This paper presents the validation of an integrated chassis controller that unites three groups of actuators for the electric vehicle (EV) with independent in-wheel electric motors (IWMs) for each wheel. Controlled actuators are the IWMs, the active suspension, and the braking system. The models of test benches and the designed architecture of the X-in-the-loop network are presented. The proposed design approach allows testing the developed controller on a vehicle model in real-time and on hardware components.
With the rapid development of automated driving systems, human drivers will soon have to share the road, and interact with, autonomous vehicles (AVs). To design AVs that can be safely introduced in our mixed traffic, research into human-AV interaction is needed. Driving simulators are invaluable tools, however, existing driving simulators are expensive, implementing new functionalities (e.g., AV control algorithms) can be difficult, and setting up new experiments can be tedious. To address these issues, we present JOAN, a framework for human-AV interaction experiments. JOAN connects to the open-source AV-simulation program Carla and enables quick and easy implementation of simple driving experiments. It supports experiments in VR, a variety of human input devices, and haptic feedback. JOAN is easy to use, flexible, and enables researchers to design, store, and perform human-factors experiments without writing a single line of code.
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