References of "Viti, Francesco 50003272"
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See detailQuasi-dynamic traffic assignment with spatial queueing, control and blocking back
Smith, Mike; Huang, Wei; Viti, Francesco UL et al

in Transportation Research. Part B, Methodological (2019)

This paper introduces a steady-state, fixed (or inelastic) demand equilibrium model with explicit link-exit capacities, explicit bottleneck or queueing delays and explicit bounds on queue storage ... [more ▼]

This paper introduces a steady-state, fixed (or inelastic) demand equilibrium model with explicit link-exit capacities, explicit bottleneck or queueing delays and explicit bounds on queue storage capacities. The model is a quasi-dynamic model. The link model at the heart of this quasi-dynamic equilibrium model is a spatial queueing model, which takes account of the space taken up by queues both when there is no blocking back and also when there is blocking back. The paper shows that if this quasi-dynamic model is utilised then for any feasible demand there is an equilibrium solution, provided (i) queue storage capacities are large or (ii) prices are used to help impose capacity restrictions; the prices either remove queueing delays entirely or just reduce spatial queues sufficiently to ensure that blocking back does not occur at equilibrium. Similar results, but now involving the P0 control policy (introduced in Smith (1979a, 1987)) and two new variations of this policy (i.e., the spatial P0 control policy, and the biased spatial P0 control policy) are obtained. In these results, the control policies allow green-times to vary in response to prices as well as spatial queueing delays. These three policies are also tested on a small simple network. In these tests, the biased spatial version of P0 is much the best in reducing equilibrium delays (on this simple network). The paper further illustrates how the spatial queueing model works on simple networks with different merge models; it is demonstrated that equilibrium may be prevented by certain (fixed ratio) merge models. It is also shown in this case that equilibrium may be imposed on just the controlled area itself by a variety of (merge model, gating strategy) combinations. Opportunities for developing such combined gating and merging control strategies are finally discussed. [less ▲]

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See detailTowards Optimized Deployment of Electric Bus Systems Using Cooperative ITS
Laskaris, Georgios UL; Seredynski, Marcin; Viti, Francesco UL

Poster (2019, January)

In this paper we analyze the impact of using cooperative intelligent transportation systems (C-ITS) to manage electrical bus systems. A simulation-based study is presented where three control strategies ... [more ▼]

In this paper we analyze the impact of using cooperative intelligent transportation systems (C-ITS) to manage electrical bus systems. A simulation-based study is presented where three control strategies are used to regulate the operations of a line, namely bus holding, Green Light Optimal Dwell Time Adaptation (GLODTA) and Transit Signal Priority (TSP). The results show, using a realistic scenario of a major line in Luxembourg City, that buses are efficiently operated without necessarily providing additional priority to public transport, hence without negatively affecting the capacity of the private vehicles system. Benefits in terms of headway regulations, energy consumption and travel time variance reductions are quantified. [less ▲]

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See detailMixed hybrid and electric bus dynamic fleet management in urban networks: a model predictive control approach
Rinaldi, Marco UL; Picarelli, Erika; Laskaris, Georgios UL et al

Scientific Conference (2019, January)

Reducing pollutant emissions and promoting sustainable mobility solutions, including Public Transport, are increasingly becoming key objectives for policymakers worldwide. In order to jointly achieve ... [more ▼]

Reducing pollutant emissions and promoting sustainable mobility solutions, including Public Transport, are increasingly becoming key objectives for policymakers worldwide. In order to jointly achieve these goals, careful consideration should be put on the operational cost and management of PT services, in order to promote the adoption of green mobility solutions and advanced management techniques by operators. In this work we develop a dynamic fleet management approach for next generation Public Transportation systems, considering the instance of mixed electric / hybrid fleet. Our objective is that of investigating to what extent electrification, coupled with optimal fleet management, can yield operational cost savings for PT operators, explicitly considering real-time disturbances, including delays, service disruptions etc. We propose a Mixed Integer Linear Program to address the problem of optimal scheduling of a mixed fleet of electric and hybrid / non-electric buses, and employ it as predictor in a Model Predictive Control approach. Test results based upon a real-life scenario showcase how the proposed approach is indeed capable of yielding a sizable reduction in operational costs, even when considerable disturbances arise from the underlying system. [less ▲]

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See detailA Big Data Demand Estimation Framework for Modelling of Urban Congested Networks
Cantelmo, Guido UL; Viti, Francesco UL

in CSUM 2018, AISC 879 proceedings (2019)

