To Cooperate or Not to Cooperate: A Systematic Review and Meta-Analysis of Human Driving Behavior in Interactions with Autonomous Vehicles
Yilin Kou, Qian Zhou, Jianping Wang, Nancy Xiaonan Yu
Abstract
Cooperation among human-driven vehicles (HVs) is essential for traffic safety and efficiency. However, the emergence of autonomous vehicles (AVs) has prompted a new question: Will HVs still cooperate with AVs? Prior studies and narrative reviews yielded inconsistent findings. To answer this question, we conducted the first systematic review and meta-analysis of HV–AV cooperation, synthesizing evidence from 24 articles, 27 samples, 32 effect sizes, and 5,778 participants. Results revealed that people drive less cooperatively when interacting with AVs than with HVs (Hedges’ g = − 0.19, 95% CI [ − 0.31, − 0.07]). The meta-regression revealed a significant link between cooperative driving and the year of publication, with more recent studies showing more cooperation; other moderators (e.g., data collection methods) were not significant. We discuss the implications of less cooperation for AV development, traffic regulations, and human–AI cooperation, and current challenges in theory, replicability, and ecological validity, in addition to offering recommendations for future research.
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