Bus Fleet Management – A Systematic Literature Review
Abstract
The research on Bus Fleet Management (BFM) has undergone significant changes. It is unclear whether these changes are accepted as technological change or as a paradigm shift. Perhaps unintentionally, BFM is still perceived as routing and scheduling by some, and by others as maintenance and replacement strategy. Therefore, the authors conducted a Systematic Literature Review (SLR) to overview the existing concepts and school of thoughts about how stakeholders perceive the BFM. The SLR post-study exposed that BFM should be acknowledged as a multi-realm system rather than a uniform dimension of fulfilling timely service. Nonetheless, the work encapsulates BFM evolution which shows the need for the multi-realm research abstracted as "Bus Fleet Mobility Management" and "Bus Fleet Asset Management". The difficulties of transport agencies and their ability to switch from conventional to Zero-Emission Buses (ZEBs) illustrates why we propose such an agenda, by which the research is validated through needs both in academia and in practice.
References
European Commission. Transport sector economic analysis. 2011. Available from: https://ec.europa.eu/jrc/en/research-topic/transport-sector-economic-analysis [cited 2019 Jun 5].
UITP. Urban Public Transport in 21st Century. Advancing Public Transport. 2017. p. 1–8. Available from: https://www.uitp.org/urban-public-transport-21st-century [cited 2018 Oct 22].
Galbieri R, Brito TLF, Mouette D, de Medeiros Costa HK, Moutinho dos Santos E, Fagá MTW. Bus fleet emissions: new strategies for mitigation by adopting natural gas. Mitig Adapt Strateg Glob Chang. 2018 Oct 12;23(7): 1039-62. Available from: http://link.springer.com/10.1007/s11027-017-9771-y
Jiménez F, Román A. Urban bus fleet-to-route assignment for pollutant emissions minimization. Transp Res Part E. 2016;85: 120-31.
Nurhadi L, Borén S, Ny H. Advancing from Efficiency to Sustainability in Swedish Medium-sized Cities: An Approach for Recommending Powertrains and Energy Carriers for Public Bus Transport Systems. Procedia - Soc Behav Sci. 2014 Feb;111: 1218-25. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1877042814000937
Worldbank. Transit Bus Operational and Maintenance Practices to Maximize Fuel Economy. 2011;(63116).
Bivona E, Montemaggiore GB. Understanding short- and long-term implications of “myopic” fleet maintenance polices: A system dynamics application to a city bus company. Syst Dyn Rev. 2010;26(3): 195-215.
Zhou Y, Kou G, Ergu D. Analysing Operating Data to Measure the Maintenance Performance. Qual Reliab Eng Int. 2014;31(2): 1-13.
Cats O, Jenelius E. Beyond a complete failure: The impact of partial capacity degradation on public transport network vulnerability. Transp B. 2016;6(2): 77-96. Available from: doi:10.1080/21680566.2016.1267596
Zhou C, Su Z, Hui Z. Bus Fleet Management System for BRT Based on Platform Screen Doors. In: Xinping Y, Ping Y, Chaozhong W, Ming Z, editors. Proceedings of the first International Conference on Transportation Information and Safety. Wuhan, China: American Society of Civil Engineers (ASCE); 2011. p. 26-32.
Osman MM, Sultana MR, Sulthana MS. Enhancement of Public Transportation Services Using Wireless Technologies. Int J Eng Trends Technol. 2013;6(7): 344-8. Available from: http://uta.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw3V09T8MwFLRKJxgQn-JT8sRSpWriNHEHBkBFraAg0TJHL7FNQE2K2vL_sWOncQoTMDFFsqVYzjudn1_OZ4SI1-44a5zACCEBBZr4jIpEeHHiMlZYucQBj6k6nPwwDp7ue5OBd9dolLelVW3_IfD9PFWRLH_y67pcZWIONYpoacmA0sBOFeetKu2ltvCtUrrXC4c
Vaughan ML, Faghri A, Li M. An Interactive Expert System Based Decision Making Model for the Management of Transit System Alternate Fuel Vehicle Assets. Intell Inf Manag. 2017;09(01): 1-20. Available from: doi:10.4236/iim.2017.91001
Wang Y, Huang Y, Xu J, Barclay N. Optimal recharging scheduling for urban electric buses: A case study in Davis. Transp Res Part E Logist Transp Rev. 2017;100: 115-32. Available from: doi:10.1016/j.tre.2017.01.001
Chen X, Han X, Yu L, Wei C. Does operation scheduling make a difference: Tapping the potential of optimized design for skipping-stop strategy in reducing bus emissions. Sustainability. 2017;9(10): 1-18.
