Comparative Performance Evaluation of Multi-Type LiDAR Sensors and Their Applicability to Sidewalk HD Mapping

Sidewalk high-definition (HD) maps require centimetre-level representation of pedestrian barriers to support mobility assistance and barrier-free infrastructure management. This study evaluates six mobile light detection and ranging (LiDAR) platforms for sidewalk HD mapping: terrestrial laser scanning (TLS), a push-cart mobile mapping system (MMS), two backpack systems (GNSS/INS (Global Navigation Satellite System/Inertial Navigation System)-aided and SLAM (simultaneous localization and mapping)-based), and two handheld systems (GNSS/INS-aided and SLAM-based). Surveys were conducted at two sites with contrasting occlusion and GNSS conditions (park and dense downtown corridors). Point clouds were transformed to a common control network, with independent checkpoints for absolute accuracy. The reference dataset achieved a planimetric root mean square error (RMSE) of 0.017-0.049 m and vertical RMSE of 0.009-0.014 m across sites. Platforms were compared for positional accuracy, point density, and extractability of key accessibility attributes (effective width, step height, and longitudinal slope). Cart-mounted MMS provided stable geometry under occlusion, while SLAM-based handheld mapping improved robustness in GNSS-degraded areas; backpack SLAM performance depended on loop-closure opportunities and scene dynamics. We provide guidance on selecting pedestrian-scale LiDAR platforms for sidewalk HD mapping under different survey conditions.