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See detailIncorporating trip chaining within online demand estimation
Cantelmo, Guido; Qurashi, Moeid; Prakash, Arun et al

in Transportation Research Procedia (2019), 38

Time-dependent Origin–Destination (OD) demand flows are fundamental inputs for Dynamic Traffic Assignment (DTA) systems and real-time traffic management. This work introduces a novel state-space framework ... [more ▼]

Time-dependent Origin–Destination (OD) demand flows are fundamental inputs for Dynamic Traffic Assignment (DTA) systems and real-time traffic management. This work introduces a novel state-space framework to estimate these demand flows in an online context. Specifically, we propose to explicitly include trip-chaining behavior within the state-space formulation, which is solved using the well-established Kalman Filtering technique. While existing works already consider structural information and recursive behavior within the online demand estimation problem, this information has been always considered at the OD level. In this study, we introduce this structural information by explicitly representing trip-chaining within the estimation framework. The advantage is twofold. First, all trips belonging to the same tour can be jointly calibrated. Second, given the estimation during a certain time interval, a prediction of the structural deviation over the whole day can be obtained without the need to run additional simulations. The effectiveness of the proposed methodology is demonstrated first on a toy network and then on a large real-world network. Results show that the model improves the prediction performance with respect to a conventional Kalman Filtering approach. We also show that, on the basis of the estimation of the morning commute, the model can be used to predict the evening commute without need of running additional simulations. [less ▲]

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See detailTraffic control which maximises network throughput: Some simple examples
Smith, Michael; Iryo, Takamasa; Mounce, Richard et al

in Transportation Research. Part C, Emerging Technologies (2019), 107

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See detailOptimal dispatching of electric and hybrid buses subject to scheduling and charging constraints
Rinaldi, Marco UL; Parisi, Federico; Laskaris, Georgios UL et al

Scientific Conference (2018, November)

We consider the problem of optimally determining the sequence of electric and hybrid buses departing from a multi-line bus terminal, considering both service constraints (schedule adherence) and energy ... [more ▼]

We consider the problem of optimally determining the sequence of electric and hybrid buses departing from a multi-line bus terminal, considering both service constraints (schedule adherence) and energy constraints (electric bus charging status, bus recharging scheduling in capacitated facilities). The problem is formulated as a Mixed Integer Linear Program, with the objective of minimizing the total operational cost for the bus lines in question. System dynamics are captured by practical sets of constraints, ranging from scheduling adherence to discharge- recharge dynamics. Individual operational costs at the bus level and at the trip level are fully parametrized, allowing for extensive sensitivity analysis. We investigate a real-life case study based on the city of Luxembourg, where two charging stations have been installed in the central station’s bus terminal. Experimental results show that, while full electrification is indeed possible, the required fleet size depends strongly on the given line(s) timetable. [less ▲]

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See detailReal time multiline holding control for networks with shared transit corridor
Laskaris, Georgios UL; Cats, Oded; Jenelius, Erik et al

Scientific Conference (2018, September 05)

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See detailControllability of transportation networks
Rinaldi, Marco UL; Viti, Francesco UL

Scientific Conference (2018, September)

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See detailDecompositions of the optimal dispatching problem of electric and electric-hybrid buses with energy constraints for Luxembourg City
Picarelli, Erika; Rinaldi, Marco UL; Viti, Francesco UL et al

Scientific Conference (2018, September)

We are a team of engineers working on a concrete project of Mobility in Luxembourg. We want to solve the problem of optimally determining the sequence of electric and hybrid electric buses, considering ... [more ▼]

We are a team of engineers working on a concrete project of Mobility in Luxembourg. We want to solve the problem of optimally determining the sequence of electric and hybrid electric buses, considering both service constraints (schedule adherence) and energy constraints (electric bus charging status, bus recharging scheduling in capacitated facilities) and at the same time ensure a high level of quality of service for the user satisfaction. The problem is formulated as a Mixed Integer Linear Program, with the objective of minimizing the total operational cost for the bus lines in question. System dynamics are captured by twenty sets of constraints, ranging from scheduling adherence to discharge-recharge dynamics. Individual operational costs at the bus level (cost of running an electric / non-electric bus per km, cost of recharging) and at the trip level (penalty due to failed schedule adherence) are fully parametrised, allowing for extensive sensitivity analysis. We investigate a real-life case study based in the city of Luxembourg, where the objective is to reach the all-electric mode for principal urban buses network. Through the model we investigate: the minimum amount of electric buses necessary to perform a day’s schedule for two currently partially electrified lines, without resorting to conventional internal combustion alternatives; the impact of electrifying two additional lines, specifically considering the trade-offs related to either adding new buses or new charging stations at the bus terminal. Finally, we studied how to best decompose the overall problem in several smaller problems, to be able to solve also realistic scenarios and using large real data sets from the Mobility Data owner of Luxembourg. We analysed and compared two kinds of decomposition: a bus line-based decomposition, and a time-based decomposition. [less ▲]

