Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userGeographic characterization of railway systems
59
0
0.0
(
0
)
Added by
Mark Matthijs Dekker
Publication date
2021
fields
Physics
and research's language is
English
Authors
Mark M. Dekker
Ask ChatGPT about the research
No Arabic abstract
Railway systems provide pivotal support to modern societies, making their efficiency and robustness important to ensure. However, these systems are susceptible to disruptions and delays, leading to accumulating economic damage. The large spatial scale of delay spreading typically make it difficult to distinguish which regions will ultimately affected from an initial disruption, creating uncertainty for risk assessment. In this paper, we identify geographical structures that reflect how delay spreads through railway networks. We do so by proposing a graph-based, hybrid schedule and empirical-based model for delay propagation and apply spectral clustering. We apply the model to four European railway systems: the Netherlands, Germany, Switzerland and Italy. We characterize geographical structures in the railway systems of these countries and interpret these regions in terms of delay severity and how dynamically disconnected they are from the rest. The method also allows us to point out important differences between these countries railway systems. For practitioners, this geographical characterization of railways provide natural boundaries for local decision-making structures and a first-order prioritization on which regions are at risk, given an initial disruption.
rate research
Read More
Available alternative routes on which traffic can be rerouted in the case of disruptions are vital for transportation networks. Line sections with less traffic under normal operational conditions but with increased importance in the case of disruptions are identified in the railway network of Hungary by using a weighted directed graph. To describe the goodness of the individual alternative routes the so-called redundancy index is used. The results show that the structure of the network is good, but the lines with the highest redundancy (lines No. 80, 2, 4 and 77 according to the numbering of the national railway operator, MAV) are mostly single tracked and in many cases the line speed is low. The building of additional tracks and electrifying these lines while still maintaining the existing diesel locomotives for the case of disruptions of the electric support are the keys to make the performance of the rather dense railway network of Hungary sustainable.
Social groups are fundamental building blocks of human societies. While our social interactions have always been constrained by geography, it has been impossible, due to practical difficulties, to evaluate the nature of this restriction on social group structure. We construct a social network of individuals whose most frequent geographical locations are also known. We also classify the individuals into groups according to a community detection algorithm. We study the variation of geographical span for social groups of varying sizes, and explore the relationship between topological positions and geographic positions of their members. We find that small social groups are geographically very tight, but become much more clumped when the group size exceeds about 30 members. Also, we find no correlation between the topological positions and geographic positions of individuals within network communities. These results suggest that spreading processes face distinct structural and spatial constraints.
Railway systems form an important means of transport across the world. However, congestions or disruptions may significantly decrease these systems efficiencies, making predicting and understanding the resulting train delays a priority for railway organisations. Delays are studied in a wide variety of models, which usually simulate trains as discrete agents carrying delays. In contrast, in this paper, we define a novel model for studying delays, where they spread across the railway network via a diffusion-like process. This type of modelling has various advantages such as quick computation and ease of applying various statistical tools like spectral methods, but it also comes with limitations related to the directional and discrete nature of delays and the trains carrying them. We apply the model to the Belgian railways and study its performance in simulating the delay propagation in severely disrupted railway situations. In particular, we discuss the role of spatial aggregation by proposing to cluster the Belgian railway system into sets of stations and adapt the model accordingly. We find that such aggregation significantly increases the models performance. For some particular situations, a non-trivial optimal level of spatial resolution is found on which the model performs best. Our results show the potential of this type of delay modelling to understand large-scale properties of railway systems.
Rockfalls pose a substantial threat to ground transportation, due to their rapidity, destructive potential and high probability of occurrence on steep topographies, found along roads and railways. Approaches for assessment of rockfall susceptibility range from purely phenomenological methods and statistical methods, suitable for modeling large areas, to purely deterministic ones, usually easier to use in local analyses. A common requirement is the need to locate potential detachment points, often found uphill on cliffs, and the subsequent assessment of the runout areas of rockfalls stemming from such points. Here, we apply a physically based model to calculate rockfall trajectories along the whole Italian railway network, within a corridor of total length of about 17,000 km and varying width. We propose a data-driven method for the location of rockfall source points based on expert mapping of potential source areas on sample representative locations. Using empirical distributions of gridded slope values in source areas mapped by experts, we derived probabilistic maps of rockfall sources in the proximity of the railway network, regardless of a particular trigger. Source areas act as starting points of simulated trajectories in the three-dimensional model STONE. The program provides a pixel-by-pixel trajectory count, covering 24,500 km2, the largest homogeneous application of the model to date. We classified the map into a vector susceptibility map of the segments of the railway, for which we provide segment-wise rockfall susceptibility. Eventually, we considered a graph representation of the network to classify the segments both on the basis of rockfall susceptibility and the role of each segment in the network, resulting in a network-ranked susceptibility. Both maps are useful for subsequent hazard assessment, and to prioritize safety improvements along the railway, at national scale.
Accurate modelling of local population movement patterns is a core contemporary concern for urban policymakers, affecting both the short term deployment of public transport resources and the longer term planning of transport infrastructure. Yet, while macro-level population movement models (such as the gravity and radiation models) are well developed, micro-level alternatives are in much shorter supply, with most macro-models known to perform badly in smaller geographic confines. In this paper we take a first step to remedying this deficit, by leveraging two novel datasets to analyse where and why macro-level models of human mobility break down at small scales. In particular, we use an anonymised aggregate dataset from a major mobility app and combine this with freely available data from OpenStreetMap concerning land-use composition of different areas around the county of Oxfordshire in the United Kingdom. We show where different models fail, and make the case for a new modelling strategy which moves beyond rough heuristics such as distance and population size towards a detailed, granular understanding of the opportunities presented in different areas of the city.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
