DEFINING THE FUNCTIONAL SPACE OF BUS STOPS FROM MLS POINT CLOUDS
Keywords: Mobile Mapping Systems, LiDAR, Object Classification, 3D Modelling, Space Delimitation, Urban Mobility
Abstract. Urban transports are essential for the mobility of citizens, therefore, functional spaces allocated to them should be correctly defined. This research defines the functional spaces for bus stops based on Mobile Laser Scanning (MLS) point clouds. Specifically, three functional spaces are defined; functional space allocated for the marquee (pedestrian space), functional space allocated for the road markings (bus space), and functional space allocated for the bus stop (pedestrians and bus). The method presented is divided into four stages; 1) Bus stop location in the point cloud from given geographical coordinates, 2) Selection of the region of interest (ROI), 3) Classification of the elements in the ROI, 4) Functional space definition. Several algorithms are used to reduce the computational time (point density reduction) and to classify the different elements contained in the bus stop (DBSCAN, height, width, and intensity filter). In addition, bounding boxes are defined to delimit the functional spaces, being compared with the ground truth box. Seven bus stops sited in Palencia (Spain) were analysed. Results show an F1-score value of 0.98 regarding the classification of the elements. Functional spaces allocated for marquees were perfectly defined. Although most of the estimated functional spaces allocated for the bus and the bus stop have high accuracy, in some cases this accuracy decreases due to the functional space allocated for the bus was overestimated.