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2019 | OriginalPaper | Buchkapitel

Performance Evaluation of GLOSA-Algorithms Under Realistic Traffic Conditions Using C2I-Communication

verfasst von: Michael Kloeppel, Jan Grimm, Severin Strobl, Rico Auerswald

Erschienen in: Data Analytics: Paving the Way to Sustainable Urban Mobility

Verlag: Springer International Publishing

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Abstract

The aim of Green Light Optimized Speed Advisory (GLOSA) systems is to assist individual vehicles approaching an intersection with speed advices (either as single target speed or as complex speed-distance relation) in order to fulfill a given objective. Common objectives include the minimization of fuel usage, emissions and/or delay. The literature provides a wide selection of GLOSA-algorithms addressing different aspects of a real world application, like surrounding traffic, fixed time or actuated traffic lights and mode of communication. However, previous research usually addressed only a subset of possible aspects. Therefore, our goal is to investigate how the existing algorithms hold up in a scenario under largely realistic conditions. We measure the performance (in terms of overall fuel usage, carbon dioxide emissions and delay) of the different GLOSA-algorithms and identify potential shortcomings.

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Metadaten
Titel
Performance Evaluation of GLOSA-Algorithms Under Realistic Traffic Conditions Using C2I-Communication
verfasst von
Michael Kloeppel
Jan Grimm
Severin Strobl
Rico Auerswald
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-02305-8_6