Using real-world traffic incident data in transport modeling

This study incorporates real-world traffic incident data into a transport simulation and analyzes the impact of roadworks, accidents and other incident types on the transport system. Traffic incidents are modeled as a reduction in road capacity to which transport users can react by adjusting their transport routes. Depending on the type of traffic incident, i.e. long-term vs. short-term effect, a different behavioral reaction is implemented which reflects a different assumption regarding the transport users level of knowledge. Simulation experiments for the Greater Berlin area indicate that traffic incidents cause an increase in average travel time per car trip of 5-7 minutes. Also, over a long period of time, traffic incidents have a significant effect on the transport system: On an average working day, for almost half of all car trips, transport users either travel on a road (segment) which is affected by a traffic incident or bypass such a road (segment). Overall, this study highlights the importance to account for traffic incidents in transport modeling. Accounting for traffic incidents allows to quantify the effects from roadworks, accidents and other incident types. Furthermore, the simulation of traffic incidents makes the model more realistic and allows for an improved policy evaluation and decision-making

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