A. Horni and K.W. Axhausen IVT, ETH Zürich GRIDLOCK MODELING WITH MATSIM.

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A. Horni and K.W. Axhausen IVT, ETH Zürich GRIDLOCK MODELING WITH MATSIM

MOTIVATION gridlocks only roughly covered in current version of microsimulations e.g., MATSim models average working day traffic + relevance/risk of gridlocks (?)

context: joint seed project VPFW ETH analyze “gridlock” events (Zürich 2013, Aargau 2014) MATSim simulation experiments -network level -impedance components (e.g., look at intersections) extend solid base of gridlock modeling for aggregate transport modeling e.g., gridlocks and network-level MFDs (Geroliminis, Daganzo, …) -microsimulation modeling -gridlock characteristics PROCEEDING

METHOD MATSim simulation experiments output execution replanning scoring input plan utils

METHOD Zürich scenario -full population -navigation net -car mode simulated simulation configuration -relaxed state normal conditions -tunnels blockage due to truck accident :30 -within-day rerouting with increasing replanning range analysis based on city count data to begin with -10. / 16. / 17. / 18. / 25. of April 2013

RESULTS link storage capacity, a.k.a. jam density normal state blocked state

RESULTS link storage capacity, a.k.a. jam density

RESULTS

link storage capacity, a.k.a. jam density

RESULTS

blocked state sim counts

RESULTS Bucheggplatz morning rush hour

RESULTS impedance modeling: missing components -intersection dynamics: signals, priority rules, … -mode interactions: crosswalks, lane merging, … -driver behavior: slow drivers, driveaway delays, parking searchers, … -road geometry network modeling & its influence on the simulation dynamics

RESULTS issues with link storage capacity, … jam density

CONCLUSIONS & FUTURE WORK inspection -microsimulation (MATSim) capability to simulate gridlocks -relevance/risk of gridlocks and concise definition -gridlock characteristics more and more suitable data -police department ZH, … other events -Aargau Zug Chur 2014 impedance modeling issues -missing components, intersections -storage capacity