Social interactions between automated vehicles and human drivers: a narrative review

Area of Science:

• Social sciences
• Human-computer interaction
• Transportation engineering

Background:

• Roads are inherently social environments for human interaction.
• The integration of automated vehicles (AVs) into traffic necessitates understanding human-AV social dynamics.
• Existing research on human-AV interactions in mixed traffic presents complex and often negative findings.

Purpose of the Study:

• To review and synthesize current research on human-AV social interactions in mixed traffic.
• To compare human-human interactions with human-AV interactions.
• To identify problematic social interaction patterns and future research directions.

Main Methods:

• Narrative review of empirical studies.
• Inclusion of diverse methodologies: survey experiments, simulator experiments, test-track experiments, on-road observations, and AV accident analysis.
• Synthesis of findings comparing regular traffic (human-human) with mixed traffic (human-AV).

Main Results:

• Evidence on human-AV interactions in mixed traffic is mixed, with an overall negative trend.
• Negative influences are bidirectional: humans may drive less cautiously around AVs, and AVs can negatively influence human driver behavior.
• Problematic interactions include aggressive driving, AV exploitation, negative peer influences, and challenges for drivers.

Conclusions:

• Human-AV interactions in mixed traffic pose significant challenges to road safety and social dynamics.
• A typology of problematic social interactions has been developed.
• Further research is needed to address the complexities and negative trends in human-AV road interactions.