Abstract

Vertically complex urban environments impose elevated spatial cognitive load on pedestrians, a  demand that static wayfinding infrastructure is structurally incapable of addressing. Smart cities  currently lack a formal cognitive navigation operating layer for managing pedestrian movement in  multi-level urban systems. This research introduces and evaluates a Cognitive Digital Twin  Operating System (Cognitive OS) — a city-scale adaptive navigation infrastructure integrating  Digital Twin environmental modelling, AI-driven route optimisation, real-time crowd intelligence,  and spatially embedded adaptive guidance to predict, manage, and reduce spatial cognitive load in  vertically complex environments. The study deploys AI-mediated human behavioral persona simulation as an independent methodological  contribution. Each of the 28 study agents constitutes a decoded human naviga- tional persona: a  behavioral reconstruction calibrated to empirical wayfinding parameters from the navigation science  literature (Argyle et al., 2023; Park et al., 2023; Aher et al., 2023), follow- ing the  simulation-first validation paradigm in which AI agents serve as surrogate participants for  rigorous proof-of-concept evaluation. A within-subjects, counterbalanced design compared  performance across an Adaptive Cognitive OS (ACO) condition and a Static Signage (SS) baseline in a  fifteen-floor mixed-use virtual building. Measures included NASA-TLX cognitive workload, wrong-turn  and hesitation frequency, navigation time, path efficiency, eye-tracking gaze metrics, and  post-navigation spatial recall. Results proved large, Significant improvements across all primary outcomes. NASA-TLX composite  workload fell by 37% (d = 1.76, p < .001); wrong-turn frequency by 67% (r = 0.93, p < .001);  navigation time by 35.9% (d = 2.29, p < .001); path efficiency improved from 0.61 to 0.87 (d =  2.37, p < .001); and visual search time by 61.0% (d = 2.80, p < .001). Spatial recall showed no  statistically significant difference across conditions (d = 0.38, p = .054), a finding that remains  inconclusive given the study’s power at that effect size. These findings establish that spatial cognitive load is a measurable, manageable urban in-  frastructure variable and that the Cognitive OS provides a viable platform for its management at  city scale. Five evidence-based design principles are derived. The research makes contributions to Cognitive Load Theory, digital twin systems, and smart city infrastructure design.

Library of Congress Subject Headings

Digital twins (Computer simulation); Orientation; Smart cities; Tall buildings

Publication Date

Spring 2026

Document Type

Thesis

Student Type

Graduate

Degree Name

Professional Studies (MS)

Department, Program, or Center

Graduate Programs & Research

Advisor

Ayman Ibrahim

Comments

This thesis has been embargoed. The full-text will be available on or around 5/12/2027.

Campus

RIT Dubai

Plan Codes

PROFST-MS

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