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It is common opinion that traditional approaches used to interpret and model users’ choice behaviour in innovative contexts may lead to neglecting numerous nonquantitative factors that may affect users’ perceptions and behaviours. Indeed, psychological factors, such as attitudes, concerns, and perceptions may play a significant role which should be explicitly modelled. By contrast, collecting psychological factors could be a time and cost consuming activity, and furthermore, real-world applications must rely on theoretical paradigms which are able to easily predict choice/market fractions. The present paper aims to investigate the above-mentioned issues with respect to an innovative automotive technology based on the after-market hybridization of internal combustion engine vehicles. In particular, three main research questions are addressed: (i) whether and how users’ characteristics and attitudes may affect users’ behaviour with respect to new technological (automotive) scenarios (e.g., after-market hybridization kit); (ii) how to better “grasp” users’ attitudes/concerns/perceptions and, in particular, which is the most effective surveying approach to observe users’ attitudes; (iii) to what extent the probability of choosing a new automotive technology is sensitive to attitudes/concerns changes. The choice to install/not install the innovative technology was modelled through a hybrid choice model with latent variables (HCMs), starting from a stated preferences survey in which attitudes were investigated using different types of questioning approaches: direct questioning, indirect questioning, or both approaches. Finally, a comparison with a traditional binomial logit model and a sensitivity analysis was carried out with respect to the instrumental attributes and the attitudes. Obtained results indicate that attitudes are significant in interpreting and predicting users’ behaviour towards the investigated technology and the HCM makes it possible to easily embed psychological factors into a random utility model/framework. Moreover, the explicit simulation of the attitudes allows for a better prediction of users’ choice with respect to the Logit formulation and points out that users’ behaviour may be significantly affected by acting on users’ attitudes.
Stefano De Luca; Roberta Di Pace. Did Attitudes Interpret and Predict “Better” Choice Behaviour towards Innovative and Greener Automotive Technologies? A Hybrid Choice Modelling Approach. Journal of Advanced Transportation 2020, 2020, 1 -22.
AMA StyleStefano De Luca, Roberta Di Pace. Did Attitudes Interpret and Predict “Better” Choice Behaviour towards Innovative and Greener Automotive Technologies? A Hybrid Choice Modelling Approach. Journal of Advanced Transportation. 2020; 2020 ():1-22.
Chicago/Turabian StyleStefano De Luca; Roberta Di Pace. 2020. "Did Attitudes Interpret and Predict “Better” Choice Behaviour towards Innovative and Greener Automotive Technologies? A Hybrid Choice Modelling Approach." Journal of Advanced Transportation 2020, no. : 1-22.
Depending on the context, several factors may affect users’ choices. In this paper, the main focus refers to modeling users’ willingness to purchase a new/innovative technology. This is a crucial task in order to increase the attractiveness of strategies that may be employed to achieve sustainable transportation. In particular this paper aims to investigate the different attributes/determinants that may influence the decision on choosing an Electric Vehicle. As a matter of fact, psychological factors, may play a significant role which should be modeled. Indeed, it is widely recognized that traditional approaches used to interpret and model users’ choice behavior may lead to neglect the numerous non-quantitative factors that may affect users’ behaviors. In particular, the role of attitudes and perception towards EVs advantages/barriers were investigated through the specification of a Hybrid Choice Model where the utility function was specified in accordance with the consolidated Random utility modeling but an alternative approach, based on the Analytic Hierarchy Process, was adopted for attitudes and perceptions representation. The purposes of the paper rely on (i) the survey data collection, (ii) data analysis, (iii) purchase behavior modeling. In particular, the main contribution of the paper is in the preliminary investigation of the combination between HCM and AHP method.
Stefano de Luca; Roberta Di Pace; Francesca Bruno. Accounting for attitudes and perceptions influencing users’ willingness to purchase Electric Vehicles through a Hybrid Choice Modeling approach based on Analytic Hierarchy Process. Transportation Research Procedia 2020, 45, 467 -474.
