Analysis and modelling road user behaviour

The summer school aims to provide with the human factors theoretical foundations for the analysis and modelling of road-user behaviour, within the context of road safety and development of driving automation systems.

13 – 17 September 2021

Keywords: active safety systems, automated driving, crash causation, human behaviour, naturalistic driving data, safety assessment, vulnerable road users


Due to the world-wide restrictions concerning Covid-19 and in order to protect our participants and lecturers, IDEA League is offering the Summer Schools in an online format.


Normally, there are no registration, tuition, and accommodation fees. Typically, students from IDEA League member universities selected to participate in this summer school only have to pay for their own travel costs.


Curriculum vitae & publication list

Letter of motivation

Letter of recommendation (optional)

Road crashes are a global concern: The World Health Organization estimates that 1.35 million road fatalities occur worldwide every year and road crashes are currently the leading cause of death for people aged 5-29 years. In Europe, although road fatalities have significantly decreased during the period 2007-2016, a less evident reduction has been shown since 2013, and a complete stagnation for cyclists’ fatalities during 2010-2018. The current situation calls for more research investigating road-user behavior, to support the design of active safety systems and automated driving and for the creation of driver’s training and coaching procedures. With the aim to enhance knowledge on the topic, this course embraces a multi-disciplinary approach to provide the theoretical foundations and the experimental methodologies to analyze and modelling road-user behavior.

Learning outcomes:

  • Explain the importance of analyzing and modelling road-user behavior, for improving road safety.
  • Illustrate different types of human factors theoretical driver models.
  • Compute relevant quantitative and qualitative metrics, to analyze and model road-user behavior.
  • Identify the challenges in the analysis of real-traffic data from naturalistic studies.
  • Compare the currently available tools for the virtual evaluation of active safety systems.

This course will be supervised and taught by professors of the Chalmers University of Technology

Organizing Committee

Giulio Bianchi Piccinini, Associate Professor at Chalmers University of Technology

Jörgen Sjöberg, Director International Affairs at Chalmers University of Technology


Day Description
Welcome reception; Introduction to road-user behaviour and road crash prevention
14 September Quantitative and qualitative measures of road-user behavior; Quantitative analysis of driving simulator data (exercise); Guided visit of the city
Naturalistic data for analysis, modelling, and assessment of road-user behavior; Analysis of Naturalistic data (exercise)
Models of road user behaviour; Sensors; Study visit (more information provided later)
Assessment of safety benefits associated to the introduction of active safety systems; Study visit (more information provided later); Closure and debriefing