Dynamic planning for recharging shared electric taxies

Master Thesis (2019)
Author(s)

H. Jamshidi (TU Delft - Civil Engineering & Geosciences)

Contributor(s)

B. van van Arem – Coach (TU Delft - Transport and Planning)

Gonçalo Correia – Mentor (TU Delft - Transport and Planning)

Theresia van Essen – Graduation committee member (TU Delft - Discrete Mathematics and Optimization)

Klaus Nökel – Coach

Faculty
Civil Engineering & Geosciences
Copyright
© 2019 Helia Jamshidi
More Info
expand_more
Publication Year
2019
Language
English
Copyright
© 2019 Helia Jamshidi
Graduation Date
24-09-2019
Awarding Institution
Delft University of Technology
Programme
['Civil Engineering | Transport and Planning']
Faculty
Civil Engineering & Geosciences
Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Abstract

An electric-recharging planning algorithm was developed in this study to accompany a dispatching algorithm that assigns real-time trip requests to vehicles of a shared taxi fleet owned by an operator. The algorithm decides on when, where, and how much each vehicle should charge, in real-time. It will also relocate idle vehicles if needed. The approach, to designing the algorithm, was to allow maximum flexibility for the dispatcher, not forcing charging on vehicles ahead of time, and restricting their chance of picking up a customer meanwhile, having limited empty routing cost (going to charger and back, and relocating trips), of course while providing enough charge for the expected level of demand to be met. Three sequential mixed linear integer programming (MLIP) optimizations were designed to achieve a pro-active charging planner, that can use aggregated prediction data, run in manageable time, and remain scalable with respect to the fleet-size.

Files

License info not available