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Displaying 3 of 3 results urban mobility clear search
This study separates operational interoperability, fare integration and revenue-sharing governance in a stylised multi-operator bus network. An agent-based model implemented in NetLogo 7.0.3 represents passengers, buses and stations across 14 stations, nine routes and three operators. A 2 × 2 institutional design is complemented by financial clearing comparisons and 43,200 robustness runs: behavioural sensitivity (E1), a 243-configuration operational factorial (E2), and targeted joint behavioural–operational stress testing (E3). The audited experiment records show favourable interoperability effects on waiting, total travel time, transfers and realised generalised cost in all 1,944 E2 and 768 E3 configuration-level primary comparisons. Fare integration substantially reduces passenger expenditure but produces an aggregate deficit under the assumed accounting coefficients. Revenue-sharing rules redistribute operator-level outcomes without changing aggregate profit or passenger trajectories by construction. The model is intended to identify mechanisms and test conditional robustness, not predict city-specific policy effects. The paper contributes an explicit separation of access, pricing and settlement mechanisms coupled with reproducible factorial and stress-test comparisons.
We present the Integrated Urban Complexity model (IUCm 1.0) that computes “climate-smart urban forms”, which are able to cut emissions related to energy consumption from urban mobility in half. Furthermore, we show the complex features that go beyond the normal debates about urban sprawl vs. compactness. Our results show how to reinforce fractal hierarchies and population density clusters within climate risk constraints to significantly decrease the energy consumption of urban mobility. The new model that we present aims to produce new advice about how cities can combat climate change. From a technical angle, this model is a geographical automaton, conceptually interfacing between cellular automata and spatial explicit optimisation to achieve normative sustainability goals related to low energy. See a complete user guide at https://iucm.readthedocs.io/en/latest/ .
This ABM deals with commuting choices in the Italian city of Varese. Empirical data inform agents’ attitudes and modal choices costs and emissions. We evaluate ex ante the impact of policies for less polluting commuting choices.