Harmann, Dennis (TU Braunschweig), Teuber, Karolin (TU Braunschweig), Bienzeisler, Lasse (TU Braunschweig, University), Friedrich, Bernhard (Technische Universität Braunschweig)

Calibrating a Car-Following Model for Autonomous Line Buses in Microscopic Traffic Simulations

Scheduled for presentation during the Regular Session "S05b-Deployment, Modeling, and Optimization in Intelligent Transportation Systems" (WE-EA-T5), Wednesday, November 19, 2025, 13:30−13:50, Surfers Paradise 2

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 19, 2025

Abstract

Simulation models are essential for assessing the impacts of autonomous vehicles (AVs) on the overall transportation system. To enhance the quality of simulation outputs, it is crucial to accurately represent AV behavior within these environments. Microscopic traffic flow simulations offer the capability to fine-tune vehicle parameters, with the chosen car-following model (CFM) dictating the longitudinal behavior of the vehicle. Existing literature has primarily concentrated on calibrating CFMs for passenger cars; however, the integration of AVs into public transit (PT) systems is a key objective for this technology, making the introduction of autonomous standard line buses particularly significant. Currently, simulating heavy AVs lacks realism due to the absence of an appropriate CFM. In this study, we address this gap by calibrating a CFM for the simulation software SUMO. Using real-world driving data from a Level 4 (L4) autonomous bus operation in a city in Finland, we adapted the parameters of the Intelligent Driver Model (IDM) by applying an optimization approach based on a genetic algorithm. The calibrated IDM variants for autonomous standard line buses show a good fit to real-world data and can therefore serve as a reliable foundation for future research in the field of autonomous PT operations.