Transportation Networks. Optimality. Cost Functions. Deterministic User Equilibrium Assignment. Stochastic User Equilibrium Assignment. Trip Table Estimation. Network Reliability. Network Design. Conclusions. References. Index.

Transportation network analysis

The transport system is critical to the welfare of modern societies. This article provides an overview of recent research on vulnerability and resilience of transport systems. Definitions of vulnerability and resilience are formulated and discussed together with related concepts. In the increasing and extensive literature of transport vulnerability studies, two distinct traditions are identified. One tradition with roots in graph theory studies the vulnerability of transport networks based on their topological properties. The other tradition also represents the demand and supply side of the transport systems to allow for a more complete assessment of the consequences of disruptions or disasters for the users and society. The merits and drawbacks of the approaches are discussed. The concept of resilience offers a broader socio-technical perspective on the transport system’s capacity to maintain or quickly recover its function after a disruption or a disaster. The transport resilience literature is less abundant, especially concerning the post-disaster phases of response and recovery. The research on transport system vulnerability and resilience is now a mature field with a developed methodology and a large amount of research findings with large potential practical usefulness. The authors argue that more cross-disciplinary collaborations between authorities, operators and researchers would be desirable to transform this knowledge into practical strategies to strengthen the resilience of the transport system.

Vulnerability and resilience of transport systems : A discussion of recent research

The efficiency of a transport system depends on several elements, such as available technology, governmental policies, the planning process, and control strategies. Indeed, the interaction between these elements is quite complex, leading to intractable decision making problems. The planning process and real-time control strategies have been widely studied in recent years, and there are several practical implementations with promising results. In this paper, we review the literature on Transit Network Planning problems and real-time control strategies suitable to bus transport systems. Our goal is to present a comprehensive review, emphasizing recent studies as well as works not addressed in previous reviews.

Planning, operation, and control of bus transport systems: A literature review

The paper presents a statistical model for urban road network travel time estimation using vehicle trajectories obtained from low frequency GPS probes as observations, where the vehicles typically cover multiple network links between reports. The network model separates trip travel times into link travel times and intersection delays and allows correlation between travel times on different network links based on a spatial moving average (SMA) structure. The observation model presents a way to estimate the parameters of the network model, including the correlation structure, through low frequency sampling of vehicle traces. Link-specific effects are combined with link attributes (speed limit, functional class, etc.) and trip conditions (day of week, season, weather, etc.) as explanatory variables. The approach captures the underlying factors behind spatial and temporal variations in speeds, which is useful for traffic management, planning and forecasting. The model is estimated using maximum likelihood. The model is applied in a case study for the network of Stockholm, Sweden. Link attributes and trip conditions (including recent snowfall) have significant effects on travel times and there is significant positive correlation between segments. The case study highlights the potential of using sparse probe vehicle data for monitoring the performance of the urban transport system.

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Travel time estimation for urban road networks using low frequency probe vehicle data

This paper provides a comprehensive overview of the literature on transportation infrastructure system performance in disasters Specifically, it reviews those articles appearing in refereed journals, conference proceedings, and technical reports since the late 1990s that provide insights and tools for the assessment of anticipated transportation system performance, along with its management, given the possibility of physical damage resulting from a future hazard event In the considered literature, performance may be gauged under characteristics of risk, vulnerability, reliability, robustness, flexibility, survivability, and resilience, the most common concepts or measures in the literature In addition to providing an archive and synthesis of recent literature on this topic, the approximately 200 articles are classified based on a host of criteria, including applied measure (qualitative or quantitative), conceptual approach, and methodology

Measuring the performance of transportation infrastructure systems in disasters: a comprehensive review

https://repository.kulib.kyoto-u.ac.jp/dspace/bitstream/2433/123445/1/15472450802644439.pdf

Using Bus Probe Data for Analysis of Travel Time Variability

This paper proposes the use of absorbing Markov chains to solve the capacity constrained transit network loading problem taking common lines into account. The approach handles congested transit networks, where some passengers will not be able to board because of the absence of sufficient space. The model also handles the common lines problem, where choice of route depends on frequency of arrivals. The mathematical formulation of the problem is presented together with a numerical example.

Capacity Constrained Transit Assignment with Common Lines

This paper proposes a frequency-based assignment model that considers travellers probability of finding a seat in their perception of route cost and hence also their route choice. The model introduces a “fail-to-sit” probability at boarding points with travel costs based on the likelihood of travelling seated or standing. Priority rules are considered; in particular it is assumed that standing on-board passengers will occupy any available seats of alighting passengers before newly boarding passengers can fill any remaining seats. At the boarding point passengers are assumed to mingle, meaning that FIFO is not observed, as is the case for many crowded bus and metro stops, particularly in European countries. The route choice considers the common lines problem and an user equilibrium solution is sought through a Markov type network loading process and the method of successive averages. The model is first illustrated with a small example network before being applied to the inner zone of London’s underground network. The effect of different values passengers might attach to finding a seat are illustrated. Applications of the model for transit planning as well as for information provision at the journey planner stage are discussed.

Frequency-based transit assignment considering seat capacities

This paper presents a first approach to dynamic frequency-based transit assignment. As such the model aims to close the gap between schedule-based and frequency-based models. Frequency-based approaches have some advantages compared to schedule-based models, however, when modelling highly congested networks a static frequency-based approach is not sufficient as it does not reveal the peaked nature of the capacity problem. The central idea for dealing with the line capacity constraints is the introduction of a "fail-to-board" probability as in some circumstances passengers are not able to board the first service arriving due to overcrowding. The common line problem is taken into account and the search for the shortest hyperpath is influenced by the fail-to-board probability. An assumption that passengers mingle on the platform allows a Markov network loading process which respects the priority of on-board passengers with respect to those wishing to board. The study period is divided into several time intervals and those passengers who failed to board are added to the demand in the subsequent time interval and so might reconsider their route choice. Trips that are longer than one interval are also carried over to subsequent time intervals. The approach is first illustrated with a small example network and then with a case study relating to London, where transit capacity problems are experienced daily during the peak period.

A quasi-dynamic capacity constrained frequency-based transit assignment model

The focuses of this paper are optimal traffic regulation after a major disaster and evaluation of capacity reliability of a network. The paper firstly discusses the context of traffic regulation and its importance after a major disaster. Then, this problem is formulated as an optimisation program in which the traffic regulator attempts to regulate the amount of traffic movements or access to some areas so as to maximise the traffic volumes in the network while (a) link flows must be less than link capacities and (b) re-routing effect due to changes of traffic condition in the network is allowed. The re-routing behaviour is assumed to follow Probit Stochastic User's Equilibrium (SUE). The paper explains an optimisation algorithm based on an implicit programming approach for solving this problem with the SUE condition. With this optimisation problem, the randomness of the link capacities (to represent random effects of the disaster) is introduced and the paper describes an approach to approximate the capacity reliability of the network using Monte-Carlo simulation. The paper then adopts this approach to evaluate the performances of different traffic regulation policies with a small network and a test network of Kobe city in Japan.

Fumitaka Kurauchi

Papers

Using Bus Probe Data for Analysis of Travel Time Variability

Capacity Constrained Transit Assignment with Common Lines

Frequency-based transit assignment considering seat capacities

A quasi-dynamic capacity constrained frequency-based transit assignment model

Network Capacity Reliability Analysis Considering Traffic Regulation after a Major Disaster