Modeling urban traffic volume incorporating driver stochasticity and traffic correlation with waveguide-based quantum walk.

Urban traffic involves two stochastic factors, complicating accurate modeling: (1) Driver stochasticity, arising from driver heterogeneity and random environment perturbations, introduces unpredictable fluctuations in urban traffic volume. (2) Traffic correlation, referring to the interaction in traffic states across different regions. This paper proposes a waveguide-based quantum walk urban traffic volume model (UTVDC-QW), incorporating driver stochasticity and traffic correlation. The model uses waveguide arrays to map urban traffic networks, incorporates random environment perturbations via noise, and traffic correlation via waveguide coupling. UTVDC-QW develops measures of environment perturbations and traffic correlations. Experiments with Chengdu traffic datasets demonstrate that UTVDC-QW improves the simulation accuracy compared to reference models. In addition, the model reveals the characteristics of environment perturbations and traffic correlation in the study area. Overall, this study effectively incorporates driver stochasticity and traffic correlation by waveguide-based quantum walk, is a pioneering attempt to apply quantum computing to urban traffic modeling. [ABSTRACT FROM AUTHOR]