Spatiotemporal Implications of Population Downscaling: A MATSim Study of Sioux Falls Morning Peak Traffic

Golan Ben-Dor, Eran Ben-Elia, Itzhak Benenson

Research output: Contribution to journalConference articlepeer-review

Abstract

Computer hardware is steadily advancing; however, simulating real urban transportation systems that serve millions of individual travelers is still a difficult task. The Multi-Agent Transportation Simulation (MATSim) is the only agent-based traffic model that includes intrinsic downscaling - procedures of changing network parameters in order to simulate the dynamics of the system as a whole while activating only a fraction k of travelers. In this paper, we present the MATSim's downscaling procedure and compare the dynamics of car traffic in the downscaled and full-scaled scenarios of the Sioux Falls test case. We compare aggregate and disaggregate statistics that represent Sioux Falls daily traffic, focusing on the morning peak. We conclude that downscaling up to k = 0.25 preserves all major statistics of urban traffic, within the interval of k between [0.1, 0.25]. Some of the statistics replicate well the statistics of the full-scaled runs, while downscaling below k = 0.1 can easily result in substantial deviations from the dynamics of the full-scale model.

Keywords

  • Agent-Based simulation
  • Car traffic
  • Downscaling
  • MATSim
  • Morning Peak

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