A multi-dimensional rescheduling model in disrupted transport network using rule-based decision making

Apart from daily recurrent traffic congestion, unforeseen events such as flood induced road damages or bridge collapses can degrade the capacity of traffic supply and cause a significant influence on travel demand. An individual realising the unexpected events would take action to reschedule its day plan in order to fit into the new circumstance. This paper analyses the potential reschedule possibilities by augmenting the Within-Day Replanning simulation model implemented in the Multi-Agent Transport Simulation (MATSim) framework. Agents can adjust day plan through multi-dimensional travel decisions including route choice, departure time choice, mode switch, trip cancellation. The enhanced model not only improves the flexibility of MATSim in rescheduling a plan during an execution day, but also lays the foundation of integrating more detailed heterogeneity decision rules into the travel behaviour simulation to cope with unexpected incidents. Furthermore, the proposed rescheduling model is capable of predicting the network performance in the real-world picture and gives a hint on how best react to transport disruptions for transport management agency

Vulnerability of the Scottish Road Network to Flooding

Between 2014 and 2021 there were over 600 recorded flooding incidents per year on trunk roads managed by the four Operating Companies. Whilst many of these incidents were relatively minor in nature, around 9% of incidents resulted in a reduction in road width or at least one lane closure, and just over 1% led to a road or carriageway closure. Around half of all recorded flooding incidents had a duration of more than one hour, and 3.4% were longer than 6 hours. On average, there was at least one flooding incident on the trunk road network every two days. The maximum number of recorded incidents in a single day was 51, which occurred on 31st December 2015 during Storm Frank, and there were more than 15 flooding incidents in a single day on 40 occasions in the period 2014-2021