AMA StyleStefano de Luca, Roberta Di Pace, Francesca Bruno. Accounting for attitudes and perceptions influencing users’ willingness to purchase Electric Vehicles through a Hybrid Choice Modeling approach based on Analytic Hierarchy Process. Transportation Research Procedia. 2020; 45 ():467-474.
Chicago/Turabian StyleStefano de Luca; Roberta Di Pace; Francesca Bruno. 2020. "Accounting for attitudes and perceptions influencing users’ willingness to purchase Electric Vehicles through a Hybrid Choice Modeling approach based on Analytic Hierarchy Process." Transportation Research Procedia 45, no. : 467-474.
The gradual penetration of new transport modes and/or new technologies (advanced information systems, automotive technologies, etc.) requires effective theoretical paradigms able to interpret and model transportation system users’ propensity to purchase and use them. Along with the traditional approaches mainly based on random utility theory, it is a common opinion that numerous nonquantitative variables (such as psychological factors, attitudes, perceptions, etc.) may affect users’ behaviors. Different traditional approaches and more advanced ones (e.g. hybrid choice model (HCM) with latent variables, theory of planned behaviour, regret theory, prospect theory, etc.) may be identified and properly applied in the literature. In particular, the chapter will focus on the hybrid choice modeling with latent variables, aiming to incorporate users’ perceptions, attitudes and concerns in order to model the user’s propensity to use and the willingness to buy a new technology. The methodology overview and the results of the application at real data are discussed.
Stefano De Luca; Roberta Di Pace; Facundo Storani. Approaches for Modelling User’s Acceptance of Innovative Transportation Technologies and Systems. Transportation Systems Analysis and Assessment 2020, 1 .
AMA StyleStefano De Luca, Roberta Di Pace, Facundo Storani. Approaches for Modelling User’s Acceptance of Innovative Transportation Technologies and Systems. Transportation Systems Analysis and Assessment. 2020; ():1.
Chicago/Turabian StyleStefano De Luca; Roberta Di Pace; Facundo Storani. 2020. "Approaches for Modelling User’s Acceptance of Innovative Transportation Technologies and Systems." Transportation Systems Analysis and Assessment , no. : 1.
This paper focuses on the presentation of an integrated framework based on two advanced strategies, aimed at mitigating the effect of traffic congestion in terms of performance and environmental impact. In particular, the paper investigates the “operational benefits” that can be derived from the combination of traffic control (TC) and route guidance (RG) strategies. The framework is based on two modules and integrates a within-day traffic control method and a day-to-day behavioral route choice model. The former module consists of an enhanced traffic control model that can be applied to design traffic signal decision variables, suitable for real-time optimization. The latter designs the information consistently with predictive user reactions to the information itself. The proposed framework is implemented to a highly congested sub-network in the city center of Naples (Italy) and different scenarios are tested and compared. The “do nothing” scenario (current; DN) and the “modeled compliance” (MC) scenario, in which travelers’ reaction to the information (i.e., compliance) is explicitly represented. In order to evaluate the effectiveness of the proposed strategy and the modeling framework, the following analyses are carried out: (i) Network performance analysis; (ii) system convergence and stability analysis, as well as the compliance evolution over time; (iii) and emissions and fuel consumption impact analysis.
Stefano De Luca; Roberta Di Pace; Silvio Memoli; Luigi Pariota. Sustainable Traffic Management in an Urban Area: An Integrated Framework for Real-Time Traffic Control and Route Guidance Design. Sustainability 2020, 12, 726 .
AMA StyleStefano De Luca, Roberta Di Pace, Silvio Memoli, Luigi Pariota. Sustainable Traffic Management in an Urban Area: An Integrated Framework for Real-Time Traffic Control and Route Guidance Design. Sustainability. 2020; 12 (2):726.
Chicago/Turabian StyleStefano De Luca; Roberta Di Pace; Silvio Memoli; Luigi Pariota. 2020. "Sustainable Traffic Management in an Urban Area: An Integrated Framework for Real-Time Traffic Control and Route Guidance Design." Sustainability 12, no. 2: 726.
