Language of Driving Concepts

The Language of Driving (LoD) describes the implicit and explicit signals that allow autonomous vehicles and humans to understand each other in mixed traffic [1–3].

Driving behavior can be analyzed as a layered communication system:

• Phonetics: visible cues such as lights or motion rhythm.
• Semantics: the meaning of those cues (e.g., yield, proceed).
• Pragmatics: how meaning changes with context and environment.

An autonomous vehicle must infer human intent and simultaneously display legible intent of its own [2].

Driving “languages” vary globally; hence interfaces must maintain universal meaning while allowing local adaptation [1]. Behavior should be recognizable but not anthropomorphic, preserving clarity across cultures [3].

Field experiments using light-based cues have shown that simple color and motion patterns effectively communicate awareness and yielding. Participants reported improved understanding when signals were consistent and redundant across modalities [2].

Formalizing LoD as a measurable framework is essential for verification, standardization, and interoperability of automated behavior [3].

References: [1] Razdan, R. et al. (2020). *Unsettled Topics Concerning Human and Autonomous Vehicle Interaction.* SAE EDGE Research Report EPR2020025. [2] Kalda, K., Sell, R., Soe, R.-M. (2021). *Use Case of Autonomous Vehicle Shuttle and Passenger Acceptance.* Proc. Estonian Academy of Sciences, 70 (4). [3] Kalda, K., Pizzagalli, S.-L., Soe, R.-M., Sell, R., Bellone, M. (2022). *Language of Driving for Autonomous Vehicles.* *Applied Sciences*, 12 (11).