When studying the road safety of a region, the primary metric used is often the number of fatalities or the mortality rate, however, this presents only a very limited perspective of the road safety for that given region. Road collisions that do not lead to a fatality or a serious injury, often cause damage to people’s physical and/or mental well-being, while also causing considerable disruption to the wider road network. Considering the widely accepted “road accident” definition, studying accident data itself is not enough to have an accurate understanding of the road safety of that given area. This is where near-miss data plays a critical role. Near-miss analysis detects incidents that are not reported as “accidents” as they don’t cause an actual collision. However, this analysis gives a unique understanding of the level of road safety as it proactively measures the risk levels for road users. When users proactively measure risk, they can proactively bring forward risk mitigation countermeasures. The goal of this technology is to predict and prevent fatalities and injuries. Acknowledging the potential of combining different data in decision-making, a prototype is developed to integrate near-miss data into an urban mobility management platform. This prototype has been developed with the collaboration between MicroTraffic and SWARCOaiming to provide a unique source of risk management data for smart cities’ vision zero programs. The near-miss measurement technology used in this project uses video analytics to measure the kinetic energy risks involved in a traffic conflict in such a way that future injury crashes can be predicted with 94% accuracy using only a short video observation period Implementing the integration of near-miss analysis to the central mobility management platform is made possible due to the modular structure of the platform. This modularity also enables further potential developments around this integration to explore additional use cases in parallel to technological advancements and changing mobility needs. In this paper, the idea behind this prototype, the solution architecture as well as its potential use cases are discussed along with the aim of triggering further discussions around unlocking the potential of combining different data for holistic mobility management. In the “Solution high-level architecture” section the developed prototype is explained together with relevant information on the mobility management platform “MyCity” and the near-miss algorithm developed by MicroTraffic. In addition to the high level solution architecture, the Future Evolutions section discusses potential use cases to be explored.

Ms. Itir Coskun, Innovation Engineer, SWARCO