Giulio Bianchi Piccinini
Giulio Bianchi Piccinini is an Associate Professor in the Crash Analysis and Prevention Group, within the division of Vehicle Safety, at Chalmers University of Technology. His research focuses on the understanding of crash causation mechanisms and modelling of driver behaviour. After obtaining his Master's degree, Giulio worked as Ergonomics and Human Factors engineer in Toyota Motor Europe's research and development, for over two years. He later earned his Ph.D. in Transportation Systems from the Faculty of Engineering of the University of Porto, in 2014, and his oavlönad docent title in Human Factors in road traffic safety from Chalmers University of Technology, in 2019. He is currently appointed as Director of the Master's Programme in Automotive Engineering and as examiner of the course Engineering of Automotive Systems.

Showing 23 publications
Identified Risk Factors Among Truck Drivers Circulating in France
Influence of oncoming traffic on drivers’ overtaking of cyclists
Great expectations: A predictive processing account of automobile driving
Comparison of Real Accident and Near Miss Incident of Cyclist Collisions Based on Drive Recorder
Influence of oncoming traffic on drivers’ decision to overtake cyclists
How do drivers overtake cyclists?
Using naturalistic data to assess e-cyclist behavior
A Review of Research on Driving Styles and Road Safety
Driver's behavioral adaptation to Adaptive Cruise Control (ACC): The case of speed and time headway
Do cyclists on e-bikes behave differently than cyclists on traditional bicycles?
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Showing 8 research projects
Safety in automated driving (ADS): modelling interaction between road-users and automated vehicles
Aerodynamic and Flexible Trucks for Next Generation of Long Distance Road Transport (AEROFLEX)
Quantitative Driver Behaviour Modelling for Active Safety Assessment Expansion (QUADRAE)
Analysis of CRASH Event Data recorder data with video (CRASHED)
Driver modelling and cross-cultural analysis of driving styles based on large-scale driving data
Analysis Framework for Safety Systems and Services