Interactions and Equilibrium Between Rescheduling Train Traffic and Routing Passengers in Microscopic Delay Management: A Game Theoretical Study

References

• Bablinski K (2015) A game-based analysis of freight paths allocation with a case study on Great Britain Brighton Main Line. Transportation Res. Procedia 13:196–208.Crossref, Google Scholar
• Bauer R, Schöbel A (2014) Rules of thumb: Practical online strategies for delay management. Public Transportation 6:85–105.Crossref, Google Scholar
• Bell MGH (2000) A game theory approach to measuring the performance reliability of transport networks. Transportation Res. Part B: Methodology 34:533–545.Crossref, Google Scholar
• Bender M, Büttner S, Krumke SO (2013) Online delay management on a single line: beyond competitive analysis. Public Transportation 5:243–266.Crossref, Google Scholar
• Binder S, Chen J, Bierlaire M (2014) Generation and evaluation of passenger-oriented railway disposition timetables. Proc. 14th Swiss Transport Research Conf. (Swiss Transport Research Conference, Ascona, Switzerland), 1–12.Google Scholar
• Binder S, Maknoon Y, Bierlaire M (2017) Exogeneous priority rules for the capacitated passenger assignment problem. Transportation Res. Part B: Methodology 105:19–42.Crossref, Google Scholar
• Böhmová K, Mihalák M, Neubert P, Pröger T, Widmayer P (2015) Robust routing in urban public transportation: Evaluating strategies that learn from the past. OpenAccess Series Informatics 48:68–81.Google Scholar
• Bouman PC, Kroon LG, Vervest PHM, Maróti G (2017) Capacity, information and minority games in public transport. Transportation Res. Part C: Emerging Tech. 70:157–170.Crossref, Google Scholar
• Brewer PJ, Plott CR (1996) A binary conflict ascending price (BICAP) mechanism for the decentralized allocation of the right to use railroad tracks. Internat. J. Indust. Organ. 14:857–886.Crossref, Google Scholar
• Cacchiani V, Huisman D, Kidd M, Kroon L, Toth P, Veelenturf L, Wagenaar J (2014) An overview of recovery models and algorithms for real-time railway rescheduling. Transporation Res. Part B: Methodology 63:15–37.Crossref, Google Scholar
• Caprara A, Kroon LG, Monaci M, Peeters M, Toth P (2006) Passenger railway optimization. Barnhart C, Laporte G, eds. Handbooks in Operations Research and Management Science, vol. 14 (Elsevier, Amsterdam), 129–187.Google Scholar
• Carey M, Crawford I (2007) Scheduling trains on a network of busy complex stations. Transporation Res. Part B: Methodology 41(2):159–178.Crossref, Google Scholar
• Cats O, Koutsopoulos H, Burghout W, Toledo T (2011) Effect of real-time transit information on dynamic path choice of passengers. Transportation Res. Rec. 2217:46–54.Crossref, Google Scholar
• Chen O, Ben-Akiva M (1998) Game-theoretic formulations of interaction between dynamic traffic control and dynamic traffic assignment. Transportation Res. Rec. 1617:179–188.Crossref, Google Scholar
• Corman F, Kecman P (2018) Stochastic prediction of train delays in real-time using Bayesian networks. Transporation Res. 95: 599–615.Google Scholar
• Corman F, D’Ariano A, Hansen IA (2014) Evaluating disturbance robustness of railway schedules. J. Intelligent Transporation Systems 18(1):106120.Google Scholar
• Corman F, D’Ariano A, Hansen IA, Pacciarelli D (2011) Optimal multi-class rescheduling of railway traffic. J. Rail Transport Planning Management 1(1):14–24.Crossref, Google Scholar
• Corman F, D’Ariano A, Pacciarelli D, Pranzo M (2012) Bi-objective conflict detection and resolution in railway traffic management. Transportation Res. Part C: Emerg. Tech. 20(1):79–94.Crossref, Google Scholar
• Corman F, D’Ariano A, Pacciarelli D, Pranzo M (2014) Dispatching and coordination in multi-area railway traffic management. Comput. Oper. Res. 44(1):146–160.Crossref, Google Scholar
• Corman F, D’Ariano A, Marra AD, Pacciarelli D, Samà M (2016) Integrating train scheduling and delay management in realtime railway traffic control. Transportation Res. Part E: Logist. Transportation Rev. 105:213–239.Crossref, Google Scholar
• D’Ariano A, Pacciarelli D, Pranzo M (2007) A branch and bound algorithm for scheduling trains in a railway network. Eur. J. Oper. Res. 183(2):643–657.Crossref, Google Scholar
