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Modelling route choice decision making in Advanced Traveler information System (ATIS) contexts is still a crucial task. In particular, two main categories of variables can be identified in order to model travelers’ behaviors: the former may be defined as endogenous and are related to the experiment environment; the latter may be defined as exogenous (referring to the respondents involved in the experiment). This paper focuses on the analysis of exogenous variables. An experiment is carried out using a driving simulator, on a real route choice context (a sub-area of the urban network in the city of Naples, in the Campania Region) reproduced in a virtual reality. All data are analyzed by aggregate and statistical approaches to preliminarily investigate the correlations between some exogenous variables and the collected choices of drivers. Furthermore, collected observations have been modelled by applying the Structural Equation Model (SEM) approach to model the effect of information on switching behaviors.
Roberta Di Pace; Stefano de Luca; Francesco Galante; Luigi Pariota. Modelling Behavior in a Route Choice Driving Simulation Experiment in Presence of Information. Inventive Computation and Information Technologies 2021, 677 -689.
AMA StyleRoberta Di Pace, Stefano de Luca, Francesco Galante, Luigi Pariota. Modelling Behavior in a Route Choice Driving Simulation Experiment in Presence of Information. Inventive Computation and Information Technologies. 2021; ():677-689.
Chicago/Turabian StyleRoberta Di Pace; Stefano de Luca; Francesco Galante; Luigi Pariota. 2021. "Modelling Behavior in a Route Choice Driving Simulation Experiment in Presence of Information." Inventive Computation and Information Technologies , no. : 677-689.
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.
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.
The paper aims to provide a further development of traffic control strategies, to propose an enhanced version of two traffic flow models and to integrate these models within an urban traffic control framework. With regard to the traffic control method, the synchronisation approach is adopted and three objective functions are considered and compared: two are mono-criterion and the third is multi-criteria. Simulated annealing and multi-objective simulated annealing are adopted as a solution algorithm. In terms of traffic flow representation the approaches analysed are macroscopic cell-based and mesoscopic link-based, both able to model path choice behaviours and vehicle dispersion phenomena. Furthermore, traffic flow prediction is pursued through a Kalman filter and a rolling horizon approach is adopted as a forecasting framework for the optimisation procedure. In order to test the framework and to compare two traffic flow models, a 15-node grid network was considered, including different levels of congestion and demand profiles.
Roberta Di Pace. A traffic control framework for urban networks based on within-day dynamic traffic flow models. Transportmetrica A: Transport Science 2019, 16, 234 -269.
AMA StyleRoberta Di Pace. A traffic control framework for urban networks based on within-day dynamic traffic flow models. Transportmetrica A: Transport Science. 2019; 16 (2):234-269.
Chicago/Turabian StyleRoberta Di Pace. 2019. "A traffic control framework for urban networks based on within-day dynamic traffic flow models." Transportmetrica A: Transport Science 16, no. 2: 234-269.
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 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.
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.
The paper focuses on Network Traffic Control based on aggregate traffic flow variables, aiming at signal settings which are consistent with within-day traffic flow dynamics. The proposed optimisation strategy is based on two successive steps: the first step refers to each single junction optimisation (green timings), the second to network coordination (offsets). Both of the optimisation problems are solved through meta-heuristic algorithms: the optimisation of green timings is carried out through a multi-criteria Genetic Algorithm whereas offset optimisation is achieved with the mono-criterion Hill Climbing algorithm. To guarantee proper queuing and spillback simulation, an advanced mesoscopic traffic flow model is embedded within the network optimisation method. The adopted mesoscopic traffic flow model also includes link horizontal queue modelling. The results attained through the proposed optimisation framework are compared with those obtained through benchmark tools.
Massimo Di Gangi; Giulio Erberto Cantarella; Roberta Di Pace; Silvio Memoli. Network traffic control based on a mesoscopic dynamic flow model. Transportation Research Part C: Emerging Technologies 2016, 66, 3 -26.
