MTDT: A Multi-Task Deep Learning Digital Twin

arXiv:2405.00922v1 Announce Type: new
Abstract: Traffic congestion has significant impacts on both the economy and the environment. Measures of Effectiveness (MOEs) have long been the standard for evaluating the level of service and operational efficiency of traffic intersections. However, the scarcity of traditional high-resolution loop detector data (ATSPM) presents challenges in accurately measuring MOEs or capturing the intricate temporospatial characteristics inherent in urban intersection traffic. In response to this challenge, we have introduced the Multi-Task Deep Learning Digital Twin (MTDT) …

abstract arxiv challenges congestion cs.lg data deep learning digital digital twin economy efficiency environment however impacts loop measuring resolution service standard the environment traffic traffic congestion twin type