Large-scale road network vulnerability analysis: a sensitivity analysis based approach

Traditionally, an assessment of transport network vulnerability is a computationally intensive operation. This article proposes a sensitivity analysis-based approach to improve computational efficiency and allow for large-scale applications of road network vulnerability analysis. Various vulnerability measures can be used with the proposed method. For illustrative purposes, this article adopts the relative accessibility index (AI), which follows the Hansen integral index, as the network vulnerability measure for evaluating the socio-economic effects of link (or road segment) capacity degradation or closure. Critical links are ranked according to the differences in the AIs between normal and degraded networks. The proposed method only requires a single computation of the network equilibrium problem. The proposed technique significantly reduces computational burden and memory storage requirements compared with the traditional approach. The road networks of the Sioux Falls city and the Bangkok metropolitan area are used to demonstrate the applicability and efficiency of the proposed method. Network manager(s) or transport planner(s) can use this approach as a decision support tool for identifying critical links in road networks. By improving these critical links or constructing new bypass roads (or parallel paths) to increase capacity redundancy, the overall vulnerability of the networks can be reduced.     

The missing link: bicycle infrastructure networks and ridership in 74 US cities

Cities promote strong bicycle networks to support and encourage bicycle commuting. However, the application of network science to bicycle facilities is not very well studied. Previous work has found relationships between the amount of bicycle infrastructure in a city and aggregate bicycle ridership, and between microscopic network structure and individual tripmaking patterns. This study fills the missing link between these two bodies of literature by developing a standard methodology for measuring bicycle facility network quality at the macroscopic level and testing its association with bicycle commuting. Bicycle infrastructure maps were collected for 74 Unites States cities and systematically analyzed to evaluate their network structure. Linear regression models revealed that connectivity and directness are important factors in predicting bicycle commuting after controlling for demographic variables and the size of the city. These findings provide a framework for transportation planners and policymakers to evaluate their local bicycle facility networks and set regional priorities that support nonmotorized travel behavior, and for continued research on the structure and quality of bicycle infrastructure and behavior.     

An assignment model with modified Logit,which obviates enumeration and overlapping problems

One of the main components of stochastic assignment models is the route choice model solved with implicit or explicit path enumeration algorithms. Such models are used both for congested networks within equilibrium or dynamic models and for non-congested networks within static or pseudo-dynamic network loading models. This paper proposes a C-Logit model specification within a Dial algorithm structure for the implicit assignment of network flows. The model and its solution algorithm, called D-C-Logit, combine several positive features found in the literature for choice set generation and choices from a given choice set: generation of a set of alternatives with a selective approach; calculation of the path choice probability in a closed form; simulation of the overlapping effect among alternative paths; computation of just one tree for each origin avoiding explicit path enumeration.This paper has two main objectives: the proposition of a Dial-like algorithm to solve a C-Logit assignment model and application of the algorithm to different networks in order to demonstrate certain properties.     

The implications of differential network flexibility for spatial structures

Transportation and telecommunications networks have profound effects on location decisions of households, firms and of public facilities. Increasingly, such decisions depend on more than one network. Yet, most analyses focus on the land use implications of single networks. This paper suggests that in a multi-network setting' network flexibility is a significant factor in determining the relative importance of a network for the organization of space. To this end, the paper defines node and link flexibility and demonstrates the implications that differences in network flexibility have on location decisions. Counter to some expectations, the spatial effects of the most flexible network, namely telecommunications, may not be substantive, as location decisions seem to be most constrained by the least flexible networks. In response to growing congestion on existing networks, high capacity upper tier networks are increasingly developed. Such networks are generally inflexible. As a result the emerging map is more differentiated than the current one, changing the trend of that prevailed during the last fifty years toward greater equalization of space.     

Network-based real option models

Building on earlier work to incorporate real option methodologies into network modeling, two models are proposed. The first is the network option design problem, which maximizes the expanded net present value of a network investment as a function of network design variables with the option to defer the committed design investment. The problem is shown to be a generalized version of the network design problem and the multi-period network design problem. A heuristic based on radial basis functions is used to solve the problem for continuous link expansion with congestion effects. The second model is a link investment deferral option set, which decomposes the network investment deferral option into individual, interacting link or project investments. This model is a project selection problem under uncertainty, where each link or project can be deferred such that the expanded net present value is maximized. The option is defined in such a way that a lower bound can be solved using an exact method based on multi-option least squares Monte Carlo simulation. Numerical tests are conducted with the classical Sioux Falls network and compared to earlier published results.     