Giulio E. Cantarella; David Paul Watling; Stefano De Luca; Roberta Di Pace. Dynamics and Stochasticity in Transportation Systems. Dynamics and Stochasticity in Transportation Systems 2020, 1 .
AMA StyleGiulio E. Cantarella, David Paul Watling, Stefano De Luca, Roberta Di Pace. Dynamics and Stochasticity in Transportation Systems. Dynamics and Stochasticity in Transportation Systems. 2020; ():1.
Chicago/Turabian StyleGiulio E. Cantarella; David Paul Watling; Stefano De Luca; Roberta Di Pace. 2020. "Dynamics and Stochasticity in Transportation Systems." Dynamics and Stochasticity in Transportation Systems , no. : 1.
In order to address the very complex problem of urban traffic congestion the paper aims to investigate some "methodological" issues and "operational" benefits which can be derived from the implementation of a hybrid traffic control (TC) strategy. The main focus is on the integration of a within-day traffic flow modelling coupled with a traffic control method in particular: (1) a microscopic traffic flow representation was considered, (2) an enhanced on-line optimisation model able to design the traffic signal decision variables was adopted. Regarding the on-line traffic control a hybrid approach combining the interacting junctions optimisation (e.g. the decision variables are the green timings, the offsets and the stage sequences) and the link metering control was considered.The proposed framework was tested on a simulated case study using a calibrated network consisting of a highly congested sub-network in the city centre of Naples (Italy). The network layout is represented by one diversion node and two alternative paths connecting the same origin-destination pair; two scenarios were analysed: i) the single junction modelling; ii) the on-line scheduled synchronisation with the activation of link metering at upstream pedestrian crossings. The framework effectiveness is evaluated in terms of within-day dynamics with respect to the travel times performance index.
Stefano De Luca; Roberta Di Pace; Silvio Memoli; Facundo Storani. A hybrid traffic control framework for urban network management. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) 2019, 1 -6.
AMA StyleStefano De Luca, Roberta Di Pace, Silvio Memoli, Facundo Storani. A hybrid traffic control framework for urban network management. 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). 2019; ():1-6.
Chicago/Turabian StyleStefano De Luca; Roberta Di Pace; Silvio Memoli; Facundo Storani. 2019. "A hybrid traffic control framework for urban network management." 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) , no. : 1-6.
The paper aims to investigate the different attributes that may influence the choosing decision on the purchase of an electric vehicle. In particular, the research focuses on the analysis of an “immature” market such the case of the Argentinean market context. From the methodological point of view, the main purpose relies on the survey data collection and data analysis and modelling. Furthermore, the results achieved from a specific Stated Preferences survey carried out on a sample of Argentinian university students are shown. Therefore, the research aims to quantify and discuss the main determinants of the choice phenomenon through the specification and calibration of a choice model based on the Random Utility Theory.
Stefano De Luca; Roberta Di Pace; Facundo Storani. A Study on Users' Behaviour Towards Electric Vehicles in Immature Markets: The Argentina Case Study. 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) 2018, 1 -6.
AMA StyleStefano De Luca, Roberta Di Pace, Facundo Storani. A Study on Users' Behaviour Towards Electric Vehicles in Immature Markets: The Argentina Case Study. 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). 2018; ():1-6.
Chicago/Turabian StyleStefano De Luca; Roberta Di Pace; Facundo Storani. 2018. "A Study on Users' Behaviour Towards Electric Vehicles in Immature Markets: The Argentina Case Study." 2018 IEEE International Conference on Environment and Electrical Engineering and 2018 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) , no. : 1-6.
Stefano De Luca; Roberta Di Pace. Aftermarket vehicle hybridization: Potential market penetration and environmental benefits of a hybrid-solar kit. International Journal of Sustainable Transportation 2018, 12, 353 -366.
