Poster: Multi-Layer Digital Transportation Twin

Digital twin is a promising technology to replicate the real-world transportation system in real time, towards safer autonomous driving and more intelligent infrastructure management. In this poster, we propose a new digital transportation twin (mDTN) to integrate multiple layers of transportation systems, including vehicle dynamics, traffic flow, and road environment. Specifically, we build the co-simulation platform by connecting state-of-the-art simulators (i.e., TruckSim, CARLA, and SUMO) and generate multi-layer datasets for advancing autonomous driving research.