Identification of Central Points in Road Networks using Betweenness Centrality Combined with Traffic Demand

Abstract-This paper aims to identify central points in road networks considering traffic demand. This is made with a variation of betweenness centrality. In this variation, the graph that corresponds to the road network is weighted according to the number of routes generated by the traffic demand. To test the proposed approach three networks have been created, which are Porto Alegre and Sioux Falls cities and a regular 10 × 10 grid. Then, trips were microscopically simulated and the results were compared with the proposed method

Evidence on Impact Evaluation of Road Transport Networks using Network Theory

The development of network theory has resulted in a growing understanding of the topological properties of transport networks. This has led to knowledge on how network indicators relate to the performance of a network, their wider socio-economic impacts and insights about how networks can best be extended. It has also provided transport planners with an insight into traffic flow, travel demand, centrality and connectivity of transport networks. This rapid evidence-review summarises literature (1999-2019) that have used network theory to evaluate the impact evaluation of road networks, it also presents the technological advancements in network theory. The identified studies outline the beneficial impacts of road networks on the economy, how connectivity can be improved to improve network resilience, reliability, performance and reduce maintenance costs. A number of studies describe how networks can be designed to reduce the impact on the environment. However, with the exception of only three studies i.e Kumar and Kumar (1999), Vasas and Magura et al. (2009) and Walker et al. (2013), the impacts are not quantified. The magnitude of the impact, for a particular network, is a function of the type of model used. As studies could not be found where different models have been used to assess similar impacts, it was not possible to compare numerically the impacts of different model types. Enhancements to network theory have focused on (i) developing new measures and indicators to assess connectivity, vulnerability and economic impact of transport networks, (ii) applying weightages to nodes and links to evaluate economic and ecological impacts and (iii) developing multiple layers within the network models for better spatial analysis. Recent studies have also expanded network theory and integrated it with risk modelling and probabilistic methodologies to identify vulnerable or critical elements within a given transport network

Network Centralities in Polycentric Urban Regions: Methods for the Measurement of Spatial Metrics

The primary aim of this thesis is to explain the complex spatial organisations of polycentric urban regions (PURs). PURs are a form of regional morphology that often evolves from post-industrial structures and describe a subnational area featuring a plurality of urban centres. As of today, the analysis of the spatial organisation of PURs constitutes a hitherto uncharted territory. This is due to PURs’ inherent complexity that poses challenges for their conceptualisation. In this context, this thesis reviews theories on the spatial organisation of regions and cities and seeks to make a foundational methodological contribution by joining space syntax and central place theory in the conceptualisation of polycentric urban regions. It takes into account human agency embedded in the physical space, as well as the reciprocal effect of the spatial organisation for the emergence of centralities and demonstrates how these concepts can give insights into the fundamental regional functioning. The thesis scrutinises the role that the spatial organisation plays in such regions, in terms of organising flows of goods and people, ordering locational occupation and fostering centres of commercial activity. It proposes a series of novel measurements and techniques to analyse large and messy datasets. This includes a method for the application of large-scale volunteered geographic information in street network analysis. This is done, in the context of two post-industrial regions: the German Ruhr Valley and the British Nottinghamshire, Derbyshire and Yorkshire region. The thesis’ contribution to the understanding of regional spatial organisation and the study of regional morphology lies in the identification of spatial structural features of socio-economic potentials of regions and particular areas within them. It constitutes the first comparative study of comprehensive large-scale regional spatial networks and presents a framework for the analysis of regions and the evaluation of the predictive potential of spatial networks for socio-economic patterns and the location of centres in regional contexts

