This researchextracts trajectories of non-directional micromobility traffic (pedestrians,cyclists, and mopeds) in a shared right-of-way urban space, applying aVoronoi-based area-weighted framework to construct Network Fundamental Diagrams(NFDs). Using an aggregation technique tha
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This researchextracts trajectories of non-directional micromobility traffic (pedestrians,cyclists, and mopeds) in a shared right-of-way urban space, applying aVoronoi-based area-weighted framework to construct Network Fundamental Diagrams(NFDs). Using an aggregation technique that weights by link length, we exploretwo Voronoi-based approaches for generating NFDs from microscopic data: astandard mixed-mode approach and a novel mode-isolated approach. Resultsdemonstrate that both methods accurately compute macroscopic traffic measures,and mode-isolated approach, in particular, reveals unique contribution of eachmode to the NFD. Cyclists and mopeds drive performance dominance, shaping theNFD even when pedestrians dominate traffic composition (mode-share dominance).This study empirically validates existence of mixed two-dimensional traffic NFDincluding critical capacities and jam densities and highlights the aggregateimpact of individual modes. The findings underscore the potential ofarea-weighted aggregation to account for heterogeneity in urban mixed traffic,offering insights into capacity and efficiency evaluations for non-motorizedtransport systems.