Skip to main content
Log in

A smartphone based DSS platform for assessing transit service attributes

  • Original Paper
  • Published:
Public Transport Aims and scope Submit manuscript

Abstract

This paper presents a methodology for determining public transportation quality attributes, based on a decision support system (DSS). The platform, once set up, combines the capability of geographic information systems (GIS) to analyze spatial attributes and the smartphone mobile technology, which is a “smart” solution to collect dynamically bus locations and their cinematic variables. The DSS has been applied to a real case study in order to test its reliability. The results highlight a good flexibility of the platform combined with a good level of scalability and interoperability of the system that can be applied in any context. Moreover, the high penetration rate of smartphones among users and the system capability of disaggregating data in both space and time, makes the DSS useful to identify operational problems and take appropriate actions with a non-intrusive approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Abrate G, Piacenza M, Vannoni D (2009) The impact of integrated tariff systems on public transport demand: evidence from Italy. Reg Sci Urban Econ 39(2):120–127

    Article  Google Scholar 

  • Algers S, Hansen S, Tegner G (1975) Role of waiting time, comfort, and convenience in modal choice for work trip. Transp Res Rec 534:38–51

    Google Scholar 

  • Alshalalfah BW, Shalaby AS (2007) Case study: relationship of walk access distance to transit with service, travel, and personal characteristics. J Urban Plan Develop 133(2):114–118

    Article  Google Scholar 

  • Atkins S, Bottom C, Sheldon R, Heywood C, Warman P (1994) Passenger information at bus stops (PIBS): results from the London countdown route 18 monitoring study. In: Proceedings of seminar E held at the 22nd PTRC European Transport Forum, vol P377. University of Warwick, England, pp 61–72

    Google Scholar 

  • Balogh S, Smith R (1992) Real-time bus information-the London transport Route 18 demonstration. In: Proceedings of the 20th PTRC European Transport, Highways and Planning Annual Meeting, PTRC Education Research Services Ltd, Glenthorne House, Hammersmith Grove, London, United Kingdom, pp 195–206

  • Beirão G, Sarsfield Cabral JA (2007) Understanding attitudes towards public transport and private car: a qualitative study. Transp Policy 14(6):478–489

    Article  Google Scholar 

  • Berry LL, Zeithaml VA, Parasuraman A (1990) Five imperatives for improving service quality. Sloan Manag Rev Summer 31(4):29–38

    Google Scholar 

  • Bertini RL, El-Geneidy AM (2003) Generating transit performance measures with archived data. Transp Res Rec 1841:109–119

    Article  Google Scholar 

  • Bertini RL, Tantiyanugulchai S (2004) Transit buses as traffic probes: use of geolocation data for empirical evaluation. Transp Res Rec 1870:35–45

    Article  Google Scholar 

  • Bierlaire M, Chen J, Newman J (2010) Modeling route choice behavior from smartphone GPS data. Report TRANSP-OR 101016, Transport and Mobility Laboratory, Ecole Polytechnique Fédérale de Lausanne

  • Bierlaire M, Chen J, Newman J (2013) A probabilistic map matching method for smartphone GPS data. Transp Res Part C Emerg Technol 26:78–98

    Article  Google Scholar 

  • Cantwell M, Caulfield B, O’Mahony M (2009) Examining the factors that impact public transport commuting satisfaction. J Public Transp 12(2):21–37

    Article  Google Scholar 

  • Carroll A, Heiser G (2010) An analysis of power consumption in a smartphone. In: Proceedings of the 2010 USENIX conference on USENIX annual technical conference, pp 21–35

  • Carstensen LW Jr (2013) GPS and GIS: enhanced accuracy in map matching through effective filtering of autonomous GPS points. Cartogr Geogr Inf Sys 25(1):1998

    Google Scholar 

  • Caulfield B, O’Mahnoy M (2009) A stated preference analysis of real-time public transit stop information. J Public Transp 12(3):1–20

    Article  Google Scholar 

  • Ceder A (2007) Public transit planning and operation. Theory, modelling and practice. Elsevier, Butterworth-Heinemann, Oxford

