English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The advent of autonomous driving and electrification is enabling thedeployment of Electric Autonomous Mobility-on-Demand (E-AMoD) systems, wherebyelectric autonomous vehicles provide on-demand mobility. Crucially, the designof the individual vehicles and the fleet, and the operation of the system arestrongly coupled. Hence, to maximize the system-level performance, they must beoptimized in a joint fashion. To this end, this paper presents a framework tojointly optimize the fleet design in terms of battery capacity and number ofvehicles, and the operational strategies of the E-AMoD system, with the aim ofmaximizing the operator's total profit. Specifically, we first formulate thisjoint optimization problem using directed acyclic graphs as a mixed integerlinear program, which can be solved using commercial solvers with optimalityguarantees. Second, to solve large instances of the problem, we propose asolution algorithm that solves for randomly sampled sub-problems, providing amore conservative solution of the full problem, and devise a heuristic approachto tackle larger individual sub-problem instances. Finally, we showcase ourframework on a real-world case study in Manhattan, where we demonstrate theinterdependence between the number of vehicles, their battery size, andoperational and fixed costs. Our results indicate that to maximize a mobilityoperator's profit, a fleet of small and light vehicles with battery capacity of20 kWh only can strike the best trade-off in terms of battery degradation,fixed costs and operational efficiency.

Electric Autonomous Mobility-on-Demand: Jointly Optimal Vehicle Design and Fleet Operation