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Il contributo propone una trattazione organica sul tema del trasporto pubblico locale, analizzando in dettaglio i principali aspetti della pianificazione, progettazione, costi, ricavi, gestione ed esercizio.

In this paper we focus on the combined assignment-control problem that arises when signal control parameters of an urban road network are locally optimised and they have to be consistent with equilibrium traffic flows. This problem can be formulated as an (asymmetric) equilibrium assignment problem. In this paper we compare some solution algorithms for solving the combined assignment-control problem, based on the MSA (Method of Successive Averages) framework; some algorithms, proposed in the literature for solving the (symmetric) assignment problem, are adapted to the combined assignment-control problem. All the algorithms are tested on a real-scale network. Numerical results show that these algorithms are able to reduce computing times significantly, respect the classic MSA algorithm, in order to solve the asymmetric assignment problem.

Rail systems represent a useful tool for reducing the use of private cars especially in urban and metropolitan areas. However, since a faulty train cannot be easily removed or overtaken, in the case of rail system failures, restoring operative conditions could take a very long time and result in considerable delays for passengers. In this context, our proposal is to provide rail systems managers (i.e. dispatchers) with an off-line procedure which adopts a microsimulation approach for analysing the most frequent breakdown conditions and suggests in advance the optimal intervention strategies to adopt. In particular, different perspectives are proposed and applied in the case of a real metro line in the south of Italy.

This paper proposes an off-line procedure for the management of rail-metro networks in the case of high-density, congested cities. Our approach maybe considered a decision support system for establishing recovery plans which take customers’ needs into accountwhen service disruption occurs. This new methodology combines a stochastic microscopic simulation of the network and passenger flows so as to evaluate effects of implemented strategies on service quality, simulating rail operations as closely as possible to reality. In other words, in order to analyse the robustness and feasibility of allowable recovery action, the method in questionconsiders the randomness of breakdown occurrence and the variability of both dwell times and travel demand levels at stations. Therefore, user flows are assigned to the network, simulating passenger behaviour on the platforms and especially the dynamic interaction with the rail system. The latter results in a fixed-point problem for the estimation of average dwell times. This, especially in high-density contexts, represents one of the main disturbances of the service and cannot be neglected. Based on this analysis, the stochastic distribution function is evaluated. Finally, an application on a real metro line in the south of Italy is performed to show the effectiveness of the proposed approach.

In this paper, we propose a sensitivity analysis for evaluating the effectiveness of recovery solutions in the case of disturbed rail operations. Indeed, when failures or breakdowns occur during daily service, new strategies have to be implemented so as to react appropriately and re-establish ordinary conditions as rapidly as possible. In this context, the use of rail simulation is vital: for each intervention strategy it provides the evaluation of interactions and performance analysis prior to application of corrective action. However, in most cases, simulation tasks are deterministic and fail to allow for the stochastic distribution of train performance and delays. Hence the strategies adopted might not be robust enough to ensure effectiveness of the intervention. We therefore propose an off-line procedure for disruption management based on a microscopic and stochastic rail simulation which considers both service operation and travel demand. An application on a real metro line in Naples (Italy) shows the benefits of the proposed approach in terms of service quality.

Due to the constant increase in travel demand, rail systems are more and more dense and service providers have the difficult task of planning a timetable which has to be robust and stable. Moreover, in order to increase customers??? satisfaction, it is necessary to provide sufficient transport capacity avoiding train and platform congestion and guaranteeing a good level of service quality. To reach this target, in this framework we provide an appropriate timetable evaluation which considers the dynamic effect of dwell time at station on the service in the case of metro networks.

The road network design problem is widely studied in the literature, both in urban and rural areas; most papers deal with the solution algorithms and with the mathematical formulation of the problem. The road network design problem is NP-hard and is very difficult to solve in acceptable computing times for real-scale networks. In urban areas, the objective of the design is usually the minimisation in total travel time on the network, while in rural areas it is usually a sum of total travel time and total (i.e. construction and maintenance) road costs. Very few papers consider other terms in the objective function and/or propose a multicriteria approach. In our best knowledge, no papers consider as objective of the design to minimise the fuel consumption, even if it is an actual objective of road network planning and design. In this paper, we compare the results obtained by solving some road network design problems adopting the classic objective functions and adopting as objective the minimisation in fuel consumptions on the network. In order to obtain this result, in the paper a fuel consumption function is proposed, based on CORINAIR models and depending on the vehicle fleet of the study area; this function is used both for estimating the reduction in fuel consumption due to the design obtained with the classic objective functions and for designing the road network using as objective function the total consumption on the network. The results obtained with these approaches are compared in terms of fuel consumed and total travel time spent on the network. The minimisation in fuel consumption is very important since greenhouse gas emissions and air pollutants are directly related to the consumption. Initial tests highlighted that the results obtained with the two different approaches are more significant in rural areas, where higher average flow speeds may produce higher consumption, according to the CORINAIR models.

