The master planning of sustainable urban nightscapes requires a parsimonious use of artificial light at night (ALAN) to meet societal needs for safety, mobility, economic and social life, while limiting energy consumption, and negative impacts for humans, for the climate and for biodiversity. But in order to promote light sobriety, lighting modifications must be acceptable to the public, and technically feasible. As the suppression of ALAN is not always an acceptable option, it is necessary to understand the constraints and the needs of the different actors in order to promote sustainable urban lighting. The development of Smart Cities and the possibilities brought by the LED technology opens up new strategies to reduce ALAN while controlling its impact on ecosystems and on the quality of life. The LUNNE project addresses several scientific challenges associated with the reduction of ALAN: 1) A more appropriate quantification of the impact of ALAN reduction strategies on ecosystems, through the development of new indicators at different spatial scales. 2) A better knowledge and quantification of the impact of these strategies on people (mobility, safety, nightlife). 3) A better understanding of the obstacles and levers to the acceptability of these urban lighting policies. All three dimensions will merge into multi-factor indices and specific methodologies, providing urban communities with decision-making tools to consider the specificities of their territory when they adapt their lighting. The impact of lighting modifications will be studied by combining the collection of behavioural data in urban observatories, the collection of subjective and social data through surveys, the collection of photometric data through measurements, and the implementation of computational models.

The European transport faces major challenges in terms of safety, greenhouse gas emissions, traffic congestion and its derived costs. In addition, the development of disruptive technologies and emergence of new mobility solutions generate a revolution in transport network and traffic management. In this context, TANGENT aims to develop new complementary tools for optimising traffic operations in a coordinated and dynamic way from a multimodal perspective and considering automated/non-automated vehicles, passengers and freight transport. TANGENT will research on advanced techniques on modelling and simulation, such as prediction and simulation models for future demand & supply of transport; optimisation techniques for balancing the demand flows between the means of transport; and users travel behaviour modelling. As result, a set of applications for decision-making support will be delivered creating a framework for coordinated traffic and transport management, encompassing an enhanced mobility information service and dashboard with associated APIs and advanced functionalities with a two-fold approach: to provide real-time traffic management recommendations and to support Transport Authorities to design network-wide optimal strategies. The framework also aims at supporting a multi-actor cooperation approach for transport network management by enabling communication channels. In this way, the services target to different actors in traffic management. The results will be tested in three case studies: Rennes (FR), Lisbon (PT), Great Manchester (UK) and a virtual case study in Athens (HE)with real data from various modes of transport, under different traffic events such as bottlenecks, accidents, pedestrian flow etc. The impact will be assessed to reach expected reduction targets of 10% in travel time, 8-10% in CO2 emissions, 5% of accidents, 5-10% increase in use public transport and use of active modes or 10% of economic costs due to a more efficient management.