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Recent years have witnessed increasing interest in Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) development, motivating the growth of new sensor technologies and control platforms. However, to keep pace with this acceleration and to evaluate system performance, a cost and time effective software development and testing framework is required. This paper presents an overview utilizing Robotic Operating System (ROS) middleware and MATLAB/Simulink® Robotics System Toolbox to achieve these goals. As an example of employing this framework for autonomous development and testing, this article utilizes the FEV Smart Vehicle Demonstrator. The demonstrator is a reconfigurable and modular platform highlighting the power and flexibility of using ROS and MATLAB/Simulink® for AD rapid prototyping. High-level autonomous path following and braking are presented as two case studies.

This paper presents a cost effective development platform, named FEV-Driver, for Advanced Driver Assistance Systems (ADAS) and autonomous driving (AD). The FEV-Driver platform is an electric go-kart that was converted into an x-by-wire vehicle which represents the behavior of a full-scale electric vehicle. FEV-Driver has the advantage of being a small-scale vehicle that can be used with a significant lower safety risk compared to full-sized vehicles. The ADAS/AD algorithms for this platform were developed in both Simulink and C++ software and implemented within the Robot Operating System (ROS) middleware. Besides the description of the platform, Lane Keep Assist (LKA) and Automatic Emergency Braking (AEB) algorithms are discussed, followed by a path planning algorithm which enables the vehicle to drive autonomously after a manually controlled training lap. The modular system architecture allows for complete controller exchange or adaptation to different vehicles.