The concept of delay

The word delay is so widely used that it may be assumed to be a simple concept which is well understood. It is taken to be a name for wasted time on a journey, but attempts to quantify it in order to use it as a measure of performance of a transportation facility have not given complete satisfaction. Drivers are observed to behave in ways which reveal attitudes to wasted time which differ from those of the researcher. These problems have been reported in many studies but do not seem to have been pursued.This paper discusses the concept of delay. A basic definition leads to problems of measurement which suggest alternative definitions which have more apparent relevance to traffic networks in which more than one cause of delay is of interest. Further speculation about these definitions points to the fact that delay can be either of two separate concepts.In conclusion it is argued that delay should no longer be regarded as an objective quantity capable of direct measurement. Instead of delay being thought the cause of driver annoyance, it should be taken that it is the existence of driver frustration which converts time lost into delay. It is better to define delay as unwanted journey time.     

Observability in traffic networks. Plate scanning added by counting information

The paper deals with the observability problem in traffic networks, including route, origin?Cdestination and link flows, based on number plate scanning and link flow observations. A revision of the main observability concepts and methods is done using a small network. Starting with the full observability of the network based only on number plate scanning on some links, the number of scanned links is reduced and replaced by counted link flows, but keeping the full observability of all flows in the network. In this way, the cost can be substantially reduced. To this end, several methods are given and discussed, and two small and one real case of networks are used to illustrate the proposed methodologies. Finally, some conclusions and final recommendations are included.     

The multi-objective railway timetable rescheduling problem

Unexpected disruptions occur for many reasons in railway networks and cause delays, cancelations, and, eventually, passenger inconvenience. This research focuses on the railway timetable rescheduling problem from a macroscopic point of view in case of large disruptions. The originality of our approach is to integrate three objectives to generate a disposition timetable: the passenger satisfaction, the operational costs and the deviation from the undisrupted timetable. We formulate the problem as an Integer Linear Program that optimizes the first objective and includes $\epsilon$-constraints for the two other ones. By solving the problem for different values of $\epsilon$, the three-dimensional Pareto frontier can be explored to understand the trade-offs among the three objectives. The model includes measures such as canceling, delaying or rerouting the trains of the undisrupted timetable, as well as scheduling emergency trains. Furthermore, passenger flows are adapted dynamically to the new timetable. Computational experiments are performed on a realistic case study based on a heavily used part of the Dutch railway network. The model is able to find optimal solutions in reasonable computational times. The results provide evidence that adopting a demand-oriented approach for the management of disruptions not only is possible, but may lead to significant improvement in passenger satisfaction, associated with a low operational cost of the disposition timetable.     

Braess' paradox in a generalised traffic network

Braess' paradox illustrates situations when adding a new link to a transport network might lead to an equilibrium state in which travel times of users will increase. The classical network configuration introduced by Braess in 1968 to demonstrate the paradox is of fundamental significance because Valiant and Roughgarden showed in 2006 that ‘the “global” behaviour of an equilibrium flow in a large random network is similar to that in Braess' original four‐node example’. Braess' paradox has been studied mainly in the context of the classical problem introduced by Braess and his colleagues, assuming a certain type of symmetry in networks. Specifically, two pairs of links in those networks are assumed to have the same volume‐delay functions. The occurrence of Braess' paradox for this specific case of network symmetry was investigated by Pas and Principio in 1997. Such a symmetry is not common in real‐life networks because the parameters of volume‐delay functions are associated with roads physical and functional characteristics, which typically differ from one link to another. This research provides an extension of previous studies on Braess' paradox by considering arbitrary volume‐delay functions, that is, symmetry properties are not assumed for any of the network's links and the occurrence of Braess' paradox is studied for a general configuration. Copyright © 2014 John Wiley & Sons, Ltd.     

Forecasting transport development: Testing the utility of a simple regression approach

The analysis tests the utility of a simple regression approach in postdictively explaining transport development in West Malaysia from 1887 to 1968. The growth of the network is modelled as a process of contagious diffusion where transport densities of adjacent cells are used as predictor variables on a lagged basis. The partial regression coefficients provide measures of network orientation over time. The results demonstrate the importance of the contagion process in transport forecasting and provide equivalent levels of explanation when compared with a model which utilizes modernization indexes as predictor weights.I am grateful to Peter Gould for his advice and suggestions in the early stages of the research and for the comments of Peter Haggett, Mark Monmonier and J. Barry Riddell, all of whom read drafts of the paper. I also wish to acknowledge the financial support provided by a University of Vermont Faculty Fellowship.     

