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Prof. Massimiliano Gastaldi
Università degli Studi di Padova - Dipartimento di Ingegneria Civile, Edile e Architettura

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0 Transportation
0 Transportation Demand Management
0 Transportation modelling
0 mobility and transport
0 TRANSPORTATION DATA MODELING AND SIMULATION

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Journal article
Published: 13 August 2021 in Sustainability
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Real-time coaching programs are designed to give feedback on driving behavior to usage-based motor insurance users; they are often general purpose programs that aim to promote smooth driving. Here, we investigated the effect of different on-board real-time coaching programs on the driving behavior on highway deceleration lanes with a driving simulator experiment. The experiment was organized into two trials. The first was a baseline trial, in which participants drove without receiving any feedback; a cluster analysis was then performed to divide participants into two groups, based on their observed driving style. One month later, a second trial was carried out, with participants driving on the same path as the first trial, this time receiving contingent feedback related to their braking/acceleration behavior. Four feedback systems were tested; overall, there were eight experimental groups, depending on the clustered driving style (aggressive and defensive), feedback modality (visual and auditory), and feedback valence (positive and negative). Speed, deceleration, trajectory, and lateral control variables, collected before and onto the deceleration lane, were investigated with mixed ANOVAs, which showed that the real-time coaching programs significantly reduced speeds and maximum deceleration values, while improving lateral control. A change toward a safer exit strategy (i.e., entering the lane before starting to decelerate) was also observed in defensive drivers.

ACS Style

Federico Orsini; Mariaelena Tagliabue; Giulia De Cet; Massimiliano Gastaldi; Riccardo Rossi. Highway Deceleration Lane Safety: Effects of Real-Time Coaching Programs on Driving Behavior. Sustainability 2021, 13, 9089 .

AMA Style

Federico Orsini, Mariaelena Tagliabue, Giulia De Cet, Massimiliano Gastaldi, Riccardo Rossi. Highway Deceleration Lane Safety: Effects of Real-Time Coaching Programs on Driving Behavior. Sustainability. 2021; 13 (16):9089.

Chicago/Turabian Style

Federico Orsini; Mariaelena Tagliabue; Giulia De Cet; Massimiliano Gastaldi; Riccardo Rossi. 2021. "Highway Deceleration Lane Safety: Effects of Real-Time Coaching Programs on Driving Behavior." Sustainability 13, no. 16: 9089.

Journal article
Published: 09 June 2021 in Sustainability
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The diffusion of the COVID-19 pandemic has induced fundamental changes in travel habits. Although many previous authors have analysed factors affecting observed variations in travel demand, only a few works have focused on predictions of future new normal conditions when people will be allowed to decide whether to travel or not, although risk mitigation measures will still be enforced on vehicles, and innovative mobility services will be implemented. In addition, few authors have considered future mandatory trips of students that constitute a great part of everyday travels and are fundamental for the development of society. In this paper, logistic regression models were calibrated by using data from a revealed and stated-preferences mobility survey administered to students and employees at the University of Padova (Italy), to predict variables impacting on their decisions to perform educational and working trips in the new normal phase. Results highlighted that these factors are different between students and employees; furthermore, available travel alternatives and specific risk mitigation measures on vehicles were found to be significant. Moreover, the promotion of the use of bikes, as well as bike sharing, car pooling and micro mobility among students can effectively foster sustainable mobility habits. On the other hand, countermeasures on studying/working places resulted in a slight effect on travel decisions.

ACS Style

Riccardo Ceccato; Riccardo Rossi; Massimiliano Gastaldi. Travel Demand Prediction during COVID-19 Pandemic: Educational and Working Trips at the University of Padova. Sustainability 2021, 13, 6596 .

AMA Style

Riccardo Ceccato, Riccardo Rossi, Massimiliano Gastaldi. Travel Demand Prediction during COVID-19 Pandemic: Educational and Working Trips at the University of Padova. Sustainability. 2021; 13 (12):6596.

Chicago/Turabian Style

Riccardo Ceccato; Riccardo Rossi; Massimiliano Gastaldi. 2021. "Travel Demand Prediction during COVID-19 Pandemic: Educational and Working Trips at the University of Padova." Sustainability 13, no. 12: 6596.

