DOI QR코드

DOI QR Code

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

  • 투고 : 2023.09.07
  • 심사 : 2023.09.19
  • 발행 : 2023.09.30

초록

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.

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.

키워드

과제정보

본 연구는 국토교통부/국토교통과학기술진흥원의 지원으로 수행되었음(과제번호 RS-2021-KA162016, 국토교통부)

참고문헌

  1. Aleksandar P. and D. Branko. 2013. Wheelchair control by head motion. Serbian Journal of Electrical Engineering 10(1):135-151. https://doi.org/10.2298/SJEE1301135P
  2. Barczyszyn, G.L., L.M.D.O. Camenar, D.D.F. Do Nascimento, N.P. Kozievitch, R.D. Da Silva, L.D.A. Almeida, J. De Santi and R. Minetto. 2018. A collaborative system for suitable wheelchair route planning. ACM Transactions on Accessible Computing 11(3):1-26. https://doi.org/10.1145/3237186
  3. Benjamin, T., K. Reuben and S. Johannes. 2019. Analyzing accessibility barriers using cost-benefit analysis to design reliable navigation services for wheelchair users. 17th IFIP Conference on Human-Computer Interaction 11, 746:1-22.
  4. Bo. N., M.J. Li, T. Liu, H.M. Shen, L. Hu and X. Fu. 2012. Human brain control of electric wheelchair with eye-blink electrooculogram signal. Intelligent Robotics & Applications 7,506:579-588.
  5. Choi, G.C., Y.B. Jo, D.S. Lee and J.S. Kim. 2018. Smart sensor based electric wheelchair function improvement for social care. Joint Conference of Digital Contents Society and Korean Institute of Information Technology: 427-430.
  6. Christian, M, S. Julian, A.A. Miriam, B. Emanuel, F. Jelena, N. Tobias and S. Tobias. 2011. EasyWheel - a mobile social navigation and support system for wheelchair users. 2011 International Conference on Information Technology: New Generation: 859-866.
  7. Jeong, U.J., K.G. Jeon, J.H. Kim, J.G. Lee, M.K. Kim and H.J. Cha. 2023. Development of a personal mobility scooter with autonomous driving and safety features. Korean Society for Control, System, and Robotics 29(5): 404-411.
  8. Kang, H.K., Y.H. Im, G.B. Lim and T.H. Ha. 2019. Building and utilizing barrier-free spatial information for the enhancement of convenience in the lives of people with disabilities, the elderly, and those with mobility issues. Korea Research Institute for Human Settlements.
  9. Kim, G.W., B.M. Gu, J.H. Si and H.H. Jeon. 2020. Location analysis of charging stations for the disabled person using big data. Journal of Korean Society of Transportation 17(5):7-16.
  10. Kim, J.H., M.K. Yeom, W.T. Woo. 2019. Optimized route navigation system design for disabled people who use electronic assistive devices. Conference of Korean Society for Human-Computer Interaction: 381-386.
  11. Kim, J.I., S.G. Kang and J.H. Kwon. 2008. The Spatial Characteristics of Transit-Poors in Urban Areas. Journal of the Korean Geographic Information Society. 11(2):1-12.
  12. Kim, K.S., S.E. Kim and B.S. Song. 2016. A study of efficiency plan of electricity charging point for powered wheelchair and scooter. Conference of Rehabilitation Engineering & Assistive Technology Society of Korea.
  13. Kim, S.E., K.S. Kim, J.B. Kang and B.S. Song. 2015. Study on the operation method of electric wheelchair and electric scooter charging stations. Journal of Rehabilitation Research 21(2):191-216.
  14. Krzysztof, S., G. Adam, I. Witold and A. Tomasz. 2015. Synthesis and evaluation of the smart electric powered wheelchair route stabilization concept-a simulation study. Archives of Control Sciences 25(2): 263-273. https://doi.org/10.1515/acsc-2015-0017
  15. Lee, J.S., M.Y. Jung, S.E. Kang and W.H. Jang. 2017. A study on assistive device support systems for manual and electric wheelchairs: focusing on Korea, the United States, and Japan. Journal of Korean Society of Assistive and Rehabilitation Technology 9(1):9-15.
  16. Lee, Y.S. and H.S. Kim. 2019. An exploratory study of the effect of mobility on social exclusion among people with disabilities. Health and Social Welfare Review 39(1): 136-165. https://doi.org/10.15709/HSWR.2019.39.1.136
  17. Moon, M.G., Y.M. Lee., K.Y. Yu and J.Y. Kim. 2016. Optimized path finding algorithm for walking convenience of the people with reduced mobility. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography 34(3): 273-282. https://doi.org/10.7848/ksgpc.2016.34.3.273
  18. Park, G.H. and J.H. Byeon. 2012. Effects of the Physical Environment around Elementary Schools on Children's Walking Safety - A case Study of the Elementary Schools in Changwon -. Journal of the Korean Geographic Information Society. 15(2):150-160.
  19. Park, J.H. and W.N. Kwang. 2015. A Study on the Low-Floor Bus Route Selection Considering a Residential Distribution and Traffic Characteristics of the Transportation Vulnerable - A Case of Busan -. Journal of the Korean Geographic Information Society. 18(2):161-173. https://doi.org/10.11108/kagis.2015.18.2.161
  20. Park, K.W., H.E. Kim and H.S. Kim. 2015. The improvement of facilities and pedestrian environments according to daily life pattern of the electric wheelchair users. Korean Journal of Housing Studies 19(2):149-161.
  21. Pascal, N. 2015. Measuring the reliability of wheelchair user route planning based on volunteered geographic information. Transactions in GIS 19(2):188-201. https://doi.org/10.1111/tgis.12087
  22. Shim, S.B. and Y.G. Son. 2020. Encoder type semantic segmentation algorithm using multi-scale learning type for road surface damage recognition. Journal of Korea Institute of Intelligent Transportation Systems Society 19(2):89-103. https://doi.org/10.12815/kits.2020.19.2.89
  23. Sumida, Y., M. Hayashi, K. Goshi and K. Matsunaga. 2012. Development of a route finding system for manual wheelchair users based on actual measurement data. 2012 9th International Conference on Ubiquitous Intelligence and Computing and 9th International Conference on Autonomic and Trusted Computing: 17-23.
  24. Yuki, S., L. Huimin, T. Joo-Kooi and H.S. Kim. 2019. Recognition of surrounding environment from electric wheel chair videos based on modified YOLOv2. In Future Generation Computer Systems 92:157-161. https://doi.org/10.1016/j.future.2018.09.068