Abstract
Taking over vehicle control from a Level 3 conditionally automated vehicle can be a demanding task for a driver. The take-over determines the controllability of automated vehicle functions and thereby also traffic safety. This paper presents models predicting the main take-over performance variables take-over time, minimum time-to-collision, brake application and crash probability. These variables are considered in relation to the situational and driver-related factors time-budget, traffic density, non-driving-related task, repetition, the current lane and driver’s age. Regression models were developed using 753 take-over situations recorded in a series of driving simulator experiments. The models were validated with data from five other driving simulator experiments of mostly unrelated authors with another 729 take-over situations. The models accurately captured take-over time, time-to-collision and crash probability, and moderately predicted the brake application. Especially the time-budget, traffic density and the repetition strongly influenced the take-over performance, while the non-driving-related tasks, the lane and drivers’ age explained a minor portion of the variance in the take-over performances
Original language | English |
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Pages (from-to) | 3-13 |
Journal | Accident Analysis & Prevention |
Volume | 116 (2018) |
DOIs | |
Publication status | Published - 2017 |
Keywords
- Automated driving
- Take-Over
- Modeling
- Driver performance
- Regression
- Human factors