Abstract
Bus regularity is a crucial factor for high frequency public transport systems, because it represents a relevant measure of quality of service for both users and transit agencies. Low regularities for users are associated with bunching phenomena or large gaps between buses, which result in low attractiveness of the service for transit agencies. Therefore, evaluating the regularity is extremely desirable, but may also be a complex task in medium-size cities due to the huge amount of data which must be collected and processed effectively. Automatic Vehicle Location (AVL) technologies, which are particularly used by transit agencies in Western Europe, can address the data collection problem, but they involve several challenges such as correcting anomalies in collected raw data and processing information efficiently. In this paper, we propose a method to automatically handle AVL raw data for measuring the Level of Service (LoS) of bus regularity at each bus stop and time interval of any high frequency route. The results are represented by easy-to-read control dashboards and graphs. We discuss the experimentation of this method in a real case study to provide insights into the detailed characterization of bus regularity. The method is applied to data obtained from the transport agency CTM in Cagliari (Italy), whose vehicles are all equipped with AVL technologies.
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References
Balcome R, Mckett R, Pulley N, Preston J, Shires J, Titheridge H, Wardman M, White P (2004) The demand for public transport: a practical guide. TRL report, TRL 593, TRL Limited
Barabino B, Corona G, Tilocca P (2008) A telematic platform to manage private and public transport: a case study in Italy. In: Proceedings of the Transport Research Arena Europe, April 2008, Ljubljana, Slovenia
Bates J, Polak J, Jones P, Cook A (2001) The valuation of reliability for personal travel. Transp Res, Part E, Logist Transp Rev 37(2):191–229
Berkow M, El-Geneidy A, Bertini RL, Crout D (2009) Beyond generating performance measures: visualizations and statistical analysis using historical data. Transp Res Rec 2111:158–168
Bertini RL, El-Geneidy A (2003) Using archived data to generate transit performance measures. Transp Res Rec 1841:109–119
Ceder A (2007) Public transit planning and operation. Theory, modelling and practice. Elsevier, Amsterdam
CEN/TC 320 (2002) Transportation—logistics and services. European Standard EN 13816: Public passenger transport—service quality definition, targeting and measurement. European Committee for Standardization, Brussels
CEN/TC 320 (2006) Transportation—logistics and services. European Standard EN 15140: Public passenger transport—basic requirements and recommendation for systems that measure delivered service quality. European Committee for Standardization, Brussels
Cham L (2006) Understanding bus service reliability: a practical framework using AVL/APC data. Master’s Thesis, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology
Chen X, Yu L, Zhang Y, Gou J (2009) Analyzing urban bus service reliability at the stop, route, and network levels. Transp Res, Part A, Policy Pract 43(8):722–734
Daganzo CF, Pilachowski J (2011) Reducing bunching with bus-to-bus cooperation. Transp Res, Part B, Methodol 45(1):267–277
Dalla Chiara B (2010) Role of automatic vehicle location systems and localization accuracy in freight transport: an analytical estimation of gained operational times. IET Intell Transp Syst 4:365–374. doi:10.1049/iet-its.2009.0138
Fattouche G (2011) How to improve high-frequency bus service reliability through scheduling. In: Proceedings of the ITRN, 31st August–1st September, University College Cork
Furth PG, Muller THJ (2006) Service reliability and hidden waiting time: insights from automated vehicle location data. Transp Res Rec 1955:79–87
Furth P, Muller THJ, Strathman J, Hemily B (2004) Designing automated vehicle location systems for archived data analysis. Transp Res Rec 1887:62–70
Furth P, Hemily B, Muller T, Strathman J (2006) Using archived AVL-APC data to improve transit performance and management. Transit Cooperative Research Program Report 113. TRB, Washington
Henderson G, Adkins H, Kwong P (1990) Toward a passenger-oriented model of subway performance. Transp Res Rec 1266:221–228
Hounsell NB, Shrestha BP (2005) AVL based bus priority at traffic signals: a review and case study of architectures. Eur J Transp Infrastruct Res 5(1):13–29
Kittelson & Associates Inc, Urbitran Inc, LKC consulting services Inc, Morpace International Inc, Queensland University of Technology, Nakanishi Y (2003a) A guidebook for developing a transit performance-measurement system. Transit cooperative research program report, vol 88. TRB, Washington
Kittelson & Associates Inc, KFH Group Inc, Parsons Brinckerhoff Quade & Douglass Inc, Zaworski KH (2003b) Transit capacity and quality of service manual, 2nd edn. TRB, Washington
Lin J, Wang ML, Barnum PD (2008) A quality control framework for bus schedule reliability. Transp Res, Part E, Logist Transp Rev 44(6):1086–1098
Liu R, Sinha S (2007) Modeling urban bus service and passenger reliability. In: Proc of the international symposium on transportation network reliability. The Hague, Netherlands
Mandelzys M, Hellinga B (2010) Identifying causes of performance issues in bus schedule adherence with automatic vehicle location and passenger count data. Transp Res Rec 2143:9–15
Marguier PHJ, Ceder A (1984) Passenger waiting strategies for overlapping bus routes. Transp Sci 18(3):207–230
McKone T, Partridge E, Martin J (2009) Eliminating bus bunching—building a process, information source, and tool box for improving service. In: Bus & paratransit conference & international bus roadeo/bus rapid transit conference, Seattle
McLeod FN (2007) Estimating bus passenger waiting times from incomplete bus arrivals data. J Oper Res Soc 58(11):1518–1525
Muller THJ, Furth P (2001) Trip time analyzers: key to transit service quality. Transp Res Rec 1760:10–19
Muller THJ, Knoppers P (2005). TRIp time analysis in public transport. http://tritapt.nl/
Nakanishi YJ (1997) Bus performance indicators. Transp Res Rec 1571:3–13
Ruan M, Lin J (2009) An investigation of bus headway regularity and service performance in Chicago bus transit system. Paper presented at the Transport Chicago, annual conference
Seddon PA, Day MP (1974) Bus passenger waiting times in Greater Manchester. Traffic Engineering and Control, January 15:442–445
Strathman JG, Kimpel TJ, Callas S (2003) Headway deviation effects on bus passenger loads: analysis of Tri-Met’s archived AVL-APC data. Technical Report PR126, Center for Urban Studies, Portland, OR
Trompet M, Liu X, Graham DJ (2011) Development of a key performance indicator to compare regularity of service between urban bus operators. Transp Res Rec 2216:33–41
Turnquist MA (1982) Strategies for improving bus transit service reliability. Transp Res Rec 818:7–13
van Oort N (2011) Service reliability and urban public transport design. PhD thesis, Delft University of Technology
van Oort N, van Nes R (2009) Regularity analysis for optimizing urban transit network design. Public Transp 1(2):155–168. doi:10.1007/S12469-009-0012-y
Acknowledgements
The authors want to thank three anonymous referees for their helpful comments, which contributed to improve this paper. The authors are also grateful to CTM.SpA for its investments in ITS, its support to this research and the possibility to use its real data for the the experimentation.
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Barabino, B., Di Francesco, M. & Mozzoni, S. Regularity diagnosis by Automatic Vehicle Location raw data. Public Transp 4, 187–208 (2013). https://doi.org/10.1007/s12469-012-0059-z
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DOI: https://doi.org/10.1007/s12469-012-0059-z