Journal article
Published: 03 February 2021 in Transportation Research Procedia
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Road traffic accidents represent one of the leading causes of death across all age groups globally. Most of these accidents can be directly attributed to drivers’ failure to select the correct driving speed. Thus, actions aimed to mitigate inappropriate driving performance, including speeding, are needed. Here, we used a dynamic driving simulator to investigate the effects of different real-time coaching programs on driving performance, specifically on the occurrence of Elevated Gravitational-Force Events (EGFEs). Forty-three drivers underwent a two-day evaluation. On the first day, participants –after an initial screening and depending on their driving style– were divided into two groups: defensive vs. aggressive drivers. On the second day, they received a different type of real time visual feedback based on their driving performance. For each of the two driving style groups, half of the drivers received contingent positive feedback (when smooth driving events occurred), the other half received contingent negative feedback (when harsh driving events occurred). Thus, there were four groups based on driving style and feedback. Overall, results showed that among aggressive drivers contingent feedback –independently from its type– reduces the occurrence of EGFEs. Potential applications of the proposed methodology include its use for Pay-how-you-drive programs aimed to improve driver speed control.

ACS Style

Riccardo Rossi; Mariaelena Tagliabue; Massimiliano Gastaldi; Giulia De Cet; Francesca Freuli; Federico Orsini; Leandro L. Di Stasi; Giulio Vidotto. Reducing Elevated Gravitational-Force Events through visual feedback: a simulator study. Transportation Research Procedia 2021, 52, 115 -122.

AMA Style

Riccardo Rossi, Mariaelena Tagliabue, Massimiliano Gastaldi, Giulia De Cet, Francesca Freuli, Federico Orsini, Leandro L. Di Stasi, Giulio Vidotto. Reducing Elevated Gravitational-Force Events through visual feedback: a simulator study. Transportation Research Procedia. 2021; 52 ():115-122.

Chicago/Turabian Style

Riccardo Rossi; Mariaelena Tagliabue; Massimiliano Gastaldi; Giulia De Cet; Francesca Freuli; Federico Orsini; Leandro L. Di Stasi; Giulio Vidotto. 2021. "Reducing Elevated Gravitational-Force Events through visual feedback: a simulator study." Transportation Research Procedia 52, no. : 115-122.

Research article
Published: 19 December 2020 in Transportation Letters
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Application of extreme value theory (EVT) to road safety analysis is gaining interest, thanks to its ability to produce quick and reliable safety evaluations without the use of crash data. Traditionally applied to single collision types and single extreme variables (i.e. surrogate measures of safety), EVT can be further exploited to simultaneously model multiple collision types, with the use of multiple extreme variables. In this paper two bivariate EVT approaches are applied for the safety evaluation of a three-leg unsignalized intersection, considering: (i) two conflict points and a single surrogate measure of safety; (ii) two surrogate measures of safety collected in a single conflict point. Each bivariate analysis was applied with two EVT methods: Component-wise Maxima (CM) and Excesses Over a Threshold (EOT). Bivariate models produced good results, especially with the EOT method, and were able to significantly improve the univariate benchmark results when the two estimation datasets were correlated.

ACS Style

Massimiliano Gastaldi; Federico Orsini; Gregorio Gecchele; Riccardo Rossi. Safety analysis of unsignalized intersections: a bivariate extreme value approach. Transportation Letters 2020, 13, 209 -218.

AMA Style

Massimiliano Gastaldi, Federico Orsini, Gregorio Gecchele, Riccardo Rossi. Safety analysis of unsignalized intersections: a bivariate extreme value approach. Transportation Letters. 2020; 13 (3):209-218.

Chicago/Turabian Style

Massimiliano Gastaldi; Federico Orsini; Gregorio Gecchele; Riccardo Rossi. 2020. "Safety analysis of unsignalized intersections: a bivariate extreme value approach." Transportation Letters 13, no. 3: 209-218.

Journal article
Published: 29 October 2020 in Sustainability
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The increasing concentration of human activities in cities has been leading to a worsening in air quality, thus negatively affecting the lives and health of humans living in urban contexts. Transport is one of the main sources of pollution in such environments. Several local authorities have therefore implemented strict traffic-restriction measures. The aim of this paper is to evaluate the effectiveness and limitations of these interventions, by analyzing the relationship between traffic flows and air quality. The used dataset contains concentrations of NO, NO2, NOx and PM10, vehicle counts and meteorology, all collected during the COVID-19 lockdown in the city of Padova (Italy), in which severe limitations to contain the spread of the virus simulated long and large-scale traffic restrictions in normal conditions. In particular, statistical tests, correlation analyses and multivariate linear regression models were applied to non-rainy days in 2020, 2018 and 2017, in order to isolate the effect of traffic. Analysis indicated that vehicle flows significantly affect NO, NO2, and NOx concentrations, although no evidence of a relationship between traffic and PM10 was highlighted. According to this perspective, measures to limit traffic flows seem to be effective in improving air quality only in terms of reducing nitrogen oxide.

