Title: MATSim research on urban traffic simulation and optimisation strategy in collaboration with SUMO

Authors: Jian Ma; Qianlong Fu; Liyan Zhang; Hairong Gu; Yuchen Zhang

Addresses: School of Civil Engineering, Suzhou University of Science and Technology, Suzhou, 215011, China ' School of Civil Engineering, Suzhou University of Science and Technology, Suzhou, 215011, China ' School of Civil Engineering, Suzhou University of Science and Technology, Suzhou, 215011, China ' School of Civil Engineering, Suzhou University of Science and Technology, Suzhou, 215011, China ' School of Civil Engineering, Suzhou University of Science and Technology, Suzhou, 215011, China

Abstract: This paper presents mesoscopic and microscopic traffic simulations to address urban congestion challenges in a context of rapid urbanisation. A co-simulation platform was developed by combining the multi-agent transport simulation (MATSim) agent-based modelling with the simulation of urban mobility (SUMO). The methodology incorporates deep Q-networks (DQN) for adaptive traffic signal control, and genetic algorithms for an optimal route planning, and the co-simulation approach can reduce bus waiting times by 29.10% and increased intersection throughput by 8.14% through a Memory Palace-enhanced DQN model for adaptive signal control. The genetic algorithms optimised route planning for 50,000 simulated residents. The utility-discrete choice framework improved travel demand realism by translating utility scores into probabilistic selections. Multi-stage optimisation balanced system efficiency with individual preferences, proving 25% faster convergence than baseline DQN. This computationally efficient platform bridges macroscopic policy analysis with microscopic behavioural modelling, offering robust decision support for urban traffic management.

Keywords: traffic simulation; MATSim; multi-agent transport simulation; SUMO; simulation of urban mobility; joint simulation; congestion relief.

DOI: 10.1504/IJVSMT.2026.155796

International Journal of Vehicle Systems Modelling and Testing, 2026 Vol.20 No.3, pp.291 - 322

Received: 16 Jun 2025
Accepted: 02 Sep 2025
Published online: 14 Aug 2026 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article