Dynamic traffic assignment for electric vehicles

  • We initiate the study of dynamic traffic assignment for electrical vehicles addressing the specific challenges such as range limitations and the possibility of battery recharge at predefined charging locations. We pose the dynamic equilibrium problem within the deterministic queueing model of Vickrey and as our main result, we establish the existence of an energy-feasible dynamic equilibrium. There are three key modeling-ingredients for obtaining this existence result: 1) We introduce a walk-based definition of dynamic traffic flows which allows for cyclic routing behavior as a result of recharging events en route. 2) We use abstract convex feasibility sets in an appropriate function space to model the energy-feasibility of used walks. 3) We introduce the concept of capacitated dynamic equilibrium walk-flows which generalize the former unrestricted dynamic equilibrium path-flows. Viewed in this framework, we show the existence of an energy-feasible dynamic equilibrium by applying anWe initiate the study of dynamic traffic assignment for electrical vehicles addressing the specific challenges such as range limitations and the possibility of battery recharge at predefined charging locations. We pose the dynamic equilibrium problem within the deterministic queueing model of Vickrey and as our main result, we establish the existence of an energy-feasible dynamic equilibrium. There are three key modeling-ingredients for obtaining this existence result: 1) We introduce a walk-based definition of dynamic traffic flows which allows for cyclic routing behavior as a result of recharging events en route. 2) We use abstract convex feasibility sets in an appropriate function space to model the energy-feasibility of used walks. 3) We introduce the concept of capacitated dynamic equilibrium walk-flows which generalize the former unrestricted dynamic equilibrium path-flows. Viewed in this framework, we show the existence of an energy-feasible dynamic equilibrium by applying an infinite dimensional variational inequality, which in turn requires a careful analysis of continuity properties of the network loading as a result of injecting flow into walks. We complement our theoretical results by a computational study in which we design a fixed-point algorithm computing energy-feasible dynamic equilibria. We apply the algorithm to standard real-world instances from the traffic assignment community illustrating the complex interplay of resulting travel times, energy consumption and prices paid at equilibrium.show moreshow less

Download full text files

Export metadata

Statistics

Number of document requests

Additional Services

Share in Twitter Search Google Scholar
Metadaten
Author:Lukas GrafORCiDGND, Tobias HarksGND, Prashant Palkar
URN:urn:nbn:de:bvb:384-opus4-1148130
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/114813
ISBN:978-3-95977-259-4OPAC
Parent Title (English):22nd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2022), September 8-9, 2022, Potsdam, Germany
Publisher:Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Place of publication:Schloss Dagstuhl
Editor:Mattia D'Emidio, Niels Lindner
Type:Conference Proceeding
Language:English
Year of first Publication:2022
Publishing Institution:Universität Augsburg
Release Date:2024/09/03
First Page:6:1
Last Page:6:15
Series:Open Access Series in Informatics (OASIcs) ; 106
DOI:https://doi.org/10.4230/OASIcs.ATMOS.2022.6
Institutes:Mathematisch-Naturwissenschaftlich-Technische Fakultät
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Mathematik
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Mathematik / Diskrete Mathematik, Optimierung und Operations Research
Nachhaltigkeitsziele
Nachhaltigkeitsziele / Ziel 7 - Bezahlbare und saubere Energie
Nachhaltigkeitsziele / Ziel 11 - Nachhaltige Städte und Gemeinden
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 51 Mathematik / 510 Mathematik
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)