• Delling D, Italiano GF, Pajor T, Santaroni F (2014) Better transit routing by exploiting vehicle GPS data. Chin X, ed. Proc. 7th ACM SIGSPATIAL Internat. Conf. (ACM, New York), 31--40.Google Scholar
• Dell’Olio L, Moura JL, Ibeas A (2006) Bi-level mathematical programming model for locating bus stops and optimizing frequencies transportation research record. Transportation Res. Rec. 1971(1):23–31.Crossref, Google Scholar
• Dollevoet T, Huisman D (2014) Fast heuristics for delay management with passenger rerouting. Public Transportation 6(1-2):67–84.Crossref, Google Scholar
• Dollevoet T, Corman F, D’Ariano A, Huisman D (2014) An iterative optimization framework for delay management and train scheduling. J. Flexible Services Manufacturing 26(4):490–515.Crossref, Google Scholar
• Dollevoet T, Huisman D, Schmidt M, Schöbel A (2012) Delay management with rerouting of passengers. Transportortation Sci. 46(1):74–89.Link, Google Scholar
• Dollevoet T, Huisman D, Kroon L, Schmidt M, Schöbel A (2015) Delay management including capacities of stations. Transportation Sci. 49(2):185–203.Link, Google Scholar
• Duc Quynh T, Thuan NG (2018) On optimization problems in urban transport. Pardalos PM, Migdalas A, eds. Open Problems in Optimization and Data Analysis, Springer Optimization and Its Applications, vol. 141 (Springer, Heidelberg), 151–170.Crossref, Google Scholar
• Easley D, Kleinberg J (2010) Modeling network traffic using game theory. Easkey D, Kleinberg J, eds. Networks, Crowds, and Markets: Reasoning about a Highly Connected World (Cambridge University Press, Cambridge, UK), 229–247.Crossref, Google Scholar
• Espinosa-Aranda J, García-Rodenas R (2013) A demand-based weighted train delay approach for rescheduling railway networks in real-time. J. Rail Transport Planning Management 3(1--2):1–13.Crossref, Google Scholar
• European Rail Research Advisory Council (2012) Rail Route 2050: The Sustainable Backbone of the Single European Transport Area (European Rail Research Advisory Council, Brussels).Google Scholar
• Fragnelli V, Sanguineti S (2014) A game theoretic model for re-optimizing a railway timetable. Eur. Transporation Res. Rev. 6:113–125.Crossref, Google Scholar
• Gatto M (2007) On the impact of uncertainty on some optimization problems: combinatorial aspects of delay management and robust online scheduling. PhD thesis, ETH Zurich.Google Scholar
• Ghaemi N, Cats O, Goverde RMP (2017) Railway disruption management challenges and possible solution directions. Public Transportation 9(1–2):343–364.Crossref, Google Scholar
• Goerigk M, Knoth M, Müller-Hannemann M, Schmidt M, Schöbel A (2013) The price of strict and light robustness in timetable information. Transportation Sci. 48:225–242.Link, Google Scholar
• Hansen IA, Pachl J, eds. (2014) Railway Timetabling & Operations: Analysis, Modelling, Optimisation, Simulation, Performance Evaluation. (Eurailpress, Hamburg, Germany).Google Scholar
• Hamdouch Y, Lawphongpanich S (2008) Schedule-based transit assignment with loading priorities. Math. Programming 101(1).Crossref, Google Scholar
• Hamdouch Y, Lawphongpanich S (2010) Congestion pricing for schedule-based transit networks. Transportation Sci. 44(3):350–366.Link, Google Scholar
• Hamdouch Y, Ho H, Sumalee A, Wang G (2011) Schedule-based transit assignment model with vehicle capacity and seat availability. Transportation Res. Part B: Methodology 42(7–8):663–684.Crossref, Google Scholar
• Harrod S (2013) Auction pricing of network access for North American railways. Transportation Res. Part E: Logist. Trans. Rev. 49:176–189.Crossref, Google Scholar
• Hollander Y, Prashker JN (2006) The applicability of non-cooperative game theory in transport analysis. Transportation 33(5):481–496.Google Scholar
• Josyula SP, Törnquist Krasemann J (2017) Passenger-oriented railway traffic re-scheduling: A review of alternative strategies utilizing passenger flow data. 7th Internat. Conf. Railway Oper. Res. Anal. Lille, France.Google Scholar
