In urban contexts, the adoption of policies to promote the use of public transport systems represents a useful tool for decision-makers to reduce the environmental impact of private car use. Especially in high-density contexts most travel demand can be satisfied efficiently by means of high-quality rail systems. However, in the event of breakdowns, since faulty trains cannot usually be overtaken and their removal could pose extreme difficulties especially in metropolitan systems with two separate tunnels, re-establishing the regular service could involve inconveniently long travel times. Hence, emergency management has to take into account effects on travel demand. In this framework, we analyse such effects for different levels of degraded services in order to define the best strategy to adopt to minimise user discomfort. We extend ideas proposed elsewhere in the literature by introducing capacity constraints of rail vehicles in order to provide more realistic simulated effects. Finally, we describe the application of the proposed approach in the case of the Naples metro system.

In this paper, we propose an off-line procedure for determining the optimal operational strategy in the case of rail and/or metro system failure. The procedure is based on a micro-simulation approach for estimating effects of each feasible intervention strategy on travel demand. Numerical results in the case of a real-size metro network show that optimal solutions could differ according to travel demand levels and/or breakdown severities

The importance of a mobility system based on railway technology as the backbone of public transport is now widely acknowledged. Indeed, rail systems are green, high performing, smart and able to ensure a high degree of safety. Therefore, modal split should be steered towards rail transport by increasing the attractiveness of this transport mode. In this context, a key element is represented by the timetabling design phase, which must aim to guarantee an appropriate degree of robustness of rail operations in order to ensure a high degree of system reliability and increase service quality. A crucial factor in the task of timetabling entails evaluating dwell times at stations. The innovative feature of this paper is the analytical definition of dwell times as flow dependent. Our proposal is based on estimating dwell times according to the crowding level at platforms and related interaction between passengers and the rail service in terms of user behaviour when a train arrives. An application in the case of a real metro system is provided in order to show the feasibility of the proposed approach.

The management of public transport for rebalancing the use of transportation systems is a useful tool for reducing negative externalities without excessively affecting zone accessibility. In this context, a rail or metro system can be a key element for producing a high-quality supply of public transport. Obviously, due to the great vulnerability of rail technology to system failures, it is necessary to develop suitable tools to identify rapidly, even with off-line procedures, the best operational strategies which minimise user discomfort produced by such failures. Hence, our proposal is to extend previous models proposed in the literature by considering travel demand as an outcome of a random variable and not only in terms of average values. The proposed approach is applied in the case of a real dimension metro network, considering a wider class of failure contexts.

In high-density contexts, such as urban or metropolitan areas, decision makers and mobility managers have to adopt suitable strategies to reduce the use of private cars and promote public transport. Indeed, such strategies may help abate the negative impacts of transportation systems (congestion, air and noise pollution, etc.). However, appropriate measures are only effective if based on the provision of high-quality public transport services. Such aims can be achieved by organizing public transport within an integrated framework where rail/metro services are the high-performing mobility backbone and bus services have a feeder function, increasing the geographical coverage of rail services. However, since a faulty train cannot be easily removed or overtaken, a rail/metro system is highly vulnerable to system breakdowns which could entail significant reductions in system quality. Suitable intervention strategies therefore have to be developed to manage rail system emergencies. The aim of this article is to provide a method to determine optimal intervention strategies in the case of a metro system failure. Since in real contexts an exhaustive approach has to be excluded due to the huge number of alternative solutions to be evaluated, it is necessary to adopt or develop appropriate algorithms to obtain sub-optimal solutions within suitable computational times. Hence a Neighbourhood Search Algorithm to identify the optimal solution is applied and tested in the case of a real metro line in order to show the feasibility of our proposal.

In railway systems, the evaluation of specific operating conditions and their impact on travel demand plays a key role both in planning and managing rail services. In this paper, we focus on the implementation of some energy saving strategies (ESSs) through the definition of energy-efficient speed profiles and estimate their effects on travel demand. In particular, speed profiles for ESSs need extra time for their implementation and hence entail a reduction in line performance. The definition of optimal speed profiles requires the use of optimisation procedures which can be formulated by considering motion parameters as control variables and energy consumption as the performance to be optimised (minimised), with respect to the available time. The proposed methodology is applied in the case of a real metro line, showing differences in user generalised costs, in order to provide additional information for rail operators which may allow evaluation of the best strategies to be adopted.

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Optimisation and simulation tools are vital for planning and managing rail systems, providing performance analysis and evaluation of interactions without any kind of disturbance to the service. We may distinguish between combinatorial optimisation and simulation models which can be also classified into macroscopic and microscopic models. The former models describe the network and the timetable in a simple way by means of a simplified graph. The latter models consist of the specification of all technical characteristics related to infrastructure, rolling stock and signalling system as well as timetable data. Macroscopic models are useful during the planning process when the design of service frequencies and capacity to satisfy demand are carried out. The major benefit of this approach is the possibility to consider jointly several features of the rail system obtaining reliable results. By contrast, microscopic models reproduce the network as closely as possible to the 'real world'; they allow evaluating the interactions among trains and the performance of the network precisely. The aim of this paper is to propose a new approach for planning and managing the rail system combining both approaches macroscopic and microscopic. In particular, an optimisation model, based on a macroscopic approach, represents the kernel of the procedure and it is used as a first step to study any kind of scenario. The microscopic simulation model, by contrast, generates detailed (and precise) data, such as headways or running times, to overcome the approximations of the macroscopic model. Above all, in case of disruptions, the combination of the two models provides reliable results taking advantage of the benefits of the two approaches. Numerical applications have been applied in a realistic case taken from a real metro network located in the south of Italy; the preliminary results show the effectiveness of the proposed approach.