Heckelmann, Paul ; Rinderknecht, Stephan (2024)
Influence of an Automated Vehicle with Predictive Longitudinal Control on Mixed Urban Traffic Using SUMO.
In: World Electric Vehicle Journal, 15 (10)
doi: 10.3390/wevj15100448
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
In this paper, an approach to quantify the area of influence of an intelligent longitudinally controlled autonomous vehicle in an urban, mixed-traffic environment is proposed. The intelligent vehicle is executed with a predictive longitudinal control, which anticipates the future traffic scenario in order to reduce unnecessary acceleration. The shown investigations are conducted within a simulated traffic environment of the city center of Darmstadt, Germany, which is carried out in the traffic simulation software “Simulation of Urban Mobility” (SUMO). The longitudinal dynamics of the not automated vehicles are considered with the Extended Intelligent Driver Model, which is an approach to simulate real human driver behavior. The results show that, in addition to the energy saving caused by a predictive longitudinal control of the ego vehicle, this system can also reduce the consumption of surrounding traffic participants significantly. The area of influence can be quantified to four vehicles and up to 250 m behind.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2024 |
| Autor(en): | Heckelmann, Paul ; Rinderknecht, Stephan |
| Art des Eintrags: | Bibliographie |
| Titel: | Influence of an Automated Vehicle with Predictive Longitudinal Control on Mixed Urban Traffic Using SUMO |
| Sprache: | Englisch |
| Publikationsjahr: | 30 September 2024 |
| Ort: | Basel |
| Verlag: | MDPI |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | World Electric Vehicle Journal |
| Jahrgang/Volume einer Zeitschrift: | 15 |
| (Heft-)Nummer: | 10 |
| Kollation: | 11 Seiten |
| DOI: | 10.3390/wevj15100448 |
| URL / URN: | https://www.mdpi.com/2032-6653/15/10/448 |
| Kurzbeschreibung (Abstract): | In this paper, an approach to quantify the area of influence of an intelligent longitudinally controlled autonomous vehicle in an urban, mixed-traffic environment is proposed. The intelligent vehicle is executed with a predictive longitudinal control, which anticipates the future traffic scenario in order to reduce unnecessary acceleration. The shown investigations are conducted within a simulated traffic environment of the city center of Darmstadt, Germany, which is carried out in the traffic simulation software “Simulation of Urban Mobility” (SUMO). The longitudinal dynamics of the not automated vehicles are considered with the Extended Intelligent Driver Model, which is an approach to simulate real human driver behavior. The results show that, in addition to the energy saving caused by a predictive longitudinal control of the ego vehicle, this system can also reduce the consumption of surrounding traffic participants significantly. The area of influence can be quantified to four vehicles and up to 250 m behind. |
| Freie Schlagworte: | longitudinal control, V2X, realistic microscopic traffic simulation, urban traffic, electric vehicles, mixed traffic |
| Zusätzliche Informationen: | This article belongs to the Special Issue Vehicle Safe Motion in Mixed Vehicle Technologies Environment |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Mechatronische Systeme im Maschinenbau (IMS) |
| Hinterlegungsdatum: | 04 Okt 2024 08:51 |
| Letzte Änderung: | 04 Okt 2024 08:51 |
| PPN: | 52189400X |
| Export: | |
| Suche nach Titel in: | TUfind oder in Google |
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