In order to improve the performances of transit modeling and in particular to assess the effects of the introduction of ITS technologies, which imply substantial changes in user behavior, in the last 10 years transit path choice and assignment models that use a schedule-based approach, instead of the traditional frequency-based one, have been developed. This paper presents a schedule-based path choice model for high-frequency transit networks, which allows us to consider the evolution in time of transit services, both within-day and day-to-day, as well as the day-to-day learning process of attributes by which users choose. On the basis of this path choice model a dynamic process assignment model, both within-day and day-to-day (from which the term “doubly dynamic” derives), was developed and tested on a realistically sized network to verify its applicability for operations planning.

Around the world, interest in urban and metropolitan goods movements is increasing since they account for a substantial share of traffic in urban/metropolitan areas. In this context, many city administrators have implemented measures to mitigate the negative effects of freight transport. Starting from an analysis of existing studies relative to freight policies implemented at urban scale, this paper proposes a general classification of measures adopted at an urban scale and an empirical analysis of obtainable results

Methods for planning and managing a transportation system in an urban area, when exogenous events occur and/or in emergency conditions, have received little attention from transportation system researchers, research institutions and journals. Models and algorithms specified and calibrated for ordinary conditions cannot be directly applied in emergency conditions. In this paper, the main problems developed concern: formalization of the risk problem in a transportation system with an improvement over consolidated quantitative risk analysis models; specification of a system of models for evacuation design and simulation, and in the particular case of path design in emergency conditions; the application of the model to simulate a real system for exposure reduction. The application was developed for an Italian town of about 9,000 inhabitants which was chosen as it has a similar number of potential evacuees to the majority of cases in real events when entire small towns, parts of a city or big buildings had to be evacuated. The curve between vulnerability and exposure is quantitatively represented. Keywords: evacuation, network design, risk analysis, simulation.1 INTRODUCTION This paper proposes methods for the simulation and design of a transportation system under conditions of safety and/or security. Safety and security problems are connected with events that generate emergency conditions, such as the 9/11 attack, the Atocha station bombings and the Asian tsunami.Methods for planning a transportation system in an urban area when exogenous events affecting the system occur and/or in emergency conditions, have received little attention from transportation system researchers, institutions and journals. Models and algorithms specified and calibrated for ordinary conditions cannot be directly applied in emergency conditions. When an exogenous event occurs, non-informed users move on the network with behaviour that is different with respect to ordinary situations: they know neither system congestion nor reliability in real time, as the system is in an exceptional condition; and even if the user has knowledge about his/her optimum, the user optimum, in general, differs from the system optimum and from the community (general public) optimum. If the system is monitored and designed in real time, a subset of users, who knows the system congestion and reliability in real time, is informed. The user optimum could be similar to the system optimum and the general public optimum.In these conditions, public decision makers must predict with transportation models (implemented by the system analyst) the effects of implementing their measures upon the system and how these measures may interact (implemented by operational forces) with the individual reactions of the users served by the transport system in question. System analysts implement a decision support system in order to evaluate in a short time the effect of the strategy that has to be implemented in the system; operational forces (military, fire brigade, etc.) organize...

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