AMA StyleStefano De Luca, Roberta Di Pace. Aftermarket vehicle hybridization: Potential market penetration and environmental benefits of a hybrid-solar kit. International Journal of Sustainable Transportation. 2018; 12 (5):353-366.
Chicago/Turabian StyleStefano De Luca; Roberta Di Pace. 2018. "Aftermarket vehicle hybridization: Potential market penetration and environmental benefits of a hybrid-solar kit." International Journal of Sustainable Transportation 12, no. 5: 353-366.
One of the most straightforward short term policies to mitigate urban traffic congestion is control through traffic lights at a single junction or network level. Existing approaches for single junction Signal Setting Design (SSD) can be grouped into two classes: Stage-based or Phase-based methods. Both these approaches take the lane marking layouts as exogenous inputs, but lane-based optimisation method may be found in literature, even though for isolated signal-controlled junctions only. The Network Signal Setting Design (NSSD) requires that offsets are introduced; a traffic flow model is also needed to compute total delay. All existing methods for NSSD follow a stage-based approach; these methods do not allow for stage matrix optimisation: it is shown that explicit enumeration of stage sequences is only practicable for very small networks.\ud \ud This paper focuses on Network Signal Setting Design introducing the so-called scheduled synchronisation that includes green scheduling, green timing and coordination into one optimisation problem. The paper proposes a stage-based method to solve such a problem, as an extension of the synchronisation method and the traffic flow model proposed in Cantarella et al. (2015): first a set of candidate stages is defined for each junction, then the stage sequences, the stage lengths and the offsets are optimised all together. To the authors’ knowledge, no other one-step optimisation method is available in literature for scheduled synchronisation. Results of the proposed method to a small network were compared with those from explicit enumeration of all stage sequences; results for a larger network are also discussed
Silvio Memoli; Giulio E. Cantarella; Stefano de Luca; Roberta Di Pace. Network signal setting design with stage sequence optimisation. Transportation Research Part B: Methodological 2017, 100, 20 -42.
AMA StyleSilvio Memoli, Giulio E. Cantarella, Stefano de Luca, Roberta Di Pace. Network signal setting design with stage sequence optimisation. Transportation Research Part B: Methodological. 2017; 100 ():20-42.
Chicago/Turabian StyleSilvio Memoli; Giulio E. Cantarella; Stefano de Luca; Roberta Di Pace. 2017. "Network signal setting design with stage sequence optimisation." Transportation Research Part B: Methodological 100, no. : 20-42.
The paper focuses on the evaluation of the combined effect of Traffic Signal Control Strategy (TSC) and Variable Message Sign (VMS). With reference to the TSC a dynamic selection strategy based on macroscopic flow variables was considered for off-line traffic signal plans design. The combination of two ITS solutions, TSC and VMS, was tested through microscopic approach by SUMO traffic simulator which allows to directly reproduce the pollutant emissions and fuel consumptions.
Stefano De Luca; Roberta Di Pace; Silvio Memoli; Luigi Pariota. Matching macro- and micro-scopic approaches for the evaluation of traffic management impacts. 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) 2017, 1 -6.
AMA StyleStefano De Luca, Roberta Di Pace, Silvio Memoli, Luigi Pariota. Matching macro- and micro-scopic approaches for the evaluation of traffic management impacts. 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). 2017; ():1-6.
Chicago/Turabian StyleStefano De Luca; Roberta Di Pace; Silvio Memoli; Luigi Pariota. 2017. "Matching macro- and micro-scopic approaches for the evaluation of traffic management impacts." 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) , no. : 1-6.
The paper aims to develop a consistent framework for traffic management allowing for the joint optimization of connected vehicle paths and departure times and of signal control. The procedure is based on the communication between connected vehicles and signal controller (Vehicle to Infrastructure communications). Thus, the optimization procedure is characterized by two steps: the first refers to the adaptive traffic signal optimization, whilst the second refers to the optimization of routes and departure times of connected vehicles. In particular, as regards the adaptive traffic signal control, stage durations and sequences, as well as the node offsets, are considered as decision variables optimized with a scheduled synchronization method based on a meta-heuristic algorithm. On the contrary, the optimization of connected vehicle paths and departure times were considered as decision variables through a Mixed Integer Mathematical Program. Finally, as regards the traffic flow model, a further development of the Cell Transmission Model was considered. The whole framework was tested on a toy network.
