This paper presents a smart research platform to foster intelligent transportation systems in urban environments, called iCab (Intelligent Campus Automobile) autonomous vehicle. The aim of the paper is to describe the initial steps to achieve a functional autonomous vehicle. The platform is a golf cart vehicle, E-Z-GO model, which is modified to operate in autonomous mode. The software core is based on Robot Operating System (ROS) architecture, which allows the fusion of multiple sensors data and time stamp of different devices in one embedded computer on the board of the platform. The proposed system shows the advantages of ROS-based architecture data management, such as but they are not limited to, huge data handling from the surrounding environment, computer vision system perception and laser scanner data interpretation. The sensors data are integrated with the ROS- based architecture to develop cutting-edge applications, which cope with the autonomous navigation requirements and real-time data processing. The experimental study shows that the ROS-based architecture outperforms former works in autonomous vehicles, for its portability and feasibility to create a network of autonomous vehicles, that is, the autonomous interaction of more than one vehicle in closeness environments fostering the urban mobility.