In this paper, we introduce and test our algorithm to create a road network representation for city-scale active transportation simulation models. The algorithm relies on open and universal data to ensure applicability for different cities around the world. In addition to the major roads, their geometries and the road attributes typically used in transport modelling (e.g., speed limit, number of lanes, permitted travel modes), the algorithm also captures minor roads usually favoured by pedestrians and cyclists, along with road attributes such as bicycle-specific infrastructure, traffic signals, and road gradient. Furthermore, it simplifies the network's complex geometries and merges parallel roads if applicable to make it suitable for large-scale simulations. To examine the utility and performance of the algorithm, we used it to create a network representation for Greater Melbourne, Australia and compared the output with a network created using an existing transport simulation toolkit along with another network from an existing city-scale transport model from the Victorian government. Through simulation experiments with these networks, we illustrated that our algorithm achieves a very good balance between simulation accuracy and run-time. For routed trips on our network for walking and cycling it is of comparable accuracy to the common network conversion tools in terms of travel distances of the shortest paths while being more than two times faster when used for simulating different sample sizes. Therefore, our algorithm offers a flexible solution for building accurate and efficient road networks for city-scale active transport models for different cities around the world.
We explore the relation between urban road network characteristics particularly circuitry, street orientation entropy and the city's topography on the one hand and the building's orientation entropy on the other in order to quantify their effect on the city's solar potential. These statistical measures of the road network reveal the interplay between the built environment's design and its sustainability.
Population mobility can be studied readily and cheaply using cellphone data, since people's mobility can be approximately mapped into tower-mobile registries. We model people moving in a grid-like city, where edges of the grid are weighted and paths are chosen according to overall weights between origin and destination. Cellphone users leave sparse signals in random nodes of the grid as they move by, mimicking the type of data collected from the tower-cellphone interactions. From this noisy data we seek to build a model of the city, {\it i.e.} to predict probabilities of paths from origin to d…
Quantifying the topological similarities of different parts of urban road networks (URNs) enables us to understand the urban growth patterns. While conventional statistics provide useful information about characteristics of either a single node's direct neighbors or the entire network, such metrics fail to measure the similarities of subnetworks considering local indirect neighborhood relationships. In this study, we propose a graph-based machine-learning method to quantify the spatial homogeneity of subnetworks. We apply the method to 11,790 urban road networks across 30 cities worldwide to m…
The study of the properties and structure of a city's road network has for many years been the focus of much work, as has the mathematical modelling of the location of its retail activity and of the emergence of clustering in retail centres. Despite these two phenomena strongly depending on one another and their fundamental importance in understanding cities, little work has been done in order to compare their evolution and their local and global properties. The contribution of this paper aims to highlight the strong relationship that retail dynamics have with the hierarchical structure of the…
We study the influence that population density and the road network have on each others' growth and evolution. We use a simple model of formation and evolution of city roads which reproduces the most important empirical features of street networks in cities. Within this framework, we explicitely introduce the topology of the road network and analyze how it evolves and interact with the evolution of population density. We show that accessibility issues -pushing individuals to get closer to high centrality nodes- lead to high density regions and the appearance of densely populated centers. In pa…
Designing and maintaining resilient transportation systems rely on identifying potential vulnerabilities and inefficiencies before crises occur. However, given the complexity of transportation networks, as well as the diversity of ways in which systems can fail, the problem of assessing the impacts of exceptional phenomena still lacks tools and metrics for analysis. Therefore, this paper aims to present a method for assessing the behavior of road networks during crises in which segments are disabled or unusable for a time. The method proposed was structured around two metrics calculated from t…
We analyse two large-scale intra-city urban networks and traffic flows therein measured by GPS traces of taxis in San Francisco and Shanghai. Our results coincide with previous findings that, based purely on topological means, it is often insufficient to characterise traffic flow. Traditional shortest-path betweenness analysis, where shortest paths are calculated from each pairs of nodes, carries an unrealistic implicit assumption that each node or junction in the urban network generates and attracts an equal amount of traffic. We also argue that weighting edges based only on euclidean distanc…
Percolation transition is widely observed in networks ranging from biology to engineering. While much attention has been paid to network topologies, studies rarely focus on critical percolation phenomena driven by network dynamics. Using extensive real data, we study the critical percolation properties in city traffic dynamics. Our results suggest that two modes of different critical percolation behaviors are switching in the same network topology under different traffic dynamics. One mode of city traffic (during nonrush hours or days off) has similar critical percolation characteristics as sm…
Rapid urbanization places increasing stress on already burdened transportation systems, resulting in delays and poor levels of service. Billions of spatiotemporal call detail records (CDRs) collected from mobile devices create new opportunities to quantify and solve these problems. However, there is a need for tools to map new data onto existing transportation infrastructure. In this work, we propose a system that leverages this data to identify patterns in road usage. First, we develop an algorithm to mine billions of calls and learn location transition probabilities of callers. These transit…
