Alfonso Micucci

Prof. Alfonso Micucci

orcid

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 November 2022 in Sustainability
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Journal Article
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MMMatteo della Mura
Matteo della Mura
SFSerena Failla
Serena Failla
NGNicolò Gori
Nicolò Gori
AMAlfonso Micucci
Alfonso Micucci
Filippo PaganelliFilippo Paganelli
Filippo Paganelli
Electric micromobility represents a sustainable mobility option for specific classes of users and distance thresholds. Had this mobility solution been integrated into a comprehensive mobility framework from the beginning, it would have expanded the coverage and accessibility of urban transit services. Instead, slow and incoherent regulation has established a contrast between enthusiastic users (who consider electric micromobility vehicles “fun” and “easy to use”) and recalcitrant public opinion (wherein electric micromobility vehicles are deemed “unsafe” and “dangerous”). Beyond the few attempts made by transport experts to assess the capability of e-scooters to become a sound mobility option (through mobility surveys, pattern analysis, fleet and routing problems), safety and infrastructure design should be developed in a consistent way in order to guarantee a balanced transport setting. With respect to this challenge, a methodology framework is proposed to address the increasing proliferation of micromobility in the context of a coherent transport system. Special attention is devoted to those aspects that have received less attention from the scientific community, namely infrastructure and safe interactions at intersections. The similarities and differences between e-scooters and bikes, chosen in this study as the representative of traditional soft mobility modes, have been taken into consideration. To support the proposed approach, tests investigating e-scooter performance and the perception of both the modes at safety-critical nodes (such as intersections) under different conditions are presented, and the methodology can be applied to a variety of urban scales. The results can be adopted by local authorities, transport companies and e-mobility providers to optimize infrastructure and increase the number and quality of available mobility options.

15 April 2019 in Sensors
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Journal Article
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AMAlfonso Micucci
Alfonso Micucci
Luca MantecchiniLuca Mantecchini
Luca Mantecchini
MSMaurizio Sangermano
Maurizio Sangermano
The investigations on the effectiveness of the turn signal in motorcyclists understanding of motorists’ potential intentions in potentially dangerous car–motorcycle interactions and on the relationships among some variables that could influence the perception of rear and front turn signal status are examined in this paper. The investigations have been based on data pooled from the answers of a survey of 136 motorcycle riders, with special regards to the correct detection of turning indicators. Experimental videos have been realized during in-situ simulations, both in urban and suburban areas, recording vehicular interactions in three-leg road intersections, able to potentially generate crash risks, through a 360-camera mounted on a motorcyclist’s helmet. The blinkers detection rate has been combined with other factors related to motorcyclist’s characteristics and test context (e.g., age, gender, location of the test site, presence of a car behind tester vehicles and if the motorcyclist are also habitual car or bicycle drivers) in a stepwise logistic regression that modelled the odds of detecting the turn signal turned on as a function of significant factors. Within the limits of the proposed methodology, the results highlight the low percentage of correct sighting of the turn indicators and confirm the existence of a relation between the detection of the turn indicators aspect and some of the variables considered (e.g., age, being habitual cyclist or car driver and the presence of a car occluding the views), suggesting the opportunity to further investigate the phenomenon through the use of ad-hoc simulations, in order to highlight connections among the factors that can influence the perception of turning indicators in potentially dangerous contexts for cars and motorcycles.

6 March 2019 in Preprints.org
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AMAlfonso Micucci
Alfonso Micucci
Luca MantecchiniLuca Mantecchini
Luca Mantecchini
MSMaurizio Sangermano
Maurizio Sangermano
The relationships among the potential causes of a car and motorcycle collision involving turn maneuvers as well as the perception of rear and front turn signal (on/off) configuration is examined in this paper. The investigation has been based on data pooled from the answers of a survey proposed to 136 people, with special regards to the correct detection of indicators aspect. Experimental videos have been realized during the tests campaign, both in urban and suburban areas, using a 360-camera attached to a motorcyclist’s helmet, reproducing vehicular conflicts able to potentially generate crash risks. The detection of the blinker was combined with other factors (e.g. age, gender, location of the test site, presence of the car behind tester vehicles and if the bikers are also habitual car or bike drivers) in a stepwise logistic regression that modelled the odds of detecting the turn signal turned on as a function of all of these factors. The results suggest the existence of a connection between the detection of the turn signal aspect and some of the variables considered (e.g. age, being a cyclist or a car driver and the presence of a protecting car).

21 October 2025 in Sustainability
Verified
Journal Article
Open access
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AMAlfonso Micucci
Alfonso Micucci
Luca MantecchiniLuca Mantecchini
Luca Mantecchini
GBGiacomo Bettazzi
Giacomo Bettazzi
FSFederico Scattolin
Federico Scattolin
Understanding vehicle acceleration behavior during intersection departures is critical for advancing traffic safety, sustainable mobility, and intelligent transport systems. This study presents a high-resolution kinematic analysis of 714 vehicle departures from signalized intersections, encompassing straight crossings, left turns, and right turns, and involving a diverse sample of internal combustion engine (ICE), hybrid electric (HEV), and battery electric vehicles (BEV). Using synchronized Micro Electro-Mechanical Systems (MEMS) accelerometers and Real-Time Kinematic (RTK)-GPS systems, the study captures longitudinal acceleration and velocity profiles over fixed distances. Results indicate that BEVs exhibit significantly higher acceleration and final speeds than ICE and HEV vehicles, particularly during straight crossings and longer left-turn maneuvers. Several mathematical models—including polynomial, arctangent, and Akçelik functions—were calibrated to describe acceleration and velocity dynamics. Findings contribute by modeling jerk and delay propagation, supporting better calibration of AV acceleration profiles and the optimization of intersection control strategies. Moreover, the study provides validated acceleration benchmarks that enhance the accuracy of forensic engineering and road accident reconstruction, particularly in scenarios involving intersection dynamics, and demonstrates that BEVs accelerate more rapidly than ICE and HEV vehicles, especially in straight crossings, with direct implications for traffic simulation, ADAS calibration, and urban crash analysis.

16 November 2023 in Preprints.org
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FSFederico Scattolin
Federico Scattolin
AMAlfonso Micucci
Alfonso Micucci
Acceleration rates of vehicles are crucially important statistics needed in two main aspects: first, they are essential to incident reconstructor professionals as having a verified database on where basing the cinematic reconstructions is definitely difficult and moreover, they are useful in order to understand how to create the safest possible environment on the road. This key topic gives es-sential information for road design like intersection schemes, acceleration and deceleration lane length as well as traffic simulation modelling and furthermore, to educate vehicle drivers when entering the traffic flow and to provide limit acceleration values needed to develop autonomous vehicle’s software in order to guarantee a comfort drive. Literature reports tons of linear acceleration stats mainly referred to vehicle performances claimed by car manufacturers, but these data don’t recreate real drivers’ behaviour when entering the road by turning left or right or crossing an intersection. This work aims to integrate the most reliable data from literature with a hybrid and an electric vehicles statistic, adding also two contemporary thermal engine vehicles, extracted conducting probes that recreates real road environment. The entirety of these experiments reconstructs the scenario in which a car is entering the traffic of a two-lanes road, from a stationary position at a stop sign and the acceleration rates are collected using a M.E.M.S. (Microelectromechanical system). Finally, the space needed between the car that is about to enter or crossing the road and the car that is approaching the intersection is calculated, basing the computations on the acceleration values extracted from the probes. These spaces are pictured, as a way to give a concrete idea to readers.