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Italian version
The project "VeHiKoMniScience - Vehicle Holistic Knowledge of Motion States", led by Basilio Lenzo from the Department of Industrial Engineering at the University of Padua, has received funding of €1.59 million from the Italian Fund for Applied Sciences (FISA), provided by the Ministry of Universities and Research. This ambitious project aims to improve car safety by developing an innovative sensor system that provides precise and reliable estimates of vehicle motion parameters, regardless of external conditions.
Basilio Lenzo emphasises the urgency of addressing the issue of road accidents, which cause over a million fatalities each year and are the leading cause of death for people aged 5 to 29, according to WHO data. He explains, "Our goal is to create a comprehensive control of the car through the use of real data" because currently, car safety systems rely on both real-time measured parameters and estimates, which can be prone to errors.
The "VeHiKoMniScience" project aims to overcome the limitations of current electronic stability control systems, which regulate engine power and brakes to prevent skidding. These systems, using estimates for certain parameters such as lateral displacement and forces between wheels and the road, can lead to inaccuracies.
The project therefore aims to achieve greater data accuracy by making advanced safety technologies applicable to the sensors already present in modern cars, tested both on scaled-down models and real cars on tracks, as well as through other low-cost devices.
One of the key technologies is, for example, a mini camera mounted on the vehicle that films the asphalt and, connected to a computer, calculates the lateral displacement speed. This data is then processed by an algorithm that can issue commands to the brakes in real time to prevent skidding, ensuring maximum precision and safety.
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Italian version
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Basilio Lenzo emphasises the urgency of addressing the issue of road accidents, which cause over a million fatalities each year and are the leading cause of death for people aged 5 to 29, according to WHO data. He explains, "Our goal is to create a comprehensive control of the car through the use of real data" because currently, car safety systems rely on both real-time measured parameters and estimates, which can be prone to errors.
The "VeHiKoMniScience" project aims to overcome the limitations of current electronic stability control systems, which regulate engine power and brakes to prevent skidding. These systems, using estimates for certain parameters such as lateral displacement and forces between wheels and the road, can lead to inaccuracies.
The project therefore aims to achieve greater data accuracy by making advanced safety technologies applicable to the sensors already present in modern cars, tested both on scaled-down models and real cars on tracks, as well as through other low-cost devices.
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Italian version
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Basilio Lenzo emphasises the urgency of addressing the issue of road accidents, which cause over a million fatalities each year and are the leading cause of death for people aged 5 to 29, according to WHO data. He explains, "Our goal is to create a comprehensive control of the car through the use of real data" because currently, car safety systems rely on both real-time measured parameters and estimates, which can be prone to errors.
The "VeHiKoMniScience" project aims to overcome the limitations of current electronic stability control systems, which regulate engine power and brakes to prevent skidding. These systems, using estimates for certain parameters such as lateral displacement and forces between wheels and the road, can lead to inaccuracies.
The project therefore aims to achieve greater data accuracy by making advanced safety technologies applicable to the sensors already present in modern cars, tested both on scaled-down models and real cars on tracks, as well as through other low-cost devices.
One of the key technologies is, for example, a mini camera mounted on the vehicle that films the asphalt and, connected to a computer, calculates the lateral displacement speed. This data is then processed by an algorithm that can issue commands to the brakes in real time to prevent skidding, ensuring maximum precision and safety.
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Italian version
The project "VeHiKoMniScience - Vehicle Holistic Knowledge of Motion States", led by Basilio Lenzo from the Department of Industrial Engineering at the University of Padua, has received funding of €1.59 million from the Italian Fund for Applied Sciences (FISA), provided by the Ministry of Universities and Research. This ambitious project aims to improve car safety by developing an innovative sensor system that provides precise and reliable estimates of vehicle motion parameters, regardless of external conditions.
Basilio Lenzo emphasises the urgency of addressing the issue of road accidents, which cause over a million fatalities each year and are the leading cause of death for people aged 5 to 29, according to WHO data. He explains, "Our goal is to create a comprehensive control of the car through the use of real data" because currently, car safety systems rely on both real-time measured parameters and estimates, which can be prone to errors.
