Crash causation and road user behaviour modelling based on naturalistic data with video

Start date 01/04/2014
End date The project is closed: 31/03/2014
​Recent advances in technology have facilitated collection of continuous naturalistic data from road users while attending their daily routines. These data can be used for several analysis, including to understand which behavioral mechanisms inform drivers about the criticality of a situation and how mismatched behavioral expectations influence how a critical situation actually unfolds. But, the increasing amount of naturalistic data and its growing potential to understand the relation between road users behavior is currently lacking appropriate analysis methodologies and tools. This project aimed at understanding driver behavior mechanisms influencing the causation of crashes and will focus on analyzing and modelling road-user behavior from naturalistic data. The project starts with the development of methods for reconstruction of the pre-crash events from video and other sensor data. By understanding how road-users interact and what makes this interaction safe or unsafe in critical situations, new guideline for infrastructure design, education reinforcement, and support systems development may be derived.
Project leader
​SHRP2, EFrame (FFI), BBS-China (CTSC), and DCBIN (FFI)

Published: Thu 09 Oct 2014.