    Google Scholar 

  • Cham LC (2006) Understanding bus service reliability: a practical framework using AVL/APC data. Thesis (S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering

  • Chien SI, Qin Z (2004) Optimization of bus stop locations for improving transit accessibility. Transp Plan Technol 27(3):211–227

    Article  Google Scholar 

  • Dargay J, Pekkarinen S (1997) Public transport pricing policy: empirical evidence of regional bus card systems in Finland. Transp Res Rec 1604(1):146–152

    Article  Google Scholar 

  • dell’Olio L, Ibeas A, Cecin P (2011) The quality of service desired by public transport users. Transp Policy 18(1):217–227

    Article  Google Scholar 

  • Dziekan K, Kottenhoff K (2007) Dynamic at-stop real-time information displays for public transport: effects on customers. Transp Res 41A(6):489–501

    Google Scholar 

  • Eboli L, Mazzulla G (2010) How to capture the passengers’ point of view on a transit service through rating and choice options. Transp Rev 30:435–450

    Article  Google Scholar 

  • Feng W, Figliozzi M (2011) Using archived AVL-APC bus data to identify spatial-temporal causes of bus bunching. In: Proceedings of the 90th Annual Meeting of Transportation Research Board, Washington

  • FitzRoy F, Smith I (1998) Public transport demand in Freiburg: why did patronage double in a decade? Transp Policy 5(3):163–173

    Article  Google Scholar 

  • Fujii S, Kitamura R (2003) What does a 1-month free bus ticket do to habitual drivers? An experimental analysis of habit and attitude change. Transportation 30(1):81–95

    Article  Google Scholar 

  • Furth P, Hemily B, Muller T, Strathman J (2006) TCRP Report 113: using archived AVL-APC data to improve transit performance and management. Transportation Research Board of the National Academies, Washington

    Google Scholar 

  • Hans R, Burgstahler D, Mueller A, Zahn M, Stingl D (2015) Knowledge for a longer life: development impetus for energy-efficient smartphone applications. In: 2015 IEEE International Conference on Mobile Services, pp 128–133

  • Hensher DA, Prioni P (2002) A service quality index for area-wide contract performance assessment. J Transp Econ Policy 36(1):93–113

    Google Scholar 

  • Hickman MD, Wilson NHM (1995) Passenger travel time and path choice implications of real-time transit information. Transp Res 3C(4):211–226

    Google Scholar 

  • Huang FM, Huang YH, Szu C, Su AYS, Chen MC, Sun YS (2015) A study of a life logging smartphone app and its power consumption observation in location-based service scenario. In: 2015 IEEE International Conference on Mobile Services, pp 225–232

  • Ingalls GL, Hartgen DT, Owens TW (1994) Public fear of crime and its role in bus transit use. Transp Res Rec 1433:201–211

    Google Scholar 

  • Iseki H, Taylor BD (2010) Style versus Service? An analysis of user perceptions of transit stops and stations. J Public Transp 13(3):23–48

    Article  Google Scholar 

  • Ji J, Gao X (2010) Analysis of people’s satisfaction with public transportation in Beijing. Habitat Int 34:464–470

    Article  Google Scholar 

  • Kumar SV, Vanajakshi L (2014) Urban arterial travel time estimation using buses as probes. Arab J Sci Eng 39(11):7555–7567

    Article  Google Scholar 

  • Levinson H, Zimmerman S, Clinger J, Rutherford S, Smith RL, Cracknell J, Soberman R (2003) Bus Rapid transit volume 1: case studies in bus rapid transit. Transport Cooperative Research Program Report 90. Washington

  • Lin J, Wang P, Barnum DT (2007) A quality control framework for bus schedule reliability. Transp Res Part E 44:1086–1098

    Article  Google Scholar 

  • Litman T (2005) Terrorism, transit and public safety: evaluating the risks. J Public Transp 8(4):33–44

    Article  Google Scholar 

  • Litman T (2008) Valuing transit service quality improvements. J Public Transp 11(2):43–63