ACS Style

Riccardo Rossi; Riccardo Ceccato; Massimiliano Gastaldi. Effect of Road Traffic on Air Pollution. Experimental Evidence from COVID-19 Lockdown. Sustainability 2020, 12, 8984 .

AMA Style

Riccardo Rossi, Riccardo Ceccato, Massimiliano Gastaldi. Effect of Road Traffic on Air Pollution. Experimental Evidence from COVID-19 Lockdown. Sustainability. 2020; 12 (21):8984.

Chicago/Turabian Style

Riccardo Rossi; Riccardo Ceccato; Massimiliano Gastaldi. 2020. "Effect of Road Traffic on Air Pollution. Experimental Evidence from COVID-19 Lockdown." Sustainability 12, no. 21: 8984.

Conference paper
Published: 31 August 2020 in Database Systems for Advanced Applications
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This work investigated the effect of mental models on the effectiveness of an advanced driver assistance system (ADAS). The system tested was a lateral control ADAS, which informed the drivers whether the vehicle was correctly positioned inside the lane or not, with the use of two visual and one auditory stimuli. Three driving simulator experiments were performed, involving three separate groups of subjects, who received different initial exposures to the technology. In Experiment 0 subjects were not exposed to ADAS in order to be able to indicate that no effect of learning affected the results. In Experiment A subjects were not instructed on the ADAS functionalities and they had to learn on their own; in Experiment B they were directly instructed on the functionalities by reading an information booklet. In all experiments drivers performed multiple driving sessions. The mean absolute lateral position (LP) and standard deviation of lateral position (SDLP) for each driver were considered as main dependent variables to measure the effectiveness of the ADAS. Findings from this work showed that the initial mental model had an impact on ADAS effectiveness, since it produced significantly different results in terms of ADAS effectiveness, with those reading the information booklet being able to improve more and faster their lateral control.

ACS Style

Riccardo Rossi; Massimiliano Gastaldi; Francesco Biondi; Federico Orsini; Giulia De Cet; Claudio Mulatti. A Driving Simulator Study Exploring the Effect of Different Mental Models on ADAS System Effectiveness. Database Systems for Advanced Applications 2020, 102 -113.

AMA Style

Riccardo Rossi, Massimiliano Gastaldi, Francesco Biondi, Federico Orsini, Giulia De Cet, Claudio Mulatti. A Driving Simulator Study Exploring the Effect of Different Mental Models on ADAS System Effectiveness. Database Systems for Advanced Applications. 2020; ():102-113.

Chicago/Turabian Style

Riccardo Rossi; Massimiliano Gastaldi; Francesco Biondi; Federico Orsini; Giulia De Cet; Claudio Mulatti. 2020. "A Driving Simulator Study Exploring the Effect of Different Mental Models on ADAS System Effectiveness." Database Systems for Advanced Applications , no. : 102-113.

Preprint
Published: 30 October 2019
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The use of neural networks to predict airport passenger activity choices inside the terminal is presented in this paper. Three network architectures are proposed: Feedforward Neural Networks (FNN), Long Short-Term Memory (LSTM) networks, and a combination of the two. Inputs to these models are both static (passenger and trip characteristics) and dynamic (real-time passenger tracking). A real-world case study exemplifies the application of these models, using anonymous WiFi traces collected at Bologna Airport to train the networks. The performance of the models were evaluated according to the misclassification rate of passenger activity choices. In the LSTM approach, two different multi-step forecasting strategies are tested. According to our findings, the direct LSTM approach provides better results than the FNN, especially when the prediction horizon is relatively short (20 minutes or less).

ACS Style

Federico Orsini; Massimiliano Gastaldi; Luca Mantecchini; Riccardo Rossi. Neural networks trained with WiFi traces to predict airport passenger behavior. 2019, 1 .

AMA Style

Federico Orsini, Massimiliano Gastaldi, Luca Mantecchini, Riccardo Rossi. Neural networks trained with WiFi traces to predict airport passenger behavior. . 2019; ():1.

