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This thesis investigates the effects of car-reducing measures on travel behaviour using the redesign of Hofplein in Rotterdam as a case study. The intervention reduces road capacity by transforming a car-oriented traffic square into a multimodal public space, thereby reducing car accessibility at an important node in the transport network. The study examines both the overall behavioural impacts of this accessibility reduction and the extent to which these impacts vary between traveller groups.
An activity-based transport model (ActivitySim) was used to simulate traveller behaviour before and after the intervention. Accessibility changes resulting from the Hofplein redesign were first estimated using the V-MRDH traffic assignment model and subsequently incorporated into ActivitySim. To improve behavioural realism, the model was calibrated against both observed modal shares and literature-based travel-time elasticities using Bayesian optimisation. Simulated travellers were subsequently linked to ten mobility personas to analyse behavioural responses across different socio-demographic groups.
The calibrated model reproduced both observed modal shares and benchmark travel-time elasticities reasonably well. Simulation results indicate that the intervention reduces car use while increasing walking, cycling, e-bike use, and public transport demand. However, modal shift explains only part of the response. Many travellers continue travelling by car by selecting alternative routes, while others adapt through destination changes or trip suppression. The analysis further shows that impacts are distributed unevenly across the population, with car-oriented personas experiencing the largest accessibility reductions and behavioural responses.
These findings demonstrate the value of activity-based transport models for evaluating transport interventions. By capturing individual behavioural adaptation and distributional effects, such models provide a more detailed understanding of the impacts of car-reducing measures and can support more equitable transport policy development. ...
This thesis investigates the effects of car-reducing measures on travel behaviour using the redesign of Hofplein in Rotterdam as a case study. The intervention reduces road capacity by transforming a car-oriented traffic square into a multimodal public space, thereby reducing car accessibility at an important node in the transport network. The study examines both the overall behavioural impacts of this accessibility reduction and the extent to which these impacts vary between traveller groups.
An activity-based transport model (ActivitySim) was used to simulate traveller behaviour before and after the intervention. Accessibility changes resulting from the Hofplein redesign were first estimated using the V-MRDH traffic assignment model and subsequently incorporated into ActivitySim. To improve behavioural realism, the model was calibrated against both observed modal shares and literature-based travel-time elasticities using Bayesian optimisation. Simulated travellers were subsequently linked to ten mobility personas to analyse behavioural responses across different socio-demographic groups.
The calibrated model reproduced both observed modal shares and benchmark travel-time elasticities reasonably well. Simulation results indicate that the intervention reduces car use while increasing walking, cycling, e-bike use, and public transport demand. However, modal shift explains only part of the response. Many travellers continue travelling by car by selecting alternative routes, while others adapt through destination changes or trip suppression. The analysis further shows that impacts are distributed unevenly across the population, with car-oriented personas experiencing the largest accessibility reductions and behavioural responses.
These findings demonstrate the value of activity-based transport models for evaluating transport interventions. By capturing individual behavioural adaptation and distributional effects, such models provide a more detailed understanding of the impacts of car-reducing measures and can support more equitable transport policy development.
Contrail Mitigation in Air Traffic Operations
Feasibility, Detection, and Optimization with Open Data
Chapter 2 explains that contrails form when engine exhaust mixes with sufficiently cold, humid air (the Schmidt-Appleman Criterion, SAC) and persist only in ice-supersaturated regions (ISSRs).
Chapter 3 tests whether open data can identify contrail formation. Contrails identified in GOES-16 imagery were matched to OpenSky trajectories and ERA5 data. SAC and ISSR together predicted persistent formation with 87% accuracy, validating ERA5 for this purpose.
Chapter 4 addresses formation altitude. A novel method estimates contrail altitude from the shadows contrails cast in Landsat 8 imagery, using solar geometry and the Hough transform to pair them. Validated against ADS-B GPS altitude, it is accurate to within a few hundred meters. A ResUNet with a novel SR loss, which penalizes deviations in Hough space to enforce contrail linearity, automates this. Contrail detection performed well, shadow detection less so.
Chapter 5 asks whether routine step-climb altitude changes suffice to avoid ISSRs. Of 5.7 million flights analyzed, about 3.5% produced persistent contrails. Among flights that could leave the ISSR within 2000 ft, about 50% could do so with a step of ±1000 or ±2000 ft.
