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Marialisa Nigro   Dr.  Post Doctoral Researcher 
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Marialisa Nigro published an article in January 2018.
Top co-authors See all
Francesco Viti

78 shared publications

Gaetano Valenti

21 shared publications

Carlo Villante

20 shared publications

Guido Cantelmo

12 shared publications

Maria Pia Valentini

7 shared publications

Publication Record
Distribution of Articles published per year 

Total number of journals
published in
Article 0 Reads 0 Citations Exploiting floating car data for time-dependent Origin–Destination matrices estimation Marialisa Nigro, Ernesto Cipriani, Andrea Del Giudice Published: 16 January 2018
Journal of Intelligent Transportation Systems, doi: 10.1080/15472450.2017.1421462
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The study evaluates the added value generated by estimating dynamic demand matrices by information gathered from Floating Car Data (FCD). Firstly, adopting a large dataset of FCD collected in Rome, Italy, during May 2010, all the monitored trips on a specific district of the city (Eur district) have been collected and analysed in terms of 1) spatial and temporal distribution; 2) actual route choices and travel times. The data analysis showed that demand data from FCD are usually not suitable to retrieve directly demand matrices, due to a strongly dependence of this information from the penetration rate of the monitoring device. Instead, origin-destination travel times and route choice probabilities from FCD are a much more reliable and powerful information with respect to FCD origin-destination flows, since they represent the traffic conditions and behaviours that vehicles experiment along the path. Thus, several synthetic experiments have been conducted adopting both travel times and route choice probabilities as additional information, with respect to standard link measurements, in the dynamic demand estimation problem (DDEP). Results demonstrated the strength and robustness associated to these network based data, while link measurements alone are not able to define the real traffic pattern. Adopting both the information of origin-destination travel times and route choice probabilities during the demand estimation process, the spatial and temporal reliability of the estimated demand matrices consistently increases.
Article 0 Reads 0 Citations The Impact of Electric Mobility Scenarios in Large Urban Areas: The Rome Case Study Carlo Liberto, Gaetano Valenti, Silvia Orchi, Maria Lelli, M... Published: 01 January 2018
IEEE Transactions on Intelligent Transportation Systems, doi: 10.1109/tits.2018.2832004
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Conference 1 Read 0 Citations The impact of battery electric buses in public transport Gaetano Valenti, Maria Lelli, Marina Ferrara, Marialisa Nigr... Published: 01 June 2017
2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), doi: 10.1109/eeeic.2017.7977517
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Conference 0 Reads 0 Citations Evaluation of the impact of e-mobility scenarios in large urban areas Carlo Liberto, Gaetano Valenti, Maria Lelli, Marina Ferrara,... Published: 01 June 2017
2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), doi: 10.1109/mtits.2017.8005701
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Article 0 Reads 0 Citations A Utility-based Dynamic Demand Estimation Model that Explicitly Accounts for Activity Scheduling and Duration. Guido Cantelmo, Francesco Viti, Ernesto Cipriani, Marialisa ... Published: 01 January 2017
Transportation Research Procedia, doi: 10.1016/j.trpro.2017.05.025
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Article 0 Reads 0 Citations Design and evaluation of electric solutions for public transport Valentina Conti, Silvia Orchi, Maria Pia Valentini, Marialis... Published: 01 January 2017
Transportation Research Procedia, doi: 10.1016/j.trpro.2017.12.033
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This study deals with the design and the evaluation of technological solutions for the electrification of public transport in urban areas. A Decision Support System (DSS) developed by ENEA † within the Research program on Electric System (RSE) has been adopted in order to verify the technical feasibility of several electric architectures of single bus lines and compare the investment and management costs, as well as the external costs due to vehicle emissions and noises, of the feasible solutions with respect to the conventional alternatives (Compressed Natural Gas, CNG, and diesel). The DSS has been applied to several bus lines located in the south-west area of the city of Rome, Italy, and covering different types of service: peripheral lines, main lines connecting suburbs with the city center and secondary lines going to the main metro stations. Input data for the DSS derived both by simulation and by open database available from the public transport operator in Rome (ATAC). Results show that a suitable electric architecture can be found for each of these lines with lower or comparable total costs with respect to the traditional alternatives. Finally, a sensitivity analysis has been performed considering several scenarios in terms of discount rate of recharge stations and batteries, battery’s duration, price of conventional fuels.