Open AccessPerformance indicators and automatic identification systems in inland freight terminals for intermodal transport
Author(s) -
Carboni Angela,
Deflorio Francesco
Publication year - 2018
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/iet-its.2017.0349
Subject(s) - identification (biology) , performance indicator , modal , transport engineering , computer science , measure (data warehouse) , representation (politics) , terminal (telecommunication) , key (lock) , homogeneous , transport network , set (abstract data type) , operations research , engineering , data mining , telecommunications , botany , biology , chemistry , physics , computer security , management , politics , law , polymer chemistry , economics , political science , programming language , thermodynamics
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.