SOURCE-LINKED INTELLIGENCE

Quantum-Inspired Modeling of Driving Behavior

arXiv · AI, language, vision and robotics · article · Aug 26, 2026 · UTC

Driver behavior is heterogeneous, context-dependent, and changes over time, and these properties shape the traffic phenomena we observe. Most models, however, fix in advance which behavioral variables interact and how. Behavior outside that form is absorbed as noise, while models flexible enough to capture it tend to lose interpretability. We introduce a quantum-inspired representation of driver behavior that combines properties usually treated separately or in part: it is continuous, probabilistic, context-dependent, history-dependent, and represents interactions among behavioral variables as

Read original source ↗ Open in workspace

recordType

paper

region

Global