Descrizione del progetto DEENESFRITPL Decodificare il comportamento di pedoni e ciclisti per strade più sicure Il numero di ciclisti e pedoni che condividono la strada è in aumento, ma non si è ancora capito come questi lenti attori del traffico interagiscono tra loro, il che rende difficile prevederne il processo decisionale e guidare in modo efficace le norme e i regolamenti sul traffico. Comprendere il comportamento di pedoni e ciclisti è una sfida importante nella teoria del traffico e dei trasporti. Il progetto ALLEGRO, finanziato dal Consiglio europeo della ricerca, ricorrerà a megadati innovativi e alla sperimentazione, alla realtà aumentata e al rilevamento a distanza e della folla per sviluppare una teoria completa del comportamento del traffico in modalità lenta, basandosi sui diversi livelli comportamentali di pedoni e ciclisti sulla strada. Mostra l’obiettivo del progetto Nascondi l’obiettivo del progetto Obiettivo A major challenge in contemporary traffic and transportation theory is having a comprehensive understanding of pedestrians and cyclists behaviour. This is notoriously hard to observe, since sensors providing abundant and detailed information about key variables characterising this behaviour have not been available until very recently. The behaviour is also far more complex than that of the much better understood fast mode. This is due to the many degrees of freedom in decision-making, the interactions among slow traffic participants that are more involved and far less guided by traffic rules and regulations than those between car-drivers, and the many fascinating but complex phenomena in slow traffic flows (self-organised patterns, turbulence, spontaneous phase transitions, herding, etc.) that are very hard to predict accurately. With slow traffic modes gaining ground in terms of mode share in many cities, lack of empirical insights, behavioural theories, predictively valid analytical and simulation models, and tools to support planning, design, management and control is posing a major societal problem as well: examples of major accidents due to bad planning, organisation and management of events are manifold, as are locations where safety of slow modes is a serious issue due to interactions with fast modes. This programme is geared towards establishing a comprehensive theory of slow mode traffic behaviour, considering the different behavioural levels relevant for understanding, reproducing and predicting slow mode traffic flows in cities. The levels deal with walking and cycling operations, activity scheduling and travel behaviour, and knowledge representation and learning. Major scientific breakthroughs are expected at each of these levels, in terms of theory and modelling, by using innovative (big) data collection and experimentation, analysis and fusion techniques, including social media data analytics, using augmented reality, and remote and crowd sensing. Campo scientifico natural sciencescomputer and information sciencesdata sciencebig datanatural sciencescomputer and information sciencesknowledge engineeringnatural sciencescomputer and information sciencesartificial intelligencemachine learningnatural sciencescomputer and information sciencessoftwaresoftware applicationssimulation softwarenatural sciencesmathematicsapplied mathematicsmathematical model Programma(i) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Argomento(i) ERC-ADG-2014 - ERC Advanced Grant Invito a presentare proposte ERC-2014-ADG Vedi altri progetti per questo bando Meccanismo di finanziamento ERC-ADG - Advanced Grant Istituzione ospitante TECHNISCHE UNIVERSITEIT DELFT Contribution nette de l'UE € 2 458 699,70 Indirizzo STEVINWEG 1 2628 CN Delft Paesi Bassi Mostra sulla mappa Regione West-Nederland Zuid-Holland Delft en Westland Tipo di attività Higher or Secondary Education Establishments Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 2 458 699,70 Beneficiari (1) Classifica in ordine alfabetico Classifica per Contributo netto dell'UE Espandi tutto Riduci tutto TECHNISCHE UNIVERSITEIT DELFT Paesi Bassi Contribution nette de l'UE € 2 458 699,70 Indirizzo STEVINWEG 1 2628 CN Delft Mostra sulla mappa Regione West-Nederland Zuid-Holland Delft en Westland Tipo di attività Higher or Secondary Education Establishments Collegamenti Contatta l’organizzazione Opens in new window Sito web Opens in new window Partecipazione a programmi di R&I dell'UE Opens in new window Rete di collaborazione HORIZON Opens in new window Costo totale € 2 458 699,70
