ABSTRACT. The electrification of ferry systems introduces substantial operational challenges due to high energy demands, charging requirements, and berth limitations. This paper proposes a Mixed Integer Linear Programming (MILP) model to optimize vessel scheduling and timetabling for electrified public transport ferries. The model minimizes a convex combination of fleet size and unproductive rebalancing time, while explicitly incorporating charging constraints, berth capacities, and crew rest periods. To ensure scalability, we develop problem-specific heuristics and apply them to a real-world case study in Sydney, Australia. The model generates feasible, efficient itineraries that outperform the benchmarks. Notably, results show that with sufficient charging infrastructure, fleet size can be reduced without significantly increasing idle time. On the other hand, electrification of the Sydney ferry network could be unfeasible depending on the charging technology. This framework supports strategic planning for electrified public transport ferries, contributing to the decarbonisation of the transport sector.

ABSTRACT. This paper introduces a novel bottleneck model incorporating nonlinear emission costs to analyze user equilibrium traffic patterns. We examine how emission-based pricing affects commuter behavior during morning rush hours, focusing on the interplay between congestion, schedule delays, and environmental impacts. Our model reveals that introducing nonlinear emission costs shifts equilibrium departure patterns, potentially reducing overall emissions without eliminating queues. We demonstrate that the longest queues no longer necessarily occur for on-time arrivals, but instead shift towards earlier departures. This research contributes to the growing body of work on sustainable urban transportation, offering insights for policymakers seeking to balance congestion management with environmental concerns.

ABSTRACT. Japan has a long history of managing natural hazards due to its geography and geology. Simultaneously, it is known as a country with a railway system that is highly punctual, reliable, and safe. This research uses an exploratory approach to review climate change adaptation and disaster risk reduction practices in the Greater Tokyo Area. Unstructured interviews with various stakeholders and a literature review discuss how the climate is changing in Japan, what strategies are used amongst railway organisations to manage meteorological hazards, and how railway organisation acknowledges climate change adaptation alongside disaster risk reduction. Results indicate that disaster risk reduction practices still dominate within the railway sector however, more efforts of climate change adaptation set forth by the government may shift practices.

ABSTRACT. Demand Responsive Transport (DRT) systems can struggle with user retention due to variability in ride-time experiences, even within guaranteed service levels. Under constant aggregate demand, the stochasticity of users’ daily travel decisions can alter the order of pick-ups and hence ride-time. Simulation results indicate that users can experience very high levels of ride-time volatility, regardless of their origin. This work investigates how the detour factor, as an individual level-of-service constraint, can limit experienced ride-time fluctuations and hence mitigate against users leaving the system.