Berthing assistance systems (BASs) for berthing operations of autonomous surface vehicles (ASVs) in restricted waters are very important. Existing BASs are primarily designed for crewed vessels and cannot satisfy the intricate demands of ASV berthing tasks due to limited assistance. In this study, a novel ASV-centric BAS comprising the following four distinctive modules is presented: localization, navigable region acquisition, idle berth determination, and berthing status estimation. The localization module employs a simultaneous localization and mapping (SLAM) algorithm that fuses LiDAR and real-time kinematic (RTK) data to achieve precise ship positioning. The navigable region acquisition module involves segmenting point clouds based on horizontal emission angles and identifies the nearest points within each segment to establish the navigable region. The idle berth determination module employs a shoreline-constrained point cloud linear fitting algorithm, thereby extracting docking zones from nearest point clouds and acquiring idle berth information. The berthing status estimation module leverages the pre-established berth lines to compute essential berthing parameters, encompassing the berthing distance, approaching angle, berthing speed, and yaw rate. Experimental validation shows the high accuracy of the proposed BAS, which maintains a 0.438494 m root mean square error for localization, 0.482% relative error in the berthing distance, and 0.493% relative error in the approaching angle. Furthermore, both the navigable region acquisition and idle berth determination modules consistently provide accurate navigable region and idle berth information. Notably, comparative analysis against existing LiDAR-based solutions demonstrates significant performance improvements of 97.86% in the berthing distance accuracy and 98.12% in the approaching angle accuracy.