Considering Time-Critical Barriers in Indoor Routing for People with Disabilities

Schmalfuß-Schwarz, Jan; Loitsch, Claudia; Weber, Gerhard

doi:10.1007/978-3-030-58805-2_37

Cited by 3 publications

(3 citation statements)

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“…For normal circumstances, a study defined time-critical barriers (Schmalfuß-Schwarz et al, 2020) for motion-impaired people, including varied crowds, temporarily unavailable elevators, and scheduled maintenance work. Thus, continuous collection of indoor mobility data is important to accessibility evaluation for pedestrians.…”

Section: Related Workmentioning

confidence: 99%

“…Some indoor obstacles are usually not included in a building dataset because they are temporary and with no fixed location. Relevant studies started to depict and model dynamic barriers for indoor pathfinding (Schmalfuß-Schwarz et al, 2020, Liu et al, 2021b. A crowd-aware pathfinding algorithm has been proposed to approach accurate crowd-avoiding paths (Liu et al, 2021b).…”

Section: Related Workmentioning

confidence: 99%

“…Researchers have proposed grid-based models for indoor emergency evacuation and considered spaces, * Corresponding author sensors, fire extension and human behaviours (Xiong et al, 2017, Gorte et al, 2019a, Gorte et al, 2019b, Aleksandrov et al, 2021, Xie et al, 2022. Recent studies started to depict and model dynamic barriers for indoor pathfinding (Schmalfuß-Schwarz et al, 2020, Liu et al, 2021b. They basically focus on dynamic path planning in the presence of obstacles.…”

Section: Introductionmentioning

confidence: 99%

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Towards Pedestrian Accessibility Analysis in Indoor Environments With Crowds

Liu,

Zlatanova

2023

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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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.

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Section: Related Workmentioning

confidence: 99%