{'fraction_non_alphanumeric': 0.017333333333333333, 'fraction_numerical': 0.0, 'mean_word_length': 5.474137931034483, '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}}
Simulation-based requirements discovery for smart driver assistive technologies

Smart driver assistive technologies (DAT) have been developed to alleviate accident risk by either reducing driver workload or assessing driver attentiveness. Such systems aim to draw drivers' attention on critical cues that improve decision making. However, in some cases, these systems can have a negative effect due to the extra information load they incur to the driver. Therefore, in addition to specifying the functional requirements for such systems there is an urgent need to address the human requirements. This work describes a simulation-based requirements discovery method that utilises the benefits of a modular simulator that models future designs of DAT.