MSE PhD Prospectus Defense of Rebecca Swaszek

  • Starts: 10:00 am on Wednesday, October 17, 2018
  • Ends: 12:00 pm on Wednesday, October 17, 2018
TITLE: Fleet Load Balancing Strategies for Shared Mobility-On-Demand Systems

ABSTRACT: Mobility on Demand (MoD) systems utilize shared vehicles to supplement or replace mass transit and private vehicles. Such systems include traditional taxis as well as bike share and ride share companies. MoD systems share many common challenges but this prospectus focuses on the load balancing problem of redistributing vehicles among service regions. This is a difficult resource reallocation problem because customer demands follow a stochastic process subject to dynamic temporal-spatial patterns.

The first part of this prospectus considers the load balancing problem for a bike sharing system in which bikes are redistributed among stations via trucks. The objective is to avoid situations in which a user wishes to rent (return) a bike to a station but cannot because the station is empty (full). Using a graph network framework, a receding horizon controller is proposed to determine the optimal paths -- over a short period of time -- for the trucks to take. When calculating the optimal paths the controller considers the current and projected inventory subject to the dynamically changing rent and return rates for every station in the network.

The second part tackles the redistribution of an autonomous taxi fleet in which the vehicles themselves are capable of performing load balancing operations across service regions. The objective is to minimize the fraction of customers whose demands are dropped due to vehicle unavailability as well as the fraction of time the vehicles spend on load balancing operations (i.e empty). The system is represented by a queuing model and, as such, dynamic programming can find the optimal solution; however, the state-space of the model grows quickly rendering all but a minuscule system impossible to solve. To this end a parametric control is proposed that uses thresholds to dictate redistribution actions.

Future work consists of utilizing concurrent estimation methods to construct many sample paths from a single sample path (live or simulated) in order to evaluate many control parameters at once to find well performing policies. The load balancing covered in this prospectus features direct controls by the system operators; further work in this areas will include how system customers may be incentivized to aid in the load balancing effort by altering their origin and/or destinations to redistribute vehicles.

COMMITTEE: Advisor: Christos Cassandras, SE/ECE; Pirooz Vakili, SE/ME; Yannis Paschalidis, SE/ECE; Sean Andersson, SE/ME

Location:
15 Saint Mary's Street, Rm 105

Back to Calendar