Modeling and Implementation of Digital Twins for the Analysis of Transportation Systems

Transport engineers, authorities, companies, stakeholders, and all experts involved on transportation planning work every day to improve the trip experience of people, and to reduce the impacts on the collectivity. Traffic congestion, pollution and energy consumption are core problems for the transportation system. On the one hand a congested road causes an exponential increase in the energy consumption and waiting times, while a not-congested road can be more attractive and slowly become congested over time; on the other hand, the environmental capacity of road links is not perceived, thus generating high emission and distribution of pollutants. In fact, the ability of transportation planners is to avoid traffic congestion but offer at the same time pleasant, accessible and sustainable trips. This may include several planning techniques which may involve traffic calming and limitations, lane reservation, changing in the road network and geometry, as well as apply new technologies, services and means of transportation. It is worth noting that trying these features directly on a city can be very expensive and produce irreparable damages to the transportation system; also, traditional transport models are not able to adeguately simulate most of these features. Recently, it has been recently introduced the digital twin, a digital reproduction of a city to be used as a test platform for ’what if’ scenarios. In fact, transport digital twin is not just a digital reproduction of the transportation system, but consider reaction of humans to the changes applied to the system, in order to make a comparison between different scenarios. The present document studies large-scale digital twins, which are able to consider the spatial propagation of effects, and particularly focuses on advanced and time-dependent models able to simulate the door-to-door trip experience of all users and adequately model the transport features of the future

Nonparametric Regression Analysis of Cyclist Waiting Times across Three Behavioral Typologies

This paper seeks to predict the average waiting time, defined as the time spent moving at 1 ms−1 or less, of urban bicyclists during rush hours while performing different maneuvers at intersections. Individual predictive models are built for the three cyclist typologies previously identified on a large database of GPS traces recorded in the city of Bologna, Italy. Individual models are built for the three cyclist typologies and bootstrapping has confirmed the validity and robustness of the results. The results allow the integration of waiting times in route choice models for cyclists, thus improving the rational bases by which cyclists makes their decisions. Moreover, the modeling allows transportation engineers to understand how different cyclist typologies perceive different variables that affect their waiting times. Future work should focus on testing the model transferability to other case studies

Using BEAM Software to Simulate the Introduction of On-Demand, Automated, and Electric Shuttles for Last Mile Connectivity in Santa Clara County

Despite growing interest in low-speed automated shuttles, pilot deployments have only just begun in a few places in the U.S., and there is a lack of studies that estimate the impacts of a widespread deployment of automated shuttles designed to supplement existing transit networks. This project estimated the potential impacts of automated shuttles based on a deployment scenario generated for a sample geographic area: Santa Clara County, California. The project identified sample deployment markets within Santa Clara County using a GIS screening exercise; tested the mode share changes of an automated shuttle deployment scenario using BEAM, an open-source beta software developed at the Lawrence Berkeley National Laboratory to run traffic simulations with MATSim; elaborated the model outputs within the R environment; and then estimated the related impacts. The main findings have been that the BEAM software, despite still being in its beta version, was able to model a scenario with the automated shuttle service: this report illustrates the potential of the software and the lessons learned. Regarding transportation aspects, the model estimated automated shuttle use throughout the county, with a higher rate of use in the downtown San José area. The shuttles would be preferred mainly by people who had been using gasoline-powered ride hail vehicles for A-to-B trips or going to the bus stop, as well as walking trips and a few car trips directed to public transport stops. As a result, the shuttles contributed to a small decrease in emissions of air pollutants, provided a competitive solution for short trips, and increased the overall use of the public transport system. The shuttles also presented a solution for short night trips—mainly between midnight and 2 am—when there are not many options for moving between points A and B. The conclusion is that the automated shuttle service is a good solution in certain contexts and can increase public transit ridership overall

Simulating the Integration of Urban Air Mobility into Existing Transportation Systems: A Survey