Hauslen RA. The promise of automatic vehicle identification. IEEE Trans Veh Technol. 1977 Feb;26(1): 30-8. Available from: http://ieeexplore.ieee.org/document/1622353/
Roth SH. History of automatic vehicle monitoring (AVM). IEEE Trans Veh Technol. 1977 Feb;26(1): 2-6. Available from: http://ieeexplore.ieee.org/document/1622348/
Maze TH, Cook AR, Dutta U. Bus Fleet Management Techniques Guide. Oklahoma, US; 1985.
Belmonte M, Fern A, Rey U, Carlos J. Agent Coordination for Bus Fleet Management. In: ACM Symposium on Applied Computing. 2005. p. 462-6.
Belmonte MV, Perez-de-la-Cruz JL, Triguero F. Ontologies and agents for a bus fleet management system. Expert Syst Appl. 2008;34: 1351-65.
Fernandez A, Ossowski S. A Multiagent Approach to the Dynamic Enactment of Semantic Transportation Services. IEEE Trans Intell Transp Syst. 2011 Jun;12(2): 333-42. Available from: http://ieeexplore.ieee.org/document/5710583/
Ossowski S, Hernandez JZ, Belmonte MV, Maseda J, Fernandez A, Serrano-Garcia A. Multi-agent systems for decision support: A case study in the transportation management domain. Appl Artifical Intell. 2004;18: 779-95.
Gao D, Jin Z, Zhang J, Li J, Ouyang M. Comparative study of two different powertrains for a fuel cell hybrid bus. J Power Sources. 2016;319: 9-18. Available from: doi:10.1016/j.jpowsour.2016.04.046
Gallet M, Massier T, Hamacher T. Estimation of the energy demand of electric buses based on real-world data for large-scale public transport networks. Appl Energy. 2018;230(January): 344-56. Available from: doi:10.1016/j.apenergy.2018.08.086
Holmberg K, Andersson P, Nylund NO, Mäkelä K, Erdemir A. Global energy consumption due to friction in trucks and buses. Tribol Int. 2014;78: 94-114. Available doi:10.1016/j.triboint.2014.05.004
Vepsäläinen J, Kivekäs K, Otto K, Lajunen A, Tammi K. Development and validation of energy demand uncertainty model for electric city buses. Transp Res Part D Transp Environ. 2018;63(June): 347-61. Available from: doi:10.1016/j.trd.2018.06.004
Ngo HH, Shah R, Mishra S. Optimal asset management strategies for mixed transit fleet. Transp Res Part A Policy Pract. 2018;117(October 2017): 103-16. Available from: doi:10.1016/j.tra.2018.08.013
Vaughan ML. Decision making model for the management of transit system alternative fuel infrastructures through the utilization of an interactive expert system interface. University of Delaware; 2017.
Stasko TH, Oliver Gao H. Developing green fleet management strategies: Repair/retrofit/replacement decisions under environmental regulation. Transp Res Part A Policy Pract. 2012 Oct;46(8): 1216-26. Available from: doi:10.1016/j.tra.2012.05.012
APTA. Bus Fleet Management in an Era of Increasing Technical Complexity: Analysis of Bus Fleet Spare Ratios; 2009. Available from: https://www.apta.com
Feng W, Figliozzi MA. Vehicle technologies and bus fleet replacement optimization: Problem properties and sensitivity analysis utilizing real-world data. Public Transp. 2014;6(1-2): 137-57.
Boudart JA. Bus Replacement Modeling and the Impacts of Budget Constraints, Fleet Cost Variability, and Market Changes on Fleet Costs and Optimal Bus Replacement Age, A Case Study. Portland State University; 2011.
