Coordinating Charging Request Allocation Between Self-Interested Navigation Service Platforms

Marianne Guillet () and Maximilian Schiffer ()
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Marianne Guillet: TomTom Location Technology Germany GmbH, 12435 Berlin, Germany; and School of Management, Technical University of Munich, 80333 Munich, Germany
Maximilian Schiffer: School of Management, Technical University of Munich, 80333 Munich, Germany; and Munich Data Science Institute, Technical University of Munich, 80333 Munich, Germany

INFORMS Journal on Computing, 2025, vol. 37, issue 2, 293-314

Abstract: Current electric vehicle market trends indicate an increasing adoption rate across several countries. To meet the expected growing charging demand, it is necessary to scale up the current charging infrastructure and to mitigate current reliability deficiencies, for example, due to broken connectors or misreported charging station availability status. However, even within a properly dimensioned charging infrastructure, a risk for local bottlenecks remains if several drivers cannot coordinate their charging station visit decisions. Here, navigation service platforms can optimally balance charging demand over available stations to reduce possible station visit conflicts and increase user satisfaction. Although such fleet-optimized charging station visit recommendations may alleviate local bottlenecks, they can also harm the system if self-interested navigation service platforms seek to maximize their own customers’ satisfaction. To study these dynamics, we model fleet-optimized charging station allocation as a resource allocation game in which navigation platforms constitute players and assign potentially free charging stations to drivers. We show that no pure Nash equilibrium guarantee exists for this game, which motivates us to study VCG mechanisms both in offline and online settings, to coordinate players’ strategies toward a better social outcome. Extensive numerical studies for the city of Berlin show that by coordinating players through VCG mechanisms, the social cost decreases on average by 42% in the online setting and by 52% in the offline setting.

Keywords: electric vehicles; congestion game; resource allocation; mechanism design (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:orijoc:v:37:y:2025:i:2:p:293-314

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