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Urban air pollution continues to represent a primary concern for human health, despite significant efforts by public authorities for mitigating its effects. Regulatory monitoring networks are essential tools for air pollution monitoring. However, they are sparse networks, unable to capture the spatial variability of the air pollutants. For addressing this issue, networks of low cost stations are deployed, supplementing the regulatory stations. Regarding this application, an important question is where these stations are installed The objective of this study was to generate a site suitability map for the development of a network of low cost multi-sensor stations across a city for a spatially dense urban air quality monitoring. To do that, a site suitability analysis was developed based on two geographical variables properly selected for representing the impact of urban pollutant sources and urban form on the pollutant concentrations. By processing information about emissions patterns and street canyon effects, we were able to identify air quality hotspot areas supposed to show high spatial variability. Low cost monitoring stations, there located, are able to provide that informative content, which is lacking for both regulatory monitoring networks and predictive modelling for high resolution air quality mapping.
Grazia Fattoruso; Martina Nocerino; Domenico Toscano; Luigi Pariota; Giampiero Sorrentino; Valentina Manna; Saverio De Vito; Armando Cartenì; Massimiliano Fabbricino; Girolamo Di Francia. Site Suitability Analysis for Low Cost Sensor Networks for Urban Spatially Dense Air Pollution Monitoring. Atmosphere 2020, 11, 1215 .
AMA StyleGrazia Fattoruso, Martina Nocerino, Domenico Toscano, Luigi Pariota, Giampiero Sorrentino, Valentina Manna, Saverio De Vito, Armando Cartenì, Massimiliano Fabbricino, Girolamo Di Francia. Site Suitability Analysis for Low Cost Sensor Networks for Urban Spatially Dense Air Pollution Monitoring. Atmosphere. 2020; 11 (11):1215.
Chicago/Turabian StyleGrazia Fattoruso; Martina Nocerino; Domenico Toscano; Luigi Pariota; Giampiero Sorrentino; Valentina Manna; Saverio De Vito; Armando Cartenì; Massimiliano Fabbricino; Girolamo Di Francia. 2020. "Site Suitability Analysis for Low Cost Sensor Networks for Urban Spatially Dense Air Pollution Monitoring." Atmosphere 11, no. 11: 1215.
The development of connected and automated driving functions involves that the interaction of autonomous/automated vehicles with the surrounding environment will increase. Accordingly, there is a necessity for an improvement in the usage of traditional tools of the automotive development process. This is a critical problem since the classic development process used in the automotive field uses a very simplified driver model and the traffic environment, while nowadays it should contemplate a realistic representation of these elements. To overcome this issue, the authors proposed an integrated simulation environment, based on the co-simulation of Matlab/Simulink environment with simulation of urban mobility, which allows for a realistic model of vehicle dynamic, control logics, driver behaviour and traffic conditions. Simulation tests have been performed to prove the reasoning for such a tool, and to show the capabilities of the instrument. By using the proposed platform, vehicles may be modelled with a higher level of details (with respect to microscopic simulators), while the autonomous/automated driving functions can be tested in realistic traffic scenarios where the features of the road traffic environment can be varied to verify in a realistic way the level of robustness of the on-board implemented functions.
Luigi Pariota; Angelo Coppola; Luca Di Costanzo; Antonio Di Vico; Arcangelo Andolfi; Claudio D'Aniello; Gennaro Nicola Bifulco. Integrating tools for an effective testing of connected and automated vehicles technologies. IET Intelligent Transport Systems 2020, 14, 1025 -1033.
AMA StyleLuigi Pariota, Angelo Coppola, Luca Di Costanzo, Antonio Di Vico, Arcangelo Andolfi, Claudio D'Aniello, Gennaro Nicola Bifulco. Integrating tools for an effective testing of connected and automated vehicles technologies. IET Intelligent Transport Systems. 2020; 14 (9):1025-1033.