Mishra S, Mathew TV, Khasnabis S. Single-Stage Integer Programming Model for Long-Term Transit Fleet Resource Allocation. J Transp Eng. 2010 Apr;136(4): 281-90. Available from: doi:10.1061/%28ASCE%290733-947X%282010%29136%3A4%28281%29
Pozhivilov N, Automobile MS, Kavalchuk I. The technique of optimal leasing duration estimation for the city bus using technical and economical parameters. SEE-Mie2015, Japan First International Conference on Science, Engineering & Environment (SEE), 19-21 November 2015,Tsu City, Mie, Japan; 2015. p. 1-7.
Hounsell NB, Shrestha BP, Wong A. Data management and applications in a world-leading bus fleet. Transp Res Part C Emerg Technol. 2012 Jun;22: 76-87. Available doi:10.1016/j.trc.2011.12.005
D’Souza C, Hounsell NB, Shrestha BP. Using automatic vehicle location (AVL) data for evaluation of bus priority at traffic signals. IET and ITS Conference on Road Transport Information and Control (RTIC 2012). London, UK: Institution of Engineering and Technology; 2012. p. 21-21. Available from: https://digital-library.theiet.org/content/conferences/10.1049/cp.2012.1550
Polyviou P, Hounsell N, Shrestha B. Modelling incidents for dynamic bus fleet management purposes: A UK perspective. Transp Plan Technol. 2012 Feb;35(1): 49-67. Available from: doi:10.1080/03081060.2012.635416
Cats O, Loutos G. Real-Time Bus Arrival Information System: An Empirical Evaluation. J Intell Transp Syst Technol Planning, Oper. 2016;20(2): 138-51.
Southworth F, Meyer MD, Weigel BA. Transit Greenhouse Gas Emissions Management Compendium. Atlanta, GA, USA: Federal Transit Administration; 2011. Available from: http://www.fta.dot.gov/research
Riechi J, Mácian V, Tormos B, Avila C. Optimal fleet replacement: A case study on a Spanish urban transport fleet. J Oper Res Soc. 2017 Aug 21;68(8): 886-94. Available from: doi:10.1057/s41274-017-0236-1
Mishra S, Sharma S, Khasnabis S, Mathew TV. Preserving an aging transit fleet: An optimal resource allocation perspective based on service life and constrained budget. Transp Res Part A Policy Pract. 2013;47: 111-23. Available from: doi:10.1016/j.tra.2012.10.029
Yu Q, Li T, Li H. Improving urban bus emission and fuel consumption modeling by incorporating passenger load factor for real world driving. Applied Energy. 2016;161: 101-11.
Li L, Lo HK, Xiao F, Cen X. Mixed bus fleet management strategy for minimizing overall and emissions external costs. Transp Res Part D Transp Environ. 2018 May;60: 104-18. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1361920916306757
Li L, Lo HK, Xiao F, Cen X. Green mixed bus fleet management strategy. In: Transport and Society - Proceeding of the 22nd International Conference of Hong Kong Society for Transportation Studies, HKSTS 2017; 2017.
Li L, Lo HK, Cen X. Optimal bus fleet management strategy for emissions reduction. Transp Res Part D Transp Environ. 2015;41: 330-47.
De A, Do N. Integrating Electric Buses in Conventional Public Transit: A First Appraisal. Universidade do Porto; 2016.
Emiliano W, Costa L, Carvalho M do S, Telhada J. Bus Fleet Management Optimization Using the Augmented Weighted Tchebycheff Method. In: Vaz AIF, Almeida JP, Olivieira JF, Pinto AA, editors. Operational Research. Valença, Portugal: Springer; 2018. p. 201-13.
Emiliano W, Costa L, Carvalho SM, Telhada J, Lanzer EA. Multiobjective optimization of transit bus fleets with alternative fuel options: The case of Joinville, Brazil. Int J Sustain Transp. 2019;0(0): 1-11. Available from: doi:
1080/15568318.2018.1518500
Zhen F. Optimization Tool for Transit Bus Fleet Management. West Virginia University; 2012.
Filippone F, Pugliese M, Manager L, Italia B, Roma SA. TLC facilities applied to the management of an integrated system of public and private mobility in a large city. 5th International Congress on Energy, Environment and Technological Innovation EETI 2004. Rio de Janeiro, Brazil; 2004. p. 1-6.
