A new methodological framework for within-day dynamic estimation of pollutant emissions in a large congested urban network

This paper presents a new methodological framework to address the problem of estimating pollutant emissions for large congested urban networks in a within-day dynamic context. It consists of three main modules: 1) a module to compute pollutant emissions for general links; 2) a module to compute pollutant emissions for all links approaching a signalized intersection; 3) a module to compute pollutant emissions for all links approaching an unsignalized intersection. A dynamic mesoscopic assignment model is performed to derive the main dynamic input of each one of the modules. All the modules have been tested in a real case study (the district of Eur in the city of Rome, Italy), so confirming the reliability of the developed models and their applicability for the estimation of pollutant emissions

Comparing pre- and post-pandemic greenhouse gas and noise emissions from road traffic in Rome (Italy): a multi-step approach

This study presents the results of a traffic simulation analysis and emissions (greenhouse gas and noise) assessment comparing pre-pandemic (2019) and post-pandemic (2022) periods. The estimation of road traffic demand is based on conventional data sources and floating car data; next, the traffic simulation procedure was performed providing road network traffic volumes, which are the input for the emission models. The diffusion of teleworking, e-commerce, as well as the digitization of many processes, services and activities, lead to a significant change in urban mobility. Results show a significant though still not complete resumption of commuters travel activity (−10% compared to pre-pandemic period) in the morning peak-hour. This translates into an 11% reduction of greenhouse gas emissions and a 0.1% increase in noise emissions

Multi-vehicle Stochastic Fundamental Diagram Consistent with Transportations Systems Theory

This paper describes a general approach to the specification the stable regime speed-flow function, for motorways, as a part of the stable regime Stochastic Fundamental Diagram consistent with main assumptions of Transportation Systems Theory. Main original elements are: • Specification of speed-flow functions consistent with travel time function, such as BPR-like functions; • Calibration from disaggregate data, say data from single vehicle trajectories; • Specification of the speed r. v. distribution consistent with those used in RUT for route choice behavior modelling, such as Gamma, Inv-Gamma

On Transport Monitoring and Forecasting during COVID-19 Pandemic in Rome

This paper presents the results of a study on the Rome mobility system aiming at estimating the impacts of the progressive lockdown, imposed by the government, due to the Covid-19 pandemic as well as to support decision makers in planning the transport system for the restart towards a post-Covid "new normal". The analysis of data obtained by the transport monitoring system has been fundamental for both investigating effects of the lockdown and feeding transport models to predict the impacts on future actions. At first, the paper focuses on the so-called transport analytics, by describing mobility trends for the multimodal transportation system of Rome. Then, the results of the simulated scenarios to design public transport services, able to ensure passengers social distancing required in the first post-Covid months, are presented and discussed

Stima delle condizioni di deflusso del traffico stradale

The aim of this study is the estimation of traffic flow conditions either in urban or in freeway contests; in order to reach the objective of the research, the micro and macro simulations have been adopted as model tools, verified through specific experiments, carried out detecting measurements with operational tools, as vehicles equipped with differential GPS devices, and fixed traffic detectors, as radar technologies. These tools either, technological or methodological, are different but completing and give the opportunities to be integrated each other. The macroscopic and microscopic models have been studied and analyzed; on the basis of the results obtained during the calibration and validation of some of the existing car-following models four new microscopic models have been formulated; one of them considers the interaction between the follower vehicle and 2 leader vehicles. Then, the attention has been focalized on the fusion of data detected by two different sensor types in order to improve the traffic flow estimation. Starting from the application of the procedure reported in Wang, Papageorgiou (2005) based on the correction through the Extended Kalman Filter of the second order traffic model, also a different type of measurement has been taken into account, such as probe vehicles, which has been added to the conventional fixed ones, in order to improve the estimation process. Different data fusion techniques have been analyzed, such as the fusion of measurements and the fusion of estimations. Moreover, an application with freeway real data has been carried out in order to validate the procedure