AMA StyleMassimo Di Gangi, Giulio Erberto Cantarella, Roberta Di Pace, Silvio Memoli. Network traffic control based on a mesoscopic dynamic flow model. Transportation Research Part C: Emerging Technologies. 2016; 66 ():3-26.
Chicago/Turabian StyleMassimo Di Gangi; Giulio Erberto Cantarella; Roberta Di Pace; Silvio Memoli. 2016. "Network traffic control based on a mesoscopic dynamic flow model." Transportation Research Part C: Emerging Technologies 66, no. : 3-26.
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.
In this paper, the effects of a inter-urban carsharing program on users’ mode choice behaviour were investigated and modelled through specification, calibration and validation of different modelling approaches founded on the behavioural paradigm of the random utility theory. To this end, switching models conditional on the usually chosen transport mode, unconditional switching models and holding models were investigated and compared. The aim was threefold: (i) to analyse the feasibility of a inter-urban carsharing program; (ii) to investigate the main determinants of the choice behaviour; (iii) to compare different approaches (switching vs. holding; conditional vs. unconditional); (iv) to investigate different modelling solutions within the random utility framework (homoscedastic, heteroscedastic and cross-correlated closed-form solutions). The set of models was calibrated on a stated preferences survey carried out on users commuting within the metropolitan area of Salerno, in particular with regard to the home-to-work trips from/to Salerno (the capital city of the Salerno province) to/from the three main municipalities belonging to the metropolitan area of Salerno. All of the involved municipalities significantly interact each other, the average trip length is about 30 km a day and all are served by public transport. The proposed carsharing program was a one-way service, working alongside public transport, with the possibility of sharing the same car among different users, with free parking slots and free access to the existent restricted traffic areas. Results indicated that the inter-urban carsharing service may be a substitute of the car transport mode, but also it could be a complementary alternative to the transit system in those time periods in which the service is not guaranteed or efficient. Estimation results highlighted that the conditional switching approach is the most effective one, whereas travel monetary cost, access time to carsharing parking slots, gender, age, trip frequency, car availability and the type of trip (home-based) were the most significant attributes. Elasticity results showed that access time to the parking slots predominantly influences choice probability for bus and carpool users; change in carsharing travel costs mainly affects carpool users; change in travel costs of the usually chosen transport mode mainly affects car and carpool users
Stefano de Luca; Roberta Di Pace. Modelling users’ behaviour in inter-urban carsharing program: A stated preference approach. Transportation Research Part A: Policy and Practice 2015, 71, 59 -76.
AMA StyleStefano de Luca, Roberta Di Pace. Modelling users’ behaviour in inter-urban carsharing program: A stated preference approach. Transportation Research Part A: Policy and Practice. 2015; 71 ():59-76.
Chicago/Turabian StyleStefano de Luca; Roberta Di Pace. 2015. "Modelling users’ behaviour in inter-urban carsharing program: A stated preference approach." Transportation Research Part A: Policy and Practice 71, no. : 59-76.
This paper proposes and compares different approaches within the general fixed-point framework that allows to deal with multi-user (stochastic) equilibrium assignment with variable demand (VD). The aim was threefold: (i) compare the efficiency and the effectiveness of the internal and the external approaches to stochastic equilibrium assignment with VD; (ii) investigate the efficiency and the effectiveness of different algorithms based on the method of successive averages and its extensions; (iii) investigate the effects of different averaging schemes, different convergence criteria and different path choice models, such as Multinomial Logit model, C-Logit model and Multinomial Probit model. Analyses were carried out with respect to a real network and considering different indicators of both efficiency and effectiveness.
Giulio E. Cantarella; S. De Luca; Massimo DI Gangi; R. Di Pace. Approaches for solving the stochastic equilibrium assignment with variable demand: internal vs. external solution algorithms. Optimization Methods and Software 2014, 30, 338 -364.