Quasi-dynamic traffic assignment with residual point queues incorporating a first order node model

Static traffic assignment models are still widely applied for strategic transport planning purposes in spite of the fact that such models produce implausible traffic flows that exceed link capacities and predict incorrect congestion locations. There have been numerous attempts to constrain link flows to capacity. Capacity constrained models with residual queues are often referred to as quasi-dynamic traffic assignment models. After reviewing the literature, we come to the conclusion that an important piece of the puzzle has been missing so far, namely the inclusion of a first order node model. In this paper we propose a novel path-based static traffic assignment model for finding a stochastic user equilibrium in general transportation networks. This model includes a first order (steady-state) node model that yields more realistic turn capacities, which are then used to determine consistent capacity constrained traffic flows, residual point (vertical) queues (upstream bottleneck links), and path travel times consistent with queuing theory. The route choice part of the model is specified as a variational inequality problem, while the network loading part is formulated as a fixed point problem. Both problems are solved using existing techniques to find a solution. We illustrate the model using hypothetical examples, and also demonstrate feasibility on large-scale networks.     

Importance and exposure in road network vulnerability analysis

The reliability and vulnerability of critical infrastructures have attracted a lot of attention recently. In order to assess these issues quantitatively, operational measures are needed. Such measures can also be used as guidance to road administrations in their prioritisation of maintenance and repair of roads, as well as for avoiding causing unnecessary disturbances in the planning of roadwork. The concepts of link importance and site exposure are introduced. In this paper, several link importance indices and site exposure indices are derived, based on the increase in generalised travel cost when links are closed. These measures are divided into two groups: one reflecting an “equal opportunities perspective”, and the other a “social efficiency perspective”. The measures are calculated for the road network of northern Sweden. Results are collected in a GIS for visualisation, and are presented per link and municipality. In view of the recent great interest in complex networks, some topological measures of the road network are also presented.     

Vulnerability analysis for large-scale and congested road networks with demand uncertainty

To assess the vulnerability of congested road networks, the commonly used full network scan approach is to evaluate all possible scenarios of link closure using a form of traffic assignment. This approach can be computationally burdensome and may not be viable for identifying the most critical links in large-scale networks. In this study, an “impact area” vulnerability analysis approach is proposed to evaluate the consequences of a link closure within its impact area instead of the whole network. The proposed approach can significantly reduce the search space for determining the most critical links in large-scale networks. In addition, a new vulnerability index is introduced to examine properly the consequences of a link closure. The effects of demand uncertainty and heterogeneous travellers’ risk-taking behaviour are explicitly considered. Numerical results for two different road networks show that in practice the proposed approach is more efficient than traditional full scan approach for identifying the same set of critical links. Numerical results also demonstrate that both stochastic demand and travellers’ risk-taking behaviour have significant impacts on network vulnerability analysis, especially under high network congestion and large demand variations. Ignoring their impacts can underestimate the consequences of link closures and misidentify the most critical links.     

An integrated measure of accessibility and reliability of mass transit systems

The growth of a city or a metropolis requires well-functioning transit systems to accommodate the ensuing increase in travel demand. As a result, mass transit networks have to develop and expand from simple to complex topological systems over time to meet this demand. Such an evolution in the networks’ structure entails not only a change in network accessibility, but also a change in the level of network reliability on the part of stations and the entire system as well. Network accessibility and reliability are popular measures that have been widely applied to evaluate the resilience and vulnerability of a spatially networked system. However, the use of a single measure, either accessibility or reliability, provides different results, which demand an integrated measure to evaluate the network’s performance comprehensively. In this paper, we propose a set of integrated measures, named ACCREL (Integrated Accessibility and Reliability indicators) that considers both metrics in combination to evaluate a network’s performance and vulnerability. We apply the new measures for hypothetical mass transit system topologies, and a case study of the metro transit system in Seoul follows, highlighting the dynamics of network performance with four evolutionary stages. The main contribution of this study lies in the results from the experiments, which can be used to inform how transport network planning can be prepared to enhance the network functionality, thereby achieving a well-balanced, accessible, and reliable system. Insights on network vulnerability are also drawn for public transportation planners and spatial decision makers.     

Evaluating road network damage caused by natural disasters in the Czech Republic between 1997 and 2010

Road networks play a vital role in maintaining a functioning modern society. Many events perceptibly affect the transport supply along these networks, especially natural disasters such as floods, landslides, and earthquakes. Contrary to more common disruptions of traffic from accidents, or maintenance closures, natural disasters are capable of destroying large numbers of roads and usually cover vast areas. When evaluating network damage no single measure alone is able to describe the full extent of network destruction. In this study, we investigated six highly damaging natural disasters, which occurred in the Czech Republic between 1997 and 2010. They were all induced by extreme rainfall or by rapid snowmelt and resulted in floods and landslides. Their impacts are evaluated with respect to the damage to road networks and decreased serviceability. For mutual comparison of the impacts and their analysis we used several criteria, described in the paper, related to economic impacts, physical harm to individuals and infrastructures, and the effects on connectivity and serviceability. We also introduced a new measure based on the network efficiency index which takes into account the importance of nodes based on their population. Moreover, we provide a detailed analysis of one such event in July 1997 that significantly affected the road network of the Zlín region.     