Chicago/Turabian StyleLuigi Pariota; Angelo Coppola; Luca Di Costanzo; Antonio Di Vico; Arcangelo Andolfi; Claudio D'Aniello; Gennaro Nicola Bifulco. 2020. "Integrating tools for an effective testing of connected and automated vehicles technologies." IET Intelligent Transport Systems 14, no. 9: 1025-1033.
The paper presents some exploratory experiments for defining a Macroscopic Fundamental Diagram starting from data collected in some specific sensor network layouts, that is by just monitoring the cordon of a study area. Variables defined in the original proposition of the MFD where here re-defined by just considering the number of vehicles estimated to be present in the study area (N) by means of this layout. We found that in some cases a strong correlation among defined variables can be found, and also similar patterns in the depicted MFD are evidenced. Findings of the paper are limited, given the limited amount of simulation performed, and also considering the limited number of factors varied in the simulations; as expected, results seem to be strongly affected by the traffic demand. Apart that, the approach is worth to be investigated, because this kind of layout is becoming very common in some urban contexts (e.g. in Italy).
Luigi Pariota; Luca Di Costanzo; Francesco Spera; Gennaro Nicola Bifulco. Simulation Experiments for an Approximate Definition of the Macroscopic Fundamental Diagram. Advances in Intelligent Systems and Computing 2020, 1408 -1417.
AMA StyleLuigi Pariota, Luca Di Costanzo, Francesco Spera, Gennaro Nicola Bifulco. Simulation Experiments for an Approximate Definition of the Macroscopic Fundamental Diagram. Advances in Intelligent Systems and Computing. 2020; ():1408-1417.
Chicago/Turabian StyleLuigi Pariota; Luca Di Costanzo; Francesco Spera; Gennaro Nicola Bifulco. 2020. "Simulation Experiments for an Approximate Definition of the Macroscopic Fundamental Diagram." Advances in Intelligent Systems and Computing , no. : 1408-1417.
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.
Cooperative-Intelligent Transportation Systems (C-ITSs) aim to connect vehicles, both with one another and with road infrastructures, so as to increase traffic safety and efficiency. This paper focuses on the European framework for supporting the development of Cooperative, Connected, and Automated Mobility, and aims to shed light on the current state of testing and deployment activities in the field at the start of 2019. This may be considered particularly timely given that the year 2019 was identified as the starting date for the deployment of mature services, and the Community legislation is currently paying great attention to the matter. In order to present a concise (but comprehensive) picture, we consulted and analysed the most diverse sources comprising more than 2000 pages.
Marilisa Botte; Luigi Pariota; Luca D’Acierno; Gennaro Nicola Bifulco. An Overview of Cooperative Driving in the European Union: Policies and Practices. Electronics 2019, 8, 616 .
AMA StyleMarilisa Botte, Luigi Pariota, Luca D’Acierno, Gennaro Nicola Bifulco. An Overview of Cooperative Driving in the European Union: Policies and Practices. Electronics. 2019; 8 (6):616.
Chicago/Turabian StyleMarilisa Botte; Luigi Pariota; Luca D’Acierno; Gennaro Nicola Bifulco. 2019. "An Overview of Cooperative Driving in the European Union: Policies and Practices." Electronics 8, no. 6: 616.
Francesco Galante; Fabrizio Bracco; Carlo Chiorri; Luigi Pariota; Luigi Biggiero; Gennaro N. Bifulco. Erratum to “Validity of Mental Workload Measures in a Driving Simulation Environment”. Journal of Advanced Transportation 2018, 2018, 1 -1.
AMA StyleFrancesco Galante, Fabrizio Bracco, Carlo Chiorri, Luigi Pariota, Luigi Biggiero, Gennaro N. Bifulco. Erratum to “Validity of Mental Workload Measures in a Driving Simulation Environment”. Journal of Advanced Transportation. 2018; 2018 ():1-1.
Chicago/Turabian StyleFrancesco Galante; Fabrizio Bracco; Carlo Chiorri; Luigi Pariota; Luigi Biggiero; Gennaro N. Bifulco. 2018. "Erratum to “Validity of Mental Workload Measures in a Driving Simulation Environment”." Journal of Advanced Transportation 2018, no. : 1-1.
