On the deployment of V2X roadside units for traffic prediction

In this paper, we evaluate the ability of connected roadside infrastructure to provide traffic predictions on highways based on the motion of connected vehicles. In particular, we establish metrics to quantify the amount of traffic prediction that is available from roadside units via vehicle-to-infrastructure (V2I) communication. We utilize analytical and numerical tools to evaluate these metrics as a function of (i) the location of the roadside units along the road, (ii) the communication range of the roadside units, and (iii) the penetration rate of connected vehicles on the road. We show that considerable amount of traffic predictions can be achieved even with sparsely distributed roadside units as distant as two thousand meters and with connected vehicle penetration rate as low as 2%. Based on the proposed metrics, we develop strategies for deploying roadside units along highways so that traffic prediction efficiency is maximized. Ultimately, the results of this paper may serve as a guideline for evaluation and deployment of connected roadside infrastructure