{'fraction_non_alphanumeric': 0.024203821656050957, 'fraction_numerical': 0.0, 'mean_word_length': 5.093023255813954, '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}}
Deconfliction of Motion Paths With Traffic Inspired Rules

In this letter, we investigate how to resolve conflicting motions for mixed robot–robot and human–robot multiagent systems. This letter is motivated by atypical driving conditions, such as parking lots, where driving rules are not as strictly enforced as on standard roads. As a result, navigation algorithms should take into account the human drivers’ behaviors, especially if they prove to be in conflict with the common rules of the road. In this letter, we make use of safety barrier certificates with a direction bias to deconflict agents’ behavior in a near-to-collision scenario, in compliance with local traffic rules. We also propose a tool to identify the driving direction bias—both for human and autonomous agents.