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See detailIncorporating activity duration and scheduling utility into equilibrium-based Dynamic Traffic Assignment
Cantelmo, Guido UL; Viti, Francesco UL

in Transportation Research. Part B, Methodological (2018)

This paper deals with the problem of jointly modelling activity scheduling and duration within a Dynamic Traffic Assignment (DTA) problem framework. Although the last decades witnessed an intense effort ... [more ▼]

This paper deals with the problem of jointly modelling activity scheduling and duration within a Dynamic Traffic Assignment (DTA) problem framework. Although the last decades witnessed an intense effort in developing utility-based departure time choice models, relatively little has been done for understanding how the different assumptions on the utility model affect the model outputs. This problem is the main focus of this paper, which evaluates the effect of explicitly incorporating activity scheduling and duration within a generic user equilibrium DTA formulation. While using utility functions to model the positive component of the utility is a quite common procedure, the object of this paper is to show that a generic utility-based framework behaves as trip-based, activity-based, tour-based, or schedule-based if specific assumptions are specified. By establishing a set of properties, we quantify the amount of utility lost due to traffic congestion and how this affects activity (re-)scheduling and duration decisions. This allows predicting the effect of using a different assumption on the evolution of the transport system – and more specifically the departure time choice model. Conclusions support the idea that, under specific conditions, complex user behaviour can be approximated through a simplified model, and that the ratio between utility at origin and destination can be used to identify systematic biases within an existing DTA model – such as anticipating the rush hour. We also propose a novel utility function suited for modelling different activities, which can be used for modelling activities with a different duration. The mathematical model used to evaluate the effect of scheduling and duration into the equilibrium-based Dynamic Traffic Assignment is a simple bottleneck model. While this model has been recently re-formulated in order to capture the interaction between morning/evening commute, this paper further generalizes it in order to account for all type of activities. [less ▲]

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See detailA utility-based dynamic demand estimation model that explicitly accounts for activity scheduling and duration
Cantelmo, Guido UL; Viti, Francesco UL; Nigro, Marialisa et al

in Transportation Research. Part A, Policy and Practice (2018)

This paper proposes a Dynamic Demand Estimation (DODE) framework that explicitly accounts for activity scheduling and duration. By assuming a Utility-Based departure time choice model, the time-dependent ... [more ▼]

This paper proposes a Dynamic Demand Estimation (DODE) framework that explicitly accounts for activity scheduling and duration. By assuming a Utility-Based departure time choice model, the time-dependent OD flow becomes a function, whose parameters are those of the utility function(s) within the departure time choice model. In this way, the DODE is solved using a parametric approach, which, on one hand, has less variables to calibrate with respect to the classical bi-level formulation while, on the other hand, it accounts for different trip purposes. Properties of the model are analytically and numerically discussed, showing that the model is more suited for estimating the systematic component of the demand with respect to the standard GLS formulation. Differently from similar approaches in literature, which rely on agent-based microsimulators and require expensive survey data, the proposed framework is applicable with all those DTA models, which are based on OD matrix, and do not necessarily need any data at user level. This has been proven by applying the proposed approach with a standard macroscopic realistic Dynamic Traffic Assignment (DTA) [less ▲]

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See detailA holding control strategy for diverging bus lines
Laskaris, Georgios UL; Cats, Oded; Jenelius, Erik et al

Scientific Conference (2018, July 24)

We introduce a holding criterion for network configurations with lines that operate jointly along a common corridor and then individually diverge. The proposed holding decision rule accounts for all ... [more ▼]

We introduce a holding criterion for network configurations with lines that operate jointly along a common corridor and then individually diverge. The proposed holding decision rule accounts for all different passengers groups in the overlapping segment and takes care of the transition to individual line operation. The holding rule is evaluated using simulation for different demand levels and segmentations and compared with other control schemes for a real-world network. Results show that gains in overall network performance as well as for specific passenger groups can be achieved under specific demand distributions. [less ▲]

