TOWARDS PEDESTRIAN ACCESSIBILITY ANALYSIS IN INDOOR ENVIRONMENTS WITH CROWDS

Abstract

Abstract. Except in emergency cases, indoor crowds could also decrease the walking speed of pedestrians in daily life. To investigate daily-based accessibility of locations to a pedestrian in the presence of crowds, this paper proposes a method of indoor accessibility analysis. We adopt a hierarchical spatial model to represent indoor environments and evaluate the varied accessibility to a user. The first level refers to a door network representing door connectivity. On the second level, spaces are gridified so that crowd density can be readily measured, and its obstruction to pedestrians can be quantified at different time slots. Instead of generating specific obstacle-avoidance paths in a short period, we depict accessibility variation with two types of paths, i.e., central and periphery paths inside rooms. Based on the hierarchical model, pathways are pre-computed between doors for a user and indexed in the grid model. In a path query, a sequence of doors is derived from the door network, and the pre-computed pathways are readily retrieved to form the two types of paths. Accordingly, walking time can be estimated with crowd density in these grids at each time slot. We conducted an initial test on a building floor to demonstrate the use of the proposed method. We sampled the locations of simulated crowds (50 persons) every 10 seconds, and the time cost between given doors in both paths are compared. A slowdown occurred in the central path, and the periphery path involves the minimum time in the test scenario. In the future, the relationship between crowd density and the possibility of blockage to pedestrians will be further investigated.