Chicago/Turabian Style

Federico Orsini; Massimiliano Gastaldi; Luca Mantecchini; Riccardo Rossi. 2019. "Neural networks trained with WiFi traces to predict airport passenger behavior." , no. : 1.

Journal article
Published: 01 July 2019 in Journal of Transportation Engineering, Part A: Systems
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Road network vulnerability analysis is helpful in the improvement of vulnerable links with proper maintenance investments and management strategies. This paper addresses issues that have received limited attention in past studies: estimation of travel demand after link disruption and analysis of accessibility variation. An activity-based model was used to estimate travel demand changes due to link closure, and link importance was evaluated using a set of vulnerability indicators. Accessibility changes induced by link closure are presented and discussed. Vulnerability analysis was conducted for the road network of the municipality of Dolo in northern Italy. Considering the spatial distribution of activities and trips, the results obtained with the activity-based model were more reliable than those obtained with the fixed demand model, which makes the unrealistic assumption of unchanged travel demand after network degradation. These findings are relevant for appropriate resource allocation strategies, which depend on correct link vulnerability analysis and ranking.

ACS Style

Gregorio Gecchele; Riccardo Ceccato; Massimiliano Gastaldi. Road Network Vulnerability Analysis: Case Study Considering Travel Demand and Accessibility Changes. Journal of Transportation Engineering, Part A: Systems 2019, 145, 05019004 .

AMA Style

Gregorio Gecchele, Riccardo Ceccato, Massimiliano Gastaldi. Road Network Vulnerability Analysis: Case Study Considering Travel Demand and Accessibility Changes. Journal of Transportation Engineering, Part A: Systems. 2019; 145 (7):05019004.

Chicago/Turabian Style

Gregorio Gecchele; Riccardo Ceccato; Massimiliano Gastaldi. 2019. "Road Network Vulnerability Analysis: Case Study Considering Travel Demand and Accessibility Changes." Journal of Transportation Engineering, Part A: Systems 145, no. 7: 05019004.

Journal article
Published: 24 January 2019 in Transportation Research Procedia
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The current practice in crash-based safety analysis is hindered by some weaknesses: rarity of crashes, lack of timeliness, mistakes in crash reporting. Researchers are testing alternative approaches to safety estimation without the need of crash data. This paper presents an application of Extreme Value Theory in road safety analysis, using Time-To-Collision as a surrogate safety measure to estimate the risk to be involved in a freeway rear-end collision. The method was tested using data from an Italian toll-road with good results.

ACS Style

Gregorio Gecchele; Federico Orsini; Massimiliano Gastaldi; Riccardo Rossi. Freeway rear-end collision risk estimation with extreme value theory approach. A case study. Transportation Research Procedia 2019, 37, 195 -202.

AMA Style

Gregorio Gecchele, Federico Orsini, Massimiliano Gastaldi, Riccardo Rossi. Freeway rear-end collision risk estimation with extreme value theory approach. A case study. Transportation Research Procedia. 2019; 37 ():195-202.

Chicago/Turabian Style

Gregorio Gecchele; Federico Orsini; Massimiliano Gastaldi; Riccardo Rossi. 2019. "Freeway rear-end collision risk estimation with extreme value theory approach. A case study." Transportation Research Procedia 37, no. : 195-202.

Editorial
Published: 20 September 2018 in Transportation Research Procedia
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ACS Style

Jaume Barceló; Massimiliano Gastaldi; Riccardo Rossi. Editorial. Transportation Research Procedia 2018, 30, 1 -3.

AMA Style

Jaume Barceló, Massimiliano Gastaldi, Riccardo Rossi. Editorial. Transportation Research Procedia. 2018; 30 ():1-3.

Chicago/Turabian Style

Jaume Barceló; Massimiliano Gastaldi; Riccardo Rossi. 2018. "Editorial." Transportation Research Procedia 30, no. : 1-3.

Articles
Published: 05 September 2018 in Transportmetrica A: Transport Science
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This work contributes to study the application of extreme value theory (EVT) in road safety analysis, estimating the risk of being involved in an entering–circulating collision in single-lane roundabouts. Detailed trajectory data of the vehicles were derived from a driving simulator experiment, and the time-to-collision (TTC) was used as a surrogate measure of safety. Three EVT approaches were applied, tested and compared: (1) the Generalized Extreme Value distribution used in the block maxima (BM) approach, (2) the Generalized Pareto Distribution used in the peak-over-threshold approach (POT), with negated-TTC (nTTC), and (3) shifted-reciprocal-TTC (srTTC). Case-study results analysis showed that BM and POT with shifted-reciprocal-TTC confidence intervals included the number of observed crashes, while POT with negated-TTC did not include it. According to these findings, both BM and POT-with-shifted-reciprocal-TTC appear promising and deserve further attention in order to develop effective ready-to-practice crash prediction models, useful in intersection design and operational analysis.