Automated in-vehicle systems and related human-machine interfaces can contribute to alleviating the workload of drivers. However, each new functionality can also introduce a new source of workload, due to the need to attend to new tasks and thus requires careful testing before being implemented in vehicles. Driving simulators have become a viable alternative to on-the-road tests, since they allow optimal experimental control and high safety. However, for each driving simulator to be a useful research tool, for each specific task an adequate correspondence must be established between the behavior in the simulator and the behavior on the road, namely, the simulator absolute and relative validity. In this study we investigated the validity of a driving-simulator-based experimental environment for research on mental workload measures by comparing behavioral and subjective measures of workload of the same large group of participants in a simulated and on-road driving task on the same route. Consistent with previous studies, mixed support was found for both types of validity, although results suggest that allowing more and/or longer familiarization sessions with the simulator may be needed to increase its validity. Simulator sickness also emerged as a critical issue for the generalizability of the results.
Francesco Galante; Fabrizio Bracco; Carlo Chiorri; Luigi Pariota; Luigi Biggero; Gennaro N. Bifulco. Validity of Mental Workload Measures in a Driving Simulation Environment. Journal of Advanced Transportation 2018, 2018, 1 -11.
AMA StyleFrancesco Galante, Fabrizio Bracco, Carlo Chiorri, Luigi Pariota, Luigi Biggero, Gennaro N. Bifulco. Validity of Mental Workload Measures in a Driving Simulation Environment. Journal of Advanced Transportation. 2018; 2018 ():1-11.
Chicago/Turabian StyleFrancesco Galante; Fabrizio Bracco; Carlo Chiorri; Luigi Pariota; Luigi Biggero; Gennaro N. Bifulco. 2018. "Validity of Mental Workload Measures in a Driving Simulation Environment." Journal of Advanced Transportation 2018, no. : 1-11.
For a driving simulator to be a valid tool for research, vehicle development, or driver training, it is crucial that it elicits similar driver behavior as the corresponding real vehicle. To assess such behavioral validity, the use of quantitative driver models has been suggested but not previously reported. Here, a task-general conceptual driver model is proposed, along with a taxonomy defining levels of behavioral validity. Based on these theoretical concepts, it is argued that driver models without explicit representations of sensory or neuromuscular dynamics should be sufficient for a model-based assessment of driving simulators in most contexts. As a task-specific example, two parsimonious driver steering models of this nature are developed and tested on a dataset of real and simulated driving in near-limit, low-friction circumstances, indicating a clear preference of one model over the other. By means of closed-loop simulations, it is demonstrated that the parameters of this preferred model can generally be accurately estimated from unperturbed driver steering data, using a simple, open-loop fitting method, as long as the vehicle positioning data are reliable. Some recurring patterns between the two studied tasks are noted in how the model’s parameters, fitted to human steering, are affected by the presence or absence of steering torques and motion cues in the simulator.
Gustav Markkula; Richard Romano; A. Hamish Jamson; Luigi Pariota; Alex Bean; Erwin R. Boer. Using Driver Control Models to Understand and Evaluate Behavioral Validity of Driving Simulators. IEEE Transactions on Human-Machine Systems 2018, 48, 592 -603.
AMA StyleGustav Markkula, Richard Romano, A. Hamish Jamson, Luigi Pariota, Alex Bean, Erwin R. Boer. Using Driver Control Models to Understand and Evaluate Behavioral Validity of Driving Simulators. IEEE Transactions on Human-Machine Systems. 2018; 48 (6):592-603.
Chicago/Turabian StyleGustav Markkula; Richard Romano; A. Hamish Jamson; Luigi Pariota; Alex Bean; Erwin R. Boer. 2018. "Using Driver Control Models to Understand and Evaluate Behavioral Validity of Driving Simulators." IEEE Transactions on Human-Machine Systems 48, no. 6: 592-603.