AMA StyleGiulio E. Cantarella, S. De Luca, Massimo DI Gangi, R. Di Pace. Approaches for solving the stochastic equilibrium assignment with variable demand: internal vs. external solution algorithms. Optimization Methods and Software. 2014; 30 (2):338-364.
Chicago/Turabian StyleGiulio E. Cantarella; S. De Luca; Massimo DI Gangi; R. Di Pace. 2014. "Approaches for solving the stochastic equilibrium assignment with variable demand: internal vs. external solution algorithms." Optimization Methods and Software 30, no. 2: 338-364.
The purpose of this paper is the application of Genetic Algorithms to solve the Signal Setting Design at a single junction. Two methods are compared: the monocriteria and the multicriteria optimisations. In the former case, three different objectives functions were considered: the capacity factor maximisation, the total delay minimisation and the total number of stops minimisation; in the latter case, two combinations of criteria were investigated: the total delay minimisation and the capacity factor maximisa-tion, the total delay minimisation and the total number of stops minimisation. Furthermore, two multicriteria genetic algorithms were compared: the Goldberg’s Pareto Ranking (GPR) and the Non Dominated Sorting Genetic Algorithms (NSGA-II). Conclusions discuss the effectiveness of multicrite-ria optimisation with respect to monocriteria optimisation, and the effec-tiveness of NSGA-II with respect to the GPR
Giulio Erberto Cantarella; Stefano De Luca; Roberta Di Pace; Silvio Memoli. Signal Setting Design at a Single Junction Through the Application of Genetic Algorithms. Advances in Intelligent Systems and Computing 2014, 321 -331.
AMA StyleGiulio Erberto Cantarella, Stefano De Luca, Roberta Di Pace, Silvio Memoli. Signal Setting Design at a Single Junction Through the Application of Genetic Algorithms. Advances in Intelligent Systems and Computing. 2014; ():321-331.
Chicago/Turabian StyleGiulio Erberto Cantarella; Stefano De Luca; Roberta Di Pace; Silvio Memoli. 2014. "Signal Setting Design at a Single Junction Through the Application of Genetic Algorithms." Advances in Intelligent Systems and Computing , no. : 321-331.
Stefano De Luca; Roberta Di Pace. Modelling the Propensity in Adhering to a Carsharing System: A Behavioral Approach. Transportation Research Procedia 2014, 3, 866 -875.
AMA StyleStefano De Luca, Roberta Di Pace. Modelling the Propensity in Adhering to a Carsharing System: A Behavioral Approach. Transportation Research Procedia. 2014; 3 ():866-875.
Chicago/Turabian StyleStefano De Luca; Roberta Di Pace. 2014. "Modelling the Propensity in Adhering to a Carsharing System: A Behavioral Approach." Transportation Research Procedia 3, no. : 866-875.
Modelling route choices is one of the most significant tasks in transportation models. Route choice models under Advanced Traveller Information Systems (ATIS) are often developed and calibrated by using, among other, Stated Preferences (SP) surveys. Different types of SP approaches can be adopted, alternatively based on Travel Simulators (TSs) or Driving Simulators (DSs). Here a pilot study is presented, aimed at setting up an SP-tool based on driving simulator developed at the Technical University of Bari. The obtained results are analysed in order to check the accordance with expectations in particular the results of application of data fusion technique are shown in order to explain how data collected by DSs, can be used to reduce the effect of choice of behaviour in unrealistic scenarios in TSs.
Mauro Dell’Orco; Roberta Di Pace; Mario Marinelli; Francesco Galante. Application of Data Fusion for Route Choice Modelling by Route Choice Driving Simulator. Advances in Intelligent Systems and Computing 2013, 305 -313.
AMA StyleMauro Dell’Orco, Roberta Di Pace, Mario Marinelli, Francesco Galante. Application of Data Fusion for Route Choice Modelling by Route Choice Driving Simulator. Advances in Intelligent Systems and Computing. 2013; ():305-313.