ACS Style

Federico Orsini; Gregorio Gecchele; Massimiliano Gastaldi; Riccardo Rossi. Collision prediction in roundabouts: a comparative study of extreme value theory approaches. Transportmetrica A: Transport Science 2018, 15, 556 -572.

AMA Style

Federico Orsini, Gregorio Gecchele, Massimiliano Gastaldi, Riccardo Rossi. Collision prediction in roundabouts: a comparative study of extreme value theory approaches. Transportmetrica A: Transport Science. 2018; 15 (2):556-572.

Chicago/Turabian Style

Federico Orsini; Gregorio Gecchele; Massimiliano Gastaldi; Riccardo Rossi. 2018. "Collision prediction in roundabouts: a comparative study of extreme value theory approaches." Transportmetrica A: Transport Science 15, no. 2: 556-572.

Research article
Published: 10 May 2018 in Journal of Advanced Transportation
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The purpose of this study is to assess the effects on air pollution that may derive from replacing a signal-controlled intersection with a roundabout, using a before-and-after approach. Based on field data collected with a test car instrumented with a Portable Emission Measurement System, the two intersection configurations were compared in terms of emissions of CO2, CO, and NOX. The existence of significant differences in emissions between the two types of control was assessed by means of a statistical technique known as two-sample biaspect permutation test. In addition, focusing on trips carried out in peak traffic conditions, binary logistic regression models were developed to identify the factors that significantly affect vehicular emissions and to quantify their effect. The findings of our analyses show that emissions of CO2 and CO are generally lower for the roundabout than for the signal-controlled intersection, while an opposite result arises for NOX emissions. As far as other influential factors are concerned, trip direction (reflecting site-specific conditions) and driver behavior have a considerable impact on the emissions of all three pollutants.

ACS Style

Claudio Meneguzzer; Massimiliano Gastaldi; Rosa Arboretti Giancristofaro. Before-and-After Field Investigation of the Effects on Pollutant Emissions of Replacing a Signal-Controlled Road Intersection with a Roundabout. Journal of Advanced Transportation 2018, 2018, 1 -15.

AMA Style

Claudio Meneguzzer, Massimiliano Gastaldi, Rosa Arboretti Giancristofaro. Before-and-After Field Investigation of the Effects on Pollutant Emissions of Replacing a Signal-Controlled Road Intersection with a Roundabout. Journal of Advanced Transportation. 2018; 2018 ():1-15.

Chicago/Turabian Style

Claudio Meneguzzer; Massimiliano Gastaldi; Rosa Arboretti Giancristofaro. 2018. "Before-and-After Field Investigation of the Effects on Pollutant Emissions of Replacing a Signal-Controlled Road Intersection with a Roundabout." Journal of Advanced Transportation 2018, no. : 1-15.

Journal article
Published: 12 February 2018 in IET Intelligent Transport Systems
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This work presents a decision support system for providing information and suggestions to airport users. The aim of the study is to design a system both to improve passengers' experience by reducing time-spent queuing and waiting and to raise airport revenues by increasing the time passengers spend in discretionary activities. Passengers' behaviour is modelled with an activity-choice model to be calibrated with their mobile phone traces. The model allows predicting activity sequences for passengers with given socio-demographic characteristics. To predict queue length at check-in desks and security control and congestion inside commercial areas, passengers' movements are simulated with a microscopic simulation tool. A system to generate suggestion has been designed: passengers are advised to perform mandatory activities when the predicted queue length is reasonable and specific discretionary activities according to time available, user profiles, location distance, location congestion and airport management preferences. A proof-of-concept case study has been developed: passengers' behaviour in both cases of receiving and not receiving suggestion has been simulated. In the first case, passengers experienced less queuing and waiting time; the time saved was spent in discretionary activities, improving passengers' airport experience and increasing airport revenues.

ACS Style

Riccardo Rossi; Massimiliano Gastaldi; Federico Orsini. How to drive passenger airport experience: a decision support system based on user profile. IET Intelligent Transport Systems 2018, 12, 301 -308.

