Energy-efficient driving (ecodriving) in electric mobility is crucial on an individual and societal level. Yet, drivers struggle to learn and sustain ecodriving. One approach to evaluate and study ecodriving interventions are driving simulator experiments. This research aims to develop and analyze a series of driving simulation test cases (ecodriving test park) for ecodriving. Driving simulators offer controlled environments. However, commonly used classifications of, e.g., “urban” or “rural” environments are limited regarding the interpretability of how cognitively and physically complex a scenario really is. It is necessary to establish a taxonomy based on situation characteristics and understand the implications of these characteristics on ecodriving behavior and driver experience.
We developed driving scenarios for simulator experiments that operationalize the following characteristics: energy relevance, defined as the disparity between the most and least energy-efficient, yet legally and socially compliant driving styles, information processing demands, as cognitive demands due to information perception, comprehension, and decision-making, and vehicle control demands, as cognitive and physical demands due to lateral and longitudinal control requirements and their time budget (based on Fastenmeier, 1995).
In an initial study for evaluation, we gathered empirical driving and questionnaire data and developed manipulation check indices. The results served as a basis for scenario selection for the final test park to encompass a broad range of complexities while maintaining high energy relevance. Through the evaluation, other potential modifications to the test park were derived.