Urban air mobility (UAM) has the potential to revolutionize transportation in metropolitan areas, providing a new mode of transportation that could alleviate congestion and improve accessibility. However, the integration of UAM into existing transportation systems is a complex task that requires a thorough understanding of its impact on traffic flow and capacity. In this paper, we conduct a survey to investigate the current state of research on UAM in metropolitan-scale traffic using simulation techniques. We identify key challenges and opportunities for the integration of UAM into urban transportation systems, including impacts on existing traffic patterns and congestion; safety analysis and risk assessment; potential economic and environmental benefits; and the development of shared infrastructure and routes for UAM and ground-based transportation. We also discuss the potential benefits of UAM, such as reduced travel times and improved accessibility for underserved areas. Our survey provides a comprehensive overview of the current state of research on UAM in metropolitan-scale traffic using simulation and highlights key areas for future research and development

Analisi dei percorsi ciclabili registrati tramite smartphone sulla rete stradale di Bologna nell'ultimo triennio

La diffusione di smartphone con GPS si è rilevata utile per lo studio di modelli di scelta del percorso da parte di utenti che si muovono in bicicletta. Nel 2012 è stata ideata la ‘European Cyclinq Challenge’ (ECC), che consiste in una “gara” europea tra città: vince quella nella quale i rispettivi abitanti registrano il maggior numero di chilometri effettuati in bicicletta. In questo modo è possibile conoscere in forma anonima i percorsi realmente seguiti dai partecipanti alla gara: nel caso in esame, sono state fornite le tracce GPS registrate a Bologna sotto forma di punti catalogati ogni 10-15 secondi, a cui sono associate informazioni di coordinate, codice identificativo e istante di registrazione. Una fase di map-matching associa tali punti alla rete stradale di Bologna, descritta nel caso in esame dalla rete di Open Street Maps (OSM). Un elemento che garantisce al meglio la comprensione relativa alle scelte dei ciclisti, è quello di confrontarle con l’alternativa più breve, per capire quanto un utente sia disposto a discostarsi da essa per privilegiare ad esempio la sicurezza personale, il fatto di evitare pendenze elevate o incroci pericolosi. A partire dai punti GPS, che rappresentano l’origine e la destinazione di ogni viaggio, è possibile individuare sulla rete il percorso più corto che li congiunge, eseguendo sulla stessa rete tramite l’algoritmo di Dijkstra, considerando come unico attributo di costo la lunghezza. È stato possibile, mediante questi dati, effettuare un confronto nei tre anni di studio, relativamente alla distribuzione statistica delle lunghezze dei viaggi percorsi dagli utenti, a quanto questi si discostino dal percorso più breve ed infine come varia la percentuale dei viaggi effettuati nelle diverse tipologie stradali. Un’ultima analisi evidenzia la possibile tendenza degli utenti che si spostano in bicicletta nella città di Bologna, a utilizzare percorsi caratterizzati dalla presenza di numerosi incroci semaforizzati

Sviluppo di un modello di domanda basato sulle attività tramite micro-simulazioni di reti di trasporto multi-modali

L’elaborato descrive inizialmente 2 diversi approcci per lo studio di un sistema di trasporto (approcci micro e macro scopico) e mette in luce le loro differenze. Successivamente, sono stai descritti alcuni software che consentono di effettuare uno studio microscopico di un sistema di trasporto secondo i modelli di domanda basati sulle attività e mi sono concentrato sui pro e contro di ogni software. È stato poi descritto un nuovo algoritmo iterativo per la selezione del piano di trasporto, appena implementato in SUMOPy, che cerca di replicare il processo decisionale effettuato dagli utenti per selezionare il loro piano di trasporto. Il metodo consiste nell'esecuzione di più micro simulazioni, dopo ognuna delle quali i parametri in output possono migliorare la scelta delle persone per le micro simulazioni successive, fino a raggiungere la convergenza in cui ogni utente (massimizzatore di utilità) seleziona il piano migliore che si suppone sceglierebbe in realtà. Dopo una serie di simulazioni sufficienti, tutte le persone avranno sperimentato i tempi di viaggio effettivi di tutti i migliori piani ed avranno scelto quello che offre il tempo di viaggio più veloce. Ho dimostrato la convergenza e la robustezza dei risultati per una piccola città con molte persone e per un area di studio reale ad ovest del centro storico di Bologna, illustrando che l'algoritmo diminuisce il tempo totale speso nella rete durante successive micro simulazioni, ottimizzando la scelta del piano per ogni utente

