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

: Klöppel, Michael; Grimm, Jan; Strobl, Severin; Auerswald, Rico


Nathanail, E.G.:
Data Analytics: Paving the Way to Sustainable Urban Mobility : Proceedings of 4th Conference on Sustainable Urban Mobility (CSUM2018), 24 - 25 May, Skiathos Island, Greece
Cham: Springer International Publishing, 2018 (Advances in Intelligent Systems and Computing 879)
ISBN: 978-3-030-02304-1 (Print)
ISBN: 978-3-030-02305-8 (Online)
ISBN: 978-3-030-02306-5
Conference on Sustainable Urban Mobility (CSUM) <4, 2018, Skiathos Island>
Fraunhofer IVI ()
GLOSA; speed advisory system; connected vehicles; ITS-G5

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.