دورية أكاديمية

Estimation of Time-Varying Passenger Demand for High Speed Rail System

التفاصيل البيبلوغرافية
العنوان: Estimation of Time-Varying Passenger Demand for High Speed Rail System
المؤلفون: Tangjian Wei, Feng Shi, Guangming Xu
المصدر: Complexity, Vol 2019 (2019)
بيانات النشر: Wiley, 2019.
سنة النشر: 2019
المجموعة: LCC:Electronic computers. Computer science
مصطلحات موضوعية: Electronic computers. Computer science, QA75.5-76.95
الوصف: Passenger demand plays an important role in railway operation and organization, and this paper aims to estimate passenger time-varying demand by simulating the ticket-booking process for High Speed Rail (HSR) system. The ticket-booking process of each OD pair can be partition into discrete booking phases by the times when the tickets of any itinerary had sold out. The ticket booking volume of each itinerary is reversely assigned to its corresponding expected departure intervals to obtain the time-varying demand in each booking phase using the rooftop model, and the total time-varying demand are estimated by summing the time-varying demand distributions in all booking phases. Only with the data about the itinerary flow, the precedence relationship is introduced to constrain the ticket sold-out order of all itineraries for each OD pair. Based on the precedence relationships of itineraries, two typical situations are proposed, in which the Single Booking Phase Reverse Assignment (SBPRA) algorithm and the Multiple Booking Phases Reverse Assignment (MBPRA) algorithm are proposed to estimate the time-varying demand respectively. Case analysis on OD pair Beijing-Shanghai are presented, and the validity analysis demonstrates that the error rates of SBPRA algorithm and MBPRA algorithm are 8.64% and 6.37%, respectively.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1076-2787
1099-0526
Relation: https://doaj.org/toc/1076-2787; https://doaj.org/toc/1099-0526
DOI: 10.1155/2019/1568941
URL الوصول: https://doaj.org/article/30abfe216c3d45678a9173ff01d2ffdb
رقم الأكسشن: edsdoj.30abfe216c3d45678a9173ff01d2ffdb
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:10762787
10990526
DOI:10.1155/2019/1568941