'Resilience thinking' in transport planning

Resilience has been discussed in ecology for over forty years. While some aspects of resilience have received attention in transport planning, there is no unified definition of resilience in transportation. To define resilience in transportation, I trace back to the origin of resilience in ecology with a view of revealing the essence of resilience thinking and its relevance to transport planning. Based on the fundamental concepts of engineering resilience and ecological resilience, I define "comprehensive resilience in transportation" as the quality that leads to recovery, reliability and sustainability. Observing that previous work in resilience analysis in transportation has focussed on addressing engineering resilience rather than ecological resilience, I conclude that transformability has been generally overlooked and needs to be incorporated in the analysis framework for comprehensive resilience in transportation

Modelling, solution and evaluation techniques for Train Timetable Rescheduling via optimisation

It is common on railways for a single train delay to cause other trains to become delayed, multiplying the negative consequences of the original problem. However, making appropriate changes to the timetable in response to the initial delay can help to reduce the amount of further delay caused. In this thesis, we tackle the Train Timetable Rescheduling Problem (TTRP), the task of finding the best combination of timetable changes to make in any given traffic scenario. The TTRP can be formulated as an optimisation problem and solved computationally to aid the process of railway traffic control. Although this approach has received considerable research attention, the practical deployment of optimisation methods for the TTRP has hitherto been limited. In this thesis, we identify and address three outstanding research challenges that remain barriers to deployment. First, we find that existing TTRP models for large station areas are either not sufficiently realistic or cannot be solved quickly enough to be used in a real-time environment. In response, a new TTRP model is introduced that models the signalling system in station areas in fine detail. Using a new set of real instances from Doncaster station, we show that our tailored solution algorithm can obtain provably optimal or near-optimal solutions in sufficiently short times. Second, we argue that existing ways of modelling train speed in TTRP models are either unrealistic, overly complex, or lead to models that cannot be solved in real-time. To address this, innovative extensions are made to our TTRP model that allow speed to be modelled parsimoniously. Real instances for Derby station are used to demonstrate that these modelling enhancements do not incur any extra computational cost. Finally, a lack of evidence is identified concerning the fairness of TTRP models with respect to competing train operators. New evaluation techniques are developed to fill this gap, and these techniques are applied to a case study of Doncaster station. We find that unfairness is present when efficiency is maximised, and find that it mostly results from competition between a small number of operators. Moreover, we find that fairness can be improved up to a point by increasing the priority given to local trains. This work represents an important step forward in optimisation techniques for the TTRP. Our results, obtained using real instances from both Doncaster and Derby stations, add significantly to the body of evidence showing that optimisation is a viable approach for the TTRP. In the long run this will make deployment of such technology more likely

Numerical Stability of Path-based Algorithms For Traffic Assignment

In this paper we study numerical stability of path-based algorithms for the traffic assignment problem. These algorithms are based on decomposition of the original problem into smaller sub-problems which are optimised sequentially. Previously, path-based algorithms were numerically tested only in the setting of moderate requirements to the level of solution precision. In this study we analyse convergence of these methods when the convergence measure approaches machine epsilon of IEEE double precision format. In particular, we demonstrate that the straightforward implementation of one of the algorithms of this group (projected gradient) suffers from loss of precision and is not able to converge to highly precise solution. We propose a way to solve this problem and test the proposed adjusted version of the algorithm on various benchmark instances

A Framework for and Empirical Study of Algorithms for Traffic Assignment

Traffic congestion is an issue in most cities worldwide. Transportation engineers and urban planners develop various tra c management projects in order to solve this issue. One way to evaluate such projects is traffic assignment (TA). The goal of TA is to predict the behaviour of road users for a given period of time (morning and evening peaks, for example). Once such a model is created, it can be used to analyse the usage of a road network and to predict the impact of implementing a potential project. The most commonly used TA model is known as user equilibrium, which is based on the assumption that all drivers minimise their travel time or generalised cost. In this study, we consider the static deterministic user equilibrium TA model. The constant growth of road networks and the need of highly precise solutions (required for select link analysis, network design, etc) motivate researchers to propose numerous methods to solve this problem. Our study aims to provide a recommendation on what methods are more suitable depending on available computational resources, time and requirements on the solution. In order to achieve this goal, we implement a flexible software framework that maximises usage of common code and, hence, ensures comparison of algorithms on common ground. In order to identify similarities and differences of the methods, we analyse groups of algorithms that are based on common principles. In addition, we implement and compare several different methods for solving sub-problems and discuss issues related to accumulated numerical errors that might occur when highly accurate solutions are required

