Planning Service Protocols for Extra-Long Trains with Transfers

Published Online:https://doi.org/10.1287/trsc.2024.0527

References

  • Ahuja RK, Cunha CB, Şahin G (2005) Network models in railroad planning and scheduling. INFORMS TutORials Oper. Res. 2005(September):54–101.LinkGoogle Scholar
  • Avesidian C (2018) He answered a call for geniuses, and the MTA says he might be one. New York Times, Section A, https://www.bu.edu/bostonia/fall18/#toc.Google Scholar
  • Badia H, Argote-Cabanero J, Daganzo CF (2017) How network structure can boost and shape the demand for bus transit. Transportation Res. Part A Policy Practice 103:83–94.CrossrefGoogle Scholar
  • Beijing Subway Limited (2023) Beijing Subway. Accessed July 1, 2023, https://www.bjsubway.com/en/ybj/bwg/.Google Scholar
  • Beijing Transport Institute (2021) 2021 Beijing Transport Development Annual Report. Report, Beijing Transport Institute, Beijing.Google Scholar
  • Borndörfer R, Klug T, Lamorgese L, Mannino C, Reuther M, Schlechte T (2018) Handbook of Optimization in the Railway Industry (Springer International Publishing, Cham, Switzerland).CrossrefGoogle Scholar
  • Bugliarello G (1999) Megacities and the developing world. Bridge 29(4):19–26.Google Scholar
  • Bussieck MR, Winter T, Zimmermann UT (1997) Discrete optimization in public rail transport. Math. Programming 79(1):415–444.CrossrefGoogle Scholar
  • Cacchiani V, Toth P (2012) Nominal and robust train timetabling problems. Eur. J. Oper. Res. 219(3):727–737.CrossrefGoogle Scholar
  • Cacchiani V, Galli L, Toth P (2015) A tutorial on non-periodic train timetabling and platforming problems. EURO J. Transportation Logist. 4(3):285–320.CrossrefGoogle Scholar
  • Chen X, Zuo T, Lang M, Li S, Li S (2022) Integrated optimization of transfer station selection and train timetables for road–rail intermodal transport network. Comput. Indust. Engrg. 165:107929.CrossrefGoogle Scholar
  • Daganzo C (2019) Four physics stories and their effect on China’s future mobility. Distinguished Lecture. Department of Civil and Environmental Engineering, University of California, Berkeley. Accessed July 1, 2023, https://ce.berkeley.edu/news/2127.Google Scholar
  • Daganzo CF (2022) An operating system for extra long urban trains. Transportation Res. Part B Methodological 158:323–340.CrossrefGoogle Scholar
  • Daganzo CF, Ouyang Y (2019) Public Transportation Systems (World Scientific, Singapore).CrossrefGoogle Scholar
  • Ding H, Di Y, Zheng X, Liu K, Zhang W, Zheng L (2021) Passenger arrival distribution model and riding guidance on an urban rail transit platform. Phys. A 571:125847.CrossrefGoogle Scholar
  • Farahani RZ, Miandoabchi E, Szeto WY, Rashidi H (2013) A review of urban transportation network design problems. Eur. J. Oper. Res. 229(2):281–302.CrossrefGoogle Scholar
  • Huisman D, Kroon LG, Lentink RM, Vromans MJCM (2005) Operations research in passenger railway transportation. Statistica Neerlandica 59(4):467–497.CrossrefGoogle Scholar
  • Jamili A, Pourseyed Aghaee M (2015) Robust stop-skipping patterns in urban railway operations under traffic alteration situation. Transportation Res. Part C Emerging Tech. 61:63–74.CrossrefGoogle Scholar
  • Kaspi M, Raviv T (2013) Service-oriented line planning and timetabling for passenger trains. Transportation Sci. 47(3):295–311.LinkGoogle Scholar
  • Kera K, Isobe E, Kawahata S (1999) Hitachi’s initiatives in addressing the challenges of 21st century railway systems. Hitachi Rev. 48(3):126–133.Google Scholar
  • Lai Y, Barkan CP (2004) Train braking distance ratio: A parameter for railway signal system design. Presented at the 83rd Annual Meeting of the Transportation Research Board. Paper 04-4307. Washington, DC. Accessed January 7, 2023, https://railtec.illinois.edu/wp/wp-content/uploads/Lai-and-Barkan-2004-TRB-002307-Train-Braking-Distance-Ratio.pdf.Google Scholar
  • Li P (2021) Six more subway stations to limit rush hours crowds. Beijinger (January 12), https://www.thebeijinger.com/blog/2015/01/12/five-more-subway-stations-limit-rush-hour-crowds.Google Scholar
  • Li Z, Mao B, Bai Y, Chen Y (2019b) Integrated optimization of train stop planning and scheduling on metro lines with express/local mode. IEEE Access 7:88534–88546.CrossrefGoogle Scholar
  • Li W, Peng Q, Wen C, Xu X (2019a) Comprehensive optimization of a metro timetable considering passenger waiting time and energy efficiency. IEEE Access 7:160144–160167.CrossrefGoogle Scholar
