{'fraction_non_alphanumeric': 0.0215633423180593, 'fraction_numerical': 0.0017969451931716084, 'mean_word_length': 5.710843373493976, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
The Impact of Environmental Complexity on Drivers’ Situation Awareness

Computational models embedded in advanced driver assistance systems (ADAS) require insights on drivers’ perception and understanding of their environment. This is particularly important as vehicles become increasingly automated and the partnership between the controllers (driver or vehicle) needs to be attentive to each other’s future intentions. This study investigates the impact of environmental factors (road type, lighting) on driver situation awareness (SA) using 75 real-world driving scenes viewed within a driving simulator environment. The Situational Awareness Global Assessment Technique (SAGAT) was adopted to compute SA scores from spatially continuous data. A hurdle model showed that visual complexity, which was not considered in previous SA prediction models, significantly impacted driver SA. The number of objects in the visual scene as well as in the peripheral view were also found to significantly affect driver SA. The findings of this study provide insights on environmental factors that may impact SA predictions.