Assessment of schedule-based and frequency-based assignment models for strategic and operational planning of high-speed rail services |
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| Institution: | 1. University of Naples “Federico II”, Italy;2. University of Rome “Tor Vergata”, Italy;1. Department of Applied Economic Analysis, Institute of Tourism and Sustainable Economic Development, University of Las Palmas de Gran Canaria, 35017 Las Palmas G.C., Spain;2. Department of Human Geography, Complutense University of Madrid, 28040 Madrid, Spain;1. Manchester Urban Institute, School of Environment, Education and Development, The University of Manchester, Manchester, UK;2. Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, CAS, Nanjing, China;1. Università degli Studi di Napoli Federico II, Dipartimento di Ingegneria Civile, Edile e Ambientale, via Claudio 21, Napoli 80125, Italy;2. Centro de Investigación del Transporte (TRANSyT), Universidad Politécnica de Madrid, C/Profesor Aranguren s/n, 28040 Madrid, Spain;1. School of Economics and Management, Anhui Normal University, Wuhu 241000, China;2. School of International Trade and Economics, University of International Business and Economics, Beijing 100029, China;1. School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan 410075, China;2. Institute of Computing Technologies, China Academy of Railway Sciences Corporation Limited, Beijing 100081, China |
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| Abstract: | Despite some substantial limitations in the simulation of low-frequency scheduled services, frequency-based (FB) assignment models are by far the most widely used in practice. They are less expensive to build and less demanding from the computational viewpoint with respect to schedule-based (SB) models, as they require neither explicit simulation of the timetable (on the supply side), nor segmentation of OD matrices by desired departure/arrival time (on the demand side).The objective of this paper is to assess to what extent the lack of modeling capabilities of FB models is acceptable, and, on the other hand, the cases in which such approximations are substantial and more detailed SB models are needed. This is a first attempt to shed light on the trade-off between (frequency-based) model inaccuracy and (scheduled-based) model development costs in the field of long-distance (e.g. High-speed Rail, HSR) service modeling.To this aim, we considered two modeling specifications estimated using mixed Revealed Preferences (RP) and Stated Preferences (SP) surveys and validated with respect to the same case study. Starting from an observed (baseline) scenario, we artificially altered the demand distributions (uniform vs. time-varying demand) and the supply configuration (i.e. train departure times), and analyzed the differences in modal split estimates and flows on individual trains, using the two different model specifications.It resulted that when the demand distribution is uniform within the period of analysis, such differences are significant only when departure times of trains are strongly unevenly spaced in time. In such cases, the difference in modal shares, using FB w.r.t. SB, is in the range of 0%, +5%] meaning that FB models tend to overestimate HSR modal shares. When the demand distribution is not uniform, the difference in modal shares, using FB w.r.t. SB, is in the range of −10%, +10%] meaning that FB models can overestimate or underestimate HSR modal shares, depending on timetable settings with respect to travelers’ desired departure times. The differences in on-board train flow estimates are more substantial in both cases of uniform and not uniform demand distribution. |
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| Keywords: | Public transport models High-speed Rail Discrete choice models Assignment model accuracy |
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