This paper presents a dynamic extra buses scheduling strategy to improve the transit service of transit routes. In this strategy, in order to decide when to dispatch an extra bus, the service reliability of transit route is assessed firstly. A model aimed at maximizing the benefit of the extra buses scheduling strategy is constructed to determine how many stops extra buses need to skip from the terminal to accommodate passengers at the following stops. A heuristic algorithm is defined and implemented to estimate the service reliability of transit route and to optimize the initial stop of extra buses scheduling strategy. Finally, the strategy is tested on two examples: a simple and a real-life transit route in the Dalian city in China. The results show that the extra buses scheduling strategy based on terminal stops with a reasonable threshold can save 8.01% waiting time of passengers.
Yu B, Yang ZZ, Yao BZ. Real-Time Partway Deadheading Strategy Based on Transit Service Reliability Assessment. Transportation Research Part A. 2012;46(8):1265-1279.
Eberlein XJ, Wilson NHM, Bernstein B. The Holding Problem with Real-Time Information Available. Transportation Science. 2001;35(1):1-18.
Ceder A. Public Transit Planning and Operation Theory. Modeling and Practice. Oxford, UK: Elsevier; 2007.
Miller EJ, Bunt PD. Simulation model of shared right-of-way streetcar operations. Transportation Research Record. 1987;1152:31-41.
van Oort N, Wilson NHM, van Nes R. Reliability Improvement in Short Headway Transit Services: Schedule-Based and Headway-Based Holding Strategies. The 89th Annual Meeting of the Transportation Research Board. Hilton, Cabinet; 2010.
Fu L, Liu Q, Calamai P. Real-Time Optimization Model for Dynamic Scheduling of Transit Operations. Transportation Research Record. 2003;1897:48-55.
Strathman JG, Kimpel TJ, Ducker KJ, Gerhart RL, Turner K, Griffin D, Callas S. Bus transit operations control: Review and an experiment involving TRIMET’s automated bus dispatching system. Journal of Public Transportation. 2001;4:1-26.
Shen S, Wilson NHM. An optimal integrated real-time disruption control model for rail transit systems. In: Voss S, Daduna JR, editors. Computer-aided Scheduling of Public Transport. Lecture Notes in Economics and Mathematical Systems. Springer-Verlag, 2001; p. 335-364.
Guo G, Luo H, Lin X, Feng Ch. Headway-based Evaluation of Bus Service Reliability. Proceedings of the 14th International IEEE Conference on Intelligent Transportation Systems; 2011 Oct 5-7; Washington, DC, USA. p. 1864-1868.
Chen X, Yu L, Zhang Y, Guo J. Analyzing Urban Bus Service Reliability at the Stop, Route, and Network Levels. Transportation Research Part A. 2009;43(8):722-734.
Carrasco N. Quantifying Reliability of Transit Service in Zurich, Switzerland. Transportation Research Record: Journal of the Transportation Research Board. 2012;2274(1):114-125.
Lin J, Wang P, Barnum DT. A Quality Control Framework for Bus Schedule Reliability. Transportation Research Part E. 2008;44(6):1086-1098.
Casello JM, Nour A, Hellinga B. Quantifying Impacts of Transit Reliability on User Costs. Transportation Research Record. 2009;2112(145):136-141.
Zhao J, Dessouky M, Bukkapatnam S. Optimal Slack Time for Schedule-Based Transit Operations. Transportation Science. 2006;40(4):529-539.
Ceder A, Stern HI. Deficit Function Bus Scheduling with Deadheading Trip Insertions for Fleet Size Reduction. Transportation Science. 1981;15(4):338-363.
Xuan YG, Argote J, Daganzo CF. Dynamic bus holding strategies for schedule reliability: Optimal linear control and performance analysis. Transportation Research Part B. 2011;45(10):1831-1845.
Sorratini JAP, Liu R, Sinha S. Assessing Bus Transport Reliability Using Micro-Simulation. Transportation Planning and Technology. 2008;31(3):303-324.
Ding Y, Chien SI. Improving transit service quality and headway regularity with real-time control. Transit. 2001;1760: 161-170.
Milla F, Saez D, Cortes CE, Cipriano A. Bus-Stop Control Strategies Based on Fuzzy Rules for the Operation of a Public Transport System. IEEE Transactions on Intelligent Transportation Systems. 2012;13(3):1394-1403.
Teng J, Xu R. Bus Dispatching Strategies in Urban Rail Emergent Events. Journal of the China Railway Society. 2010;32(5):13-17.
Van Oort N, van Nes R. Regularity Analysis for Optimizing Urban Transit Network Design. Public Transp. 2009;1(2):155-168.
Fu LP, Yang XH. Design and implementation of bus-holding control strategies with real-time information. Transit. 2002;1791:6-12.
Dessouky M, Hall R, Zhang L, Singh A. Real-time Control of Buses for Schedule Coordination at A Terminal. Transportation Research Part A. 2003;37(2):145-164.
Eberlein XJ, Wilson NHM, Barnhart C, Bernstein D. The Real-Time Deadheading Problem in Transit Operations Control. Transportation Research Part B. 1998;32(2):77-100.
Wei M, Jin WZ, Sun B. Ant Colony Algorithm for Regional Bus Scheduling Problem. Journal of Highway and Transportation Research and Development. 2011;28(6):141-145,152.
Rossetti MD, Turitto T. Comparing Static and Dynamic Threshold Based Control Strategies. Transportation Research Part A. 1998;32(8):607-620.
Adamski A, Turnau A. Simulation Support Tool for Real-Time Dispatching Control in Public Transport. Transportation Research Part A. 1998;32(2):73-87.
Yu B, Yang ZZ, Yao BZ. Genetic Algorithm for Bus Frequency Optimization. Journal of Transportation Engineering. 2009;136(6):576-583.
Yao BZ, Hu P, Lu XH, Gao JJ, Zhang MH. Transit network design based on travel time reliability. Transportation Research Part C. 2014;43:233–248.
Yao BZ, Hu P, Zhang MH, Jin MQ. A Support Vector Machine with the Tabu Search Algorithm For Freeway Incident Detection. International Journal of Applied Mathematics and Computer Science. 2014;24(2):397-404.
Yao BZ, Hu P, Zhang MH, Tian XM. Improved Ant Colony Optimization for Seafood Product Delivery Routing Problem. Promet – Traffic & Transportation. 2014;26(1):1-10.
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