A Benchmark for Multi-Objective Routing in Vehicle Ad-Hoc Networks Using The Ant Colony Optimization Algorithm

The growing number of vehicles in cities has a great impact on our quality of life, such as air and noise pollution, traffic jams and traffic accidents. Cooperative Intelligent Transportation System (C-ITS) relies on communication technologies to provide innovative services and applications for transportation and traffic management. In the C-ITS context, users, roadside infrastructure and vehicles need to be connected and, for this purpose, a wide variety of wireless technologies can be used (e.g, vehicular WiFi, cellular and visible light communication). In this work we consider a VANET (Vehicular Ad-hoc NETwork) using vehicular WiFi (based on 802.11p). The communications in VANET networks have been studied for years and several routing algorithms have been developed for such a kind of network. However, a benchmark to compare the performance of such algorithms is still lacking. To fill this gap, the present work proposes a benchmark composed by instances of data routing for different scenarios in the VANET. Moreover, we propose a multi-objective algorithm based on ACO (Ant Colony Optimization) to compare with such benchmark. The results of simulations show the impact of several factors in the VANET connectivity, such as vehicle density, geographical location, propagation and fading models. The results are promising and indicate the importance of choosing appropriated simulation models.