Simulating platooned connected autonomous vehicle in a large scale urban scenario

This article is concerned with the performance evaluation of connected, autonomous vehicles (CAVs) in a realistic large-scale microsimulation scenario. In particular the question is: how much could a high diffusion of CAVs possibly change (1)~the average travel speeds (2)~the trip times of all traffic participants, including pedestrians, and (3)~the energy/fuel consumption? For this purpose, admittedly favourable assumptions are made: a 100\% diffusion of platooning-capable CAVs as substitution for private cars as well as a high maximum speed of platooned vehiclesin order to enable platoon formation. The morning rush hour scenario of the metropolitan area of Bologna, Italy has been selected for assessment. This scenario, which has been created and validated in previous works, represents an activity based demand model with travel plans for individual citizens, including all relevant transport modes.  The microsimulation is performed by means of the SUMO simulator. The entire demand has been generated with the SUMOPy tool. For the platooning of CAVs, SUMO's SIMPLA module has been used, which controlls the vehicles via the interactive TRACI API. Results show an increased speed and reduced travel time for CAV vehicles, with respect to human driven cars, in particular in the periphery and less in the center with a dense road network.  However, the reason for improved speeds and travel times is predominantly the higher maximum speed  allowed for vehicles trying to catch up and join a platoon. Furthermore these higher speed would also be resposible for an increase in fuel consumption of approximately 5\%. In conclusion, CAVs alone are unlikely to reduce congestion in an urban area. To make the platooning concept work, additional technology and infrastructure is required in order to merge platoons effectively at freeways and at traffic lights. The latter could be simulated with GLOSA

Evolution of the Road and Rail Transport of Goods in European Countries before and after the Financial Crises

The main goal of this paper is to analyse recent trends in freight transport volumes as well as their relation to socio-economic and infrastructural variables, in the case of the following major European countries: France, Germany, Italy, Poland, Spain and the United Kingdom. This analysis refers to the period 2005-2016, so that years affected by the global economic crisis, which shows its peak in 2009, are taken into account. This research demonstrated that not all the countries under study show a strong relation between freight traffic and GDP as it could have been expected based on well consolidated experiences and studies. Moreover, other relations are investigated, with mixed results, between the freight traffic volumes and the extension of the rail and road networks as well as oil price data

Building a Large-Scale Micro-Simulation Transport Scenario Using Big Data

A large-scale agent-based microsimulation scenario including the transport modes car, bus, bicycle, scooter, and pedestrian, is built and validated for the city of Bologna (Italy) during the morning peak hour. Large-scale microsimulations enable the evaluation of city-wide effects of novel and complex transport technologies and services, such as intelligent traffic lights or shared autonomous vehicles. Large-scale microsimulations can be seen as an interdisciplinary project where transport planners and technology developers can work together on the same scenario; big data from OpenStreetMap, traffic surveys, GPS traces, traffic counts and transit details are merged into a unique transport scenario. The employed activity-based demand model is able to simulate and evaluate door-to-door trip times while testing different mobility strategies. Indeed, a utility-based mode choice model is calibrated that matches the official modal split. The scenario is implemented and analyzed with the software SUMOPy/SUMO which is an open source software, available on GitHub. The simulated traffic flows are compared with flows from traffic counters using different indicators. The determination coefficient has been 0.7 for larger roads (width greater than seven meters). The present work shows that it is possible to build realistic microsimulation scenarios for larger urban areas. A higher precision of the results could be achieved by using more coherent data and by merging different data sources