This work presents a novel algorithm for the deployment of roadside units based on partial mobility information. Instead of relying on the individual vehicles trajectories, our proposal relies on the migration ratios between urban regions in order to infer the better locations for the deployment of the roadside units. Our goal is to identify those α locations maximizing the number of distinct vehicles experiencing at least one vehicle-to-infrastructure contact opportunity. We compare our strategy to two deployment algorithms: MCP-g relies on full mobility information (i.e., full knowledge of the individual vehicles trajectories), while MCP-kp does not assume any mobility information at all (simply places the roadside units at the densest locations of the road network). The results demonstrate that full knowledge of the vehicles trajectories is not mandatory for achieving a close-to-optimal deployment performance: by covering 1.0% of the Cologne's road network, our approach yields 89.8% of all vehicles experiencing at least one vehicle-to-infrastructure contact opportunity. If we assume previous knowledge of individual vehicles trajectories, we improve the coverage performance in just 2.3%. Complementary, our strategy provides a deployment layout very similar to the one obtained when considering the individual vehicles trajectories.
['Cristiano M. Silva', 'Joao F. M. Sarubbi', 'Wagner Meira']
Planning the communication infrastructure for vehicular networks without tracking vehicles