Comparative safety analysis of take-over control mechanisms of conditionally automated vehicles

• Published in: Accident analysis and prevention Vol. 217; p. 108068
• Main Authors: Karimi, Arastoo, Barbin, Arash Hassani, Hazoor, Abrar, Marinelli, Giuseppe, Bassani, Marco
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.07.2025
• Subjects: Acceleration; Accidents, Traffic - prevention & control; Adult; Automation; Automobile Driving - psychology; Automobiles; Computer Simulation; Conditionally automated driving; Critical driving situation; Driver behavior; Female; Humans; Linear Models; Male; Man-Machine Systems; Road safety; Safety; Survival function; Take over control; Young Adult; Conditionally automated driving; Critical driving situation; Road safety; Take over control; Survival function; Driver behavior
• ISSN: 0001-4575; 1879-2057; 1879-2057
• DOI: 10.1016/j.aap.2025.108068

•Take-over mechanisms impact safety in unsafe and ordinary driving scenarios.•Weibull accelerated failure time models applied to take-over control analysis.•Pedals enable quickest take-over control in unsafe scenarios.•Steering mechanism delays take-over and reduces driving quality in ordinary scenarios.•Button mechanism extends take-over time reducing safety in unsafe scenarios. Conditionally Automated driving (CAD) represents a pivotal point in the evolution of automotive technology, bridging full automation and human intervention through effective control mechanisms that ensure safe driver-system transitions. This research consisted of a comparative analysis of take-over mechanisms, focusing on ordinary merging and diverging maneuvers and critical collision-avoidance scenarios. Three take-over control (TOC) methods, including (i) accelerating/braking, (ii) pressing a dedicated button, and (iii) steering, were investigated. Thirty participants were recruited using a mixed factorial design with both within- and between-subject factors. The experimental simulations were conducted on the fixed-base driving simulator. The participants completed three runs on a motorway track comprising ordinary merging and diverging sections, with the final run involving a sudden critical decision to avoid the collision against two crashed vehicles. Weibull accelerated failure time models with and without shared frailty, mixed effects linear regression and multiple linear regression were used to model TOC time, maximum resultant acceleration, and minimum time to collision values. The results indicate that the pedal mechanism generally provides faster and safer takeovers, especially in critical situations, while the button mechanism results in the longest TOC times, and lowest minimum time to collision values, indicating higher risks. The steering wheel mechanism, associated with the highest maximum resultant acceleration and TOC times in merging and diverging maneuvers, suggests that lateral control may be more cognitively demanding for drivers. These findings emphasize the importance of selecting appropriate TOC mechanisms to improve the safety and efficiency of CAD systems.