AMA Style

Riccardo Rossi, Massimiliano Gastaldi, Federico Orsini. How to drive passenger airport experience: a decision support system based on user profile. IET Intelligent Transport Systems. 2018; 12 (4):301-308.

Chicago/Turabian Style

Riccardo Rossi; Massimiliano Gastaldi; Federico Orsini. 2018. "How to drive passenger airport experience: a decision support system based on user profile." IET Intelligent Transport Systems 12, no. 4: 301-308.

Conference paper
Published: 05 July 2017 in Advances in Intelligent Systems and Computing
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Vehicle loop detectors or other equipment installed on highway sections are commonly used for monitoring traffic flow conditions on road networks. For operational analysis, it is essential to be able to distinguish low levels of service due to over-saturated conditions from those caused by extraordinary events such as incidents. In the case of incidents, prompt responses are crucial for activating any required countermeasures, such as rescue activation or traffic detours. Automatic Incident Detection methods for basic freeway segments are widely reported in the literature, but their application to freeway ramp merging zones is limited. This work introduces a control system which can identify incidents from vehicle loop detector data on freeway ramp merging zones. The system was developed with fuzzy logic concepts and calibrated with data from micro-simulation experiments. The main finding of this study is that the detection system, despite its simplicity, shows excellent False Alarm Rate (FAR) and satisfactory Detection Rate (DR) and Mean Time To Detection (MTTD), generally better than those obtained with the traditional California#7 comparative algorithm.

ACS Style

Riccardo Rossi; Massimiliano Gastaldi; Gregorio Gecchele. Automatic Incident Detection on Freeway Ramp Junctions. A Fuzzy Logic-Based System Using Loop Detector Data. Advances in Intelligent Systems and Computing 2017, 370 -383.

AMA Style

Riccardo Rossi, Massimiliano Gastaldi, Gregorio Gecchele. Automatic Incident Detection on Freeway Ramp Junctions. A Fuzzy Logic-Based System Using Loop Detector Data. Advances in Intelligent Systems and Computing. 2017; ():370-383.

Chicago/Turabian Style

Riccardo Rossi; Massimiliano Gastaldi; Gregorio Gecchele. 2017. "Automatic Incident Detection on Freeway Ramp Junctions. A Fuzzy Logic-Based System Using Loop Detector Data." Advances in Intelligent Systems and Computing , no. : 370-383.

Conference paper
Published: 01 June 2017 in 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS)
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This work presents initial findings of a research project aimed at designing an assistance system able to improve driver ability and reduce accident risk. The proposed system is an innovative Advanced Driver Assistance System based on the integration of two main components: a training procedure based on precision teaching, and a control equipment monitoring driver behavior and providing feedbacks during regular driving and in critical traffic conditions. With reference to the first component, two driving simulator experiments were designed and implemented. Experiments aimed at demonstrating the effectiveness of precision teaching for training drivers and observing the effectiveness of the feedbacks system in enhancing vehicle control. Vehicle lateral position was considered as main dependent measure. Feedbacks were successful in improving vehicle position within the lane with lateral variability being reduced after three trials.

ACS Style

Riccardo Rossi; Gregorio Gecchele; Massimiliano Gastaldi; Francesco Biondi; Claudio Mulatti. An advanced driver assistance system for improving driver ability. Design and test in virtual environment. 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) 2017, 509 -513.

AMA Style

Riccardo Rossi, Gregorio Gecchele, Massimiliano Gastaldi, Francesco Biondi, Claudio Mulatti. An advanced driver assistance system for improving driver ability. Design and test in virtual environment. 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS). 2017; ():509-513.

Chicago/Turabian Style

Riccardo Rossi; Gregorio Gecchele; Massimiliano Gastaldi; Francesco Biondi; Claudio Mulatti. 2017. "An advanced driver assistance system for improving driver ability. Design and test in virtual environment." 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) , no. : 509-513.

Journal article
Published: 01 January 2017 in Transportation Research Procedia
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The environmental impact of road intersection operations, and in particular of alternative types of traffic control, has received increasing attention in recent years as a factor to be considered in addition to efficiency and safety. The purpose of this study is to provide experimental evidence about this issue based on direct measurement of CO2 emissions produced by a vehicle under traffic signal versus roundabout control. Carbon Dioxide was chosen as specific target of the analysis because of its important contribution to the “greenhouse effect”. Using data collected with a Portable Emission Measurement System (PEMS) installed on a test car, a before-and-after analysis was conducted on an intersection where a roundabout has replaced a traffic signal. A total of 396 trips were carried out by two drivers in different traffic conditions and in opposite directions along a designated route. Using statistical methods, the existence of significant differences in CO2 emissions in relation to the type of intersection control was investigated based on the collected data, also considering the effect of other explanatory variables and focusing in particular on peak traffic conditions. More precisely, the effect of the type of control has been characterized using descriptive statistics and permutation tests applied to the entire data set, while an analysis based on binary logistic regression has been performed with specific reference to trips carried out under peak traffic conditions. The results of these analyses support the conclusion that converting a signal-controlled intersection to a roundabout may lead to a decrease in CO2 emissions.