In this paper a car-following model is formulated as a time-continuous dynamic process, depending on two parameters and two inputs. One of these inputs is the follower’s desired equilibrium spacing, assumed to exist and to be known. Another input is the speed of the lead vehicle. Given the formulation of the model, the contribution of these two inputs is separable from an analytical point of view. The proposed model is simple enough (whereas not being simplistic) to support real-time applications in the field of advanced driving assistance systems. Starting from the equilibrium spacing, it is possible to estimate the parameters of the model, allowing for a full identification procedure. The modeling framework was prevalidated against observed data from two different data sets, collected by means of two instrumented vehicles in independent experiments, carried out in Italy and the United Kingdom. The validation proved that the proposed car-following model gives good results not only around the desired equilibrium spacing but also in general car-following conditions. The experimental data sets are discussed in terms of parameter values as well as performance of the dynamic process against observed data.
Luigi Pariota; Gennaro Nicola Bifulco; Mark Brackstone. A Linear Dynamic Model for Driving Behavior in Car Following. Transportation Science 2016, 50, 1032 -1042.
AMA StyleLuigi Pariota, Gennaro Nicola Bifulco, Mark Brackstone. A Linear Dynamic Model for Driving Behavior in Car Following. Transportation Science. 2016; 50 (3):1032-1042.
Chicago/Turabian StyleLuigi Pariota; Gennaro Nicola Bifulco; Mark Brackstone. 2016. "A Linear Dynamic Model for Driving Behavior in Car Following." Transportation Science 50, no. 3: 1032-1042.
This paper analyses driving behaviour in car-following conditions, based on extensive individual vehicle data collected during experimental field surveys carried out in Italy and the UK. The aim is to contribute to identify simple evidence to be exploited in the ongoing process of driving assistance and automation which, in turn, would reduce rear-end crashes. In particular, identification of differences and similarities in observed car-following behaviours for different samples of drivers could justify common tuning, at a European or worldwide level, of a technological solution aimed at active safety, or, in the event of differences, could suggest the most critical aspects to be taken into account for localisation or customisation of driving assistance solutions. Without intending to be exhaustive, this paper moves one step in this direction. Indeed, driving behaviour and human errors are considered to be among the main crash contributory factors, and a promising approach for safety improvement is the progressive introduction of increasing levels of driving automation in next-generation vehicles, according to the active/preventive safety approach. However, the more advanced the system, the more complex will be the integration in the vehicle, and the interaction with the driver may sometimes become unproductive, or risky, should the driver be removed from the driving control loop. Thus, implementation of these systems will require the interaction of human driving logics with automation logics and then an enhanced ability in modelling drivers’ behaviour. This will allow both higher active-safety levels and higher user acceptance to be achieved, thus ensuring that the driver is always in the control loop, even if his/her role is limited to supervising the automatic logic. Currently, the driving mode most targeted by driving assistance systems is longitudinal driving. This is required in various driving conditions, among which car-following assumes key importance because of the huge number of rear-end crashes. The increased availability of lower-cost information and communication technologies (ICTs) has enhanced the possibility of collecting copious and reliable car-following individual vehicle data. In this work, data collected from three different experiments, two carried out in Italy and one in the UK, are analysed and compared. The experiments involved 146 drivers (105 Italian drivers and 41 UK drivers). Data were collected by two instrumented vehicles. Our analysis focused on inter-vehicular spacing in equilibrium car-following conditions. We observed that (i) the adopted equilibrium spacing can be fitted using lognormal distributions, (ii) the adopted equilibrium spacing increases with speed, and (iii) the dispersion between drivers increases with speed. In addition, according to different headway thresholds (up to 1 second) a significant number of potentially dangerous behaviours is observed. Three different car-following paradigms are also applied to each of the experiments, and modelling parameters are calibrated and compared to obtain indirect confirmation about the observed similarities and differences in driving behaviour.
Luigi Pariota; Gennaro Nicola Bifulco; Francesco Galante; Alfonso Montella; Mark Brackstone. Longitudinal control behaviour: Analysis and modelling based on experimental surveys in Italy and the UK. Accident Analysis & Prevention 2016, 89, 74 -87.
