Assessing Travel Disruption and Decentralised Responses in Multimodal Transport Systems

Disruption of travel due to extreme weather and other forms of damage, such as network isolation, travel delays, and associated wider economic losses, can far exceed direct damages. The scale of these indirect impacts depends critically on how operators and travellers respond to disruptions, which combines centralised responses with operational actions and behavioural adaptation in shaping the system performance.

This study proposes an innovative framework for multimodal transport systems that integrates decentralised operator response and passenger disruption-aware routing to evaluate indirect disruption impacts. Historical flood events are used to define plausible stress scenarios that locally reduce network capacity and service quality. When disruption occur, operators respond independently by prioritising either disrupted service recovery (e.g., speed up early road clearance and recovery process) or reinforcement of non-disrupted modes and corridors (e.g., adding bus frequencies and train short turns). These decentralised actions modify travel conditions and perceived generalised costs, and passengers subsequently reselect modes and routes through a logit-based choice model, leading to the change of travel demand at origin-destination level.

The framework is applied to road and rail networks in Great Britain using observed demand and future demand scenarios in 2030 and 2050 derived from long-term housing plans. By comparing indirect disruption impacts under a road-only system with those under an integrated road-rail system, the analysis highlights the extent to which multimodal connectivity mitigates indirect damages and reduces network isolation. Additionally, by capturing the interaction between disruption, decentralised response, and passenger behavioural change, the framework produces risk-weighted post-disruption capacity gaps that identify where congestion and service shortfalls persist. The results explicitly identify corridors and modes where capacity investment is most effective under future demand growth and plausible disruption conditions, providing actionable insights for long-term capacity planning and transport resilience. Indirect impacts are not just a property of infrastructure damage, but of how systems adapt.

Keywords: indirect disruption impacts; decentralised response; multimodal transport; integrated capacity planning and resilience