ACS Style

Massimiliano Gastaldi; Claudio Meneguzzer; Rosa Arboretti Giancristofaro; Gregorio Gecchele; Luca Della Lucia; Maria Vittoria Prati. On-road measurement of CO 2 vehicle emissions under alternative forms of intersection control. Transportation Research Procedia 2017, 27, 476 -483.

AMA Style

Massimiliano Gastaldi, Claudio Meneguzzer, Rosa Arboretti Giancristofaro, Gregorio Gecchele, Luca Della Lucia, Maria Vittoria Prati. On-road measurement of CO 2 vehicle emissions under alternative forms of intersection control. Transportation Research Procedia. 2017; 27 ():476-483.

Chicago/Turabian Style

Massimiliano Gastaldi; Claudio Meneguzzer; Rosa Arboretti Giancristofaro; Gregorio Gecchele; Luca Della Lucia; Maria Vittoria Prati. 2017. "On-road measurement of CO 2 vehicle emissions under alternative forms of intersection control." Transportation Research Procedia 27, no. : 476-483.

Journal article
Published: 01 January 2017 in Applied Ergonomics
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This study investigated whether multimodal redundant warnings presented by advanced assistance systems reduce brake response times. Warnings presented by assistance systems are designed to assist drivers by informing them that evasive driving maneuvers are needed in order to avoid a potential accident. If these warnings are poorly designed, they may distract drivers, slow their responses, and reduce road safety. In two experiments, participants drove a simulated vehicle equipped with a forward collision avoidance system. Auditory, vibrotactile, and multimodal warnings were presented when the time to collision was shorter than five seconds. The effects of these warnings were investigated with participants performing a concurrent cell phone conversation (Exp. 1) or driving in high-density traffic (Exp. 2). Braking times and subjective workload were measured. Multimodal redundant warnings elicited faster braking reaction times. These warnings were found to be effective even when talking on a cell phone (Exp. 1) or driving in dense traffic (Exp. 2). Multimodal warnings produced higher ratings of urgency, but ratings of frustration did not increase compared to other warnings. Findings obtained in these two experiments are important given that faster braking responses may reduce the potential for a collision.

ACS Style

Francesco Biondi; David L. Strayer; Riccardo Rossi; Massimiliano Gastaldi; Claudio Mulatti. Advanced driver assistance systems: Using multimodal redundant warnings to enhance road safety. Applied Ergonomics 2017, 58, 238 -244.

AMA Style

Francesco Biondi, David L. Strayer, Riccardo Rossi, Massimiliano Gastaldi, Claudio Mulatti. Advanced driver assistance systems: Using multimodal redundant warnings to enhance road safety. Applied Ergonomics. 2017; 58 ():238-244.

Chicago/Turabian Style

Francesco Biondi; David L. Strayer; Riccardo Rossi; Massimiliano Gastaldi; Claudio Mulatti. 2017. "Advanced driver assistance systems: Using multimodal redundant warnings to enhance road safety." Applied Ergonomics 58, no. : 238-244.

Journal article
Published: 01 January 2017 in Transportation Research Procedia
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ACS Style

Akira Kawamura; Kazuya Tomiyama; Riccardo Rossi; Massimiliano Gastaldi; Claudio Mulatti. Driving on Rough Surface Requires Care and Attention. Transportation Research Procedia 2017, 22, 392 -398.

AMA Style

Akira Kawamura, Kazuya Tomiyama, Riccardo Rossi, Massimiliano Gastaldi, Claudio Mulatti. Driving on Rough Surface Requires Care and Attention. Transportation Research Procedia. 2017; 22 ():392-398.

Chicago/Turabian Style

Akira Kawamura; Kazuya Tomiyama; Riccardo Rossi; Massimiliano Gastaldi; Claudio Mulatti. 2017. "Driving on Rough Surface Requires Care and Attention." Transportation Research Procedia 22, no. : 392-398.

