An IoT Architecture for Assessing Road Safety in Smart Cities

Abstract EN

The Safe System (SS) approach to road safety emphasizes safety-by-design through ensuring safe vehicles, road networks, and road users.

With a strong motivation from the World Health Organization (WHO), this approach is increasingly adopted worldwide.

Considerations in SS, however, are made for the medium-to-long term.

Our interest in this work is to complement the approach with a short-to-medium term dynamic assessment of road safety.

Toward this end, we introduce a novel, cost-effective Internet of Things (IoT) architecture that facilitates the realization of a robust and dynamic computational core in assessing the safety of a road network and its elements.

In doing so, we introduce a new, meaningful, and scalable metric for assessing road safety.

We also showcase the use of machine learning in the design of the metric computation core through a novel application of Hidden Markov Models (HMMs).

Finally, the impact of the proposed architecture is demonstrated through an application to safety-based route planning.