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See detailAssessing the performance of coordinated predictive control strategies on urban-motorway networks
Rinaldi, Marco UL; Viti, Francesco UL

in IFAC-PapersOnLine (2018, July), 51(9), 285-290

Coordination and integration of different traffic control policies have been of considerable interest in research in the last decades and, recently, have been object of large scale implementation trials ... [more ▼]

Coordination and integration of different traffic control policies have been of considerable interest in research in the last decades and, recently, have been object of large scale implementation trials. In the setting of peri-urban motorway systems, coordination of various kinds of controllers must however be accompanied by accurate prediction of both propagation of flows and queues in the network, as well as the users’ response in terms of route choice. In this paper, we showcase through a real-life case study how coordination and prediction are both essential when performing hybrid urban-motorway control. Simulation results of a Model Predictive Control application are compared to simpler local control approaches, and the impact of coordinated intersection control and, additionally, Ramp Metering is evaluated. [less ▲]

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See detailOptimal multi-line bus dispatching at terminals with electric charging scheduling constraints
Rinaldi, Marco UL; Parisi, Federico; D'Ariano, Andrea et al

Scientific Conference (2018, July)

We consider the problem of optimally determining the sequence of electric and conventional internal combustion buses departing from a multi-line bus terminal, considering both service constraints ... [more ▼]

We consider the problem of optimally determining the sequence of electric and conventional internal combustion buses departing from a multi-line bus terminal, considering both service constraints (schedule adherence) and energy constraints (electric bus charging status, bus recharging scheduling in capacitated facilities). The problem is formulated as a Mixed Integer Linear Program, with the objective of minimizing the total operational cost for the bus lines in question. System dynamics are captured by twenty sets of constraints, ranging from scheduling adherence to discharge-recharge dynamics. Individual operational costs at the bus level (cost of running an electric / non electric bus per km, cost of recharging) and at the trip level (penalty due to failed schedule adherence) are fully parametrised, allowing for extensive sensitivity analysis. We investigate a real-life case study based in the city of Luxembourg, where two charging stations have been installed in the central station’s bus terminal. Through the model we investigate: i) the minimum amount of electric buses necessary to perform a day’s schedule for two currently partially electrified lines, without resorting to conventional internal combustion alternatives; ii) the impact of electrifying two additional lines, specifically considering the trade-offs related to either adding new buses or new charging stations at the bus terminal. [less ▲]

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See detailTowards Optimised Deployment of Electric Bus Systems with On-Route Charging using Cooperative ITS
Laskaris, Georgios UL; Seredynski, Marcin; Viti, Francesco UL

Scientific Conference (2018, July)

Detailed reference viewed: 45 (6 UL)
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See detailUsing mobile phone data for urban network state estimation
Derrmann, Thierry; Frank, Raphaël UL; Engel, Thomas UL et al

Scientific Conference (2018, June)

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See detailA New Modelling Framework over Temporal Graphs for Collaborative Mobility Recommendation Systems
Toader, Bogdan UL; Moawad, Assaad UL; Fouquet, François UL et al

in A New Modelling Framework over Temporal Graphs for Collaborative Mobility Recommendation Systems (2018, March 15)

Over the years, collaborative mobility proved to be an important but challenging component of the smart cities paradigm. One of the biggest challenges in the smart mobility domain is the use of data ... [more ▼]

Over the years, collaborative mobility proved to be an important but challenging component of the smart cities paradigm. One of the biggest challenges in the smart mobility domain is the use of data science as an enabler for the implementation of large scale transportation sharing solutions. In particular, the next generation of Intelligent Transportation Systems (ITS) requires the combination of artificial intelligence and discrete simulations when exploring the effects of whatif decisions in complex scenarios with millions of users. In this paper, we address this challenge by presenting an innovative data modelling framework that can be used for ITS related problems. We demonstrate that the use of graphs and time series in multi-dimensional data models can satisfy the requirements of descriptive and predictive analytics in real-world case studies with massive amounts of continuously changing data. The features of the framework are explained in a case study of a complex collaborative mobility system that combines carpooling, carsharing and shared parking. The performance of the framework is tested with a large-scale dataset, performing machine learning tasks and interactive realtime data visualization. The outcome is a fast, efficient and complete architecture that can be easily deployed, tested and used for research as well in an industrial environment. [less ▲]

Detailed reference viewed: 181 (35 UL)