AMA StyleLuigi Pariota, Gennaro Nicola Bifulco, Francesco Galante, Alfonso Montella, Mark Brackstone. Longitudinal control behaviour: Analysis and modelling based on experimental surveys in Italy and the UK. Accident Analysis & Prevention. 2016; 89 ():74-87.
Chicago/Turabian StyleLuigi Pariota; Gennaro Nicola Bifulco; Francesco Galante; Alfonso Montella; Mark Brackstone. 2016. "Longitudinal control behaviour: Analysis and modelling based on experimental surveys in Italy and the UK." Accident Analysis & Prevention 89, no. : 74-87.
Many application fields in transportation engineering can benefit from an accurate modelling of car-following behavior. In particular, in recent years, an increased importance is assigned to embed behavioral abilities in ADAS (Advanced Driving Assistance Systems) and in driving automation solutions. However, accurate development of car-following models needs for accounting of the drivers’ heterogeneity, which can be easily observed in car-following data. This paper contributes to analyze different sources of heterogeneity with particular focus on three factors: the dispersion over-time of the behavior of a single driver; the heterogeneous behaviors of different drivers; and the possible bias introduced by some over-simplification of the modelling framework, with particular reference to the type of leading vehicle. Our analyses are based on the observation of car-following trajectories collected in a large experiment involving one hundred drivers. Observed behaviors have been interpreted by means of several car-following models proposed in past. The comparison of the values of the parameters identified for the models (versus observed data) is adopted for the analyses. Moreover, directly observed variables (car-following speed and spacing) are adopted to complement and confirm the analyses. Results show that the greater among the sources of dispersion is the across-driver heterogeneity and that by taking into account such an inherent drivers’ dispersion of car-following behaviors it is possible to better identify also the effect of the modelling oversimplifications induced by not considering the type of leading vehicle.
Luigi Pariota; Francesco Galante; Gennaro Nicola Bifulco. Heterogeneity of Driving Behaviors in Different Car-Following Conditions. Periodica Polytechnica Transportation Engineering 2016, 44, 105 -114.
AMA StyleLuigi Pariota, Francesco Galante, Gennaro Nicola Bifulco. Heterogeneity of Driving Behaviors in Different Car-Following Conditions. Periodica Polytechnica Transportation Engineering. 2016; 44 (2):105-114.
Chicago/Turabian StyleLuigi Pariota; Francesco Galante; Gennaro Nicola Bifulco. 2016. "Heterogeneity of Driving Behaviors in Different Car-Following Conditions." Periodica Polytechnica Transportation Engineering 44, no. 2: 105-114.
The Action Point theory is one of the paradigms that can be applied to understand and reproduce car-following behaviour. Several different approaches to this theory have been proposed, some more simple and others more complex. In particular, the reference point in this field is still the paradigm from Wiedemann, which requires the identification of four action-point thresholds. In this paper we review Action Point theories in order to highlight similarities and differences and to ascertain whether all the thresholds proposed by Wiedemann actually bind the driving behaviour. Based on a large-scale experiment in which car-following data were collected, we identified all candidate action points assuming that the more complex (four-threshold) theory holds. Then we tested these points with respect to the large data set of available observations, in order to check whether actual actions are performed at the points. The results show that very often simpler approaches better match the observed data and that in order to explain car-following behaviour it is sufficient in most cases to refer to two thresholds. The results obtained by real-world observation were also tested in virtual environments (two different kinds of driving simulators) and were confirmed.
Luigi Pariota; Gennaro Nicola Bifulco. Experimental evidence supporting simpler Action Point paradigms for car-following. Transportation Research Part F: Traffic Psychology and Behaviour 2015, 35, 1 -15.
AMA StyleLuigi Pariota, Gennaro Nicola Bifulco. Experimental evidence supporting simpler Action Point paradigms for car-following. Transportation Research Part F: Traffic Psychology and Behaviour. 2015; 35 ():1-15.
