Pre-study and insights to a sequential MATSim-SUMO tool-coupling to deduce 24h driving profiles for SAEVs




New mobility concepts such as shared, autonomous, electric vehicle (SAEV) fleets raise questions to the vehicles’ technical design. Compared to privately owned human driven cars, SAEVs are expected to exhibit different load profiles that entail the need for newly dimensioned powertrain and battery components. Since vehicle architecture is very sensitive to operating characteristics, detailed SAEV driving cycles are crucial for requirement engineering. As real world measurements reach their limit with new mobility concepts, this contribution seeks to evaluate three different traffic simulation approaches in their ability to model detailed SAEV driving profiles. (i) The mesoscopic traffic simulation framework MATSim is analyzed as it is predestined for large-scale fleet simulation and allows the tracking of individual vehicles. (ii) To improve driving dynamics, MATSim’s simplified velocity profiles are enhanced with real-world driving cycles. (iii) A sequential tool-coupling of MATSim with the microscopic traffic simulation tool SUMO is pursued. All three approaches are compared and evaluated by means of a comprehensive test case study. The simulation results are compared in terms of driving dynamics and energy related key performance indicators (KPI) and then benchmarked against real driving cycles. The sequential tool-coupling approach shows the greatest potential to generate reliable SAEV driving profiles.


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How to Cite

Triebke, H., Kromer, M., & Vortisch, P. (2022). Pre-study and insights to a sequential MATSim-SUMO tool-coupling to deduce 24h driving profiles for SAEVs. SUMO Conference Proceedings, 1, 93–112.

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