Forecasting C-ITS Deployments: a discrete choice modelling approach

Aiming to overcome challenges associated with urban mobility, cities adopt different strategies to attain safer and more efficient traffic, among other objectives. An example of such endeavours involves the deployment of Cooperative Intelligent Transport Systems (C-ITS). However, cities face strong uncertainty regarding different deployment-related aspects, such as the choice of technology and the ideal sequence of services and use cases. This paper, based on data collected by the C-Roads initiative (EU-funded project), proposes a discrete choice modelling approach to predict the ideal implementation period for a specific C-ITS use case. The model aims to assist city authorities in deciding when to implement it, thereby reducing uncertainties in C-ITS deployment. Using data from 22 European cities, the study considers key features that may influence the use case deployment periods, including infrastructure dimension, network design, public and private participation, funding sources, and policy goals. Significant associations between the implementation periods and critical characteristics were revealed, such as public-private participation in the deployment stages, the presence of national funding, and environmental concerns being an essential policy goal. Despite limitations arising from data constraints, the model contributes to the decision-making process for a specific use case.