Detectable clonal mosaicism and its relationship to aging and cancer

In an analysis of 31,717 cancer cases and 26,136 cancer-free controls from 13 genome-wide association studies, we observed large chromosomal abnormalities in a subset of clones in DNA obtained from blood or buccal samples. We observed mosaic abnormalities, either aneuploidy or copy-neutral loss of heterozygosity, of >2 Mb in size in autosomes of 517 individuals (0.89%), with abnormal cell proportions of between 7% and 95%. In cancer-free individuals, frequency increased with age, from 0.23% under 50 years to 1.91% between 75 and 79 years (P = 4.8 × 10(-8)). Mosaic abnormalities were more frequent in individuals with solid tumors (0.97% versus 0.74% in cancer-free individuals; odds ratio (OR) = 1.25; P = 0.016), with stronger association with cases who had DNA collected before diagnosis or treatment (OR = 1.45; P = 0.0005). Detectable mosaicism was also more common in individuals for whom DNA was collected at least 1 year before diagnosis with leukemia compared to cancer-free individuals (OR = 35.4; P = 3.8 × 10(-11)). These findings underscore the time-dependent nature of somatic events in the etiology of cancer and potentially other late-onset diseases

A game-theoretic analysis of competition in a deregulated bus market

A game theoretical approach is applied to model the strategic interactions between the operators in a deregulated bus market, taking into consideration price competition as well as competition over service frequency. The conditions for market entry and predatory behavior are determined. The impact of deregulation of the bus market is then assessed in terms of profits and social cost to the society. A hypothetical case is constructed to test the model. Numerical results indicate that deterrence is a dominant strategy in most market situations, which leads to lower fare and higher service frequency, and consequently brings benefits to the society.Bus industry Nash equilibrium Competition Transport economics

An evaluation of the fairness of railway timetable rescheduling in the presence of competition between train operators

Using the output of optimisation models to make real-time changes to railway timetables can be an effective way to reduce the propagation of delay. In this study, we develop a methodology for evaluating the fairness of such optimisation models with respect to competing train operators. Whilst both fairness and optimisation-based railway timetable rescheduling have both been widely studied, they have not previously been studied together. We propose definitions of fairness and efficiency for timetable rescheduling, and analyse the fairness of efficiency-maximising solutions for a case study with seven train operators. We also investigate the pairwise trade-offs between operators and show that the priority given to different train classes has an important impact on fairness

Nonlinear pricing on private roads with congestion and toll collection costs

Nonlinear pricing (a form of second-degree price discrimination) is widely used in transportation and other industries but it has been largely overlooked in the road-pricing literature. This paper explores the incentives for a profit-maximizing toll-road operator to adopt some simple nonlinear pricing schemes when there is congestion and collecting tolls is costly. Users are assumed to differ in their demands to use the road. Regardless of the severity of congestion, an access fee is always profitable to implement either as part of a two-part tariff or as an alternative to paying a toll. Use of access fees for profit maximization can increase or decrease welfare relative to usage-only pricing for profit maximization. Hence a ban on access fees could reduce welfare.Congestion pricing Two-part pricing Private roads Toll collection costs

Strategic Interactions of Bilateral Monopoly on a Private Highway

This paper investigates strategic interactions between a private highway operator anda private transit operator who uses the same highway for its services. Heterogeneity oftravellers is taken into account by considering a continuous distribution of values of time.Demand elasticity arises from the inclusion of an outside virtual mode. Game theory is appliedto model the possible moves taken by the operators in their interactions. Four games areformulated, representing different decision making processes, including Nash and Stackelberg(leader-follower) games. The different timings of long-run and short-run decisions are alsomodeled in a two-stage game. Our results indicate that the market equilibria in the four gamesformulated are quite different as a result of the different sequences of moves. The highwayoperator is considered to be in a better position in terms of profit making in most cases,while for the transit operator it will generally be more advantag!eous to be the follower rather than in the leader position.Bilateral monopoly; private highway; private bus services; game theory; competitive equilibrium.