Please use this identifier to cite or link to this item: https://doi.org/10.48441/4427.3248
Publisher DOI: 10.52825/scp.v2i.91
Title: Simulation based method for the analysis of energy-efficient driving algorithms using SUMO
Language: English
Authors: Buhk, Benedikt 
Rettig, Rasmus 
Editor: Alvarez López, Pablo 
Banse Bueno, Olaf Angelo 
Armellini, Maria Giuliana 
Behrisch, Michael 
Bieker-Walz, Laura 
Erdmann, Jakob 
Flötteröd, Yun-Pang 
Hilbrich, Robert 
Nippold, Ronald 
Rummel, Johannes 
Schwamborn, Matthias 
Wagner, Peter 
Weber, Melanie 
Other : Deutsches Zentrum für Luft- und Raumfahrt 
Issue Date: 12-Feb-2026
Publisher: TIB Open Publishing
Book title: SUMO User Conference, 13-15 September 2021, virtual event
Part of Series: SUMO conference proceedings 
Volume number: 2
Startpage: 149
Endpage: 167
Project: IMOS Urban Mobility Lab 
Conference: SUMO User Conference 2021 
Abstract: 
The limited possibilities to evaluate the energy eciency of driving algorithms forconnected and autonomous vehicles (CAVs) make it very dicult for policymakers to decideon the potential of autonomous driving. This study is introducing a method to analyze theenergy performance of a driving algorithm under various simulated trac conditions usingthe microscopic trac simulator SUMO. The method can also be used to optimize drivingalgorithm parameters for chosen trac scenarios. Therefore, a tool-chain is developedthat can simulate a CAV under many trac scenarios in SUMO systematically. In thosescenarios, one or more vehicles are controlled by the implemented driving algorithm. Theresulting driving cycles are then analyzed by a forward-facing energy model to calculate theconsumed energy. To validate the model, three measurement cycles under real urban tracconditions were taken and the speed and state of charge (SOC) data of the test vehicle, a2017 Tesla Model S 75D, were collected. The energy model was shown to be highly accurateand the simulated road network and trac, which were chosen to represent the same urbantrac scenario as the measured cycles, were shown to result in similar statistics as themeasurements. A simple driving algorithm that is already implemented in SUMO’s Krauscar-following model was chosen to verify the model’s applicability. For di↵erent values ofthe algorithm parameters acceleration and deceleration, a range of random driving cycleswas simulated. In the simulations and the measurements, the e↵ect of higher and loweruse of auxiliary systems was also analyzed. The results show that the analyzed drivingalgorithm achieves similar results for the energy consumption as the human driver in themeasurements with the best performing parameters. Also, the significance of auxiliarysystem use on the energy consumption and its e↵ect on a driving algorithm’s parameterto remain energy ecient due to the higher impact of the trip duration is pointed out.
URI: https://hdl.handle.net/20.500.12738/18921
DOI: 10.48441/4427.3248
ISSN: 2750-4425
Review status: This version was peer reviewed (peer review)
Institute: Fakultät für Elektro-, Medien- und Informationstechnik 
Type: Chapter/Article (Proceedings)
Additional note: Buhk, B., & Rettig, R. (2026). Simulation based method for the analysis of energy-efficient driving algorithms using SUMO. SUMO Conference Proceedings, 2, 149–167. https://doi.org/10.52825/scp.v2i.91
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