Rail and metro networks are nowadays the backbone of public transportation systems especially in high density contexts. Due to the constant increase in travel demand, rail systems are more and more dense and service providers have the difficult task of planning a timetable which has to be robust and stable. Moreover, in order to increase customers??? satisfaction, it is necessary to provide sufficient transport capacity avoiding train and platform congestion and guaranteeing a good level of service quality. To reach this target, an appropriate timetable evaluation, which expresses the interactions between train operation and passenger flows, is essential. In particular, the aim of the paper is to analyse the dynamic effect of dwell time at station on the service in the case of metro networks. In fact, above all in crowded situations, train can be forced to remain stopped in a station more time than what has been planned, causing a delay. As a consequence, the more a train is delayed, the more the passengers arrive at the station and get on the train further increasing the dwell time. The evaluation of this dynamic effect, known in the literature as ???snowball effect???, provides an analysis of the timetable which is as closely as possible to the real phenomenon and, above all, yields an estimation of the effective congestion of carriages. Hence, by adopting suitable indexes which reflect passenger experiences of the service, it is possible to establish an appropriate evaluation method for planning train operations. An application on a real metro line in the city of Naples (Italy) has been applied in order to show the utility of the proposed approach.

In this paper we propose a general model and some solution algorithms for solving the Transit Network Design Problem in urban areas. The model is a constrained optimisation model where the decision variables are line routes and frequencies, the constraints regard feasible values for the frequencies, budget, line capacities and user assignment. The general model, that can be particularised in function of the aim of the design, can assume the transportation demand as rigid or elastic. In the paper some meta-heuristic algorithms are proposed for solving the problem and tested on a case study.

Negli ultimi anni molte città europee hanno introdotto politiche di tariffazione come strumento di gestione della domanda di trasporto, in particolare per ridurre la congestione e riequilibrare la ripartizione modale tra trasporto individuale e collettivo. Infatti, il comportamento degli utenti conduce il sistema ad una condizione di Equilibrio dell’Utente (User Equilibrium) che non corrisponde alla massimizzazione dell’utilità globale e non prende in considerazione i costi esterni. Pertanto, al fine di raggiungere una configurazione efficiente nell’utilizzo dei sistemi di trasporto (indicata in letteratura come Equilibrio del Sistema – System Equilibrium), è necessario imporre una tariffazione sulle strade urbane in modo da massimizzare il surplus sociale. Per numerose ragioni (teoriche, politiche, sociali) è impossibile applicare “tariffe efficienti” (indicate in letteratura come first-best solutions); perciò sulle reti reali bisogna applicare tariffe sub-ottimali (second-best solutions). Inoltre, una delle problematiche principali dell’applicazione delle politiche di pricing è la loro “accettazione” da parte della comunità e/o di sue componenti (commercianti, residenti, pendolari, ecc.) che conduce a conflitti ed opposizioni.In questa nota, si analizza il problema del progetto delle tariffe ottimali nel caso in cui i ricavi siano investiti totalmente o parzialmente per migliorare il trasporto collettivo. In particolare, si formula un modello che sia multimodale e multiutente, in cui gli aspetti relativi alla scelta modale siano calcolati in maniera esplicita su rete in corrispondenza di ciascuna configurazione tariffaria. Il modello è applicato ad una rete test (costruita con differenti valori di accessibilità relativa tra le differenti zone), analizzando alcune strategie “second-best” con particolare riferimento al reinvestimento dei ricavi., Tema. Journal of Land Use, Mobility and Environment, Vol 4, N° 4 (2011): Mobilità e conflitti

In this paper we focus on the road network design problem in regional contexts. In this case a planner may have financial resources to invest for improving performance on existing roads. Against the background of an extensive literature of optimisation models and algorithms to solve this problem, the innovative aspects of this paper are as follows: the optimisation model refers to the daily operation of the network; the objective function also considers the environmental costs; the proposed meta-heuristic solution algorithm has never been used to solve this problem; and the assignment algorithm is based on Ant Colony Optimisation in order to reduce computing times. The model and algorithm were tested on a real-scale problem, showing their applicability to real dimension networks.

