High-Fidelity Modeling of Curbside Driving Behavior in SUMO: Preprint

Research output: Contribution to conferencePaper


Recent advances in mobility technologies have considerably increased the need for curbside use and congestion at curb-lanes. At airports and in dense urban centers, the growing adoption of Transportation Network Companies (TNCs), such as Uber and Lyft, has led to an increase in curbside traffic due to the reduction in the use public transit and other shared modes. In dense city areas, the curbside demand and congestion were further augmented by the growing use of e-commerce, which requires home-delivery of goods. To model vehicles' curbside interactions realistically, there is a need for high-fidelity simulation models that can represent the complex interplay of vehicles as they complete pick-up or drop-off trips. Vehicles' curbside behaviors are usually not modeled with high-fidelity in microscopic simulators such Simulation of Urban of Mobility (SUMO). This paper presents such a high-resolution model for vehicle curbside behavior in SUMO, using SUMO's Traci interface. Simulations results demonstrate that the improved curbside behavior captures vehicles' curbside maneuvering more accurately than the default SUMO curbside model, and increases the curbside utilization and capacity.
Original languageAmerican English
Number of pages12
StatePublished - 2022
EventSUMO User Conference 2021 -
Duration: 13 Sep 202115 Sep 2021


ConferenceSUMO User Conference 2021

NREL Publication Number

  • NREL/CP-2C00-80870


  • curbside
  • simulation
  • traffic


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