Chicago/Turabian StyleLuigi Pariota; Gennaro Nicola Bifulco. 2015. "Experimental evidence supporting simpler Action Point paradigms for car-following." Transportation Research Part F: Traffic Psychology and Behaviour 35, no. : 1-15.
Reduction of the environmental impact of cars represents one of the biggest transport industry challenges. Beyond more efficient engines, a promising approach is to use eco-driving technologies that help drivers achieve lower fuel consumption and emission levels. In this study, a real-time microscopic fuel consumption model was developed. It was designed to be integrated into simulation platforms for the design and testing of Advanced Driving Assistance Systems (ADAS), aimed at keeping the vehicle within the environmentally friendly driving zone and hence reducing harmful exhaust gases. To allow integration in platforms employed at early stages of ADAS development and testing, the model was kept very simple and dependent on a few easily computable variables. To show the feasibility of the identification of the model (and to validate it), a large experiment involving more than 100 drivers and about 8000 km of driving was carried out using an instrumented vehicle. An instantaneous model was identified based on vehicle speed, acceleration level and gas pedal excursion, applicable in an extra-urban traffic context. Both instantaneous and aggregate validation was performed and the model was shown to estimate vehicle fuel consumption consistently with in-field instantaneous measurements. Very accurate estimations were also shown for the aggregate consumption of each driving session.
Gennaro Nicola Bifulco; Francesco Galante; Luigi Pariota; Maria Russo Spena. A Linear Model for the Estimation of Fuel Consumption and the Impact Evaluation of Advanced Driving Assistance Systems. Sustainability 2015, 7, 14326 -14343.
AMA StyleGennaro Nicola Bifulco, Francesco Galante, Luigi Pariota, Maria Russo Spena. A Linear Model for the Estimation of Fuel Consumption and the Impact Evaluation of Advanced Driving Assistance Systems. Sustainability. 2015; 7 (10):14326-14343.
Chicago/Turabian StyleGennaro Nicola Bifulco; Francesco Galante; Luigi Pariota; Maria Russo Spena. 2015. "A Linear Model for the Estimation of Fuel Consumption and the Impact Evaluation of Advanced Driving Assistance Systems." Sustainability 7, no. 10: 14326-14343.
Advanced Travel Information Systems (ATISs) are designed to assist travellers in making better travel choices by providing pre-trip and en-route information such as travel times on the relevant alternatives. Travellers??? choices are likely to be sensitive to the accuracy of the provided information in addition to travel time uncertainty. A route-choice experiment with 36 participants, involving 20 repetitions under three different levels of information accuracy was conducted to investigate the impact of information accuracy. In each experiment respondents had to choose one of three routes (risky, useless and reliable). Provided information included descriptive information about the average estimated travel times for each route, prescriptive information regarding the suggested route and experiential feedback information about the actual travel times on all routes. Aggregate analysis using non-parametric statistics and disaggregate analysis using a mixed logit choice model were applied. The results suggest decreasing accuracy shifts choices mainly from the riskier to the reliable route but also to the useless alternative. Prescriptive information has the largest behavioural impact followed by descriptive and experiential feedback information. Risk attitudes also seem to play a role. The implications for ATIS design and future research are further discussed
Gennaro Nicola Bifulco; Luigi Pariota; Mark Brackstione; Michael McDonald. Driving behaviour models enabling the simulation of Advanced Driving Assistance Systems: revisiting the Action Point paradigm. Transportation Research Part C: Emerging Technologies 2013, 36, 352 -366.
AMA StyleGennaro Nicola Bifulco, Luigi Pariota, Mark Brackstione, Michael McDonald. Driving behaviour models enabling the simulation of Advanced Driving Assistance Systems: revisiting the Action Point paradigm. Transportation Research Part C: Emerging Technologies. 2013; 36 ():352-366.