Stefano De Luca; Roberta Di Pace; Angela Di Febbraro; Nicola Sacco. Transportation systems with connected and non-connected vehicles: Optimal traffic control. 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) 2017, 13 -18.
AMA StyleStefano De Luca, Roberta Di Pace, Angela Di Febbraro, Nicola Sacco. Transportation systems with connected and non-connected vehicles: Optimal traffic control. 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS). 2017; ():13-18.
Chicago/Turabian StyleStefano De Luca; Roberta Di Pace; Angela Di Febbraro; Nicola Sacco. 2017. "Transportation systems with connected and non-connected vehicles: Optimal traffic control." 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) , no. : 13-18.
The aim of the present paper is to investigate if behavioural models which are more accurate and effective (latent variables hybrid choice models) in simulating new automotive technology adoption, may significantly affect market forecasts and environmental impacts estimation. Since the time and the cost to develop each modelling solution are significantly different and require different types of surveys, the main goal of the paper is to give some insights into the costs and the benefits of each solution. Moreover, different models are compared in terms of sensitivity to different market scenarios and in terms of estimated environmental impacts on a real case study (the city of Salerno - southern Italy).
Stefano De Luca; Roberta Di Pace. Traditional random utility models vs hybrid choice models for assessing environmental impacts of a new technology: The HySolaKit case study. 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) 2017, 1 -6.
AMA StyleStefano De Luca, Roberta Di Pace. Traditional random utility models vs hybrid choice models for assessing environmental impacts of a new technology: The HySolaKit case study. 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). 2017; ():1-6.
Chicago/Turabian StyleStefano De Luca; Roberta Di Pace. 2017. "Traditional random utility models vs hybrid choice models for assessing environmental impacts of a new technology: The HySolaKit case study." 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) , no. : 1-6.
The paper focuses on the application of an AHP (Analytic Hierarchy Process) procedure for helping the decision maker in the identification of the road maintenance actions aiming to improve safety conditions and optimize the interchanges/interactions in terms of origin/destination flows among some strategic areas of the municipality of Naples.
Silvio Memoli; Mario Calabrese; Pasquale Di Pace; Nicola Pascale; Stefano De Luca. The use of the analytic hierarchy process method for supporting urban road regeneration actions: The case study of Naples. 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) 2017, 1 -6.
AMA StyleSilvio Memoli, Mario Calabrese, Pasquale Di Pace, Nicola Pascale, Stefano De Luca. The use of the analytic hierarchy process method for supporting urban road regeneration actions: The case study of Naples. 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). 2017; ():1-6.
Chicago/Turabian StyleSilvio Memoli; Mario Calabrese; Pasquale Di Pace; Nicola Pascale; Stefano De Luca. 2017. "The use of the analytic hierarchy process method for supporting urban road regeneration actions: The case study of Naples." 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) , no. : 1-6.
This paper proposes a method for netwok signal setting design, based on enhacements of an existing coordination method aiming: 1) to extend the existing approach in order to address the Traffic Control through Scheduled Synchronisation (i.e ‘one step’ optimisation of stage matrix, green timings, and node offsets ); 2) to extend the considered Mesoscopic Traffic Flow model (TRAFFMED) to the vehicle platoon speed dispersion; 3) to build up a solution method suitable for both off-line and on-line applications. The proposed optimisation method is an application of the Simulated Annealing meta-heuristic. Some numerical applications are proposed, specifically analysing ‘two step’ optimisation (synchronisation), and‘one step’ optimisation (scheduled synchronisation), for off-line (pre-timed strategy) and on-line applications (on-line computation strategy). A grid network was considered as case study and the effectiveness of the proposed strategies were evaluated by comparing the obtained results with those computed through commercial (benchmark) and in-house codes.
