References of "Viti, Francesco 50003272"
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See detailMixed-fleet single-terminal bus scheduling problem: Modelling, solution scheme and potential applications
Rinaldi, Marco UL; Picarelli, Erika UL; D'Ariano, Andrea et al

in Omega: the International Journal of Management Science (in press)

Reducing pollutant emissions and promoting sustainable mobility solutions, including Public Transport (PT), are increasingly becoming key objectives for policymakers worldwide. In this work we develop an ... [more ▼]

Reducing pollutant emissions and promoting sustainable mobility solutions, including Public Transport (PT), are increasingly becoming key objectives for policymakers worldwide. In this work we develop an optimal vehicle scheduling approach for next generation PT 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. We propose a Mixed In- teger Linear Program (MILP) to address the problem of optimal scheduling of a mixed fleet of electric and hybrid / non-electric buses, coupled with an ad-hoc decomposition scheme aimed at enhancing the scalability of the proposed MILP. Two case studies arising from the PT network of the city of Luxem- bourg are employed in order to validate the model; sensitivity analysis to fleet design parameters is performed, specifically in terms of fleet size and fleet composition. Conclusions point to the fact that careful modelling and handling of mixed-fleet conditions are necessary to achieve operational savings, and that marginal savings gradually reduce as more conventional buses are replaced by their electric counterparts. We believe the methodology proposed may be a key part of advanced decision support systems for policymakers and operators that are dealing with the on-going transition from conventional bus fleets towards greener transport solutions. [less ▲]

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See detailUsing Passive Data Collection Methods to Learn Complex Mobility Patterns: An Exploratory Analysis
Toader, Bogdan UL; Cantelmo, Guido UL; Popescu, Mioara et al

Scientific Conference (in press)

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

in Transportation Research Procedia (in press)

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 detailMixed hybrid and electric bus dynamic fleet management in urban networks: a model predictive control approach
Rinaldi, Marco UL; Picarelli, Erika UL; D'Ariano, Andrea et al

Scientific Conference (2019, June)

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

Abstract—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 real time hybrid controller for regulating bus operations and reducing stops at signals
Laskaris, Georgios UL; Seredynski, Marcin; Viti, Francesco UL

Scientific Conference (2019, June)

We propose a hybrid controller which consists of holding and a Driver Advisory System (DAS). It combines the objectives of seeking the regularization of operation and the reduction of stop and go actions ... [more ▼]

We propose a hybrid controller which consists of holding and a Driver Advisory System (DAS). It combines the objectives of seeking the regularization of operation and the reduction of stop and go actions at signalized intersections. A simple headway based holding criterion is applied at stops to define the time needed to maintain even spaced headways between buses and additionally a speed recommendation is given to traverse during green indication at the downstream signalized intersection. The controller is tested using simulation for a bus line of the city of Luxembourg, Luxembourg and compared to a benchmark scenario, the single application of bus holding, two advisory systems and different levels of transit signal priority. Results show that there are additional benefits compared to traditional holding in terms of regularity while similar performance to strong transit signal priority is achieved in terms of time spent at traffic lights. [less ▲]

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See detailLeveraging GIS Data and Topological Information to Infer Trip Chaining Behaviour at Macroscopic Level
Carrese, Filippo; Fusco, Gaetano; Cantelmo, Guido et al

Scientific Conference (2019, June)

One of the open challenges in transport modelling is to estimate within-day demand flows that reflect the complexity of individual activity-travel behaviour. While disaggregate (Activity-Based) demand ... [more ▼]

One of the open challenges in transport modelling is to estimate within-day demand flows that reflect the complexity of individual activity-travel behaviour. While disaggregate (Activity-Based) demand models can recreate realistic daily mobility patterns at an individual level, they usually require an accurate knowledge of individual user behaviour (i.e. via travel surveys), which is not always available. As a result, practitioners often turn to aggregate demand models, that have the advantage of being less demanding in terms of data but typically under represent the demand for secondary activities. In this work, we take research on within-day demand modelling one step forward by proposing a framework that combines traditional methodologies with heterogeneous data sources in order to explicitly represent trip chaining at an aggregated level. We show that the combination of web-based crowd sensed data, network data and behavioural constraints allows to capture complex spatial and temporal correlations between demand patterns. The methodology is applied on the classical Gravity model to show how to incorporate within-day dynamics. Yet, any alternative demand model can be adopted. In our case, Generation and Attraction are used to estimate the systematic demand, that is enriched of information about individual activity patterns, and then a novel definition of impedance function based on Hagestraand ellipse theory plays a central role in spatially distributing locations of trips using geographic relationships and constraints deriving from space-time behaviour. A case study for Luxembourg City has been presented to show the potential of the methodology: the choice of using data from a different spatial context to account for the temporal dimension has been validated through comparisons with official statistics. The results of simulating a workplace relocation show the advantages of this new approach in representing demand related to secondary activities. [less ▲]