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Italian version
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Basilio Lenzo emphasises the urgency of addressing the issue of road accidents, which cause over a million fatalities each year and are the leading cause of death for people aged 5 to 29, according to WHO data. He explains, "Our goal is to create a comprehensive control of the car through the use of real data" because currently, car safety systems rely on both real-time measured parameters and estimates, which can be prone to errors.
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Basilio Lenzo emphasises the urgency of addressing the issue of road accidents, which cause over a million fatalities each year and are the leading cause of death for people aged 5 to 29, according to WHO data. He explains, "Our goal is to create a comprehensive control of the car through the use of real data" because currently, car safety systems rely on both real-time measured parameters and estimates, which can be prone to errors.
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The project therefore aims to achieve greater data accuracy by making advanced safety technologies applicable to the sensors already present in modern cars, tested both on scaled-down models and real cars on tracks, as well as through other low-cost devices.
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Italian version
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Basilio Lenzo emphasises the urgency of addressing the issue of road accidents, which cause over a million fatalities each year and are the leading cause of death for people aged 5 to 29, according to WHO data. He explains, "Our goal is to create a comprehensive control of the car through the use of real data" because currently, car safety systems rely on both real-time measured parameters and estimates, which can be prone to errors.
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Italian version
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Basilio Lenzo emphasises the urgency of addressing the issue of road accidents, which cause over a million fatalities each year and are the leading cause of death for people aged 5 to 29, according to WHO data. He explains, "Our goal is to create a comprehensive control of the car through the use of real data" because currently, car safety systems rely on both real-time measured parameters and estimates, which can be prone to errors.
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Italian version
The project "VeHiKoMniScience - Vehicle Holistic Knowledge of Motion States", led by Basilio Lenzo from the Department of Industrial Engineering at the University of Padua, has received funding of €1.59 million from the Italian Fund for Applied Sciences (FISA), provided by the Ministry of Universities and Research. This ambitious project aims to improve car safety by developing an innovative sensor system that provides precise and reliable estimates of vehicle motion parameters, regardless of external conditions.
Basilio Lenzo emphasises the urgency of addressing the issue of road accidents, which cause over a million fatalities each year and are the leading cause of death for people aged 5 to 29, according to WHO data. He explains, "Our goal is to create a comprehensive control of the car through the use of real data" because currently, car safety systems rely on both real-time measured parameters and estimates, which can be prone to errors.
The "VeHiKoMniScience" project aims to overcome the limitations of current electronic stability control systems, which regulate engine power and brakes to prevent skidding. These systems, using estimates for certain parameters such as lateral displacement and forces between wheels and the road, can lead to inaccuracies.
The project therefore aims to achieve greater data accuracy by making advanced safety technologies applicable to the sensors already present in modern cars, tested both on scaled-down models and real cars on tracks, as well as through other low-cost devices.
One of the key technologies is, for example, a mini camera mounted on the vehicle that films the asphalt and, connected to a computer, calculates the lateral displacement speed. This data is then processed by an algorithm that can issue commands to the brakes in real time to prevent skidding, ensuring maximum precision and safety.
This approach promises to significantly improve the safety of human-driven, autonomous, and semi-autonomous vehicles, helping to save many lives.
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Italian version
The project "VeHiKoMniScience - Vehicle Holistic Knowledge of Motion States", led by Basilio Lenzo from the Department of Industrial Engineering at the University of Padua, has received funding of €1.59 million from the Italian Fund for Applied Sciences (FISA), provided by the Ministry of Universities and Research. This ambitious project aims to improve car safety by developing an innovative sensor system that provides precise and reliable estimates of vehicle motion parameters, regardless of external conditions.
Basilio Lenzo emphasises the urgency of addressing the issue of road accidents, which cause over a million fatalities each year and are the leading cause of death for people aged 5 to 29, according to WHO data. He explains, "Our goal is to create a comprehensive control of the car through the use of real data" because currently, car safety systems rely on both real-time measured parameters and estimates, which can be prone to errors.
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