DEA (data envelopment analysis) is a non-parametric linear programming method for determining the relative efficiencies of a set of decision making units (e.g. public transport companies) with multi-inputs and multi-outputs. The advantage of using DEA is that it does not require any assumption on the shape of the frontier surface and it makes no assumptions concerning the internal operations of a DMU. It is very often used in the transport sector for estimating the efficiency of airports, ports, railways and public transport companies. In order to make better assessment of green intermodal freight transportation, the aim of this paper is to applied DEA method to evaluate the relative efficiency of two green intermodal freight transport (GIFT) corridors (IV,V) of South East Europe. Input variables considered in this DEA problem are relative unit cost, transport time, delay risk, CO2 and SO2 emissions. Frequency of regular service is output variable. The application of this method aims at the identification of strengths and weaknesses of each GIFT Corridor and will pinpoints the actions that should be taken in order to improve their operational status and their transformation to Green Corridors.

The concept of transport corridors is marked by a concentration of freight traffic between major hubs and by relatively long distances of transport. Green transport corridors will reflect an integrated transport concept where short sea shipping, rail, inland waterways and road complement each other to enable the choice of environmentally friendly transport. The main aim of Green Intermodal Freight Transport (GIFT) project is to map, analyze, and evaluate the status of the transport sector in the selected transport network and propose new policies and strategies in infrastructure, processes, assets, Information and Communication Technologies, legislation, norms and harmonization/standardization issues, in order to promote innovative green intermodal freight transport corridors. The purpose of this paper is to present the central activities of the project, and the expected/ achieved results and outputs.

Current mobile systems for assisted navigation have limited effectiveness in satisfying user needs. The information content supporting location-based service discovery and path calculation is usually limited. Semantic-based technologies can allow to overcome these limitations, by exploiting accurate and meaningful descriptions of locations, POIs, road segments and environmental conditions. We present here a general framework leveraging an enriched cartography, which may be useful not only to enhance travel satisfaction and safety, but also to regulate vehicle efficiency, traffic and environmental impact. The availability of semantically annotated map data is a crucial requirement for this kind of proposals to be practically viable. Unfortunately, the majority of available systems is developed upon closed and proprietary solutions for both maps and software applications, so third parties cannot extend their functionality. In order to overcome this restriction, the framework proposed here is based on open standards and tools: in particular, it leverages Semantic Web technologies and crowd-sourced maps available from OpenStreetMap (http://www.openstreetmap.org/), enriching nodes and POIs with semantic annotations to enable innovative Location Based Services (LBSs) for traveling users. Particularly, the paper proposes a general method for storing semantic annotations into OpenStreetMap road nodes and POIs, expressed w.r.t. ontologies in standard Semantic Web languages. A user-friendly software tool is also presented for editing semantic annotations through a fully visual user interface, based on simple drag-and-drop operations, implemented as a plugin for the popular open source JOSM Open-StreetMap editor (http://josm.openstreetmap.de/), that will make any OpenStreetMap contributor capable of enriching maps with semantic information. Finally, a semantic-enhanced navigation tool is proposed, capable of exploiting the enriched OpenStreetMap cartography. We present the framework, the tool, and an initial users’ evaluation.