[논문]교통약자를 위한 전동 이동 보조기기 안전 경로 서비스의 개발과 평가

우제승; 홍순기; 유상경; 김회경

doi:10.11108/kagis.2023.26.3.085

[국내논문] 교통약자를 위한 전동 이동 보조기기 안전 경로 서비스의 개발과 평가
Development and Evaluation of Safe Route Service of Electric Personal Assistive Mobility Devices for the Mobility Impaired People 원문보기

한국지리정보학회지 = Journal of the Korean Association of Geographic Information Studies, v.26 no.3, 2023년, pp.85 - 96

우제승 ((주)경성테크놀러지) , 홍순기 ((주)경성테크놀러지) , 유상경 ((주)경성테크놀러지) , 김회경 (동아대학교 도시공학과)

초록
AI-Helper

본 연구는 최근 이동권 개선을 위해 교통약자들을 중심으로 이용되고 있는 전동 이동 보조기기의 안전 경로를 제공하는 서비스를 개발하고 평가하였다. 부산광역시에 거주하는 교통약자들과 관련 기관 종사자(부산광역시 내 장애인 자립 생활센터, 장애인 협회 정회원, 전동 이동 보조기기 수리기사, 활동 보조사)들과의 설문을 통해 전동 이동 보조기기의 이동에 영향을 미치는 13종의 요인을 도출하였다. 각각의 요인들에 안전성 점수를 부여하고 현장에서 수집된 데이터로 객체 인식 AI 모델을 학습시켜 해당 요인들을 판별한 후, 최적경로 탐색 알고리즘을 통해 전동 이동 보조기기 경로 안내 서비스를 개발하였다. 동일한 출도착 경로를 대상으로 T-map에서 제공하는 일반 경로와 본 연구의 추천 경로를 비교한 결과, 일반 경로에서는 전동 이동 보조기기의 주행에 방해가 되거나 승차감을 불편하게 하는 장애물이 많았고 가파른 경사로 인해 이동이 불편했지만, 본 연구의 추천 경로에서는 상대적으로 장애물이 적었고 경사도 완만하여 전동 이동 보조기기의 주행에 무리가 없었다. 향후 연구에서는 전동 이동 보조기기 이용자의 실시간 위치를 기반으로 경로 안내 서비스를 구현하고 다수의 이용자를 대상으로 현장 실증테스트를 진행하여 사회적 수용성 평가 및 검증을 수행할 필요가 있다.

Abstract ▼ AI-Helper

This study developed and evaluated a safe route guidance service for electric personal assistive mobility device used mainly by the mobility impaired people to improve their mobility. Thirteen underlying factors affecting the mobility of electric personal assistive mobility device have been derived through a survey with the mobility impaired people and employees in related organizations in Busan Metropolitan City. After assigning safety scores to individual factors and identifying the relevant factors along routes of interest with an object detection AI model, the safe route for electric personal assistive mobility device was provided through an optimal path-finding algorithm. As a result of comparing the general route of T-map and the recommended route of this study for the identical routes, the latter had relatively fewer obstacles and the gentler slope than the former, implicating that the recommended route is safer than the general one. As future works, it is necessary to enhance the function of a route guidance service based on the real-time location of users and to conduct spot investigations to evaluate and verify its social acceptability.

주제어

표/그림 (6)

그림 FIGURE 1. Research flow
표 TABLE 1. Research efforts to improve the service of electric personal assistive mobility devices
표 TABLE 2. Typical images and number of images corresponding to nine factors for learning AI model
표 TABLE 3. Slope analysis of routes for AI model testing
표 TABLE 4. Safety scores associated with factors affecting mobility of electric personal assistive mobility devices
표 TABLE 5. Comparison of general routes and recommend routes

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