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Mobility On Demand: What About the Weekend?

Grace O Kagho1, Milos Balac2, Kay W Axhausen1

  • 1Institute for Transport Planning and Systems (IVT), ETH Zurich, Switzerland.

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Summary
This summary is machine-generated.

Weekend travel patterns differ significantly from weekdays, impacting mobility on demand (MoD) service planning. Simulations must account for these unique weekend demands to optimize autonomous MoD policies and operations.

Keywords:
MATSimMobility-on-demandagent-basedride-sharingshared

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Area of Science:

  • Transportation science
  • Simulation modeling
  • Urban planning

Background:

  • Mobility on demand (MoD) services offer flexible travel options, transforming urban mobility.
  • Current simulations often model only average weekdays, neglecting distinct weekend travel behaviors.
  • Weekend travel demand is more evenly distributed, unlike weekday peaks.

Purpose of the Study:

  • To compare weekday and weekend travel demand patterns for mobility on demand (MoD) services.
  • To analyze the impact of weekend travel characteristics on MoD service operations and policy.
  • To evaluate the simulation of autonomous mobility on demand (aMoD) in Zurich.

Main Methods:

  • Utilized agent-based simulation framework MATSim for modeling.
  • Simulated the introduction of an autonomous mobility on demand (aMoD) service in Zurich.
  • Compared simulated weekday and weekend travel demand and operational metrics.

Main Results:

  • Weekend travel demand exhibits unique patterns compared to weekdays, with more even distribution.
  • MoD services could replace public transport and private vehicle trips during weekends, especially for longer distances.
  • Optimal fleet sizes for aMoD services differ between weekdays and weekends due to demand variations.

Conclusions:

  • Transport policies and MoD simulations must incorporate unique weekend travel characteristics for effective planning.
  • Accounting for weekend travel ensures reliable service by balancing wait times, travel times, occupancy, and costs.
  • Simulation insights support the development of robust policies for autonomous mobility on demand services.