Heckelmann, Paul (TU Darmstadt), Breuer, Sandro Chris (Technical University of Darmstadt), Rinderknecht, Stephan (Technische Universität Darmstadt)

Simulative Investigation of Consumption-Optimized Intersection Control for Autonomous Vehicles

Scheduled for presentation during the Regular Session "S40a-Cooperative and Connected Autonomous Systems" (FR-LM-T40), Friday, November 21, 2025, 10:30−10:50, Cooleangata 4

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 18, 2025

Abstract

Autonomous transportation systems are increasingly being implemented in urban areas. However, the potential for energy savings through optimized longitudinal dynamic control of cooperatively operating connected vehicles in urban areas remains largely untapped. In this paper, an approach to control connected autonomous vehicles in an urban environment is presented. Therefore, useful situations in urban traffic are identified and based on these scenarios, a speed control approach is applied for vehicles passing through this situation. This approach optimizes trajectories and arranges the order of the vehicles to achieve the most efficient solution for the traffic situation. This system is tested within a simulative traffic environment using SUMO. To investigate the energy consumption, a simulation of the drivetrain of an existing autonomous vehicle is modeled and validated based on driving tests. With the validated drivetrain, a comparison of speed and energy consumption for non-autonomous vehicles and autonomous vehicles equipped with the shown approach is executed. For the traffic situations in this paper, an energy saving of up to 46 % with a mean speed reduction of not more than 12.3 % is observed.