Simulation Framework for Platooning based on Gazebo and SUMO

The role of autonomous cooperative vehicles will undoubtedly be important in Intelligent Transportation Systems (ITS) to increase both the safety and the overall efficiency of a high traffic network system. An autonomous platooning provides one promising strategy for decreasing total fuel consumption of a fleet of vehicles and potential risk of accidents, especially during long-distance transportation. In this work, we provide a proof-of-concept for a simulation framework in which it is possible to simulate platoon and other multi-vehicle systems using realistic vehicle models within different traffic scenarios, which is based on ROS, Gazebo and SUMO. The framework enables an easy-to-use perception and control modules of the autonomous driving stack for a realistic vehicle models, while preserving a convenient setup of different high traffic platooning scenarios. Consequently, it provides a platooning design step for conducting reliable development analyses and a platform for comparisons of different platooning strategies. We illustrate the effectiveness of the proposed platooning framework through three typical scenarios using a distributed model predictive control scheme with a platoon consisted of Toyota Prius car models.