In urban context, the improvement of rail systems represents a useful tool to promote the use of public transport and reduce environmental impacts of private car use. However, in the event of breakdowns, since faulty trains cannot usually be overtaken and their removal could pose extreme difficulties, re-establishing the regular service could involve inconveniently long travel times. Therefore, in this framework, we analyse effects of management strategies for different levels of degraded services in order to define the best solution to adopt to minimise travel demand discomfort.

Mesoscopic and microscopic simulation models of railway systems hold a fundamental role in supporting designing phases of both infrastructure components and railway operation strategies. Limits of such approaches regard the scarce accuracy in results of the former, which are unable to describe transient train dynamics, and the computational inefficiency of the latter which prevent their application to large-sized networks or probabilistic analyses. In this paper a microscopic and a mesoscopic “own built” railway simulation models are firstly introduced. Their application to a common case study and a comparison between the corresponding outputs and computing performances is then presented. Results comparison show that the dynamical integration of the approaches would overcome the respective limits improving both the range of possible applications and the accuracy of results.

In this paper we propose an Ant Colony Optimisation (ACO) algorithm for optimising the signal settings on urban networks following a local approach. This problem, also known as LOSS (Local Optimisation of Signal Settings), has been widely studied in the literature and can be formulated as an asymmetric assignment problem (Cascetta, E., Gallo, M. and B. Montella, 2006. Models and algorithms for the optimization of signal setting on urban networks with stochastic assignment models. Ann. Oper. Res., 144, 301-328). The problem consists in optimising the signal settings of each intersection of an urban network as a function only of traffic flows at the accesses to the same intersection, taking account of the effects of signal settings on costs and on user route choices. The proposed ACO algorithm is based on two kinds of behaviour of artificial ants which allow the LOSS problem to be solved: traditional behaviour based on the response to pheromones for simulating user route choice, and innovative behaviour based on the pressure of an ant stream for solving the signal setting definition problem. Our results on a real-scale network show that the proposed approach allows the solution to be obtained in less time but with the same accuracy as in traditional MSA approaches.

In this paper we focus on the multimodal network design problem that consists in designing jointly road and transit systems, assuming elastic demand at least at the mode choice level. We refer to regional contexts where a planner may have financial resources to be invested for improving the mobility of a wide area and have to decide how these resources should be allocated between transit and road systems. We propose an optimisation model for solving the problem, whereby we introduce an objective function that takes into account different objectives of the problem (reduction in user costs, reduction in external costs, etc.) and all constraints to be considered (budget constraints, capacity constraints, assignment constraints, etc.). We then propose a meta-heuristic solution algorithm for solving the problem and test it on a trial and a real-scale network.

In this paper a model for the optimisation of transit fares is proposed and tested on a real-dimension network. Formulated as a multidimensional constrained minimisation problem, the model considers a multimodal transportation system under the assumption of elastic demand for simulating the impacts of fare policies on modal split and network performances. We suggest that the proposed model be applied with the adoption of two objective functions in order to take into account all system and social costs: (transit and road) user costs, firm costs and external costs. Preliminary tests on a real-dimension network show that the main constraints in fare definition are related to the size of public transport subsidies provided by public administration.

In this paper, we propose an ACO-based algorithm to imitate the behaviour of public transport users. In particular, we show that the proposed algorithm allows transit systems to be simulated in less time but with the same accuracy compared with traditional assignment algorithms. Moreover, we state the equivalence in terms of hyperpath choice behaviour between artificial ants (simulated with the proposed algorithm) and transit users (simulated with traditional assignment algorithms). Finally, we apply the proposed algorithm on a real-scale network highlighting performances of the ACO approach.

