Hardware in the loop framework proposal for a semi-autonomous car architecture in a closed route environment

The development of intelligent vehicles has been increasing at great speed in recent years, which has allowed to improve their capabilities in autonomous driving systems. Many of these features are related to advanced driving assistance systems and autonomous driving systems. This capability improvement, has been achieved because of recent developments of automation oriented software and hardware. Such improvements, allowed the vehicle to achieve a more precise perception of it’s working environment. For this improvement it is important the integration and simulation of the systems in different configurations, such as hardware-in-the-loop, software-in-the-loop and model-in-the-loop. In this paper, we present a framework proposal that allows the design and testing of computer vision and control systems for the partial automation of a vehicle, with the use of hardware and software systems in the loop. This proposal is focused on the rapid experimental development of these systems for the implementation by autonomous vehicle designers and engineers. Our proposal allows faster data capture, either in a real or simulated environment, to improve and optimize data training with machine learning algorithms; this proposal integrates several open source systems and hardware with the necessary capacity for real-time implementation.