KonSULT. Bus Fleet Management Systems. Policy Instruments: A policy Guidebook. 2016. Available from: http://www.konsult.leeds.ac.uk/pg/34/ [cited 2019 Feb 3].
Zhou C. Platform Screen Doors Enhanced Bus Rapid Transit Intelligent Performance. Int J Inf Eng Electron Bus. 2011;3: 52-9.
Perhinschi MG, Marlowe C, Tamayo S, Tu J, Wayne WS. Evolutionary Algorithm for Vehicle Driving Cycle Generation. J Air Waste Manage Assoc. 2011 Sep 29;61(9): 923-31. Available from: doi:10.1080/10473289.2011.596742
Vaughan ML, Faghri A, Li M. Knowledge-based decision-making model for the management of transit system alternative fuel infrastructures. Int J Sustain Dev World Ecol. 2018 Feb 17;25(2): 184-94. Available from: doi:10.1080/13504509.2017.1333541
Krawiec S, Karoń G, Janecki R, Sierpiński G, Krawiec K, Markusik S. Economic Conditions to Introduce the Battery Drive to Busses in the Urban Public Transport. Transp Res Procedia. 2016;14: 2630-9. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2352146516304264
Yoshioka LR, Santos GHR, Costa RD, Vas A. Case Studies of the Fleet Operational Efficiency Gains through Onboard Intelligence and Managerial Processes. SAE Technical Paper 2010-36-0332, 2010. p. 1-12. Available from: https://www.sae.org/content/2010-36-0332/
Gong J, Wu C. A transit fleet replacement model for emissions reduction. Proceedings of 2011 IEEE International Conference on Service Operations, Logistics and Informatics; 2011. p. 22-5.
Achimugu P, Selamat A, Ibrahim R, Naz M. A systematic literature review of software requirements prioritization research. Inf Softw Technol. 2014;56(6): 568-85. Available doi:10.1016/j.infsof.2014.02.001
Tranfield D, Denyer D, Smart P. Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review. Br J Manag. 2003 Sep;14(3): 207-22. Available from: doi:10.1111/1467-8551.00375
Cronin P, Ryan F, Coughlan M. Undertaking a Literature Review: A step-by-step approach. Br J Nurs. 2004;17(1): 38-43.
Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med. 2009 Jul 21;6(7): e1000097. Available from: doi:10.1371/journal.pmed.1000097
Ferreira ML, de Gouveia JAM, Fachchini E, Pokorny MS, Dias EM. Real time monitoring of public transit passenger flows through Radio Frequency Identification - RFID technology embedded in fare smart cards. Latest Trends Syst. 2012;II: 599-605.
Cai X. Collaborative prediction for bus arrival time based on CPS. J Cent South Univ. 2014 Mar 16;21(3): 1242-8. Available from: http://link.springer.com/10.1007/s11771-014-2058-5
Mohamed M, Ferguson M, Kanaroglou P. What hinders adoption of the electric bus in Canadian transit? Perspectives of transit providers. Transp Res Part D. 2018;64(August 2017): 134-49. Available from: doi:10.1016/j.trd.2017.09.019
Rogge M, Wollny S, Sauer D. Fast Charging Battery Buses for the Electrification of Urban Public Transport—A Feasibility Study Focusing on Charging Infrastructure and Energy Storage Requirements. Energies. 2015 May 21;8(5): 4587-606. Available from: http://www.mdpi.com/1996-1073/8/5/4587
Rogge M, van der Hurk E, Larsen A, Sauer DU. Electric bus fleet size and mix problem with optimization of charging infrastructure. Appl Energy. 2018;211(February 2017): 282-95. Available from: doi:10.1016/j.apenergy.2017.11.051
Li L, Lo HK, Xiao F, Cen X. Mixed bus fleet management strategy for minimizing overall and emissions external costs. Transp Res Part D Transp Environ. 2018;60: 104-18.
