Kasper M. van Zuilekom

A Decision support system for preventive evacuation of people

As a densely populated country in a delta the Netherlands have to be very considered about flooding risks. Up to 65% of its surface is threatened by either sea or rivers. The Dutch government has started a research project ‘Floris’ (Flood Risk and Safety in the Netherlands) to calculate the risks of about half of the 53 dike-ring areas of The Netherlands. This project has four tracks: (1) determining the probability of flooding risks of dike-rings areas; (2) the reliability of hydraulic structures; (3) the consequences of flooding and (4) coping with uncertainties.

Comparison of Neural Networks and Gravity Models in Trip Distribution

Transportation engineers are commonly faced with the question of how to extract information from expensive and scarce field data. Modeling the distribution of trips between zones is complex and dependent on the quality and availability of field data. This research explores the performance of neural networks in trip distribution modeling and compares the results with commonly used doubly constrained gravity models. The approach differs from other research in several respects; the study is based on both synthetic data, varying in complexity, as well as real-world data. Furthermore, neural networks and gravity models are calibrated using different percentages of hold out data. Extensive statistical analyses are conducted to obtain necessary sample sizes for significant results. The results show that neural networks outperform gravity models when data are scarce in both synthesized as well as real-world cases. Sample size for statistically significant results is forty times lower for neural networks.

Evacuation a serious game for preparation

Mass evacuation is a measure to reduce possible loss of life in the case of potential disasters. Planning for mass evacuation is only useful if these plans are tested and evaluated by government and the public in reality or in simulated events. As a result, any prior experience is likely to be outdated by the next incident, because social structures, public perceptions, perception of decision makers, emergency planning and infrastructure all change over time and based on the previous experience. Especially in the Netherlands mass evacuation in the case of large-scale flooding is once-in-a-lifetime experience or less event because of the high protection level for flooding. The use of serious gaming is an alternative to gather required experience of conduction an evacuation in several events. This article describes the development of a serious game for mass evacuation, as well as experiences gathered from exercises using SPOEL. Finally is concluded that it is possible to evaluate emergency planning for evacuation and develop realistic experience through exercises using SPOEL, in an effort to compensate the gap in experience because of a lack of real life mass-evacuation experience.