Roberta Di Pace; Giulio E. Cantarella; Stefano De Luca; Massimo Di Gangi. Scheduled Synchronisation based on a mesoscopic flow model with speed dispersion. Transportation Research Procedia 2017, 27, 180 -187.
AMA StyleRoberta Di Pace, Giulio E. Cantarella, Stefano De Luca, Massimo Di Gangi. Scheduled Synchronisation based on a mesoscopic flow model with speed dispersion. Transportation Research Procedia. 2017; 27 ():180-187.
Chicago/Turabian StyleRoberta Di Pace; Giulio E. Cantarella; Stefano De Luca; Massimo Di Gangi. 2017. "Scheduled Synchronisation based on a mesoscopic flow model with speed dispersion." Transportation Research Procedia 27, no. : 180-187.
In general in case of crash situations the quality of collected data is very limited and several information are usually unreliable. Thus it is recognised that a significant effort is required in order to improve the quality of the crash prediction models moreover a crucial role is played by the identification of the factors influencing the crashes occurrence and the levels of severity estimation. In this paper two injury crash rate prediction models related to single-vehicle run-off-road crashes type are calibrated and in particular significant attributes estimated are identified not only with roadway geometric characteristics and surface conditions, but also with gender/number-of-drivers. To this aim a survey of injury crashes on two-lane rural roads collected in the Southern Italy was considered and analysed. Finally before the calibration step, a preliminary analysis of the data was provided through the estimation of the levels of severity by multinomial logit; in fact by this model only segments with highest values of severity are identified and involved in the calibration procedure.
Francesca Russo; Roberta Di Pace; Gianluca Dell'Acqua; Stefano De Luca. Estimating an Injury Crash Rate Prediction Model based on severity levels evaluation: the case study of single-vehicle run-off-road crashes on rural context. Transportation Research Procedia 2017, 27, 1088 -1096.
AMA StyleFrancesca Russo, Roberta Di Pace, Gianluca Dell'Acqua, Stefano De Luca. Estimating an Injury Crash Rate Prediction Model based on severity levels evaluation: the case study of single-vehicle run-off-road crashes on rural context. Transportation Research Procedia. 2017; 27 ():1088-1096.
Chicago/Turabian StyleFrancesca Russo; Roberta Di Pace; Gianluca Dell'Acqua; Stefano De Luca. 2017. "Estimating an Injury Crash Rate Prediction Model based on severity levels evaluation: the case study of single-vehicle run-off-road crashes on rural context." Transportation Research Procedia 27, no. : 1088-1096.
In order to address the Signal Setting Design at urban level two main approaches may be pursued: the coordination and the synchronisation approaches depending on the steps considered for the optimisation of decision variables (two steps vs. one step). Furthermore, in terms of objective functions mono-criterion or multi-criteria may be adopted. In this paper the coordination approach is implemented considering the multi-criteria optimisation at single junctions and mono-criterion optimisation at network level whereas the synchronisation is implemented considering the mono-criterion optimisation. The main purpose of the paper is the evaluation of the performances of two strategies not only considering indicators such as the total delay, the queue length etc. but also considering other indicators such as the emissions and the fuel consumption. The methodological framework is composed by three stages: (i) the decision variables (green timings and offsets) computation through optimisation methods; (ii) the implementation of optimal signal settings in a microscopic traffic flow simulator (“Simulation of Urban MObility”-SUMO); (iii) the estimation of emissions and fuel consumption indicators.
S. De Luca; R. Di Pace; S. Memoli; L. Pariota. Comparing Signal Setting Design Methods Through Emission and Fuel Consumption Performance Indicators. Advances in Intelligent Systems and Computing 2016, 200 -209.
AMA StyleS. De Luca, R. Di Pace, S. Memoli, L. Pariota. Comparing Signal Setting Design Methods Through Emission and Fuel Consumption Performance Indicators. Advances in Intelligent Systems and Computing. 2016; ():200-209.
