Effects of the driving context on the usage of Automated Driver Assistance Systems (ADAS) -Naturalistic Driving Study for ADAS evaluation
Artikel i vetenskaplig tidskrift, 2020

Automated Driver Assistance Systems (ADAS) are designed to support the driver and enhance the driving experience. Due to ADAS limitations associated with the driving context, the intended use of ADAS functions is often non-transparent for the end-user. The system performance capabilities affected by the continuously changing driving context influence ADAS usage. However, the cumulative effect of the driving context on driver behavior and ADAS usage is insufficiently covered in the ongoing research. This paper aims to investigate and understand how the driving context affects the use of ADAS. Throughout this research, data from a Naturalistic Driving (ND) study was collected and analyzed. The analysis of the ND data helped to register how drivers use ADAS in different driving conditions and indicated several issues associated with ADAS usage. To be able to clarify the outcomes of quantitative sensor-based data analysis, an explanatory sequential mixed-method design was implemented. The method facilitated the subsequent design of qualitative in-depth interviews with the drivers. The combined data analysis allowed a holistic interpretation and evaluation of the findings regarding the effect of the driving context on ADAS usage. The findings warrant consideration of the driving context as a key factor enabling the effective development of ADAS functions. © 2020 The Authors

ADAS

Driving context

Mixed-method study

Driving behavior

Semi-automated systems

Naturalistic driving study

Författare

Julia Orlovska

Chalmers, Industri- och materialvetenskap, Produktutveckling

Fjolle Novakazi

Volvo Cars

Chalmers, Industri- och materialvetenskap, Design and Human Factors

Lars-Ola Bligård

Chalmers, Industri- och materialvetenskap, Design and Human Factors

Mari Anne Karlsson

Casper Wickman

Volvo Cars

Chalmers, Industri- och materialvetenskap, Produktutveckling

Rikard Söderberg

Chalmers, Industri- och materialvetenskap

Transportation Research Interdisciplinary Perspectives

25901982 (eISSN)

Vol. 4 100093

Ämneskategorier

Tillämpad psykologi

Datavetenskap (datalogi)

Datorsystem

DOI

10.1016/j.trip.2020.100093

Mer information

Senast uppdaterat

2020-05-26