Post-Takeover Proficiency in Conditionally Automated Driving: Understanding Stabilization Time with Driving and Physiological Signals

Author:

Gruden Timotej1ORCID,Tomažič Sašo1,Jakus Grega1ORCID

Affiliation:

1. Faculty of Electrical Engineering, University of Ljubljana, Tržaška cesta 25, 1000 Ljubljana, Slovenia

Abstract

In the realm of conditionally automated driving, understanding the crucial transition phase after a takeover is paramount. This study delves into the concept of post-takeover stabilization by analyzing data recorded in two driving simulator experiments. By analyzing both driving and physiological signals, we investigate the time required for the driver to regain full control and adapt to the dynamic driving task following automation. Our findings show that the stabilization time varies between measured parameters. While the drivers achieved driving-related stabilization (winding, speed) in eight to ten seconds, physiological parameters (heart rate, phasic skin conductance) exhibited a prolonged response. By elucidating the temporal and cognitive dynamics underlying the stabilization process, our results pave the way for the development of more effective and user-friendly automated driving systems, ultimately enhancing safety and driving experience on the roads.

Funder

Slovenian Research Agency

Publisher

MDPI AG

Reference106 articles.

1. (2023, January 28). SAE International J3016_202104: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles. Available online: https://www.sae.org/standards/content/j3016_202104/.

2. City Readiness for Connected and Autonomous Vehicles: A Multi-Stakeholder and Multi-Criteria Analysis through Analytic Hierarchy Process;Jiang;Transp. Policy,2022

3. Understanding Acceptance of Shared Autonomous Vehicles among People with Different Mobility and Communication Needs;Miller;Travel Behav. Soc.,2022

4. Safety Effectiveness of Autonomous Vehicles and Connected Autonomous Vehicles in Reducing Pedestrian Crashes;Susilawati;Transp. Res. Rec.,2022

5. Examining Motivations for Owning Autonomous Vehicles: Implications for Land Use and Transportation;Tao;J. Transp. Geogr.,2022

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