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2022 Vol.40, Issue 2 Preview Page

Article

Modeling Pedestrian Movement Behavior Using Social Force Model and Fuzzy Inference

퍼지추론을 반영한 Social Force Model 기반의 보행자 이동행태 모형 개발

Myungjoo HAN1
,
Dongjae JUNG2*
,
Young-Ihn LEE3
,
Soongbong LEE4
한 명주1
,
정 동재2*
,
이 영인3
,
이 숭봉4
1Research Fellow, Gyeonggi Public Investment Management Center, Gyeonggi Research Institute, Gunpo 15880, Korea
2Research Fellow, Department of Transportation and Logistics Research, Incheon Research Institute, Incheon 22711, Korea
3Professor, Graduate School of Environmental Studies, Seoul National University, Seoul 08826, Korea
4Research Fellow, Division for AI and Big Data Platform, The Korea Transport Institute, Sejong 30147, Korea
1경기연구원 공공투자관리센터 투자분석위원
2인천연구원 교통물류연구부 부연구위원
3서울대학교 환경대학원 명예교수
4한국교통연구원 AI ‧ 빅데이터플랫폼연구팀 부연구위원
*Corresponding Author
30 April 2022. pp. 218-229
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Abstract

The aim of this paper is to develop a microscopic pedestrian movement behavior model reflecting the walking speed and direction of pedestrians through fuzzy inference approach and social force model. The model can analyze the movement of each pedestrian and the interaction between pedestrians by using individual pedestrians as the unit of analysis, which would complement the limitations of existing studies have analyzed pedestrians as homogeneous and continuous flow. In addition, by reflecting the pedestrian’s probabilistic decision-making process on the change of walking speed and direction, the limited assumption of the social force model that assumes the pedestrian’s movement is deterministic has been alleviated in this model. In the process, fuzzy inference approach was applied to process pedestrians’ subjective and ambiguous information about the pedestrian’s decision-making factors. The model was verified by comparing simulated model values and actual observations using object-oriented programming for each macroscopic and microscopic characteristics. The results of verification would show the error in the explanatory power of the model was low, and the explanatory power of the model was high.

Keywords
decision-making process
fuzzy inference
pedestrian movement behavior
pedestrian simulation
social force model

이 연구는 퍼지추론을 적용한 보행속력 또는 이동방향 변경확률 모형을 사회역학모형 기반의 반응행태 모형에 반영한 미시적 보행자 이동행태 모형을 개발하였다. 이 모형은 개별 보행자를 분석 단위로 하여 보행자 특성별 움직임과 보행자간 상호작용을 분석할 수 있다는 점에서 보행자 집단을 동질적이고 연속된 흐름으로 간주하고 집계된 평균 특성으로 보행행태를 분석하는 거시적 접근법 연구의 한계를 보완한다. 또한 보행속력 또는 이동방향 변경에 대한 보행자의 확률적 의사결정 행태를 반영함으로써 보행자의 움직임을 결정적이라 전제하는 사회역학모형의 이론적 가정을 완화하였다. 이 과정에서 보행자의 의사결정 요인에 관한 보행자의 주관적이고 애매한 정보를 처리하기 위하여 퍼지추론이 적용되었다. 모형의 검증은 객체지향 프로그래밍을 활용하여 시뮬레이션한 모형치와 실제 관측치를 비교하며 이루어졌다. 두 가지 관점의 보행특성, 즉 거시적 보행특성과 미시적 보행특성에 대한 설명력을 검토하였는데, 모두 오차가 크지 않고 관측치에 대한 모형치의 설명력이 높게 도출되었다.

키워드
의사결정과정
퍼지추론
보행이동행태
보행시뮬레이션
사회역학모형
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Information
  • Publisher :Korean Society of Transportation
  • Publisher(Ko) :대한교통학회
  • Journal Title :Journal of Korean Society of Transportation
  • Journal Title(Ko) :대한교통학회지
  • Volume : 40
  • No :2
  • Pages :218-229
  • Received Date : 2021-05-31
  • Revised Date : 2021-07-22
  • Accepted Date : 2022-03-05
  • DOI :https://doi.org/10.7470/jkst.2022.40.2.218
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