This study proposes a statistical modeling framework for estimating the daily number of bus stops at highway transfer facilities (ex-HUBs) where demand information is often uncertain during the early planning stages. Accurate estimation of the daily number of bus stops is critical for efficient design and operation; however, reliable demand data are rarely available in the initial planning phase. Using pooled data from 16 facilities, a direct demand estimation approach was implemented, based on facility characteristics, transportation connectivity, highway traffic conditions, and socioeconomic factors. Log-linear model (LLM) and negative binomial model (NBM) were developed to capture the count data characteristics. Ensemble models using arithmetic and weighted means were also constructed to improve predictive reliability. The analysis revealed that the arithmetic mean ensemble of NBM and LLM produced the most accurate predictions. The daily number of bus stops was significantly influenced by the distance from bus terminals, highway traffic volume, public transportation connectivity, economically active population, and level of urbanization. The framework proposed in this study provides a practical tool for estimating the daily number of bus stops at highway transfer facilities, and can support more reliable feasibility analyses and infrastructure planning under demand uncertainty.

ABSTRACT
1. 연구의 배경 및 목적
2. 이론적 고찰 및 선행연구 검토
    2.1. 고속도로 환승시설의 개념 및 유형
    2.2. 고속도로 환승시설 관련 선행 연구
    2.3. 교통수요 추정 관련 선행 연구
    2.4. 고찰 결과 및 시사점
3. 연구 방법론
    3.1. 연구의 범위
    3.2. 연구의 방법 및 절차
4. 분석 데이터 구축
    4.1. 데이터 수집 및 정제
    4.2. 기초 통계 분석
5. 버스 정차 대수 추정 모형 구축 및 분석
    5.1. 1차 모형: 단일 통계 모형(Base Models)
    5.2. 2차 모형: 앙상블 기반 예측 고도화
6. 최종 모형 선정 및 활용 방안
    6.1. 주 모형(Main Model) 선정
    6.2. 보조 모형(Auxiliary Model) 선정
    6.3. 모형 진단 및 일반화
7. 결론
감사의 글
REFERENCES

• 기한솔(인천대학교 일반대학원 건설환경공학과 박사과정) | Gi Hansol
• 김응철(인천대학교 도시과학대학 도시환경공학부 교수) | Kim Eungcheol Corresponding author