Optimized Path Finding Algorithm for Walking Convenience of the People with Reduced Mobility

Abstract

There has been growing social interest recently in the movement rights of people with reduced mobility. However, it simply eliminates the temporary inconvenience of walking of people with reduced mobility because it focuses only on supply of institutional facilities. Therefore, we look forward to improving movement welfare by proposing an optimized path finding algorithm for people with reduced mobility that takes into consideration physical elements affecting their movement, such as slope, steps etc. We selected Walking barrier factor by analyzing previous studies and calculated the relative importance of Walking barrier factors using an Analytic Hierarchy Process(AHP). Next, through the fuzzy system, the Walking disturbance level of link, which integrates the weights of Walking barrier factors and the attributes of each link, is derived. Then, Walking path cost that takes into consideration the 'length' factors is calculated and an optimized path for people with reduced mobility is searched using Dijkstra's Algorithm. Nineteen different paths were searched and we confirmed that the derived paths are meaningful in terms of improving the mobility of people with reduced mobility by conducting a field test. We look forward to improving movement welfare by providing a navigation service using the path finding algorithm proposed in this study. 2016. 04. 18, Revised 2016. 05. 31, Accepted 2016. 21 1) Dept. of Civil Environmental Engineering, Seoul National University (E-mail: coco0320@snu.ac.kr) 2) Dept. of Civil Environmental Engineering, Seoul National University (E-mail: daldanka@snu.ac.kr) 3) Member, Dept. of Civil Environmental Engineering, Seoul National University (E-mail: kiyun@snu.ac.kr) 4) Corresponding Author, Member, Institute of Construction and Environmental Engineering, Seoul National University (E-mail: soodaq@snu.ac.kr) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Light mode and dark mode: Which one is suitable when using public‐facing web maps? An experimental evaluation using eye‐tracking

“…The possible reasons are as follows: generally, low‐level tasks are easier to perform than high‐level, multistep tasks (Griffin et al, 2017). Space‐alone tasks are relatively simple; the participants need to confirm only the positions of the label, which is the most recognizable map feature using the human visual system because it is essentially natural language (Moon & Hwang, 2019). There is no need to identify the labeled symbols and their attributes when performing space‐alone tasks, unlike attributes‐in‐space tasks.…”

Urban services, pedestrian networks and behaviors to measure elderly accessibility

“…-physical characteristics that refer to the geometry and quality of the pedestrian paths, such as the slope and the state of the pavement; -characteristics of the pedestrian paths and of the surrounding context, such as to perceive support, protection and a sense of safety in walking to places and services, for example the density of lighting and presence of escalators; and -characteristics of the urban context that refer to the attractiveness of a pedestrian path, for example the presence of green areas or panoramic points. On the basis of the scientific literature, the most significant variables have been identified following multivariate statistical analysis (Moon et al, 2016;Wey & Chiu, 2013). In addition, other variables relevant to the research objectives have been introduced with respect to these studies.…”

Construction of a walkability quality dataset in GIS: the case study of Berlin

“…Some studies have pointed out that high levels of connectivity indicate that there are many options for a pedestrian to choose different routes to travel between two specific points in an urban area (Chan & Farber, 2020;Liu et al,2020). In contrast, Moon et al (2016) pointed out that sidewalk quality (e.g., the type of material used for a sidewalk) and the absence of steps are among the main factors that encourage walking (Gaglione et al,2021). The second aspect on which studies have focused on the perceived safety of the built environment and which can reduce the risk of pedestrians falling due to slippery conditions, the risk of conflicts between pedestrians and vehicles (Southworth, 2005).…”