• Klabes S (2010) Algorithmic railway capacity allocation in a competitive european railway market. Dissertation, RWTH Aachen, Germany.Google Scholar
• Kuo A, Miller-Hooks E (2012) Developing responsive rail services through collaboration. Transportation Res. Part B: Methodology 46:424–439.Crossref, Google Scholar
• Lamorgese L, Mannino C (2015) An exact decomposition approach for the real-time train dispatching problem. Oper. Res. 63(1):48–64.Link, Google Scholar
• Lamorgese L, Mannino C, Pacciarelli P, Törnquist Krasemann J (2018) Train dispatching. Borndörfer R, et al.., eds. Handbook of Optimization in the Railway Industry, International Series in Operations Research & Management Science, vol. 268, (Springer, Heidelberg, Germany), 265–284.Crossref, Google Scholar
• Lalive R, Schmutzler A (2008) Exploring the effects of competition for railway markets. Internat. J. Indust. Organ. 26:443–458.Crossref, Google Scholar
• Luan X, Meng L, Corman F (2017) Non-discriminatory train dispatching in a rail transport market with multiple competing and collaborative train operating companies. Transportation Res. Part C: Emerging Tech. 80:148–174.Crossref, Google Scholar
• Mascis A, Pacciarelli D (2002) Job shop scheduling with blocking and no-wait constraints. Eur. J. Oper. Res. 143(3):498–517.Crossref, Google Scholar
• Meschini L, Gentile G, Papola N (2007) A frequency based transit model for dynamic traffic assignment to multimodal networks. Allsop RE, Bell MGH, Heydecker BG, eds. Proc. Internat. Symp. Transportation Traffic Theory 17 (Elsevier, Amsterdam), 407–436.Google Scholar
• Meng L, Zhou X (2014) Simultaneous train rerouting and rescheduling on an N-track network: A model reformulation with network-based cumulative flow variables. Transportation Res. Part B: Methodology 67(1):208–234.Crossref, Google Scholar
• Mesbah M, Sarvi M, Ouveysi I, Currie G (2011) Optimization of transit priority in the transportation network using a decomposition methodology. Transportation Res. Part C: Emerging Tech. 19(2):363–373.Crossref, Google Scholar
• Nassir N, Hickman M, Ma ZL (2019) A strategy-based recursive path choice model for public transit smart card data. Transportation Res. Part B: Methodology 126(August):528–548.Google Scholar
• Nielsen OA, Frederiksen RD (2006) Optimisation of timetable-based, stochastic transit assignment models based on MSA. Ann. Oper. Res. 144(1):263–285.Crossref, Google Scholar
• Nielsen OA, Landex Rasmus OA, Frederiksen D (2009) Passenger delay models for rail networks. Nuzzolo A, Wilson NHM, eds. Schedule-Based Modeling of Transportation Networks, Operations Research/Computer Science Interfaces Series, vol. 46 (Springer, New York), 1–23.Google Scholar
• Parbo J, Nielsen OA, Prato CG (2016) Passenger perspectives in railway timetabling: A literature review. Transport Rev. 36:500–526.Google Scholar
• Patriksson M (2008) Robust bi-level optimization models in transportation science. Philos. Trans. Roy. Soc. A: Math. Phys. Engrg. Sci. 366(1872):1989–2004.Google Scholar
• Pellegrini P, Rodriguez J (2013) Single European sky and single European railway area: A system level analysis of air and rail transportation. Transportation Res. Part A: Policy Practice 57(1):64–86.Crossref, Google Scholar
• Pellegrini P, Marlière G, Rodriguez J (2014) Optimal train routing and scheduling for managing traffic perturbations in complex junctions. Transportation Res. Part B: Methodology 59(1):58–80.Crossref, Google Scholar
• Poon M, Wong S, Tong C (2004) A dynamic schedule-based model for congested transit networks. Transportation Res. Part B: Methodology 38(4):343–368.Google Scholar
• Rosenthal RW (1973) A class of games possessing pure-strategy Nash equilibria. Internat. J. Game Theory 2:65–67.Crossref, Google Scholar
• Rückert R, Lemnian M, Blendinger C, Rechner S, Müller-Hannemann M (2017) PANDA: A software tool for improved train dispatching with focus on passenger flows. Public Transportation 9(1):307–324.Crossref, Google Scholar
• Samà M, D’Ariano A, Corman F, Pacciarelli D (2016) A variable neighborhood search for fast train scheduling and routing during disturbed railway traffic situations. Comput. Oper. Res. 78:480–499.Google Scholar
