SP조사를 활용한 중소도시의 수요응답형 대중교통 이용자 선호 요인 분석
A Research on User Preference Factor of DRT in Small and Medium-sized Cities Using Stated Preference Survey
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초록
수요응답형 대중교통(이하 DRT, Demand Response Transit)은 스마트폰 앱과 차량단말 등을 활용하여 이용자호출에 따라 가변적인 노선으로 운행되는 대중교통이다. DRT는 호출 후 대기시간, 탑승지점접근시간, 차내통행시간, 우회통행시간, 하차 후 도달시간 등이 운행방식에 기반한 이용자 선호요인이발생된다. 본 연구는 SP조사를 통해 시민들이 위 요인 중 어떤 요인에 가장 민감하게 반응하는지조사하였다. 조사는 5개의 속성변수로 구성된 2개의 DRT 대안을 제시하여 보다 선호하는 수단을선택하도록 하였으며, 출퇴근 상황과 여가 상황 2가지 상황에 대한 응답을 조사하였다. 분석결과출퇴근시에도 여가시에도 호출 후 대기시간이 가장 큰 선호요인이었으며, 탑승지점 접근시간은가장 약한 영향요인인 것으로 분석되었다. 단, 우회통행에 대한 민감도는 출퇴근 상황에서 여가시간대비 2배 이상인 것으로 나타났다. 본 연구의 결과는 DRT 운영 시 시간대에 따라서 최적화 목표를차별화하여 이용자 만족도와 시스템 효율성을 향상시키는 데 기여할 것으로 보여진다.
Abstract
Demand-Response Transit (DRT) is public transportation that operates on flexible routes according to user requests via smartphone apps and vehicle terminals. In DRT, user preference factors are generated based on the operational method, such as wait time after calling, approach time to the boarding point, in-vehicle time, detour time (if any), and egress time after arrival. Through an SP survey, this study investigated which of these factors citizens are most sensitive to. The survey presented two DRT alternatives consisting of five attribute variables, and asked respondents to choose the preferred mode, examining two situations: commuting and leisure travel. The analysis showed that wait time after calling was the strongest factor for both commuting and leisure travel, whereas boarding point access time had the weakest influence. However, sensitivity to detours was found to be more than twice as important in leisure travel compared to commuting. The results of this study are expected to contribute to improving user satisfaction and system efficiency by differentiating optimization targets according to the time of day in DRT operations.
참고문헌 (24)
- Amirgholy, M., "Demand responsive transit systems with time-dependent demand : User equilibrium, system optimum, and management strategy", Transportation Research Part B : Methodological, 92, pp.234~252 (2016)
- Arbex, R. O., "Efficient transit network design and frequencies settingmulti-objective optimization by alternating objective genetic algorithm", Transportation Research Part B : Methodological, 81(2), pp.355~376 (2015)
- Coslovich, L., "A Two-phase insertion technique of unexpected customers for a dynamic dial-a-ride problem", European Journal of Operational Research, 175(3), pp.1605~1615 (2006)
- Dessouky, M., "Jointly optimizing cost, service, and environmental performance in demand-responsive transit scheduling", Transportation Research Part D : Transport and Environment, 8(6), pp.433~465 (2003)
- Farah, A., "User preference analysis for an integrated system of bus rapid transit and on-demand shared mobility services in Amman, Jordan", Urban Science, 7(4), pp.111~ (2023)[DOI]
- Go, Y., "A stated preference analysis of on-demand mobility services in the commuting context in Seoul metropolitan area", Journal of Korean Society of Transportation, 40(5), pp.700~716 (2022)
- Guo, R., "Route design problem of customized buses: Mixed integer programming model and case study", Journal of Transportation Engineering, Part A: Systems, 144(11), pp.04018069~ (2018)
- Guo, R., "Customized bus routing problem with time window restrictions : Model and case study", Transportmetrica A : Transport Science, 15(2), pp.1804~1824 (2019)
- Han, S. W., "Incentive strategy to improve passenger convenience and operation efficiency of demand-responsive transportation systems", Journal of Korean Society of Transportation, 42(2), pp.180~195 (2024)
- Huang, D., "An analytical model for the many-to-one demand responsive transit systems", Sustainability, 12(1), pp.298~ (2020)[DOI]
- Incheon metropolitan city I-MOD public transport policymaking study, "Incheon Institute", ~ (2022)
- Jaw, J. J., "A heuristic algorithm for the multi-vehicle advance request dial-a-ride problem with time windows", Transportation Research Part B : Methodological, 20(3), pp.243~257 (1986)
- Kim, J., "Development of a model for dynamic station assignmentto optimize demand responsive transit operation", Journal of Korea Institute of Intelligent Transport Systems, 21(1), pp.18~34 (2022)
- Kim, W., "A comparative study on factors affecting satisfaction by travel purpose for urban demand response transport service : Focusing on Sejong Shucle", Journal of Korea Institute of Intelligent Transport Systems, 23(2), pp.132~141 (2024)
- The feasibility study on the introduction of Demand-Responsive Transprot(DRT) in rural areas, "Korea Research Institute of Transportation Industries", ~ (2012)
- Impact analysis of implementing the demand responsive transit system in metropolitan areas, "Korea Transportation Institute", ~ (2022)
- Lyu, Y., "CB-Planner: A bus line planning framework for customized bus systems", Transportation Research Part C : Emerging Technologies, 101, pp.233~253 (2019)
- Nourbakhsh, S. M., "A structured flexible transit system for low demand areas", Transportation Research Part B : Methodological, 46(1), pp.204~216 (2012)
- Quadrifoglio, L., "A simulation study of demand responsive transit system design", Transportation Research Part A : Policy and Practice, 42(4), pp.718~737 (2008)
- Saxena, N., "Determining the market uptake of demand responsive transport enabled public transport service", Sustainability, 12(12), pp.4914~ (2020)[DOI]
- Seo, S., "Analysis on the importance rank of service components of autonomous mobility-on-demand service by potential user groups", The Journal of the Korea Institute of Intelligent Transport Systems, 21(6), pp.177~193 (2022)[DOI]
- Shen, C. W., "Evaluation of zoning design with transfers for paratransit services", Transportation Research Record, 2277(1), pp.82~89 (2012)
- Tolic, I. H., "Optimization of public transport services to minimize passengers waiting times and maximize vehicles occupancy ratios", Electronics, 9(2), pp.360~ (2020)[DOI]
- Wang, C., "Multi-objective optimization of real-time customized bus routes based on two-stage method", Physica A: Statistical Mechanics and its Applications, 537, pp.122774~ (2020)