Data-Driven Spatial-Temporal Modeling for Bicycle Traffic Prediction
X. Wen (TU Delft - Traffic Systems Engineering)
S.P. Hoogendoorn – Promotor (TU Delft - Traffic Systems Engineering)
D.C. Duives – Copromotor (TU Delft - Transport, Mobility and Logistics)
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Abstract
With increasing awareness of the environmental impacts of motorized trans-port. low-carbon mobility modes such as cycling are gaining importance. This dissertation investigates bicycle traffic dynamics and develops data-driven spatial-temporal prediction models under varying environmental and operational conditions. The findings aim to support policymakers, mobility providers, and system developers in making more efficient and evidence-based decisions for bicycle transportation systems.