The activity system of an urban area can be decomposed into three subsystem consisting of the households living in each zone, the economic activities located in each zone, and the floor-space (and the relative market prices) available in each zone for various uses. For instance, the number of households in a zone depend on employment opportunities (i.e. the subsystem of economic activities), the location of economic activities depends on the distribution of households, and both households and economic activities in each zone depend on the availability of specific types of floor-space and on the relative prices. In this context, the transportation system study and design represents a relevant element in the urban area planning because the relative 'accessibility' generated among different activities could support or limit the development of these activities. Indeed, the need to use different urban functions on different places yields the potential transportation demand; but this potential demand has to (or should) be satisfied by suitable transportation system. Hence, since household members make their travel choice in function of some characteristics of transportation services offered by the different travel modes (individual car, bus, metro, walking), it is necessary to have some synthetic indexes that allow decision-makers to evaluate and forecast effects of transportation systems on urban activity development. Moreover, the relative accessibility of a zone in urban contexts influences also the real-estate market: zones with high level of accessibility generally are characterised by high real-estate prices. Hence, users locate their residence also in function of their value of time, which can be considered as a measure of their income level (i.e. people with high incomes, and therefore with an high value of time, locate their residences in place with high accessibility characterised by high real-estate prices). These remarks are confirmed by the fact that the construction of a new metro station generally yields an increase in the real-estate prices. Many authors (see for instance Bath et al., 2000; Cascetta, 2001) agree that synthetic indexes for evaluating transportation system effects on the external environment are accessibility indexes which can be defined as "a measure of the ease of an individual to pursue an activity of a desired type, at a desired location, by a desired mode, and at a desired time" (Bath et al., 2000). In urban contexts, the variation of level of transportation services (and therefore of accessibility among different zones) is hard to be implemented by means of the construction of new transportation infrastructures. Therefore, a simpler and more feasible approach for yielding these variations is the optimisation of existing transportation systems as for instance by means of pricing policies (road pricing, cordon pricing, parking pricing, integrated mass-transit system fare, etc.). Indeed, these policies allow to modify substantially the modal split between road and mass-transit systems and therefore performances of each single transportation mode. Obviously these fares have to be designed taking into account the accessibility indexes in order to avoid that an odd pricing strategy could reduce accessibility and impoverish a zone. Hence, pricing policies supported by accessibility indexes can be considered an useful tool for planners for taking into account influences that transportation systems yield on the urban environment.

In this paper we focus on the road network design problem in regional contexts; in this case a planner may have financial resources to be invested for improving performances of an existing network. In the literature many optimisation models for solving this problem exist; we propose a model that considers also the evaluation of environmental external costs in the objective function. Then, the paper will focus on the solution algorithm: we will propose a Scatter Search algorithm that will be able to solve the problem for real-scale networks in acceptable computing times.

Il contributo propone una metodologia di predimensionamento degli interventi sul Trasporto Pubblico Locale mediante la quale è possibile, fissate le risorse finanziarie utilizzabili, definire la migliore strategia di progettazione/pianificazione da implementare ed i relativi effetti in termini di ripartizioni modali aggregate. I risultati applicati in un contesto regionale hanno mostrato la perfetta equivalenza della metodologia proposta con l'approccio tradizionale basato sulla simulazione esplicita a livello micro tra domanda ed offerta di trasporto.

In this paper we propose an assignment model on urban networks to simulate parking choices; this model, besides simulating the choice of parking, the search time and the walking time (between parking and destination), is able to simulate the impact of cruising for parking on the traffic congestion.

The air pollution due to road traffic represents a real environmental emergency, in particular in urban and metropolitan areas with high population density. The admitted maximum values of air pollutants are frequently exceeded and therefore local administrations have to adopt measures based on limitations of vehicular circulation. Several epidemiologic studies have highlighted as the atmospheric pollution produces serious damages to the human health. In particular, the thin powders, or particular matter, (PM10) are considered one of more dangerous pollutants for the human health (van Gent and Rietvels, 1993; Danielis and Chiabai, 1998; Kelly, 2003; Nel, 2005; Neidell, 2006). When in a zone of an urban area an important event occurs, the road traffic increases in a short time window producing congestion and environmental impacts. This paper studies some Travel Demand Management (TDM) strategies that can be adopted for limiting (and/or for redistributing) the road traffic in these cases, reducing road traffic emissions (as proposed by Gärling et al., 2002; Etyemezian et al., 2003; Loukopoulos et al., 2004; Concas and Winters, 2007; VTPI, 2009). After a literature review of 'general' TDM strategies, that can be adopted in urban areas for reducing private car use, the paper explores the possibility of applying these strategies in the occurrence of important events and proposes new innovative strategies that can be adopted in these particular cases. The proposed TDM strategies are tested and results concerning pollution are compared on a simplified network.