    Article  Google Scholar 

  • Loader C, Stanley J (2009) Growing bus patronage and addressing transport disadvantage—the Melbourne experience. Transp Policy 16(3):106–114

    Article  Google Scholar 

  • Ma X, Wang Y (2014) Development of a data-driven platform for transit performance measures using smart card and GPS data. J Transp Eng 140(12):1–12

    Article  Google Scholar 

  • Ma M, Yan X, Huang H, Abdel-Aty M (2010) Safety of public transportation occupational drivers. Transp Res Rec 2145(3):72–79

    Article  Google Scholar 

  • Mane PS, Khairnar V (2013) Power efficient location based services on smart phones. Int J Emerg Technol Adv Eng 3(10):350–354

    Google Scholar 

  • Mesbah M, Currie G, Lennon C, Northcott T (2012) Spatial and temporal visualization of transit operations performance data at a network level. J Transp Geogr 25:15–26

    Article  Google Scholar 

  • Murray AT (2001) Strategic analysis of public transport coverage. Socio Econ Plan Sci 35(3):175–188

    Article  Google Scholar 

  • Murray AT, Davis R, Stimson RJ, Ferreira L (1998) Public transportation access. Transp Res Part D 3(5):319–328

    Article  Google Scholar 

  • Nathanail E (2008) Measuring the quality of service for passengers on the Hellenic railways. Transp Res Part A 42:48–66

    Google Scholar 

  • Oshin TO, Poslad S, Ma A (2012) Improving the energy-efficiency of GPS based location sensing smartphone applications. In: 11th International Conference on Trust, Security and Privacy in Computing and Communications, pp 1698–1705

  • Paek J, Kim J, Govindan R (2010) Energy-efficient rate-adaptive GPS-based positioning for smartphones. In: Proceedings of the 8th international conference on Mobile systems, applications, and services, pp 299–314

  • Parkan C (2002) Measuring the operational performance of a public transit company. Int J Oper Prod Manag 22(6):693–720

    Article  Google Scholar 

  • Peng Z, Huang R (2000) Design and development of interactive trip planning for web-based transit information systems. Transp Res Part C 8(1–6):409–425

    Article  Google Scholar 

  • Qi Y, Yu C, Suh YJ, Jang SY (2015) GPS tethering for energy conservation. In: IEEE Wireless Communications and Networking Conference (WCNC), pp 1320–1325

  • Randall T, Churchill C, Baetz B (2005) Geographic information system (GIS) based decision support for neighborhood traffic calming. Can J Civ Eng 32:86–98

    Article  Google Scholar 

  • Rastogi R, Krishna Rao KV (2003) Defining transits accessibility with environmental inputs. Transp Res Part D 8(5):383–396

    Article  Google Scholar 

  • Rastogi R, Krishna Rao KV (2009) Segmentation analysis of commuters accessing transit: a Mumbai study. J Transp Eng 135(8):506–515

    Article  Google Scholar 

  • Redman L, Friman M, Garling T, Hartig T (2013) Quality attributes of public transport that attract car users: a research review. Transp Policy 25:119–127

    Article  Google Scholar 

  • Robinson S, Polak JW (2007) Characterising the components of urban travel time variability using the K-NN method. In: Proceedings of the 86th Annual Meeting of Transportation Research Board, Washington

  • Rodriguez DA, Targa F (2004) Value of accessibility to Bogotá’s bus rapid transit system. Transp Rev 24(5):587–610

    Article  Google Scholar 

  • Sharaby N, Shiftan Y (2012) The impact of fare integration on travel behavior and transit ridership. Transp Policy 21:63–70

    Article  Google Scholar 

  • Singletracks (2014) GPS distance accuracy test: smartphone Apps vs. dedicated GPS. http://www.singletracks.com/blog/gps/gps-distance-accuracy-test-smartphone-apps-vs-dedicated-gps/. Accessed on 17 Dec 2015

  • Sleep C, Somenahalli S, Magiera J, Lotfi M, Bruce J (2013) Analysing bus transit on-time performance at the stop level using AVL data. In: Proceedings of the Eastern Asia Society for Transportation Studies, vol. 9

