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arXiv · 2603.22729

Behavioral Heterogeneity as Quantum-Inspired Representation

Mohammad Elayan·Wissam Kontar
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Abstract

Driver heterogeneity is often reduced to labels or discrete regimes, compressing what is inherently dynamic into static categories. We introduce quantum-inspired representation that models each driver as an evolving latent state, presented as a density matrix with structured mathematical properties. Behavioral observations are embedded via non-linear Random Fourier Features, while state evolution blends temporal persistence of behavior with context-dependent profile activation. We evaluate our approach on empirical driving data, Third Generation Simulation Data (TGSIM), showing how driving profiles are extracted and analyzed.

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Mohammad Elayan, Wissam Kontar. 2026-03-24. Behavioral Heterogeneity as Quantum-Inspired Representation. https://arxiv.org/abs/2603.22729

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