Behavioral Heterogeneity as Quantum-Inspired Representation

• URL: http://arxiv.org/abs/2603.22729v1
• Date: Tue, 24 Mar 2026 02:48:18 GMT
• Title: Behavioral Heterogeneity as Quantum-Inspired Representation
• Abstract summary: We introduce quantum-inspired representation that models each driver as an evolving latent state, presented as a density matrix with structured mathematical properties.<n>We evaluate our approach on empirical driving data, Third Generation Data, showing how driving profiles are extracted and analyzed.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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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