Chapter 6 develops an open-source climate trajectory optimizer on OpenAP.top and applies it to nearly 1.4 million Euro-Atlantic flights. Climate-optimized trajectories reduced persistent contrail time by roughly 15% relative to fuel-optimal routing, at 20–25% more fuel. Since fuel-optimal routes are about 23% more efficient than flown trajectories, climate-optimal fuel burn stays comparable to current operations.
Chapter 7 examines operations and economics. For 1.6 million flights, optimization on ARPEGE forecasts differed from an ERA5 benchmark by only 0.8% in flight time and 2.2% in fuel burn, but retained about 25% more contrail time. In 91.3% of Flight Information Regions, traffic changed by at most five aircraft per three-hour window. The average cost was €1551 per flight.
Together, the chapters show that contrail mitigation is technically feasible at network scale without unacceptable safety or capacity impact. The main barrier is the reliability of humidity forecasts, not the optimization. Because a small fraction of flights drives most of the contrail impact, targeting them yields large benefit at moderate cost. This requires better numerical weather prediction, regulatory clarity on forecast-error accountability, and open data sharing. ...
Chapter 2 explains that contrails form when engine exhaust mixes with sufficiently cold, humid air (the Schmidt-Appleman Criterion, SAC) and persist only in ice-supersaturated regions (ISSRs).
Chapter 3 tests whether open data can identify contrail formation. Contrails identified in GOES-16 imagery were matched to OpenSky trajectories and ERA5 data. SAC and ISSR together predicted persistent formation with 87% accuracy, validating ERA5 for this purpose.
Chapter 4 addresses formation altitude. A novel method estimates contrail altitude from the shadows contrails cast in Landsat 8 imagery, using solar geometry and the Hough transform to pair them. Validated against ADS-B GPS altitude, it is accurate to within a few hundred meters. A ResUNet with a novel SR loss, which penalizes deviations in Hough space to enforce contrail linearity, automates this. Contrail detection performed well, shadow detection less so.
Chapter 5 asks whether routine step-climb altitude changes suffice to avoid ISSRs. Of 5.7 million flights analyzed, about 3.5% produced persistent contrails. Among flights that could leave the ISSR within 2000 ft, about 50% could do so with a step of ±1000 or ±2000 ft.
Chapter 6 develops an open-source climate trajectory optimizer on OpenAP.top and applies it to nearly 1.4 million Euro-Atlantic flights. Climate-optimized trajectories reduced persistent contrail time by roughly 15% relative to fuel-optimal routing, at 20–25% more fuel. Since fuel-optimal routes are about 23% more efficient than flown trajectories, climate-optimal fuel burn stays comparable to current operations.
Chapter 7 examines operations and economics. For 1.6 million flights, optimization on ARPEGE forecasts differed from an ERA5 benchmark by only 0.8% in flight time and 2.2% in fuel burn, but retained about 25% more contrail time. In 91.3% of Flight Information Regions, traffic changed by at most five aircraft per three-hour window. The average cost was €1551 per flight.
Together, the chapters show that contrail mitigation is technically feasible at network scale without unacceptable safety or capacity impact. The main barrier is the reliability of humidity forecasts, not the optimization. Because a small fraction of flights drives most of the contrail impact, targeting them yields large benefit at moderate cost. This requires better numerical weather prediction, regulatory clarity on forecast-error accountability, and open data sharing.
Improving Arithmetic Skills through Online Puzzle Games
An analysis of the features of online arithmetic puzzle games that contribute to the development of procedural fluency, strategic competence and adaptive reasoning of secondary school students
Hacking adaptation
What role can policy hackathons play in understanding and adapting to climate change impacts?
Planners and policy makers face complex and pressing decisions under climate change. To complement traditional planning processes, new tools and methods are needed to make rapid and integrated assessments of climate change impacts and adaptation options. In this perspective, we reflect on the potential of policy hackathons to support climate adaptation planning and policy development. Drawing on five hackathons conducted in Brazil and the Netherlands, we illustrate how these short, intensive, co-creation events enabled first-order assessments of climate risks and adaptation options, fostered interdisciplinary collaboration, and catalyzed action. We argue that policy hackathons are a promising approach for exploring urgent and emergent questions, identifying knowledge gaps, and generating momentum within planning and policy-making processes. Hackathons also support the continuous learning and innovation required by adaptation. Most importantly, within planning and policy processes, hackathons can contribute to accelerating climate action.