Adapting driver behaviour for lower emissions
YEARS
European partners
international partners
pilot sites
MODALES vision is to substantially reduce air pollution from all types of on-road vehicles by encouraging the adoption of low-emission driving behaviour and proper maintenance choice.
MODALES proposes a user-centric approach to addressing all of the challenges which on the one hand enhance low-emission practices and on the other hand suppress high-emission behaviour by researching, developing and testing a number of innovative and complementary solutions in four key areas (namely, Driver, Retrofits, EOBD and Inspection) in order to substantially reduce vehicle emissions from 3 main sources (i.e. powertrain, brake wear and tyre wear).
News
Shaping the characteristics of low emission driving with MODALES member VTT
MODALES is back with VTT (Technical Research Centre of Finland). Meet the project’s technical coordinator, Dr. Juhani Laurikko, who leads the experimental activities that establish the relationships between driving behaviour and exhaust emissions, and more!
New guidelines on low-emission driving are now available
The European-funded project MODALES works towards reducing air pollution from all types of on-road vehicles by encouraging the adoption of low-emission driving behaviour and proper maintenance...
ITS World Congress 2021: Deadline for Call for Contributions extended
No matter what 2021 may bring, and whatever the new normal may look like, ERTICO – ITS Europe will adapt and do whatever is necessary to ensure project activities and the ITS Congresses move forward...
Upcoming Events
19
-22 SEPT 2021
24th IEEE International Conference on Intelligent Transportation – ITSC2021, Indianapolis, IN, United States. Read more.
View the Full Calendar
Contact Us
MODALES is the first major project considering the interaction of powertrain, brakes and tyres together with the driver’s behaviour, to develop knowledge and guidance for “low-emission driving”, together with maintenance and retrofit aspects.
Our Partners
This project has received funding from the European Union’s Horizon 2020
research and innovation programme under grant agreement No 815189.