← 研踪 PaperTrailarXiv:2611.14499 · v1
Spatial patterns of transportation choice in Niterói
首次提交 2026-11-11 02:51
版本更新 2026-11-11 02:51
雷达观测 2026-11-11 13:07
摘要
Characterizing how people move through a city requires spatially and temporally fine-grained data that are often costly and difficult to obtain. Here, we introduce a computational framework that uses macroscopic, aggregated, and static urban data to construct a microscopic, dynamic, and spatially detailed representation of urban mobility. Building on an existing activity simulator, the framework combines a synthetic population, the built environment, and transport networks to generate daily trips and assign walking, car, or public transit. Applied to approximately 475,000 synthetic residents of Niterói, Brazil, simulated neighborhood-level transit patterns show a strong association with an empirical activity proxy (Pearson r=0.885). Walking is more prevalent in compact central areas, car use increases toward the periphery, and public-transit use remains comparatively high along bus corridors. Reducing walking times to and from bus stops by 30% increases the modeled public-transit-to-car ratio by 11.3%, with larger transit-share gains in several peripheral areas. These results reveal spatial differences in transportation choice and identify where improved transit access may have the greatest modeled effect.
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v1 · 2026-11-11 02:51 · 最新观测版本
Spatial patterns of transportation choice in Niterói
Characterizing how people move through a city requires spatially and temporally fine-grained data that are often costly and difficult to obtain. Here, we introduce a computational framework that uses macroscopic, aggregated, and static urban data to construct a microscopic, dynamic, and spatially detailed representation of urban mobility. Building on an existing activity simulator, the framework combines a synthetic population, the built environment, and transport networks to generate daily trips and assign walking, car, or public transit. Applied to approximately 475,000 synthetic residents of Niterói, Brazil, simulated neighborhood-level transit patterns show a strong association with an empirical activity proxy (Pearson r=0.885). Walking is more prevalent in compact central areas, car use increases toward the periphery, and public-transit use remains comparatively high along bus corridors. Reducing walking times to and from bus stops by 30% increases the modeled public-transit-to-car ratio by 11.3%, with larger transit-share gains in several peripheral areas. These results reveal spatial differences in transportation choice and identify where improved transit access may have the greatest modeled effect.
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