Abstract
In the development of highly automated driving systems (L3 and 4), much research has been done on the subject of driver takeover. Strong focus has been placed on the takeover quality. Previous research has shown that one of the main influencing factors is the complexity of a traffic situation that has not been sufficiently addressed so far, as different approaches towards complexity exist. This paper differentiates between the objective complexity and the subjectively perceived complexity. In addition, the familiarity with a takeover situation is examined. Gold et al. show that repetition of takeover scenarios strongly influences the take-over performance. Yet, both complexity and familiarity have not been considered at the same time. Therefore, the aim of the present study is to examine the impact of objective complexity and familiarity on the subjectively perceived complexity and the resulting takeover quality. In a driving simulator study, participants are requested to take over vehicle control in an uncritical situation. Familiarity and objective complexity are varied by the number of surrounding vehicles and scenario repetitions. Subjective complexity is measured using the NASA-TLX; the takeover quality is gathered using the take-over controllability rating (TOC-Rating). The statistical evaluation results show that the parameters significantly influence the takeover quality. This is an important finding for the design of cognitive assistance systems for future highly automated and intelligent vehicles.
Highlights
Within recent years, human factors have become an important research topic in automating driving [1]
As it is already shown that the drivers’ familiarity with a situation and the objective complexity of the current traffic situation influence the subjective complexity [9,11,12], this study investigates the impact of the situational variables familiarity, objective complexity and subjective complexity on the takeover quality
Regression analysis is used to examine the influence of the independent variables on the dependent variable takeover quality
Summary
Human factors have become an important research topic in automating driving [1]. Approaching the Level 3 of automation [2], the driver may shift attention to a non driving related task (NDRT) during the automated drive. The driver remains as fallback if the automation requests a takeover (TOR; [2]). Most takeover requests in Level 3 highly automated driving [2]. Will be non-critical [3], giving the driver sufficient comfortable transition time [4]. The focus in this study lies on non-critical takeover situations in different scenarios and the resulting takeover quality. In contrast to critical takeover situations, where drivers abbreviate the takeover process, the driver has enough time to properly perceive the driving environment before performing a maneuver
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