Risk Management in Transportation Systems: How Big Data Can Help Predict Behaviors and Events

In recent years, thanks to the widespread use of mobile phones and IoT devices, it has been possible to collect a large amount of data. Big data contains information on human behavior, the recurrence of environmental disasters and how urban traffic becomes congested when an emergency event occurs. In this article, the scientific literature on the usefulness of big data in predicting environmental disasters and human behaviors following emergency situations is analyzed, along with how these behaviors impact on road network congestion. Thanks to the ability to predict events and human behaviors provided by big data, it is possible to help users to have more orderly behaviors and to take those paths that are safe because they are not compromised or damaged by the cause of the emergency. A comprehensive bibliometric-based literature review was performed to summarize the scientific progress in the field of the use of machine learning models capable of predicting human behavior and disastrous events starting from big data. To perform this analysis, the authors have identified the main keywords capable of collecting scientific works that analyze the same topic, even if applied from different points of view. This paper aims to gather information on the current state of the art and technological advancements in the field of adaptive responses to large environmental disasters that threaten urban areas. Considering the significant technological advancements in scientific research, it will soon be possible to meticulously guide people during rescue operations and evacuations in catastrophic events. However, the ways in which information reaches users have not yet been thoroughly explored. Much work remains to be done on improving warning and communication methods.