Effect of speed limits in degradable transport networks

This paper studies how link-specific speed limits influence the performance of degradable transport networks, in which the capacity of each link is a degradable random variable. The distribution and cumulative distribution of link travel time have been presented with the effect of speed limits taken into account. The mean and variance of link and route travel time are formulated. Three link states have been classified, and their physical meanings have been discussed. The relationship between critical capacity, travel time and speed limit has been elaborated. We have proposed a Speed Limit- and Reliability-based User Equilibrium (SLRUE), adopting travel time budget as the principle of travelers’ route choice. A heuristic method employing the method of successive averages is developed to solve the SLRUE in degradable networks. Through numerical studies, we find that for some networks both the mean and standard deviation of the total travel time could be reduced simultaneously by imposing some speed limits. The speed limit design problem has been studied, and it is found that imposing speed limits cannot always reduce the total travel time budget of a network.     

Optimization models to characterize the broadcast capacity of vehicular ad hoc networks

Broadcast capacity of the entire network is one of the fundamental properties of vehicular ad hoc networks (VANETs). It measures how efficiently the information can be transmitted in the network and usually it is limited by the interference between the concurrent transmissions in the physical layer of the network. This study defines the broadcast capacity of vehicular ad hoc network as the maximum successful concurrent transmissions. In other words, we measure the maximum number of packets which can be transmitted in a VANET simultaneously, which characterizes how fast a new message such as a traffic incident can be transmitted in a VANET. Integer programming (IP) models are first developed to explore the maximum number of successful receiving nodes as well as the maximum number of transmitting nodes in a VANET. The models embed an traffic flow model in the optimization problem. Since IP model cannot be efficiently solved as the network size increases, this study develops a statistical model to predict the network capacity based on the significant parameters in the transportation and communication networks. MITSIMLab is used to generate the necessary traffic flow data. Response surface method and linear regression technologies are applied to build the statistical models. Thus, this paper brings together an array of tools to solve the broadcast capacity problem in VANETs. The proposed methodology provides an efficient approach to estimate the performance of a VANET in real-time, which will impact the efficacy of travel decision making.     

Characterizing metro networks: state,form, and structure

The broad goal of this paper is to characterize the network feature of metro systems. By looking at 33 metro systems in the world, we adapt various concepts of graph theory to describe characteristics of State, Form and Structure; these three characteristics are defined using new or existing network indicators. State measures the complexity of a network; we identify three phases in the development of transit networks, with mature systems being 66% completely connected. Form investigates the link between metro systems and the built environment, distinguishing networks oriented towards regional accessibility, local coverage or regional coverage. Structure examines the intrinsic properties of current networks; indicators of connectivity and directness are formulated. The method presented is this paper should be taken as a supplement to traditional planning factors such as demand, demography, geography, costs, etc. It is particularly useful at the strategic planning phase as it offers information on current and planned systems, which can then be used towards setting a vision, defining new targets and making decision between various scenarios; it can also be used to compare existing systems. We also link the three characteristics to transit line type and land-use; overall the presence of tangential and/or (semi)-circumferential lines may be key. In addition, we have been able to identify paths of development, which should be strongly considered in future projects.     

A method to assess demand growth vulnerability of travel times on road network links

Many national governments around the world have turned their recent focus to monitoring the actual reliability of their road networks. In parallel there have been major research efforts aimed at developing modelling approaches for predicting the potential vulnerability of such networks, and in forecasting the future impact of any mitigating actions. In practice—whether monitoring the past or planning for the future—a confounding factor may arise, namely the potential for systematic growth in demand over a period of years. As this growth occurs the networks will operate in a regime closer to capacity, in which they are more sensitive to any variation in flow or capacity. Such growth will be partially an explanation for trends observed in historic data, and it will have an impact in forecasting too, where we can interpret this as implying that the networks are vulnerable to demand growth. This fact is not reflected in current vulnerability methods which focus almost exclusively on vulnerability to loss in capacity. In the paper, a simple, moment-based method is developed to separate out this effect of demand growth on the distribution of travel times on a network link, the aim being to develop a simple, tractable, analytic method for medium-term planning applications. Thus the impact of demand growth on the mean, variance and skewness in travel times may be isolated. For given critical changes in these summary measures, we are thus able to identify what (location-specific) level of demand growth would cause these critical values to be exceeded, and this level is referred to as Demand Growth Reliability Vulnerability (DGRV). Computing the DGRV index for each link of a network also allows the planner to identify the most vulnerable locations, in terms of their ability to accommodate growth in demand. Numerical examples are used to illustrate the principles and computation of the DGRV measure.