Stasko TH, Oliver Gao H. Reducing transit fleet emissions through vehicle retrofits, replacements, and usage changes over multiple time periods. Transp Res Part D Transp Environ. 2010 Jul;15(5): 254-62. Available from: doi:10.1016/j.trd.2010.03.004
Nasibov E, Eliiyi U, Erac MO, Kuvvetli U. Deadhead trip minimization in city bus transportation: A real life application. Promet – Traffic&Transportation. 2013;25(2): 137-45.
Cats O, Loutos G. Evaluating the added-value of online bus arrival prediction schemes. Transp Res Part A Policy Pract. 2016;86: 35-55. Available from: doi:10.1016/j.tra.2016.02.004
Fletcher G, El-Geneidy A. Effects of Fare Payment Types and Crowding on Dwell Time. Transp Res Rec J Transp Res Board. 2013 Jan;2351(1): 124-32. Available from: doi:10.3141/2351-14
Guirao B, García A, López M, Acha C, Comendador J. New QR Survey Methodologies to Analyze User Perception of Service Quality in Public Transport: The Experience of Madrid. J Public Transp. 2015 Sep;18(3): 71-88. Available from: http://scholarcommons.usf.edu/jpt/vol18/iss3/5/
Hosseini-Motlagh S-M, Ahadpour P, Haeri A. Proposing an approach to calculate headway intervals to improve bus fleet scheduling using a data mining algorithm. 2015;8(4): 72-86.
Zhang L, Liang W, Zheng X. Eco-Driving for Public Transit in Cyber-Physical Systems Using V2I Communication. Int J Intell Transp Syst Res. 2018;16(2): 79-89.
Polyviou P. A new micro-simulation approach to model the impacts of bus and traffic incidents on bus performance - The bus operators’ perspective. European Transport Conference, 10-12 October 2011, Glasgow, UK. Association for European Transport and Contributors; 2011. p. 1-14.
Kumara BH. Planning for Bus Rapid Transit System (BRTS) in Indian Metropolitan Cities: Challenges and
options. Inst T Planners, India J. 2009;6(4): 9-21.
Ardila DS, Parker B, Perry D. Policy mobilities and urban change: The case of bus rapid transit in Colombia.
University of Illinois Chicago; 2016.
Misanovic S, Zivanovic Z, Tica S. Energy efficiency of different bus subsystems in Belgrade public transport. Therm Sci. 2015;19(6): 2233-44. Available from: http://www.doiserbia.nb.rs/Article.aspx-?ID=0354-98361500193M
Li D, Li L, Meng H, Zhang W. Integrated Dynamic Transit Operation System for Multimodal Suburban Transit.
21st International Conference on Intelligent Transportation Systems (ITSC), 4-7 Nov. 2018, Maui, HI, USA. IEEE; 2018. p. 3662-7. Available from: https://ieeexplore.ieee.org/document/8569231
D’Souza C, Gardner K, Hounsell NB, Shrestha BP. New developments for bus priority at traffic signals in London using iBus. IET Road Transport Information and Control Conference and the ITS United Kingdom Members’ Conference (RTIC 2010) Better transport through technology. IET; 2010. p. 72-72. Available from: doi:0.1049/cp.2010.0386#
Predic B, Rancic D, Milosavljevic A. Impacts of applying automated vehicle location systems to public bus transport management. J Res Pract Inf Technol. 2010;42(2): 79-98.
Wong A, Hounsell N. Using the iBus system to provide improved public transport information and applications for London. 12th WCTR. Lisbon, Portugal; 2010. p. 1-10.
Beltrán P, Gschwender A, Palma C. The impact of compliance measures on the operation of a bus system: The case of Transantiago. Res Transp Econ. 2013 Mar;39(1): 79-89. Available from: doi:10.1016/j.retrec.2012.05.026
Tang C, Ceder A, Ge Y. Optimal public-transport operational strategies to reduce cost and vehicle’s emission. PLoS One. 2018;13(8): 1-17.
Zhang Q. Simulation of Agent-Based of Intelligent Public Transit System. Proceedings of 2011 International Conference on Electronic Engineering, Communication and Management, Beijing, China. Springer; 2012. p. 129-35. Available from: doi:10.1007/978-3-642-27296-7_21
Chao Z, Xiaohong C. Optimizing Battery Electric Bus Transit Vehicle Scheduling with Battery Exchanging: Model and Case Study. Procedia - Soc Behav Sci. 2013 Nov;96(Cictp): 2725-36. Available from: http://linkinghub.
elsevier.com/retrieve/pii/S1877042813024324
Zhen F. Optimization tool for transit bus fleet management. West Virginia University; 2012.
