Alessandra Renna

Dr. Alessandra Renna

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Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 September 2021 in Sustainability
Verified
Journal Article
Open access
PDF file
ARAlessandra Renna
Alessandra Renna
MPMarco Petrelli
Marco Petrelli
Stefano CarreseStefano Carrese
Stefano Carrese
RBRiccardo Bertocci
Riccardo Bertocci
This research proposes an innovative approach to evaluate modal shift from the road-only to the combined sea-road transport in order to implement new policies and introduce a Decision Support System (DSS) for the transportation planner’s decision. The impact of these is carried out by using an innovative simulation tool which has the capability to simulate the real choice process of all stakeholders involved, specifically modelling the freight forwarder’s point of view. The model runs as a single-agent based simulation which uses a multimodal network with detailed zoning. The simulation tool, capable of simulating the assignment of the whole network simultaneously, consists of a path choice model and a mode choice model for each o/d pair considered, establishing o/d pairs suitable and not suitable for modal shift. Three policies have been designed and tested through the simulation tool with an application in the Italian context: (1) internalization of the external costs of heavy vehicles; (2) introduction of a bonus for shipping companies; (3) design of new Ro-Ro services. The most affecting policy concerns an increase of speed of some Ro-Ro services to 22 kn, proposing a good balance between the navigation costs and the potential demand attracted.

5 May 2022 in Sustainability
Verified
Journal Article
Open access
PDF file
Dario BallaranoDario Ballarano
Dario Ballarano
MPMarco Petrelli
Marco Petrelli
ARAlessandra Renna
Alessandra Renna
The implementation of valid freight transport simulation models requires an extensive and detailed validation phase for understanding the feasibility of the outputs and the capacity of the structure of the proposed models in representing the real-world data. Traditional methods involve the use of surveys in order to describe the behaviour of stakeholders and to gather some aspects of the modal choices. Recent studies integrate this approach with Big Data as Floating Car Data to obtain better statistical information of the details at different levels. The current research involves the unexplored field of the validation of freight transport simulation models using a data-driven approach based on a large database of over 292 million Floating Car Data (FCD) signals generated by 29,298 commercial vehicles during the month of October 2019. The paper proposes an FCD processing methodology to identify freight vehicles using Ro-Ro/Ro-Pax services, and presents the results of an in-depth tracking analysis for combined transport and road transport. The validation phase permits the evaluation of the simulation tool results with real choices of heavy vehicles, referring also to the statistical information on travel times and the achievement of additional information through an in-depth analysis of tracking single vehicles.