Chicago/Turabian StyleGennaro Nicola Bifulco; Luigi Pariota; Mark Brackstione; Michael McDonald. 2013. "Driving behaviour models enabling the simulation of Advanced Driving Assistance Systems: revisiting the Action Point paradigm." Transportation Research Part C: Emerging Technologies 36, no. : 352-366.
Identification of driving behavior is a crucial task in several Intelligent Transportation Systems applications, both to increase safety and assist drivers. Here we identify driving behaviors by means of an analytical model. In order to estimate the model parameters, data are collected with an instrumented vehicle. The paper presents the model, the procedure for the estimation of the parameters and the results of the proposed framework with respect to a pilot experiment to assess the feasibility and potential of the approach. Some practical implementations of the proposed model are presented. In particular, road safety assessment is introduced in greater depth to show the potential of the approach. For this purpose, a modified (and original) version of some surrogate measures of safety is introduced.
Gennaro Nicola Bifulco; Francesco Galante; Luigi Pariota; Maria Russo-Spena. Identification of Driving Behaviors with Computer-Aided Tools. 2012 Sixth UKSim/AMSS European Symposium on Computer Modeling and Simulation 2012, 331 -336.
AMA StyleGennaro Nicola Bifulco, Francesco Galante, Luigi Pariota, Maria Russo-Spena. Identification of Driving Behaviors with Computer-Aided Tools. 2012 Sixth UKSim/AMSS European Symposium on Computer Modeling and Simulation. 2012; ():331-336.
Chicago/Turabian StyleGennaro Nicola Bifulco; Francesco Galante; Luigi Pariota; Maria Russo-Spena. 2012. "Identification of Driving Behaviors with Computer-Aided Tools." 2012 Sixth UKSim/AMSS European Symposium on Computer Modeling and Simulation , no. : 331-336.
Observation of vehicles kinematics is an important task for many applications in ITS (Intelligent Transportation Systems). It is at the base of both theoretical analyses and application developments, especially in case of positioning and tracing/tracking of vehicles, car-following analyses and models, navigation and other ATIS (Advanced Traveller Information Systems), ACC (Adaptive Cruise Control) systems, CAS and CWS (Collision Avoidance Systems and Collision Warning Systems) and other ADAS (Advanced Driving Assistance Systems). Modern technologies supply low-cost devices able to collect time series of kinematic and positioning data with medium to very high frequency. Even more data can be (almost continually) collected if vehicle-to-vehicle (V2 V) communications come true. However, some of the ITS applications (as well as car-following models, on which many ADAS and ACC are based) require highly accurate measures or, at least, smooth profiles of collected data. Unfortunately, even relatively high-cost devices can collect biased data because of many technical reasons and often this bias could lead to unrealistic kinematics, incorrect absolute positioning and/or inconsistencies between vehicles (e.g. negative spacing). As a consequence, data need filtering in most of the ITS applications. To this aim proper algorithms are required and several sensors and sources of data possibly integrated in order to obtain the maximum quality at the minimal cost. This work addresses the previous issues by developing a specific Kalman smoothing approach. The approach is developed in order to deal with car-following conditions but is conceived to take into account also navigation issues. The performances are analysed with respect to real-world car-following data, voluntarily biased for evaluation purposes. Assessment is carried out with reference to different mixtures of sensors and different sensors accuracies.
Gennaro Nicola Bifulco; Luigi Pariota; Fulvio Simonelli; Roberta Di Pace. Real-time smoothing of car-following data through sensor-fusion techniques. Procedia - Social and Behavioral Sciences 2011, 20, 524 -535.
AMA StyleGennaro Nicola Bifulco, Luigi Pariota, Fulvio Simonelli, Roberta Di Pace. Real-time smoothing of car-following data through sensor-fusion techniques. Procedia - Social and Behavioral Sciences. 2011; 20 ():524-535.
Chicago/Turabian StyleGennaro Nicola Bifulco; Luigi Pariota; Fulvio Simonelli; Roberta Di Pace. 2011. "Real-time smoothing of car-following data through sensor-fusion techniques." Procedia - Social and Behavioral Sciences 20, no. : 524-535.