Default Strategy

Default Strategy#

The current implementation of the default strategy allows:

  • Assignment: a batching-based assignment is provided with batching interval allowed to be set to 1 second (previous versions included instant assignment, but a 1 second batch provides slightly better but comparable results)

  • Parking: finding the nearest parking location up to a distance threshold or idle in place

  • Charging: charging decisions based on minimum battery state of charge requirements and idling time

  • Repositioning: ORTOOLS or GLPK-powered repositioning with a zone-level formulation

  • Maintenance/Cleaning: manages cleaning after every y requests served or at specific hours of they day to rotate the fleet in and out of cleaning stations

  • Fares: basic fares using base, per-mile, per-minute factors that vary by mode (TNC vs FMLM)

Important

Default strategy is continually evolving to provide algorithms across all types of strategies to POLARIS users, but the following article remains the best description of the original implementation:

Gurumurthy, K.M., de Souza, F., Enam, A. and Auld, J., 2020. Integrating supply and demand perspectives for a large-scale simulation of shared autonomous vehicles. Transportation Research Record, 2674(7), pp.181-192. https://doi.org/10.1177/0361198120921157

Important

Repositioning implementation details are available here:

de Souza, F., Gurumurthy, K.M., Auld, J. and Kockelman, K.M., 2020. A repositioning method for shared autonomous vehicles operation. Procedia Computer Science, 170, pp.791-798. https://doi.org/10.1016/j.procs.2020.03.154

de Souza, F., Gurumurthy, K.M., Auld, J. and Kockelman, K.M., 2020, May. An Optimization-based Strategy for Shared Autonomous Vehicle Fleet Repositioning. In Vehits (pp. 370-376). https://www.anl.gov/argonne-scientific-publications/pub/159229

Important

Parking related implementation details are available here:

Fakhrmoosavi, F., Gurumurthy, K.M., Kockelman, K.M., Hunter, C.B. and Dean, M.D., 2024. Parking strategies and outcomes for shared autonomous vehicle fleet operations. Journal of Transportation Engineering, Part A: Systems, 150(4), p.04024009. https://doi.org/10.1061/JTEPBS.TEENG-7955