Are you a robot? Detecting Autonomous Vehicles from Behavior Analysis

As car manufactures keep developing autonomous driving systems to improve the safety and comfort of passengers, traffic authorities need to establish new procedures to manage the transition from human-driven to fully autonomous vehicles. Thus, a way to automatically profile autonomous vehicles and differentiate those from human-driven ones is a 'must'.In this work, we present a fully-fledged framework that monitors active vehicles using camera images and state information in order to determine whether vehicles are autonomous, without requiring any active notification from the vehicles themselves. Essentially, it builds on the cooperation among vehicles, which share their data acquired on the road feeding a machine learning model to identify autonomous cars. We extensively tested our solution and created the NexusStreet dataset, by means of the CARLA simulator, employing an autonomous driving control agent and a steering wheel maneuvered by licensed drivers.Our results show that it is possible to discriminate the behaviors of human and autonomous drivers by analyzing video images with an accuracy of ∼ 80%, which improves up to ∼93% when the target’s state information is available.