  • Lin W (2021) After experiencing the morning peak of Nanshan Science and Technology Park, my mentality collapsed. Accessed July 1, 2023, https://min.news/en/news/06f5d575e0557c7b52fa3ad7bbdabb85.html.Google Scholar
  • Lusby RM, Larsen J, Bull S (2018) A survey on robustness in railway planning. Eur. J. Oper. Res. 266(1):1–15.CrossrefGoogle Scholar
  • Metro de Santiago (2023) Plano de red de metro. Accessed July 1, 2023, https://www.metro.cl.Google Scholar
  • Michaelis M, Schöbel A (2009) Integrating line planning, timetabling, and vehicle scheduling: A customer-oriented heuristic. Public Transport 1(3):211–232.CrossrefGoogle Scholar
  • National Academies of Sciences, Engineering, and Medicine (2013) Transit Capacity and Quality of Service Manual, 3rd ed. (The National Academies Press, Washington, DC).Google Scholar
  • Niu H, Zhou X (2013) Optimizing urban rail timetable under time-dependent demand and oversaturated conditions. Transportation Res. Part C Emerging Tech. 36:212–230.CrossrefGoogle Scholar
  • Schöbel A (2012) Line planning in public transportation: Models and methods. OR Spectrum 34(3):491–510.CrossrefGoogle Scholar
  • Shen S, Osorio J, Ouyang Y (2024) Optimizing block configuration and operation protocol for extra-long metro trains. Transportation Res. Part C Emerging Tech. 162:104612.CrossrefGoogle Scholar
  • Shi J, Yang L, Yang J, Zhou F, Gao Z (2019) Cooperative passenger flow control in an oversaturated metro network with operational risk thresholds. Transportation Res. Part C Emerging Tech. 107:301–336.CrossrefGoogle Scholar
  • Villalobos C, Munoz J (2014) Hipertrén: Esquema de operación de una línea de metro que permite aumentar su capacidad con baja inversión en infraestructura. Intellectual Property Certificate No. 238.247, Departamento de Transporte y Logística Pontificia Universidad Católica de Chile, Santiago.Google Scholar
  • Wang Y, D’Ariano A, Yin J, Meng L, Tang T, Ning B (2018) Passenger demand oriented train scheduling and rolling stock circulation planning for an urban rail transit line. Transportation Res. Part B Methodological 118:193–227.CrossrefGoogle Scholar
  • Xu X, Li C-L, Xu Z (2021) Train timetabling with stop-skipping, passenger flow, and platform choice considerations. Transportation Res. Part B Methodological 150:52–74.CrossrefGoogle Scholar
  • Xu J, Liang Q, Huang X, Wang L (2021) Optimization of stop plan for skip-stop operation on suburban railway line. Appl. Sci. 11(20):9519.CrossrefGoogle Scholar
  • Xue H, Guo J, Jia L (2022) Waiting time equalized collaborative passenger flow control model in peak hours for a subway line. Liang J, Jia L, Qin Y, Liu Z, Diao L, An M, eds. Proc. 5th Internat. Conf. Electr. Engrg. Inform. Tech. Rail Transportation (EITRT) 2021, Lecture Notes in Electrical Engineering, vol. 867 (Springer, Singapore), 476–490.Google Scholar
  • Yuhua Y, Marcella S, Dario P, Shaoquan N (2023) Train timetabling with passenger data and heterogeneous rolling stocks circulation on urban rail transit line. Soft Comput. 27(18):12959–12977.Google Scholar
  • Zhang C, Gao Y, Yang L, Gao Z, Qi J (2020) Joint optimization of train scheduling and maintenance planning in a railway network: A heuristic algorithm using Lagrangian relaxation. Transportation Res. Part B Methodological 134:64–92.CrossrefGoogle Scholar
  • Zhang R, Yin S, Ye M, Yang Z, He S (2021) A timetable optimization model for urban rail transit with express/local mode. J. Adv. Transportation 2021:e5589185.Google Scholar
  • Zhang Y, Peng Q, Lu G, Zhong Q, Yan X, Zhou X (2022) Integrated line planning and train timetabling through price-based cross-resolution feedback mechanism. Transportation Res. Part B Methodological 155:240–277.CrossrefGoogle Scholar
  • Zhou H, Qi J, Yang L, Shi J, Mo P (2022) Joint optimization of train scheduling and rolling stock circulation planning with passenger flow control on tidal overcrowded metro lines. Transportation Res. Part C Emerging Tech. 140:103708.CrossrefGoogle Scholar
  • Zhu Y, Koutsopoulos HN, Wilson NH (2021) Inferring left behind passengers in congested metro systems from automated data. Transportation Res. Procedia 23:362–379.CrossrefGoogle Scholar
  • Zhu K, Cheng Z, Wu J, Yuan F, Sun L (2022) Quantifying out-of-station waiting time in oversaturated urban metro systems. Comm. Transportation Res. 2:100052.CrossrefGoogle Scholar
INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.