Applications of deep learning in congestion detection, prediction and alleviation: A survey

Detecting, predicting, and alleviating traffic congestion are targeted at improving the level of service transportation network. With increasing access to larger datasets higher resolution, relevance deep learning for such tasks is increasing. Several comprehensive survey papers in recent years have summarised applications domain. However, system dynamics network vary greatly between non-congested state congested — thereby necessitating need a clear understanding challenges specific prediction. In this survey, we present current related detection, prediction, alleviation congestion. Recurring non-recurring discussed separately. Our leads us uncover inherent gaps research. Finally, some suggestions future research directions as answers identified challenges.