Chicago/Turabian StyleS. De Luca; R. Di Pace; S. Memoli; L. Pariota. 2016. "Comparing Signal Setting Design Methods Through Emission and Fuel Consumption Performance Indicators." Advances in Intelligent Systems and Computing , no. : 200-209.
Most of the existing Carsharing business models mainly rely on gasoline vehicles and diesel vehicles, but in recent years there has been a significant increase in hybrid electric vehicles (HEVs) and a resurgence in electric vehicles (EVs). Within this framework, this paper investigates and models the choice to switch from a private car trip to a carsharing service available in peripheral parks as well as the propensity to choose an electric vehicle for such a service. In particular, three issues are addressed: (i) investigating and modelling the propensity to choose carsharing as a transport alternative within a neighbourhood residential carsharing business model; (ii) estimating the effect of also having an EV option available; (iii) measuring the “pure preference”, if any, in using electric vehicles over traditional ones, in a context excluding factors that may bias such users preference (e.g. purchase price, energy costs, recharging facilities etc). The analyses are based on a stated preferences survey undertaken on 600 car drivers entering the city centre of Salerno (Southern Italy), and on the estimation of a binomial Logit model with serial correlation. Results allow an interpretation of the main determinants of the short-term choice of carsharing services (i.e. without any car-ownership changes), give general behavioural insights, make it possible to quantify the “pure preference” for EV and the demand elasticity with regard to different pricing strategies of the carsharing services.
Armando Cartenì; Ennio Cascetta; Stefano de Luca. A random utility model for park & carsharing services and the pure preference for electric vehicles. Transport Policy 2016, 48, 49 -59.
AMA StyleArmando Cartenì, Ennio Cascetta, Stefano de Luca. A random utility model for park & carsharing services and the pure preference for electric vehicles. Transport Policy. 2016; 48 ():49-59.
Chicago/Turabian StyleArmando Cartenì; Ennio Cascetta; Stefano de Luca. 2016. "A random utility model for park & carsharing services and the pure preference for electric vehicles." Transport Policy 48, no. : 49-59.
The paper focuses on the analysis of the traveler's behavior in a route choice context in presence of information. In general, in case of choice contexts where the uncertainty is due to the actual travel times variances and/or the information accuracy, travelers' reaction, usually modeled by considering the utility maximization paradigm, may be affected by the risk perception. However, depending on the considered tool for collecting data (driving vs. web-based simulator) different behaviors (such as risk aversion) may be observed. This paper aims to applying the Cumulative Prospect theory in order to model travelers' behavior in a risky route choice context using data collected by different tools. In particular, in this paper data collected by (static) driving simulator and (web-based) travel simulator are compared by aggregated analysis. Finally, the results of the modelling approach are shown in order to properly evaluate how the simulation environment may affect the travelers' risk perception by introducing a bias in alternative choice.
Stefano De Luca; Roberta Di Pace. Evaluation of Risk Perception in Route Choice Experiments: An Application of the Cumulative Prospect Theory. 2015 IEEE 18th International Conference on Intelligent Transportation Systems 2015, 309 -315.
AMA StyleStefano De Luca, Roberta Di Pace. Evaluation of Risk Perception in Route Choice Experiments: An Application of the Cumulative Prospect Theory. 2015 IEEE 18th International Conference on Intelligent Transportation Systems. 2015; ():309-315.
Chicago/Turabian StyleStefano De Luca; Roberta Di Pace. 2015. "Evaluation of Risk Perception in Route Choice Experiments: An Application of the Cumulative Prospect Theory." 2015 IEEE 18th International Conference on Intelligent Transportation Systems , no. : 309-315.