• Samà M, Meloni C, D’Ariano A, Corman F (2015) A multi-criteria decision support methodology for real-time train scheduling. J. Rail Transport Planning Management 5(3):146–162.Google Scholar
• Sato K, Tamura K, Tomii N (2013) A MIP-based timetable rescheduling formulation and algorithm minimizing further inconvenience to passengers. J. Rail Transport Planning Management 3(3):38–53.Crossref, Google Scholar
• Schachtebeck M, Schöbel A (2010) To wait or not to wait—And who goes first? Delay management with priority decisions. Transportation Sci. 44(3):307–321.Link, Google Scholar
• Schöbel A (2001) A model for the delay management problem based on mixed-integer programming. Proceedings of the 1st Workshop on Algorithmic Methods and Models for Optimization of Railways. Electron. Notes Theoret. Comput. Sci. 50(1):1–10.Crossref, Google Scholar
• Schöbel A (2007) Integer programming approaches for solving the delay management problem. robust and online large-scale optimization. Algorithmic Methods for Railway Optimization, Lecture Notes Comput. Sci., vol. 4359, (Springer, Berlin), 145–170.Google Scholar
• Schöbel A (2009) Capacity constraints in delay management. Public Transport Planning Oper. 1(2):135–154.Crossref, Google Scholar
• Schön C, König E (2019) A stochastic dynamic programming approach for delay management of a single train line. Eur. J. Oper. Res. 271:501–518.Crossref, Google Scholar
• Schmidt M, Kroon L, Schöbel A, Bouman P (2017) The travelers route choice problem under uncertainty: Dominance relations between strategies. Oper. Res. 65(1):184–199.Link, Google Scholar
• Spiess H, Florian M (1989) Optimal strategies: A new assignment model for transit networks. Transportation Res. Part B: Methodology 23(2):83–102.Google Scholar
• Staňková K (2009) On Stackelberg and inverse Stackelberg games and their applications in the optimal toll design problem, the energy markets liberalization problem, and in the theory of incentives. PhD thesis, Delft University of Technology, Netherlands.Google Scholar
• Suhl L, Biederbick C, Kliewer N (2001). Design of customer-oriented dispatching support for railways. Voss S, Daduna JR, eds. Computer-Aided Scheduling of Public Transport, vol. 505 (Springer, New York).Crossref, Google Scholar
• Taale H (2008) Integrated anticipatory control of road networks: A game-theoretical approach. PhD thesis, Delft University of Technology, Netherlands.Google Scholar
• Tomii N, Tashiro Y, Tanabe N, Hirai C, Muraki K (2005) Train rescheduling algorithm which minimizes passengers’ dissatisfaction. Ali M, Esposito F, eds. Innovations in Applied Artificial Intelligence, Lecture Notes in Artificial Intelligence, vol. 3533 (Springer, Berlin), 829–838.Google Scholar
• Törnquist J, Persson JA (2007) N-tracked railway traffic re-scheduling during disturbances. Transportation Res. Part B: Methodology 41(3):342–362.Google Scholar
• Van Der Hurk E, Kroon L, Maróti G, Vervest P (2015) Deduction of passengers’ route choices from smart card data. IEEE Trans. Intelligent Transportation Systems 16(1):430–440.Crossref, Google Scholar
• Van Thielen S, Corman F, Vansteenwegen P (2018) Considering a dynamic impact zone for real-time railway traffic management. Transportation Res. Part B: Methodology 111:39–59.Crossref, Google Scholar
• Vansteenwegen P, Van Oudheusden D (2007) Decreasing the passenger waiting time for an intercity rail network. Transportation Res. Part B: Methodology 41(4):478–492.Crossref, Google Scholar
• Wang YB, De Schutter TJJ, van den Boom B, Tang N (2014) Efficient bilevel approach for urban rail transit operation with stop-skipping. IEEE Trans. Intelligent Transportation Systems 15(6):2658–2670.Crossref, Google Scholar
• Wilson NHM, Nuzzolo A, eds. (2004) Schedule-Based Dynamic Transit Modeling: Theory and Applications, Operations Research/Computer Science Interfaces Series, vol. 28. (Springer, New York).Crossref, Google Scholar
• Zhang H, Su Y, Peng L, Yao D (2010) A review of game theory applications in transportation analysis. Wang Z, ed. Proc. IEEE Internat. Conf. Computer and Information Application ICCIA 2010 (IEEE, Piscataway, NJ), 152–157.Google Scholar