SENSYNC: Instrumentalização de Plataforma Veicular para Testes de Sincronização Multissensor e Geração de Datasets - Coelho, Alexsandro Ferreira; Silva-Filho, Abel G.; Costa, Alef Gabryel Lorenco da; Barbosa, Lucas Alves (Anais do Workshop Latinoamericano de Dependabilidade e Segurança em Sistemas Veiculares (SSV); 2025: Anais do II Workshop Latinoamericano de Dependabilidade e Segurança em Sistemas VeicularesDO - 10.5753/ssv.2025.39494, 2025)
Multimodal perception systems used in autonomous vehicles rely on precise temporal synchronization between sensors such as cameras, radars, and LiDAR. Small misalignments of only a few milliseconds can compromise perception and decision-making in dynamic scenarios. This work presents the SENSYNC architecture, an entirely software-based solution built on ROS 2 for acquiring and synchronizing sensors in a Jeep Renegade equipped with three cameras, three FMCW radars, and a VLP-16 LiDAR. The platform is evaluated under real urban traffic conditions, quantifying temporal offsets between sensors and the robustness of multimodal recording. The results show average offsets close to 1 ms for radar/camera pairs and typically below 25 ms for radar/LiDAR pairs, values suitable for multimodal fusion in urban environments. Approximately 12 GB of multimodal data were collected, with an average recording rate of 29 MB/s (1.74 GB/min). These results confirm the feasibility of achieving fully software-based synchronization in real vehicles.