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In this paper we study the Multimodal Network Design Problem (MNDP); this problem arises when a decision maker (e.g. traffic authority) can operate on different transportation modes simultaneously. For this problem we formulate a general multimodal network design model from which descend multimodal and monomodal network design submodels. Possible solution approaches and research perspectives are identified. This paper, therefore, provides a general framework on multimodal and monomodal network design problems and their modeling.

The planning of an efficient and effective public transport system is a key element in managing modern mobility both in densely populated urban areas and in peripheral and/or rural areas where the population densities are considerably lower. Indeed, the presence of public transport designed to meet travel demand could allow a reduction in negative externalities produced by private cars without excessively penalising user travel times or accessibility to different zones. However, the recent financial crisis has forced many public administrations to reduce resources allocated to public services and replan related services in order to mitigate negative effects on users. In this context, the authors propose two methods for replanning public transport services in the case of budget reductions. The first approach, indicated as CLP (Change the Least Possible), can be adopted when the initial services are actually able to satisfy user needs and in some time slots are probably surplus to requirements. The second approach, CFR (Change the FRamework), instead, should be used when the initial services are already inadequate or barely sufficient to serve users in the study area. Indeed, in the latter case, it is very difficult to eliminate some runs without producing a significant reduction in levels of service. Finally, the proposed methodology has been applied by our research group when replanning bus services in the provinces of Naples and Avellino, in southern Italy, where we implemented respectively the CLP and CFR approaches by solving some problems related to interference with pre-existing planning tools.

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, the authors 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 this paper, the authors propose a model framework for providing optimal driving strategies and related speed profiles which minimise the energy consumption of rail convoys. Previous models were extended and applied to evaluate the effects of different signalling systems upon rail operating costs. The proposed method was tested on a real rail network, the Cumana suburban railway (Italy).

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 a model for optimising bus frequencies under the assumption of elastic demand, considering explicitly the effects of changes in transit supply on modal split. Indeed, neglecting demand elasticity may lead to solutions that may not represent actual design objectives. Using an objective function that is a weighted sum of user costs on all transportation systems (car and bus), operation costs and external costs, we propose a heuristic solution algorithm that is able to solve the problem in acceptable computing times, also for real-scale problems. The model and the algorithm are tested on a large urban multimodal network.

The objective of this paper is to propose a hyper-network model for simulating intermodal trips, such as park-and-ride trips, assuming elastic travel demand as regards mode choice. In particular, user flows on both road and transit networks can be estimated by the proposed model that is based on dummy links, with suitable cost functions, which are able to simulate virtually ‘on-network’ modal split and transfer operations. In particular, the authors of the paper state that with these suitable functions, mathematical equivalence is ensured between the results obtained on the hypernetwork and those obtained by applying a general assignment model with elastic demand at mode choice level.

This paper will propose an ant colony optimization (ACO)-based algorithm that can be used to simulate mass-transit networks; this algorithm imitates the behavior of public transport users. In particular, the authors show that the proposed algorithm, which is an extension of that proposed by D’Acierno et al. (A stochastic traffic assignment algorithm based on ACO, Lecture Notes in Computer Science 4150, pp. 25–36, 2006), allows mass-transit systems to be simulated in less time but with the same accuracy compared with traditional assignment algorithms. Finally, the authors state theoretically the perfect equivalence in terms of hyperpath choice behavior between artificial ants (simulated with the proposed algorithm) and mass-transit users (simulated with traditional assignment algorithms).

A model for the optimization of transit fares is proposed and tested on a trial network in this paper. This model considers a multimodal transportation system under the assumption of elastic demand for simulating the impacts of fare policies on modal split. The model takes into account all system and social costs: (transit and road) user costs, firm costs and external costs. First tests on a trial network show the non-negligible impacts of transit fare design on the overall transportation system conditions and on social costs.

This paper on urban freight distribution is from the proceedings of 14th international Conference on Urban Transport and the Environment in the 21st Century, which was held in Malta in 2008. The authors present a fixed-point model and algorithms for simulating urban freight distribution in a multimodal context with crossed congestion. They use the three different kinds of vehicles: private cars, buses and freight vehicles, that generally share urban road networks. The authors developed a multimodal assignment model that takes into account the effects of reciprocal influences among vehicles on user travel choices (at least on mode and path choices). They apply this model to urban freight distribution simulation, considering crossed congestion among all considered transportation systems. They report on a study of the model on a real dimension network that uses three algorithmic approaches (external, internal and hyper-network) for its solution and compare their performances in terms of calculation times and result reliability. They conclude that neglecting the multimodal aspects in the urban context can considerably change the minimum cost path used by freight vehicles.