Journal article
Published: 01 January 2017 in Transportation Research Procedia
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The traditional approach to the comparison of alternative types of road intersection control has focused mainly on efficiency and safety. In recent years, the increasing importance of air pollution produced by vehicular traffic has suggested that environmental considerations should be added to the above aspects as a criterion for intersection design. This study describes a before-and-after analysis conducted on a road intersection where a roundabout has replaced a traffic signal. Using a Portable Emission Measurement Systems (PEMS) installed on a test car, the instantaneous emissions of CO2, NOX and CO have been measured over repeated trips along a designated route. A total of 396 trips have been carried out in different traffic conditions and in opposite directions along the chosen route. Using statistical methods the existence of significant differences in emissions attributable to the type of intersection control has been investigated based on the experimental data. The results indicate that replacing the traffic signal with the roundabout tends to reduce CO2 emissions, even if the differences are not always statistically significant; on the contrary, the signalized intersection performs better in terms of NOX emissions. Finally, results are less clear for CO emissions, and differences are statistically non significant in most cases

ACS Style

Claudio Meneguzzer; Massimiliano Gastaldi; Riccardo Rossi; Gregorio Gecchele; Maria Vittoria Prati. Comparison of exhaust emissions at intersections under traffic signal versus roundabout control using an instrumented vehicle. Transportation Research Procedia 2017, 25, 1597 -1609.

AMA Style

Claudio Meneguzzer, Massimiliano Gastaldi, Riccardo Rossi, Gregorio Gecchele, Maria Vittoria Prati. Comparison of exhaust emissions at intersections under traffic signal versus roundabout control using an instrumented vehicle. Transportation Research Procedia. 2017; 25 ():1597-1609.

Chicago/Turabian Style

Claudio Meneguzzer; Massimiliano Gastaldi; Riccardo Rossi; Gregorio Gecchele; Maria Vittoria Prati. 2017. "Comparison of exhaust emissions at intersections under traffic signal versus roundabout control using an instrumented vehicle." Transportation Research Procedia 25, no. : 1597-1609.

Journal article
Published: 01 January 2017 in Transportation Research Procedia
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Natural and man-created disasters, such as hurricanes, earthquakes, tsunamis, accidents and terrorist attacks, require evacuation and assistance routes. Evacuation routes are mostly based on the capacities of the road network. However, in extreme cases, such as earthquakes, road network infrastructure may adversely be affected, and may not supply their required capacities. If for various situations, the potential damage for critical roads can be identified in advance, it is possible to develop an evacuation model, that can be used in various situations. This paper focuses on the development of a model for the design of an optimal evacuation network which simultaneously minimizes retrofit costs of critical links (bridges, tunnels, etc.) and evacuation time. The model considers infrastructures’ vulnerability (as a stochastic function which is dependent on the event location and magnitude), road network, transportation demand and evacuation areas. Furthermore, the model evaluates the benefits of managed evacuation (system optimum) when compared to unmanaged evacuation (user equilibrium). The paper presents a mathematic model for the presented problem. However, since an optimal solution cannot be found within a reasonable timeframe, a heuristic model is presented as well. This heuristic model is based on evolutionary algorithms, which also provides a mechanism for solving the problem as a multi-objective stochastic problem. Using a real-world data, the algorithm is evaluated and compared to the unmanaged evacuation conditions. The results clearly demonstrate the advantages of managed evacuation, as the average travel time can be reduced by 5% to 30%.

ACS Style

Oren E. Nahum; Yuval Hadas; Mariano Zanini; Carlo Pellegrino; Riccardo Rossi; Massimiliano Gastaldi. Stochastic Multi-Objective Evacuation Model Under Managed and Unmanaged policies. Transportation Research Procedia 2017, 27, 728 -735.

AMA Style

Oren E. Nahum, Yuval Hadas, Mariano Zanini, Carlo Pellegrino, Riccardo Rossi, Massimiliano Gastaldi. Stochastic Multi-Objective Evacuation Model Under Managed and Unmanaged policies. Transportation Research Procedia. 2017; 27 ():728-735.

Chicago/Turabian Style

Oren E. Nahum; Yuval Hadas; Mariano Zanini; Carlo Pellegrino; Riccardo Rossi; Massimiliano Gastaldi. 2017. "Stochastic Multi-Objective Evacuation Model Under Managed and Unmanaged policies." Transportation Research Procedia 27, no. : 728-735.