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See detailSupply characteristics and membership choice in round-trip and free-floating carsharing systems
Cisterna, Carolina UL; Giorgione, Giulio UL; Cipriani, Ernesto et al

Scientific Conference (2019, June)

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See detailAvailability-based dynamic pricing on a round-trip carsharing service: an explorative analysis using agent-based simulation 
Giorgione, Giulio UL; Ciari, Francesco; Viti, Francesco UL

in Transportation Research Procedia (2019)

Carsharing companies aim to customize their service to increase fleet usage and revenues with different pricing schemes and offer types. Dynamic pricing policies can be designed to adjust and balance ... [more ▼]

Carsharing companies aim to customize their service to increase fleet usage and revenues with different pricing schemes and offer types. Dynamic pricing policies can be designed to adjust and balance temporally and spatially cars availability but may pose some question on customers’ fairness. In this paper, we propose an explorative analysis of how an availability-based dynamic pricing scheme impacts the demand and the supply performance. The policy is simulated in MATSim and compared to a fixed pricing policy scheme. This simulation consists of analyzing the behavior of a synthetic population of car-sharing members for Berlin and the surrounding region in which is applied an availability-based dynamic pricing in which price depends on vehicle availability in booking stations. Results show that when the dynamic pricing is applied there is a light decrease in the number of bookings and people with low value of time tend to abandon the carsharing mode in favor of other modes of transportation. [less ▲]

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See detailAnalysis of Cooperative Bus Priority at Traffic Signals
Seredynski, Marcin; Laskaris, Georgios UL; Viti, Francesco UL

in IEEE Transactions on Intelligent Transportation Systems (2019)

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See detailHow Road and Mobile Networks Correlate: Estimating Urban Traffic Using Handovers
Derrmann, Thierry; Frank, Raphaël UL; Viti, Francesco UL et al

in IEEE Transactions on Intelligent Transportation Systems (2019)

We propose a novel way of linking mobile network signaling data to the state of the underlying urban road network. We show how a predictive model of traffic flows can be created from mobile network ... [more ▼]

We propose a novel way of linking mobile network signaling data to the state of the underlying urban road network. We show how a predictive model of traffic flows can be created from mobile network signaling data. To achieve this, we estimate the vehicular density inside specific areas using a polynomial function of the inner and exiting mobile phone handovers performed by the base stations covering those areas. We can then use the aggregated handovers as flow proxies alongside the density proxy to directly estimate an average velocity within an area. We evaluate the model in a simulation study of Luxembourg city and generalize our findings using a real-world data set extracted from the LTE network of a Luxembourg operator. By predicting the real traffic states as measured through floating car data, we achieve a mean absolute percentage error of 11.12%. Furthermore, in our study case, the approximations of the network macroscopic fundamental diagrams (MFD) of road network partitions can be generated. The analyzed data exhibit low variance with respect to a quadratic concave flow-density function, which is inline with the previous theoretical results on MFDs and are similar when estimated from simulation and real data. These results indicate that mobile signaling data can potentially be used to approximate MFDs of the underlying road network and contribute to better estimate road traffic states in urban congested networks. [less ▲]

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

in Transportation Research. Part B, Methodological (2019)

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

Time-dependent Origin–Destination (OD) demand flows are fundamental inputs for Dy- namic Traffic Assignment (DTA) systems and real-time traffic management. This work in- troduces a novel state-space framework to estimate these demand flows in an online con- text. 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 net- work. 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 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 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)

Detailed reference viewed: 89 (2 UL)
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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 Markov Chain Mote Carlo Approach for Estimating Daily Activity Patterns
Scheffer, Ariane Hélène Marie UL; Bandiera, Claudia; Cantelmo, Guido et al

Poster (2019, January)

Determining the purpose of trips brings is a fundamental information to evaluate travel demand during the day and to predict longer-term impacts on the population’s travel behavior. The concept of tours ... [more ▼]

Determining the purpose of trips brings is a fundamental information to evaluate travel demand during the day and to predict longer-term impacts on the population’s travel behavior. The concept of tours is the most suited to consider the value of a daily scheduling of individuals and travel interdependencies. However, the meticulous care required for both collecting data of high quality and interpret results of advanced demand models are frequently considered as major drawbacks. The objective of this study is to incorporate into a standard trip-based model some inherent concepts of activity-based models in order to enhance the representation of travel behavior. The main focus of this work is to infer, employing utility theory, the trip purpose of a population, at a zonal level. Making use of Markov Chain Monte Carlo, a set of parameters is estimated in order to retrieve tour-based primitives of the demand. The main advantage of this methodology is the low requirements in terms of data, as no individual information are used, and the good interpretation of the model. Estimated parameters of the priors set a utility-based probability function for departure time, which allows to have a dynamic overview of the demand. In order to account for the tour consistency of travel decisions, a duration constraint is added to the model. The proposed model is applied to the region of Luxembourg city and the results show the potential of the methodologies for dividing an observed demand based on the activity at destination. [less ▲]

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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)

Detailed reference viewed: 29 (1 UL)