the project provides travellers with personalized multi-modal navigation tools that allow, help and persuade them to travel and drive ecological friendlier. To convince users in making more sustainable travel choices it will enrich navigation systems with innovative approaches and features:
- Peacox integrates automated travel mode detection based on real-time GPS data into the trip planning thereby minimizing the need for explicit user input.
- Peacox has the capability to automatically detect users’ trip purpose through the analysis of behavioural patterns allowing tailoring trip suggestions to these purposes.
- Peacox builds dynamic user models allowing personalizing recommendations based on prior trip choices and individual preferences.
- Peacox develops advanced door-to-door emissions models that provide accurate feedback on the ecological/carbon footprint and exposure levels in planning as well as during travelling and car driving activities
- Peacox develops and utilizes persuasive interface strategies to give feedback about the ecological impact of individuals’ behavior as well as make the ecological friendliest behavioral pattern visible and attractive.
eCoMove is a 3-year integrated project (April 2010 - March 2013),
funded by the European Commission under the 7th Framework Programme of
Research and Technological Development.
This project will create an integrated solution for road transport
energy efficiency to help drivers, freight and road operators by saving unnecessary kilometres driven (optimised routing), fuel (eco-driving support) and manage traffic more efficiently (optimised network management).
The project’s core concept is that there is a theoretical minimum
energy consumption achievable with the “perfect eco-driver” travelling
through the “perfectly eco-managed” road network.
ICT-Emissions aims at developing a novel methodology to evaluate the impact of ICT related measures on mobility, vehicle energy consumption and CO2 emissions of vehicle fleets at the local scale, in order to promote the wider application of the most appropriate ICT measures.
The proposed methodology combines traffic and emission modelling at micro and macro scales. These will be linked with interfaces and submodules which will be specifically designed and developed. Particular emphasis is given to:
- the correct estimation of driver behaviour, as a result of traffic related ICT measures,
- the coverage of a large number of current vehicle technologies, including ICT systems, and
- near future technologies such as hybrid, plug-in hybrids, and electric vehicles.
eCOMPASS introduces new mobility concepts and establishes a methodological framework for route planning optimization following a holistic approach in addressing the environmental impact of urban mobility. eCOMPASS aims at delivering a comprehensive set of tools and services for end users to enable eco-awareness in urban multi-modal transportations. eCOMPASS involves a generic architecture that will consider all types and scenarios of human and goods mobility in urban environments minimizing their corresponding environmental impact. Firstly, the project will focus on the design and development of intelligent on-board and centralized vehicles’ fleet management systems; the fundamental objective of eco-awareness will be addressed through employing intelligent traffic prediction and traffic balancing methods, while also taking into account driving behaviour and considering the option of car drivers transferred to means of public transportation at suitable locations. Secondly, eCOMPASS will develop web and mobile services providing multi-modal public transportation route planning, taking into account contextual information (such as location and time) as well as various restrictions and/or user constraints. Recommended routes will be optimized mainly in terms of the transports’ environmental footprint, although additional objectives will also be considered. An important objective of eCOMPASS is to develop novel algorithmic solutions and deliver the respective services to familiar end-user mobile devices.