• The Problem. Driving is, most of the time, a self-paced task where drivers proactively control the driving situation, based on their expectations of how things will develop in the near future. Crashes are typically associated with unexpected events where this type of proactive adaptation failed in one way or another. These types of scenarios are the main targets for active safety systems. In evaluation studies, drivers’ responses to expected events may be qualitatively different from responses to similar, but unexpected, events. Hence, creating artificial active safety evaluation scenarios that truly represent the targeted real-world scenarios is a difficult challenge. Role of Driving Simulators. Driving simulators offer great possibilities to test active safety systems with real drivers in specific target scenarios under tight experimental control. However, in simulator studies, experimental control generally has to be traded against realism. The objective of this chapter is to address some key problems related to driver expectancy and associated adaptive behavior in the context of simulator-based active safety system evaluation. Key Results of Driving Simulator Studies. The chapter briefly reviews common types of adaptive driver strategies found in the literature and proposes a general conceptual framework for describing adaptive driver behavior. Based on this framework, some key challenges in dealing with these types of issues in simulator studies are identified and potential solutions discussed. Scenarios and Dependent Variables. Key variables representing adaptive driver behavior include the selection of speed, headway, and lane position as well as the allocation of attention and effort. It will never be possible to create artificial simulator scenarios for active safety evaluation that perfectly match their real-world counterparts, but there are several means that could be used to reduce the discrepancy. Problems with expectancy and resulting adaptive behavior may at least be partly overcome by various means to “trick” drivers into critical situations, several of which are addressed in the chapter. Platform Specificity and Equipment Limitations. The issues discussed in this chapter should apply across all types of driving simulator platforms. However, some of the proposed methods for tricking drivers into critical situations may require specific simulator features, such as a motion base.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Samhällsbyggnadsteknik -- Transportteknik och logistik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Civil Engineering -- Transport Systems and Logistics (hsv//eng)

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Farkostteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Vehicle Engineering (hsv//eng)

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)

Nyckelord

Active Safety Systems

Expectancy

Evaluation

Simulator Scenario Design

Adaptive Driver Behavior

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