustavsson

Volvo Group

Transportation Research Interdisciplinary Perspectives

25901982 (eISSN)

Vol. 25 101130

Data Driven User Experience - DDUX

VINNOVA (2018-05017), 2019-02-01 -- 2021-12-31.

Subject Categories (SSIF 2011)

Applied Psychology

Vehicle Engineering

DOI

10.1016/j.trip.2024.101130

More information

Latest update

2/4/2025 8