The study of urban mobility has been recently enriched by important contributions made by physicists. In fact, by applying principles from statistical physics and network theory, physicists have uncovered patterns and dynamics within cities, shedding light on the intricate web of interactions governing commuter movement. For instance, physicists have utilized concepts from statistical physics to model traffic flow, simulating the movement of vehicles and pedestrians in complex urban environments. Network theorists have played a pivotal role in unraveling the structural complexities of transportation networks, revealing how nodes and edges represent vital intersections and routes crucial for efficient mobility. In this context, this Master's thesis explores the Padova bus network using advanced computational techniques, including Monte Carlo simulations and agent-based modeling. The research simulates traffic flow within a bilevel temporal graph framework, capturing the dynamic interplay of pedestrian and bus transit layers. A significant focus of the study is the evaluation of proposed modifications to the network, such as the introduction of a new tram line, along with the impact of an informed rescheduling of routes. These interventions are assessed through metrics like temporal distance, network efficiency, and travel demand clustering, providing insights into their impact on commuter behavior and overall connectivity. By leveraging these methods, the study offers actionable recommendations for optimizing public transport systems, aiding urban planners in enhancing traffic flow and addressing mobility challenges within the Padova province.
Lo studio della mobilità urbana è stato recentemente arricchito da importanti contributi forniti dai fisici. Infatti, applicando i principi della fisica statistica e della teoria delle reti, i fisici hanno scoperto schemi e dinamiche all'interno delle città, facendo luce sull'intricata rete di interazioni che governano i movimenti dei pendolari. Ad esempio, i fisici hanno utilizzato concetti della fisica statistica per modellare il flusso del traffico, simulando il movimento di veicoli e pedoni in ambienti urbani complessi. Gli studiosi di teoria delle reti hanno svolto un ruolo cruciale nello svelare le complessità strutturali delle reti di trasporto, rivelando come nodi e collegamenti rappresentino intersezioni e percorsi fondamentali per una mobilità efficiente. In questo contesto, questa tesi di laurea magistrale esplora la rete degli autobus di Padova utilizzando tecniche computazionali avanzate, tra cui simulazioni Monte Carlo e modelli basati su agenti. La ricerca simula il flusso del traffico all'interno di una struttura di grafo temporale a due livelli, catturando l'interazione dinamica tra gli strati di transito pedonale e quello degli autobus. Un focus significativo dello studio riguarda la valutazione delle modifiche proposte alla rete, come l'introduzione di una nuova linea tranviaria, insieme all'impatto di una riorganizzazione informata delle tratte. Questi interventi vengono analizzati tramite metriche quali la distanza temporale, l'efficienza della rete e la clusterizzazione della domanda di trasporto, fornendo approfondimenti sul loro impatto sul comportamento dei pendolari e sulla connettività complessiva. Sfruttando questi metodi, lo studio offre raccomandazioni pratiche per ottimizzare i sistemi di trasporto pubblico, aiutando i pianificatori urbani a migliorare il flusso del traffico e affrontare le sfide della mobilità nella provincia di Padova.
Montecarlo Simulations of Bus Flows
ZANOLI, ALESSANDRO
2023/2024
Abstract
The study of urban mobility has been recently enriched by important contributions made by physicists. In fact, by applying principles from statistical physics and network theory, physicists have uncovered patterns and dynamics within cities, shedding light on the intricate web of interactions governing commuter movement. For instance, physicists have utilized concepts from statistical physics to model traffic flow, simulating the movement of vehicles and pedestrians in complex urban environments. Network theorists have played a pivotal role in unraveling the structural complexities of transportation networks, revealing how nodes and edges represent vital intersections and routes crucial for efficient mobility. In this context, this Master's thesis explores the Padova bus network using advanced computational techniques, including Monte Carlo simulations and agent-based modeling. The research simulates traffic flow within a bilevel temporal graph framework, capturing the dynamic interplay of pedestrian and bus transit layers. A significant focus of the study is the evaluation of proposed modifications to the network, such as the introduction of a new tram line, along with the impact of an informed rescheduling of routes. These interventions are assessed through metrics like temporal distance, network efficiency, and travel demand clustering, providing insights into their impact on commuter behavior and overall connectivity. By leveraging these methods, the study offers actionable recommendations for optimizing public transport systems, aiding urban planners in enhancing traffic flow and addressing mobility challenges within the Padova province.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/78387