A Micro-Scale Analysis of Cycling Demand, Safety, and Network Quality

This research uses a unique database of cycling volumes from the San Diego region to estimate cycling demand and cycling collision models. Continuous cycling count data collected from 34 automated counters are used to extrapolate over 1,400 short duration counts to average annual daily bicycle volumes (AADB). Network characteristics, built environment, and socio-economic characteristics are primary independent variables employed in the modeling. A key contribution of this research is to incorporate both a whole-network measure (betweenness centrality) and a network quality measure (LTS) in estimating cycling volumes. This research also improves upon cycling risk assessment by using more rigorous exposure measures, meaning that not only is the number of collisions at a particular location taken into consideration, but the overall cyclist volume is also considered. A final key contribution is to assess the correlation between ad hoc cycling propensity models used by practicing planners in San Diego and actual AADB. The research findings show that betweenness centrality is significant in estimating cycling volumes, meaning that as the centrality or importance of a roadway segment increases, cycling volumes also increase. It is important for long-range bicycle planners and local government traffic engineers to understand that key connections in the network draw cyclists as well as drivers and should have cycling infrastructure of adequate quality. In many instances, when connections are critical and constrained, cycling infrastructure is the first design element to be dropped. The rate of cycling collisions is found to be significantly related to proximity to freeways (higher collision rates closer to freeways), to lower income neighborhoods (higher cycling collision rates in lower income neighborhoods), and to higher density neighborhoods. In the case of San Diego’s ad hoc bicycle planning tools, this research shows that indeed, high cycling propensity is related to higher bicycle volumes. A critical policy implication of this research is that local government mobility planners should more holistically consider cycling networks in their long-range plans and short-range implementation efforts, and that network-based performance measures can be more informative than demand- based performance metrics for the cycling mode. Network-based performance metrics need to be explored more rigorously in local planning as they are easy to calculate and shown to be statistically significant predictors of cycling demand

Modeling the Internet of Things: a simulation perspective

This paper deals with the problem of properly simulating the Internet of Things (IoT). Simulating an IoT allows evaluating strategies that can be employed to deploy smart services over different kinds of territories. However, the heterogeneity of scenarios seriously complicates this task. This imposes the use of sophisticated modeling and simulation techniques. We discuss novel approaches for the provision of scalable simulation scenarios, that enable the real-time execution of massively populated IoT environments. Attention is given to novel hybrid and multi-level simulation techniques that, when combined with agent-based, adaptive Parallel and Distributed Simulation (PADS) approaches, can provide means to perform highly detailed simulations on demand. To support this claim, we detail a use case concerned with the simulation of vehicular transportation systems.Comment: Proceedings of the IEEE 2017 International Conference on High Performance Computing and Simulation (HPCS 2017

Rethinking Streets: a study of streetspace allocation metrics and street networks in London

This research investigates streetspace allocation metrics for all streets in London providing quantitative evidence about a key parameter of street design citywide. A new methodology to quantify streetspace allocation is introduced using a geocomputational approach that allows both the processing of high-resolution topographic data over a large geographic extent and enables replicability for other cities. The correlation between streetspace allocation metrics and street network centrality at distinct scales is investigated across different geographic areas. These variables are then examined using cluster analysis to identify a typology of streets based on streetspace allocation and centrality. The results provide the framework for a design scenario study of inner London applying shortest-path analysis under an active travel prioritisation perspective. Streetspace statistics for London confirm the predominance of space allocated for vehicular transport over pedestrian uses. Most streets display standard "residential" street metrics, coinciding with traditional street classification schemes. Also, this serves to demonstrate quantitatively the spatially efficient organisation of the London street system with few wider distributors and many narrower local streets. In addition, through the combined examination of the streets' allocation and configurational metrics, it is possible to identify a new sub-type of local streets. The spatial arrangement of the streets segments types follows a centre-periphery pattern: wider and higher centrality streets are clustered at the city centre and show relative larger streetspace designated to pedestrians, corresponding with higher levels of estimated activity. On a prescriptive streetspace model of Inner London, the streetspace allocation of critical pathways is modified to illustrate how strategic scale street properties affect and are affected by design scale street parameters. The fine-grain physical metrics analysed here, not only can be useful to tackle a wide range of contemporary street related questions from urban environmental quality to the adoption of new technologies but also offer alternative analytical methods for street research, planning and design

Graph-Based Analysis and Visualisation of Mobility Data

Urban mobility forecast and analysis can be addressed through grid-based and graph-based models. However, graph-based representations have the advantage of more realistically depicting the mobility networks and being more robust since they allow the implementation of Graph Theory machinery, enhancing the analysis and visualisation of mobility flows. We define two types of mobility graphs: Region Adjacency graphs and Origin-Destination graphs. Several node centrality metrics of graphs are applied to identify the most relevant nodes of the network in terms of graph connectivity. Additionally, the Perron vector associated with a strongly connected graph is applied to define a circulation function on the mobility graph. Such node values are visualised in the geographically embedded graphs, showing clustering patterns within the network. Since mobility graphs can be directed or undirected, we define several Graph Laplacian for both cases and show that these matrices and their spectral properties provide insightful information for network analysis. The computation of node centrality metrics and Perron-induced circulation functions for three different geographical regions demonstrate that basic elements from Graph Theory applied to mobility networks can lead to structure analysis for graphs of different connectivity, size, and orientation properties.Comment: 19 pages, 7 figure