Transport and Covid-19: responses and resources

Artificial Intelligence in Road Traffic Crash Prevention Roundtable

Urban intersection
This Roundtable sought to determine the most relevant use cases for artificial intelligence (AI) in the prevention of crashes on the road network.

The Roundtable explored the possibility of computer vision to acquire relevant information and the capability of computer models to identify high-risk locations and situations. Participants offered recommendations to all relevant stakeholders to lift barriers to the development and the appropriate utilisation of life-saving AI solutions. 


Chair's Summary

George Yannis, National Technical University of Athens (NTUA)

The role of AI in the mapping of dangerous locations on the road network

Alexandre Santacreu, International Transport Forum

The Accelerated and intelligent collection of RAP attributes

Monica Olyslagers, iRAP

Road Danger Prediction - Classic models, AI models and Data Challenges

Richard Owen, Craig Smith and George Uraschi, Agilysis, UK

Probe Vehicle Data

Michelle Fransen and Bas Turpijin National Road Traffic Data Portal NDW, NL

Using AI for Spatial Prediction of Driver Behaviour

Apostolos Ziakopoulos and George Yannis National Technical University of Athens (NTUA)

Average Speeds and Road Safety in São Paulo

Luis Fernando and Villaça Meyer Cordial Institute, Brazil