Demand forecasting and adaptive management of intermodal transport hubs based on risk management and crowdsourcing

Abstract

Due to martial law in Ukraine, a significant portion of the transport infrastructure has undergone considerable disruption: dynamic population migration, unpredictable delays, risks of functional failures due to shelling, air raid alerts, or damaged infrastructure. Railway hubs that integrate several modes of transport (metro, buses, trams, etc.) play a crucial role in maintaining population mobility, particularly in crisis situations. Given the limited access to traditional data sources, the use of crowd-sourced data has become especially important for real-time demand forecasting and risk monitoring.