Traffic incident management is combining the assets of authorities to identify, deal with, and
manage traffic problems as rapidly as possible while providing the safety of on-scene …

Due to the heterogeneous case-by-case nature of traffic incidents, plenty of relevant
information is recorded in free flow text fields instead of constrained value fields. As a result …

Problems such as traffic congestion and environmental sustainability are forcing us to review
our long-term plans for transport, whose aim should be to develop and improve safety …

This work aims to reorganise theoretical and empirical research on urban smart mobility
projects evaluation through the systematic literature review approach. The research goal is …

The rapid development of the internet of things (IoT), sensing technologies, and machine
learning and deep learning techniques, along with the growing variety and volume of data …

The Internet of Things (IoT) has inspired solutions that are already available for addressing
problems in various application scenarios, such as healthcare, security, emergency support …

In the paper it's proposed an algorithm for the management of traffic incidents, aimed at
minimizing the impact of incidents on the road traffic in general. The proposed algorithm is …

Due to modern powerful computing and the explosion in data availability and advanced
analytics, there should be opportunities to use a Big Data approach to proactively identify …

In this work, we focus accident causation for the railway industry by exploiting text analysis
approaches mainly Natural Language Processing (NLP). We review and analyse …

This project aimd at developing a decision support system (DSS) for Integrated Active Traffic
Management (IATM) for both freeways/expressways and arterials/collectors. In order to …