Alam A, Hatzopoulou M. Reducing transit bus emissions: Alternative fuels or traffic operations? Atmos Environ. 2014 Jun;89: 129-39. Available from: doi:10.1016/j.atmosenv.2014.02.043
Santos D, Kokkinogenis Z, Sousa JF De, Perrotta D, Rossetti RJF, Ieee M. Towards the Integration of Electric Buses in Conventional Bus Fleets. 19th International Conference on Intelligent Transportation Systems (ITSC), Rio de Janeiro, Brazil. IEEE; 2016. p. 88-93.
Lajunen A. Energy consumption and cost-benefit analysis of hybrid and electric city buses. Transp Res Part C Emerg Technol. 2014;38: 1-15. Available from: doi:10.1016/j.trc.2013.10.008
Lajunen A. Lifecycle costs and charging requirements of electric buses with different charging methods. J Clean Prod. 2018 Jan;172: 56-67. Available from: doi:10.1016/j.jclepro.2017.10.066
Lajunen A, Lipman T. Lifecycle cost assessment and carbon dioxide emissions of diesel, natural gas, hybrid
electric, fuel cell hybrid and electric transit buses. Energy. 2016 Jul;106: 329-42. Available from: doi:10.1016/j.
energy.2016.03.075
Xylia M, Leduc S, Patrizio P, Kraxner F, Silveira S. Locating charging infrastructure for electric buses in Stockholm. Transp Res Part C Emerg Technol. 2017 May;78: 183-200. Available from: doi:10.1016/j.trc.2017.03.005
Paul T, Yamada H. Operation and charging scheduling of electric buses in a city bus route network. 17th IEEE International Conference on Intelligent Transportation Systems (ITSC), 8-11 Oct. 2014, Qingdao, China; 2014. p. 2780-6.
Mathew TV, Khasnabis S, Mishra S. Optimal resource allocation among transit agencies for fleet management. Transp Res Part A Policy Pract. 2010 Jul;44(6): 418-32. Available from: doi:10.1016/j.tra.2010.03.016
Li S, Kahn ME, Nickelsburg J. The Political Economy of Public Bus Procurement: The Role of Regulation, Energy Prices and Federal Subsidies; 2013.
Li S, Kahn ME, Nickelsburg J. Public transit bus procurement: The role of energy prices, regulation and federal subsidies. J Urban Econ. 2015 May;87: 57-71. Available from: doi:10.1016/j.jue.2015.01.004
Mohamed M, Farag H, El-Taweel N, Ferguson M. Simulation of electric buses on a full transit network: Operational feasibility and grid impact analysis. Electr Power Syst Res. 2017;142: 163-75. Available from: doi:10.1016/j.epsr.2016.09.032
Bi Z, De Kleine R, Keoleian GA. Integrated Life Cycle Assessment and Life Cycle Cost Model for Comparing Plug-in versus Wireless Charging for an Electric Bus System. J Ind Ecol. 2017 Apr;21(2): 344-55. Available from: doi:10.1111/jiec.12419
Gabsalikhova L, Sadygova G, Almetova Z. Activities to convert the public transport fleet to electric buses. Transp Res Procedia. 2018;36: 669-75. Available from: doi:10.1016/j.trpro.2018.12.127
European Commission. Orientations Towards the First Strategic Plan for Horizon Europe; 2019. p. 1-164. Available from: https://ec.europa.eu/info/sites/info/files/research_and_innovation/strategy_on_research_
and_innovation/documents/ec_rtd_he-orientations-towards-strategic-plan_102019.pdf [cited 2019 Dec 3].
ZEB. 2018 European Zero Emission Bus Conference Report. JIVE 2; 2018. p. 2018-20. Available from: http://
zebconference.com/wp-content/uploads/2019/02/Appendix-3-Conference-Report.pdf [cited 2019 Mar 25].
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