Performance indicators and automatic identification systems in inland freight terminals for intermodal transport

Performance indicators and automatic identification systems in inland freight terminals for intermodal transport

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
IET Intelligent Transport Systems — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The inland terminals play an important role in the intermodal freight transport network to transfer loading units and achieve seamless cross-modal processes. Their efficiency contributes to competiveness of intermodal transport which shifts medium distance freight journeys from road to other modes as required by European Policies. Based on the scientific literature, a set of selected performance indicators for inland terminals is identified and classified, considering the terminal subprocess and the actors involved. Also, the main relations between the key performance indicators identified and the possible solutions for automatic identification to detect vehicles and units during the gate operations are analysed. These applications are useful for two main reasons: they contribute to terminal performance improvement, affecting the indicator value, and also may enable the computation of the indicators itself. The aim of the study is to provide a method to measure a particular indicator even in different procedures for check-in. To compare solutions in homogeneous conditions, with a consistent calculation of the indicator, the scenarios are analysed and modelled with a standard system architectures representation. The approach allows stakeholders a standard and simple analysis to effective compare different possible scenarios, in which alternative detection solutions may be implemented.


    1. 1)
      • 1. Gieseman, D., Maze, T.H.: ‘Evaluating capacity and delay given the implementation of ITS technology at truck weight and safety inspection stations’, IET Intell. Transp. Syst., 2007, 1, (2), pp. 124130.
    2. 2)
      • 2. Yoon, Y., Ban, K., Yoon, H., et al: ‘Automatic container code recognition from multiple views’, ETRI J., 2016, 38, pp. 767775.
    3. 3)
      • 3., accessed January 2018.
    4. 4)
      • 4. Cimino, M.G.C.A., Palumbo, F., Vaglini, G., et al: ‘Evaluating the impact of smart technologies on harbor's logistics via BPMN modeling and simulation’, Inf. Technol. Manag., 2017, 18, pp. 223239.
    5. 5)
      • 5. Object Management Group: ‘Business process model and notation’, Lecture Notes in Business Information Processing, 134, 2013.
    6. 6)
      • 6. The Open Group: ‘Archimate® 3.0.1 specification’, 2017.
    7. 7)
      • 7. Caceres, R., Mendoza, H., Tuñón, G., et al: ‘Modeling and simulation of berthing processes for a Panamanian container terminal using BPMN and discrete event simulation’. Proc. 2015 Int. Conf. Operations Excellence Service Engineering, 2015, pp. 111.
    8. 8)
      • 8. Siciliano, G., Vaghi, C., Ruesch, M., et al: ‘Indicatori di qualità e performance per i terminal intermodali europei’, SIET VIII Riunione Scientifica, Trieste, 2006.
    9. 9)
      • 9. Ricci, S., Capodilupo, L., Mueller, B., et al: ‘Assessment methods for innovative operational measures and technologies for intermodal freight terminals’, Transp. Res. Procedia, 2016, 14, pp. 28402849.
    10. 10)
      • 10. Garcìa, A.: ‘Study of alternative operation strategies in railroad terminals using simulation’. Proc. of 2015 Int. Conf. on Industrial Engineering and Systems Management, IEEE IESM 2015, 2016, pp. 725732.
    11. 11)
      • 11. Wang, Y., Bilegan, I.C., Crainic, T.G., et al: ‘Performance indicators for planning intermodal barge transportation systems’, Transp. Res. Procedia, 2014, 3, pp. 621630.
    12. 12)
      • 12. Martín, E., Dombriz, M.Á., Soley, G.: ‘Study of the state of the art and description of KPI and KRI of terminals, hinterland mobility and rail network’, Intermodel EU Project, 2017.
    13. 13)
      • 13. Carboni, A., Deflorio, F.: ‘Quality and energy evaluation of rail-road terminals by microsimulation’. Transport Infrastructure and Systems: Proc. of the AIIT Int. Congress on Transport Infrastructure and Systems, Rome, Italy, 10–12 April 2017, pp. 617624.
    14. 14)
      • 14. Mbiydzenyuy, G., Persson, J.A., Davidsson, P., et al: ‘Method for quantitative valuation of road freight transport telematic services’, IET Intell. Transp. Syst., 2012, 6, pp. 388396.
    15. 15)
      • 15. Ballis, A., Golias, J.: ‘Towards the improvement of a combined transport chain performance’, Eur. J. Oper. Res., 2004, 152, pp. 420436.
    16. 16)
      • 16. Van Binsbergen, A., Tavasszy, L., Van Duin, R., et al: ‘Innovations in intermodal freight transport: lessons from Europe’. TRB 2014 Annual Meeting, 2014, pp. 130.
    17. 17)
      • 17. Mangone, A., Ricci, S.: ‘Modeling of port – freight village systems and loading units tracking functions’, Ing. Ferrov., 2014, 1, pp. 737.
    18. 18)
      • 18. Dalla Chiara, B., Barabino, B., Bifulco, G.N., et al: ‘ITS nei trasporti stradali’ (EGAF, Forli, 2013, 1st edn.).
    19. 19)
      • 19. Wu, W., Liu, Z., Chen, M., et al: ‘An automated vision system for container-code recognition’, Expert Syst. Appl., 2012, 39, pp. 28422855.
    20. 20)
      • 20. Shi, X., Tao, D., Voß, S.: ‘RFID technology and its application to port-based container logistics’, J. Organ. Comput. Electron. Commer., 2011, 21, pp. 332347.

Related content

This is a required field
Please enter a valid email address