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Author/Affiliation: Mohammed ElhenawyOpen AccessArticle
9 Pages, 1,946 KB 
Spatiotemporal Traffic State Prediction Based on Discriminatively Pre-trained Deep Neural Networks
Abstract:
The availability of traffic data and computational advances now make it possible to build data-driven models that capture the evolution of the state of traffic along modeled stretches of road. These models are used for short-time prediction so that transportation facilities can be operated in an efficient way that guarantees a high level of service.…
Read More(This article belongs to the Special issue on Recent Advances in Engineering Systems 2017 & Section Artificial Intelligence in Computer Science (CAI))