Electric Vehicle Travel Planning with Lazy Evaluation of Recharging Times

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00338088" target="_blank" >RIV/68407700:21230/19:00338088 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1109/SMC.2019.8913902" target="_blank" >https://doi.org/10.1109/SMC.2019.8913902</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/SMC.2019.8913902" target="_blank" >10.1109/SMC.2019.8913902</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Electric Vehicle Travel Planning with Lazy Evaluation of Recharging Times

Popis výsledku v původním jazyce

The basic premise of existing route planning algorithms is that complete information required for computing optimum routes is available at the time of the search. With the increasing complexity of transport systems, such an assumption is no longer valid as transport service providers are not willing to disclose full information about certain aspects of their services for business sensitivity reasons. Therefore, new approaches capable of computing optimal routes while minimizing the required amount of information about the services are required. In this paper, we investigate the incomplete information route planning problem in the context of planning routes with charging for electric vehicles. We have formalized the problem as a resource-constrained shortest path problem with time-dependent edge costs; the costs are only partially known and their values can be obtained by querying external data sources. We propose an optimum algorithm solving this problem utilizing two interchanging phases built on a multi-objective A* algorithm. We evaluate the properties of the algorithm on a comprehensive suite of test scenarios based on real-world data and derive insights into the properties of this emerging route planning problem.

Název v anglickém jazyce

Electric Vehicle Travel Planning with Lazy Evaluation of Recharging Times

Popis výsledku anglicky

The basic premise of existing route planning algorithms is that complete information required for computing optimum routes is available at the time of the search. With the increasing complexity of transport systems, such an assumption is no longer valid as transport service providers are not willing to disclose full information about certain aspects of their services for business sensitivity reasons. Therefore, new approaches capable of computing optimal routes while minimizing the required amount of information about the services are required. In this paper, we investigate the incomplete information route planning problem in the context of planning routes with charging for electric vehicles. We have formalized the problem as a resource-constrained shortest path problem with time-dependent edge costs; the costs are only partially known and their values can be obtained by querying external data sources. We propose an optimum algorithm solving this problem utilizing two interchanging phases built on a multi-objective A* algorithm. We evaluate the properties of the algorithm on a comprehensive suite of test scenarios based on real-world data and derive insights into the properties of this emerging route planning problem.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)

ISBN

978-1-7281-4569-3

ISSN

2577-1655

e-ISSN

—

Počet stran výsledku

6

Strana od-do

3168-3173

Název nakladatele

IEEE

Místo vydání

Piscataway

Místo konání akce

Bari

Datum konání akce

6. 10. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—