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Using real-world traffic incident data in transport modeling

Kaddoura, Ihab; Nagel, Kai

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.
Published in: Procedia Computer Science, 10.1016/j.procs.2018.04.084, Elsevier