There is a rich literature, mainly developed in the last two decades, about risk reduction in transport system in emergency conditions. One of the challenges regards the development of ad-hoc transport system models (TSMs) in order to simulate emergency conditions. The paper focuses on the supply (network) component of the TSMs. The general objective of the research is the development of a framework capable to capture the relevant changes of the network from the ordinary conditions, due to an approaching calamitous event. The research will consider non-stationary conditions in transport supply models for continuous services. In relation to the consolidated static models, this evolution is necessary to capture the dynamics of the transportation network during the evacuation in terms of both topology (e.g. link closure, contraflow) and capacity of the links and of the network. The concept of learning process will be introduced to take into account how the transport costs (disutilities) in ordinary and emergency conditions will be perceived by the users.
RISK REDUCTION IN TRANSPORT SYSTEM IN EMERGENCY CONDITIONS: A FRAMEWORK FOR SUPPLY ANALYSIS / Musolino, Giuseppe. - 206:(2021), pp. 275-284. (Intervento presentato al convegno 9th International Conference on Safety and Security Engineering, SAFE 2021 tenutosi a ita nel 2021) [10.2495/SAFE210231].
RISK REDUCTION IN TRANSPORT SYSTEM IN EMERGENCY CONDITIONS: A FRAMEWORK FOR SUPPLY ANALYSIS
Musolino Giuseppe
2021-01-01
Abstract
There is a rich literature, mainly developed in the last two decades, about risk reduction in transport system in emergency conditions. One of the challenges regards the development of ad-hoc transport system models (TSMs) in order to simulate emergency conditions. The paper focuses on the supply (network) component of the TSMs. The general objective of the research is the development of a framework capable to capture the relevant changes of the network from the ordinary conditions, due to an approaching calamitous event. The research will consider non-stationary conditions in transport supply models for continuous services. In relation to the consolidated static models, this evolution is necessary to capture the dynamics of the transportation network during the evacuation in terms of both topology (e.g. link closure, contraflow) and capacity of the links and of the network. The concept of learning process will be introduced to take into account how the transport costs (disutilities) in ordinary and emergency conditions will be perceived by the users.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.