  • Stenneth L, Wolfson O, Yu PS, Yu B (2011) Transportation mode detection using mobile phones and GIS information. In: Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp 54–63

  • Stopher PR, Jiang Q, FitzGerald C (2005) Processing GPS data from travel surveys. 2nd International colloquium on the behavioural foundations of integrated land-use and transportation models: frameworks, models and applications, Toronto, pp 1–21

  • Strathman JG, Dueker KJ, Kimpel T (1999) Automated bus dispatching, operations control, and service reliability. Transp Res Rec 1666:28–36

    Article  Google Scholar 

  • Thiagarajan A, Biagioni J, Gerlich T, Eriksson J (2010) Cooperative transit tracking using smart-phones. In: Proceedings of the 8th ACM conference on embedded networked sensor systems (SenSys), pp 85–98

  • Thøgersen J (2009) Promoting public transport as a subscription service: effects of a free month travel card. Transp Policy 16(6):335–343

    Article  Google Scholar 

  • Thøgersen J, Møller B (2008) Breaking car use habits: the effectiveness of a free one-month travel card. Transportation 35(3):329–345

    Article  Google Scholar 

  • Tirachinia A, Hensher DA, Roseb JM (2013) Crowding in public transport systems: effects on users, operation and implications for the estimation of demand. Transp Res Part A 53:36–52

    Google Scholar 

  • Too L, Earl G (2010) Public transport service quality and sustainable development: a community stakeholder perspective. Sustain Dev 18(1):51–61

    Google Scholar 

  • Transportation Research Board (1999) A handbook for measuring customer satisfaction and service quality, TRCP Report 47. National Academy Press, Washington

    Google Scholar 

  • Transportation Research Board (2003) A guidebook for developing a transit performance-measurement system, TCRP Report 88. National Academy Press, Washington

    Google Scholar 

  • Transportation Research Board (2004) TCRP REPORT 95, transit pricing and fares, traveler response to transportation system changes, Transport Cooperative Research Program. Washington, D.C., USA

  • Transportation Research Board (2013) Transit capacity and quality of service manual. TCRP Report 165, National Academy Press, Washington

  • Turnquist M, Blume S (1980) Evaluating potential effectiveness of headway control strategies for transit systems. Transp Res Rec 746:25–29

    Google Scholar 

  • Turnquist M, Bowman LA (1980) The effects of network structure on reliability of transit service. Transp Res B 14:79–86

    Article  Google Scholar 

  • Tyrinopoulos Y, Antoniou C (2008) Public transit user satisfaction: variability and policy implications. Transp Policy 15(4):260–272

    Article  Google Scholar 

  • Vija A, Shankari K (2015) When is big data big enough? Implications of using GPS-based surveys for travel demand analysis. Transp Res Part C Emerg Technol 56:446–462

    Article  Google Scholar 

  • Vuchic VR (2005) Urban transit operations, planning and economics. Wiley, Hoboken

    Google Scholar 

  • Vuchic VR (2007) Urban transit: systems and technology. Wiley, New York

    Book  Google Scholar 

  • Vuk G (2005) Transport impacts of the Copenhagen metro. J Transp Geogr 13(3):223–233

    Article  Google Scholar 

  • Wall G, McDonald M (2007) Improving bus service quality and information in Winchester. Transp Policy 14(2):165–179

    Article  Google Scholar 

  • Zandbergen PA (2009) Accuracy of I-phone locations: a comparison of assisted GPS, WiFi and cellular positioning. Trans GIS 13(s1):5–26

    Article  Google Scholar 

  • Zandbergen PA, Barbeau SJ (2011) Positional accuracy of assisted GPS data from high-sensitivity GPS-enabled mobile phones. J Navig 64:381–399

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Giuseppe Guido.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vitale, A., Guido, G. & Rogano, D. A smartphone based DSS platform for assessing transit service attributes. Public Transp 8, 315–340 (2016). https://doi.org/10.1007/s12469-016-0133-z

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12469-016-0133-z

Keywords

Navigation