The aim of this work is to propose a demand model for the simulation of a transportation system in emergency conditions. The model is specified, calibrated and validated using data obtained from real experimentation in the urban area of Melito Porto Salvo in the province of Reggio Calabria (Italy), in relation to the research project SICURO, organized by LAST -Laboratory for Transport Systems Analysis and funded by the Calabria Regional Authority (EU Structural Funds 2000-2006. In this paper we analyse a formal demand model subdivided into the following sub-models: generation; modal split with distribution. All sub-models were validated using formal and informal tests.
An advancement on demand models for the simulation of a transportation system in emergency conditions is the aim of this work. Advancement is related to demand models specified for the research project SICURO, organized by the Laboratory for Transport Systems Analysis (LAST). Herein we propose specification and calibration of generation and distribution with modal choice models. In comparison with demand models previously presented, a generation model according to a behavioural approach is proposed. Major attention is focused on SP (Stated Preference) surveys, in comparison with the RP (Revealed Preference) surveys previously considered.
The SICURO research project was developed by the Laboratory for Transport Systems Analysis (LAST). The project includes demand analysis for transportation system simulation in emergency conditions. Herein we propose the specification and calibration of generation and distribution with modal choice models. Using SP (Stated Preference) and RP (Revealed Preference) surveys. Software for demand model calibration and estimation is described, with some being used for the proposed model experimentation.
When a dangerous event occurs, a variety of events affects the system characteristics of users and of the transportation network in the time. Dynamic models allow us to simulate variation in choice probability from one time to another, considering temporal evolution of user characteristics and of dangerous event. Among dynamic models, sequential dynamic discrete choice models represent a special class and are proposed in this work to simulate evacuation conditions. Sequential tests are introduced to validate the proposed model and in order to ascertain whether current decisions are directly influenced by the most recent previous decisions. Sequential tests are specified for evacuation condition simulation and allow us to assess the significance of the reduction in uncertainty.
Simulation of evacuation demand in some emergency conditions requires the use of dynamic models, among which sequential dynamic discrete choice models represent a special class. Sequential dynamic discrete choice models are based on discrete choice model theory and on sequential analysis, a statistical approach which allows one to analyze the given dynamic phenomenon in the sample database and to highlight, if it exists, a specific lag. This work is subdivided into two main parts. In the first part we propose an analysis of evacuation conditions requiring a dynamic approach and a state of the art of literature models which deal with these. In the second part we propose a brief description of sequential analysis and we introduce a sequential dynamic discrete choice model to simulate evacuation conditions.
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