SPAT – Situational Prosocial and Aggressive Behaviour in Traffic Scale

Hatice Şahin Ippoliti, Mark Colley, Debargha Dey, Philipp Wintersberger, Shadan Sadeghian, Andreas Löcken, Andrii Matviienko, Azra Habibovic, Heiko Müller, Andrea Hildebrandt, Susanne Boll
Multiple institutions, AutomotiveUI 2025 (ACM)
Paper (pre‑print) Scale (SPAT) SPAT for LimeSurvey SPAT for Qualtrics SPAT in Word

SPAT enables rigorous evaluation of social perception in mixed traffic, supporting safer and more cooperative interaction between human and automated road users.

Abstract

Automated vehicles are nearing deployment maturity, yet effective interaction in mixed traffic hinges on reliable social judgement. We introduce SPAT, a twelve‑item semantic‑differential scale that quantifies perceived prosocial and aggressive behaviour across road users, including automated vehicles. Exploratory and confirmatory factor analyses (N = 318) established a robust three‑factor structure – socialness, predictability, and awareness. External validity was demonstrated in a controlled test‑track study, where SPAT captured drivers’ perception shifts in response to an automated vehicle’s intent display. SPAT offers a concise tool for researchers and practitioners to assess social‑behaviour perception and inform interface or policy design.

BibTeX

@inproceedings{SahinIppoliti2018SPAT,
  author       = {Şahin Ippoliti, Hatice and Colley, Mark and Dey, Debargha and
                  Wintersberger, Philipp and Sadeghian, Shadan and Löcken, Andreas and
                  Matviienko, Andrii and Habibovic, Azra and Müller, Heiko and
                  Hildebrandt, Andrea and Boll, Susanne},
  title        = {{SPAT: Situational Prosocial and Aggressive Behavior Perception in Traffic Scale}},
  booktitle    = {Proceedings of AutomotiveUI ’25},
  year         = {2025},
  publisher    = {ACM},
  address      = {New York, NY, USA},
  url		   = {https://doi.org/10.1145/3744333.3747812},
  doi		   = {10.1145/3744333.3747812}
}