Due to the rising popularity and interest in autonomous vehicles, it is beneficial to build a low-cost prototype autonomous vehicle for educational purposes. Thus, more students would be able to acquire hands-on experiences in designing and implementing critical smart navigational functionalities for autonomous vehicles. In this study, Proportional-Integral-Derivative (PID) control and steering control algorithms are developed to maneuver a 1/10-scale autonomous vehicle in a real-world scaled-down driving environment. An obstacle detection system is also designed. The state-of-the-art Robot Operating System (ROS) is employed in the software development and vehicle control to communicate between components. This paper, as part of a few related papers on autonomous vehicle from our research group, focuses on the control algorithms design and implementation, which incorporates continuous real-time feedback to generate a correction value to keep the vehicle on track. The algorithm combines the lane tracking, stop sign detection, and obstacle detection of the vehicle and sends data values to motors. Experimental results suggest the efficacy of our developed approaches. The future work of this study is discussed.