Despite the recent commercial success of hybrid, plug-in hybrid and electric vehicles their market share is still insufficient to produce either a significant impact on energy consumption on a global basis or a profitable automotive segment. In this context, the possibility of upgrading conventional vehicles to hybrid electric vehicles is gaining increasing interest. To this aim this paper investigated and modelled the intention to install an after-market hybridization solar-kit (HySolarKit) in order to ascertain the main behavioural determinants of the choice process and set up an operational model with which to estimate the market potential of such technology. In particular, two behavioural stages of the choice process were analysed and modelled: (i) the intention to adopt the HySolarKit; (ii) the choice to install the HySolarKit. Both issues were addressed through ad hoc stated preference surveys carried out in two different Italian cities, and through the specification and the calibration of discrete choice models based on the behavioural paradigm of random utility theory. Different modelling solutions (homoscedastic and heteroscedastic) were compared in terms of goodness-of-fit and sensitivity to level-of-service attributes. The results showed the technological potential of the HySolarKit, and that both behavioural stages may be effectively modelled through random utility theory. Estimation results allowed an interpretation of the main determinants of the investigated phenomena, making it possible to quantify the potential effects and the concerns towards such a green solution, and making it possible to draw up operative marketing strategies. In particular, the intention to adopt the kit mainly depends on socio-economic factors as well as activity-related and attitudinal attributes, whereas the probability of installing the kit is greatly affected, to the same extent, by installation cost, the charging cost and the weekly mileage driven
Stefano De Luca; Roberta Di Pace; Vincenzo Marano. Modelling the adoption intention and installation choice of an automotive after-market mild-solar-hybridization kit. Transportation Research Part C: Emerging Technologies 2015, 56, 426 -445.
AMA StyleStefano De Luca, Roberta Di Pace, Vincenzo Marano. Modelling the adoption intention and installation choice of an automotive after-market mild-solar-hybridization kit. Transportation Research Part C: Emerging Technologies. 2015; 56 ():426-445.
Chicago/Turabian StyleStefano De Luca; Roberta Di Pace; Vincenzo Marano. 2015. "Modelling the adoption intention and installation choice of an automotive after-market mild-solar-hybridization kit." Transportation Research Part C: Emerging Technologies 56, no. : 426-445.
This paper aims to investigate the application of meta-heuristic optimisation methods to Network Signal Setting Design. The adopted approaches are (i) three step optimisation, in which first the stage matrix (stage composition and sequence), the green timings at each single junction are optimised, then the node offsets are computed in three successive steps; (ii) two step optimisation, in which the stage matrix is defined at a first step, then the green timings and the node offsets are computed at a second step. In both approaches the stage matrix optimisation is carried out through explicit complete enumeration. In the first approach multi-criteria optimisation is followed for single junction signal setting design (green timings), whilst the coordination (node offsets) is approached through mono-criterion optimisation, as well as for the synchronisation (green timings and offsets) in the second approach. A new traffic flow model mixing \CTM\ and \PDM\ has been applied. This model allows to explicitly represent horizontal queuing phenomena as well as dispersion along a link. Some meta-heuristic algorithms (i.e. Genetic Algorithms, Hill Climbing and Simulated Annealing) are investigated in order to solve the two problems. The proposed strategies are applied to two different layouts (a two junction arterial vs. a four junction network) and their effectiveness is evaluated by comparing the obtained results with those from benchmark approaches implementing mono-criterion optimisation only
Giulio E. Cantarella; Stefano de Luca; Roberta Di Pace; Silvio Memoli. Network Signal Setting Design: Meta-heuristic optimisation methods. Transportation Research Part C: Emerging Technologies 2015, 55, 24 -45.
AMA StyleGiulio E. Cantarella, Stefano de Luca, Roberta Di Pace, Silvio Memoli. Network Signal Setting Design: Meta-heuristic optimisation methods. Transportation Research Part C: Emerging Technologies. 2015; 55 ():24-45.
Chicago/Turabian StyleGiulio E. Cantarella; Stefano de Luca; Roberta Di Pace; Silvio Memoli. 2015. "Network Signal Setting Design: Meta-heuristic optimisation methods." Transportation Research Part C: Emerging Technologies 55, no. : 24-45.