TY  - CONF
T1  - Evaluation of Traffic Controller Performance via Systematic Exploration
A1  - Kušić, Krešimir
A1  - Calvaresi, Davide
A1  - Liffey, Amy
A1  - Fanda, Lora
A1  - Gregurić, Martin
A1  - Ivanjko, Edouard
A1  - Schumann, René
TI  - Post-proceedings of the 66th International Symposium ELMAR-2024
Y1  - 2024
SP  - 165
EP  - 168
PB  - IEEE
CY  - Zadar, Croatia
SN  - 979-8-3503-7542-8
SN  - 2835-3781
UR  - https://ieeexplore.ieee.org/document/10694499
M2  - doi: 10.1109/ELMAR62909.2024.10694499
KW  - Function approximation
KW  - Microscopic traffic simulation
KW  - Structured simulations
KW  - Traffic control
N2  - Traffic controllers must operate reliably across diverse traffic states. Due to the stochastic non-linear characteristics of traffic flow, commonly used feedback-based controllers require parameter tuning for each specific traffic regime, which is
done offline using simulations. Generating representative traffic scenarios for large-scale simulations is often computationally
expensive. To reduce the computational burden, this paper proposes a systematic exploration of the Structured Simulation
Framework (SSF). This approach aims to approximate controller performance with a minimal number of simulations, by adjusting the parameter space continuously to regions where controller performances are weakly approximated. This process continues until controller performance is well approximated across the entire input domain. Results show SSF convergence of performance estimate of the controller while reducing the number of required simulations. This helps identify traffic scenarios where the controller performs poorly, and, thus, can be used as a framework towards guided controller tuning.
ER  -