In the wake of the pandemic, the inadequacy of urban sidewalks to comply with social distancing remains untackled in academy. Beyond isolated efforts (from sidewalk widenings to car-free Open Streets), there is a need for a large-scale and quantitative strategy for cities to handle the challenges that COVID-19 poses in the use of public space. The main obstacle is a generalized lack of publicly available data on sidewalk infrastructure worldwide, and thus city governments have not yet benefited from a complex systems approach of treating urban sidewalks as networks. Here, we leverage sidewalk …
Northeastern University London（伦敦东北大学）；Corvinus University of Budapest（布达佩斯科维努斯大学）；Centre for Economic and Regional Studies（经济区域研究中心）；Óbuda University（欧比乌大学）
Evaluation of the demand for emerging transportation technologies and policies can vary by time of day due to spillbacks on roadways, rescheduling of travelers' activity patterns, and shifting to other modes that affect the level of congestion. These effects are not well-captured with static travel demand models. We calibrate and validate the first open-source multi-agent simulation model for New York City, called MATSim-NYC, to support agencies in evaluating policies such as congestion pricing. The simulation-based virtual test bed is loaded with an 8M+ synthetic 2016 population calibrated in…
Spatial road networks have been widely employed to model the structure and connectivity of cities. In such representation, the question of spatial scale of the entities in the network, i.e. what its nodes and edges actually embody in reality, is of particular importance so that redundant information can be identified and eliminated to provide an improved understanding of city structure. To address this, we investigate in this work the relationship between the spatial scale of the modelled network entities against the amount of useful information contained within it. We employ an entropy measur…
Just as natural river networks are known to be globally self-similar, recent research has shown that human-built urban networks, such as road networks, are also functionally self-similar, and have fractal topology with power-law node-degree distributions (p(k) = a k). Here we show, for the first time, that other urban infrastructure networks (sanitary and storm-water sewers), which sustain flows of critical services for urban citizens, also show scale-free functional topologies. For roads and drainage networks, we compared functional topological metrics, derived from high-resolution data (70,0…
Khulna University of Engineering & Technology（库尔纳工程技术大学）
Mobility is a key factor in urban life and transport network plays a vital role in mobility. Worse transport network having less mobility is one of the key reasons to decline the living standard in any unplanned mega city. Transport mobility enhancement in an unplanned mega city is always challenging due to various constraints including complex design and high cost involvement. The aim of this thesis is to enhance transport mobility in a megacity introducing a bicycle lane. To design the bicycle lane natural Physarum, brainless single celled multi-nucleated protist, is studied and modified for…
During the last decade, road network vulnerability assessment has received an increasing attention. On one hand, it is due to the significant advances in Network Science and the potentialities that its tools offer. On the other hand, it is due to its utility for urban planning and emergency response. Despite these facts and the increasingly available data, related work is still sparse in Latin America, even more so in Ecuador. Due to its geographical, historical, and social characteristics, the city of Quito is considered as a case study. At first, the spatial distributions of several topologi…
The quantitative study of traffic dynamics is crucial to ensure the efficiency of urban transportation networks. The current work investigates the spatial properties of congestion, that is, we aim to characterize the city areas where traffic bottlenecks occur. The analysis of a large amount of real road networks in previous works showed that congestion points experience spatial abrupt transitions, namely they shift away from the city center as larger urban areas are incorporated. The fundamental ingredient behind this effect is the entanglement of central and arterial roads, embedded in separa…
We use a set of four theoretical navigability indices for street maps to investigate the shape of the resulting street networks, if they are grown by optimizing these indices. The indices compare the performance of simulated navigators (having a partial information about the surroundings, like humans in many real situations) to the performance of optimally navigating individuals. We show that our simple greedy shortcut construction strategy generates the emerging structures that are different from real road network, but not inconceivable. The resulting city plans, for all navigation indices, s…
The development of smart city transport systems, including self-driving cars, leads to an increase in the threat of hostile interference in the processes of vehicle control. This interference may disrupt the normal functioning of the transport system, and, if is performed covertly, the system can be negatively affected for a long period of time. This paper develops a simulation stochastic cellular automata model of traffic on a circular two-lane road based on the Sakai-Nishinari-Fukui-Schadschneider (S-NFS) rules. In the presented model, in addition to ordinary vehicles, there are covertly cou…
Interventions of central, top-down planning are serious limitations to the possibility of modelling the dynamics of cities. An example is the city of Paris (France), which during the 19th century experienced large modifications supervised by a central authority, the `Haussmann period'. In this article, we report an empirical analysis of more than 200 years (1789-2010) of the evolution of the street network of Paris. We show that the usual network measures display a smooth behavior and that the most important quantitative signatures of central planning is the spatial reorganization of centralit…
Describing the basic properties of road network systems, such as their robustness, vulnerability, and reliability, has been a very important research topic in the field of urban transportation. Current research mainly uses several statistical indicators of complex networks to analyze the road network systems. However, these methods are essentially node-based. These node-based methods are more concerned with the number of connections between nodes, and lack of consideration for interactions. So, this leads to the well-known node paradox problem, and their ability of characterizing the local and…
We present a model of traffic flow on generic urban road networks based on cellular automata. We apply this model to an existing road network in the Australian city of Melbourne, using empirical data as input. For comparison, we also apply this model to a square-grid network using hypothetical input data. On both networks we compare the effects of non-adaptive vs adaptive traffic lights, in which instantaneous traffic state information feeds back into the traffic signal schedule. We observe that not only do adaptive traffic lights result in better averages of network observables, they also lea…