Chicago/Turabian StyleMauro Dell’Orco; Roberta Di Pace; Mario Marinelli; Francesco Galante. 2013. "Application of Data Fusion for Route Choice Modelling by Route Choice Driving Simulator." Advances in Intelligent Systems and Computing , no. : 305-313.
Giulio E. Cantarella; Stefano De Luca; Massimo Di Gangi; Roberta Di Pace. Two Variables Algorithms for Solving the Stochastic Equilibrium Assignment with Variable Demand: Performance Analysis and Effects of Path Choice Models. Procedia - Social and Behavioral Sciences 2013, 87, 177 -192.
AMA StyleGiulio E. Cantarella, Stefano De Luca, Massimo Di Gangi, Roberta Di Pace. Two Variables Algorithms for Solving the Stochastic Equilibrium Assignment with Variable Demand: Performance Analysis and Effects of Path Choice Models. Procedia - Social and Behavioral Sciences. 2013; 87 ():177-192.
Chicago/Turabian StyleGiulio E. Cantarella; Stefano De Luca; Massimo Di Gangi; Roberta Di Pace. 2013. "Two Variables Algorithms for Solving the Stochastic Equilibrium Assignment with Variable Demand: Performance Analysis and Effects of Path Choice Models." Procedia - Social and Behavioral Sciences 87, no. : 177-192.
This paper analyses travellers' behaviour with respect to route choice in a context where an Advanced Traveller Information System (ATIS) is in place. ATIS are important applications in the field of intelligent transportation systems (ITS). However, the practical impact of ATIS is still a matter for debate, and identification of expected route choice behaviour under ATIS is one of the main ways to assess their practical importance. Travellers' choices are frequently explored by means of stated preference (SP) approaches. In this paper we discuss some issues to be addressed when an SP survey is carried out, with particular reference to cases where a repeated choice approach is employed in the survey. Our analysis concerns an application of the SP approach in a pilot study aimed at identifying the effects of ATIS accuracy on travellers’ compliance with information.\ud This paper aims to make two major contributions. First of all, empirical analyses based on proper indicators and statistical tests are suggested in order to evaluate how the collected data have to be handled in order to eliminate transient route-choice observations. These are due to the warm-up phase inherently associated with the survey method adopted, dealing with repeated choices. Secondly, we analyse (stationary) route choice in order to assess the effects of information reliability (and the kind of information) on both route choice and compliance
Gennaro Nicola Bifulco; Roberta Di Pace; Francesco Viti. Evaluating the effects of information reliability on travellers’ route choice. European Transport Research Review 2013, 6, 61 -70.
AMA StyleGennaro Nicola Bifulco, Roberta Di Pace, Francesco Viti. Evaluating the effects of information reliability on travellers’ route choice. European Transport Research Review. 2013; 6 (1):61-70.
Chicago/Turabian StyleGennaro Nicola Bifulco; Roberta Di Pace; Francesco Viti. 2013. "Evaluating the effects of information reliability on travellers’ route choice." European Transport Research Review 6, no. 1: 61-70.
The aim of this paper is threefold: (1) propose a detailed literature review; (2) compare existing approaches and (3) discuss the main research...
Giulio E. Cantarella; S. De Luca; Massimo DI Gangi; Roberta Di Pace. Stochastic equilibrium assignment with variable demand: literature review, comparisons and research needs. Urban Transport XIX 2013, 130, 349 -364.
AMA StyleGiulio E. Cantarella, S. De Luca, Massimo DI Gangi, Roberta Di Pace. Stochastic equilibrium assignment with variable demand: literature review, comparisons and research needs. Urban Transport XIX. 2013; 130 ():349-364.
Chicago/Turabian StyleGiulio E. Cantarella; S. De Luca; Massimo DI Gangi; Roberta Di Pace. 2013. "Stochastic equilibrium assignment with variable demand: literature review, comparisons and research needs." Urban Transport XIX 130, no. : 349-364.