This letter presents an integrated navigation and control strategy for an autonomous surface vehicle (ASV) to operate in narrow waterways without relying on GPS. The proposed method uses a camera and a light detection and ranging (LiDAR) sensor to detect navigable regions in the waterway. A deep learning-based semantic segmentation algorithm is applied to detect the navigable region in camera images, and the segmented region is projected onto the water surface using planar homography. A line-detection algorithm is also introduced to improve the reliability of detecting navigable regions from LiDAR measurements. A safe collision-free path for the ASV is generated within the navigable regions using model predictive control-based local path planning and control algorithms. The performance and practical utility of the proposed method were demonstrated through field experiments using a small cruise boat, modified as an autonomous surface vehicle.