Assessing energy consumption in scalable semi-autonomous destination-based E-platoons: A multiplayer approach

Recent developments in connected and automated vehicle technologies have opened up new possibilities but also posed enduring challenges. One of the primary challenges is the efficient coordination of vehicles in urban environments, specifically through scalable and destination-based platooning. While considerable research has focused on platooning with a limited number of vehicles demonstrating seamless connectivity and coordination on highways, there remains a significant gap in understanding and implementing scalable platoons in more dynamic urban settings. This paper bridges these gaps by developing a novel extension to the 3DCoAutosim simulation platform. Our model introduces ’Scalable Semi-autonomous Destination-based Multiplayer E-Platoons’, accommodating different automation levels and simulation characteristics of vehicles in five distinct platoons. We employed seven electric vehicles to create these platoons, each consisting of an autonomous lead vehicle, followers that are either autonomous or semi-autonomous (accompanied by drivers), customised according to the specific requirements of each platoon. Utilising Time Series Analysis, Multiple Linear Regression and a comprehensive, comparative scenario-based analysis, we assessed and validated our developed model’s impact on battery energy consumption under varying road slopes and car-following models. Our assessment employs real-world trip data from Upper Austria, with results indicating a potential reduction in total battery energy consumption when operating in platoon mode.

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Publication Details

Journal
Transportation Research Part D Transport and Environment
Published
2024-10-24
DOI
https://doi.org/10.1016/j.trd.2024.104464
Citations
3
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
0.98

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article

Assessing energy consumption in scalable semi-autonomous destination-based E-platoons: A multiplayer approach

Cristina Olaverri-Monreal, Aso Validi
3 citations
Transportation Research Part D Transport and Environment
Traffic control and management
0.98
article

Assessing energy consumption in scalable semi-autonomous destination-based E-platoons: A multiplayer approach

Cristina Olaverri-Monreal, Aso Validi
article en
3 citations

Abstract

Recent developments in connected and automated vehicle technologies have opened up new possibilities but also posed enduring challenges. One of the primary challenges is the efficient coordination of vehicles in urban environments, specifically through scalable and destination-based platooning. While considerable research has focused on platooning with a limited number of vehicles demonstrating seamless connectivity and coordination on highways, there remains a significant gap in understanding and implementing scalable platoons in more dynamic urban settings. This paper bridges these gaps by developing a novel extension to the 3DCoAutosim simulation platform. Our model introduces ’Scalable Semi-autonomous Destination-based Multiplayer E-Platoons’, accommodating different automation levels and simulation characteristics of vehicles in five distinct platoons. We employed seven electric vehicles to create these platoons, each consisting of an autonomous lead vehicle, followers that are either autonomous or semi-autonomous (accompanied by drivers), customised according to the specific requirements of each platoon. Utilising Time Series Analysis, Multiple Linear Regression and a comprehensive, comparative scenario-based analysis, we assessed and validated our developed model’s impact on battery energy consumption under varying road slopes and car-following models. Our assessment employs real-world trip data from Upper Austria, with results indicating a potential reduction in total battery energy consumption when operating in platoon mode.

Transportation Research Part D Transport and EnvironmentVol. 136
Johannes Kepler University of Linz (AT)
Chinese Academy of Sciences, Österreichische Forschungsförderungsgesellschaft
Affordable and clean energy
Openalex Percentile: Top 23%
Traffic control and management
0.98
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