The introduction of automated vehicles (AVs) on public roads rises a variety of challenges for the traffic system, since it is not known to which extend AVs will impact traffic efficiency and traffic safety. Traffic flow simulation is often used to investigate the impact of AVs. In previous studies AVs were frequently modelled by adapting existing driver models, which were initially developed to model human driver behaviour. However, it is not known whether these models are capable of reflecting AV driving behaviour realistically. In addition, model adaptations are limited to the given parameter set provided by the simulation framework. Therefore, we developed new automated driving functions for multi-lane highway segments. Previous research showed, that lane change manoeuvres will be a challenging task for AVs. Lane changing also has a large impact on traffic flow. Hence, in course of this study, we present and examine the lane change model of the newly developed automated driving functions, focusing on gap acceptance of mandatory lane changes. A simulation experiment is conducted to verify the AV model functionalities and to analyse the effects on surrounding vehicles.


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    Titel :

    Lane Change Model for Automated Vehicles on Multi-Lane Highways in Mixed Traffic


    Beteiligte:


    Erscheinungsdatum :

    2023-09-24


    Format / Umfang :

    346591 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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