RailPrepared - Developing resilient railway transport planning towards probable future disruptions

• Applicant: Professor Dr. Nikola Besinovic
• Subject Area: Traffic and Transport Systems, Intelligent and Automated Traffic
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 545127954

Railway systems are becoming more unstable and vulnerable to various reoccurring disruptions both internal (infrastructure/vehicle failures) and external (physical-/cyberattacks). The current railway transport planning focuses mostly on matching transport capacity with the existing demand and assumes regular conditions, i.e. all resources are available. However, when a disruption occurs, many trains are cancelled and excessively delayed, which results in many passengers not reaching their destinations or not arriving on time, and compromises customers need for mobility. To meet societal requirements for reliable future transport, we need a new way of thinking and novel modelling for transport planning to make it more anticipative towards possible disruptions. To achieve this, we propose an innovative, integrated railway transport planning methodology that will greatly improve efficiency, availability and reliability of busy railway networks. The methodology is based on an innovative analytical framework embracing new resilience metrics, data analytics, and mathematical optimization. RailPrepared represents a novel anticipative planning which learns from historical traffic data and uses disruption management decisions during planning in order to enable intelligent adjustments to services provided. To do so, new mathematical models will need to efficiently evaluate millions of potential timetable alternatives and at the same time estimate their performance for thousands of probable disruption scenarios. In particular, the framework diversifies passengers’ routing alternatives, localises expected spatial impact of disruptions, and minimizes expected loss of transport demand. The RailPrepared approach will be validated using traffic data from German railway companies. The result of RailPrepared project is an effective decision support planning system that guarantees a high level of service under regular conditions, as well as better preparedness and recovery during disruptions.

• DFG Programme: Research Grants