About.

Currently, for various reasons environmental concerns are not usually a priority associated with the task of driving. However, this context may change as connected and automated vehicles diffuse through the transport networks, integrating pervasive cooperative algorithms contributing to the positive-sum game of both efficiency and environmental sustainability. The main vision of InFLOWence is to take advantage of the predictable market penetration of connected and autonomous vehicles (CAVs) in short-medium term to influence, in a positive way, the performance of the road transport system in terms of congestion, energy consumption and pollutant emissions. This will be achieved through the development of a prototype of a digital mapping platform incorporating advanced link-based performance functions to support eco driving commands for CAVs.

The first objective of InFLOWence is anticipating changes in transport demand and mobility patterns due to market penetration of CAVs in Portugal. This analysis will be conducted through advanced statistical tools to determine the key factors that can change mobility patterns. Then, for different scenarios of CAVs market penetration, a set of strategic tactical decisions (route selection) and operational eco-driving decisions (vehicle dynamics) will be assessed.

Regarding operational decisions, the main deliverable is a computational framework to influence the impact of CAVs in traffic performance over different types of links and traffic demand. Two research questions will be addressed. First, if there are evidences supporting the notion that CAVs can be operated in such a way that generate environmental benefits to themselves and to the remaining traffic flow. The second research question is to understand to which extent cooperative ITS systems and increasing connectivity between cars and infrastructure may contribute to yield environmental benefits.

With respect to tactical decisions, the main deliver will be to provide a sustainable traffic assignment and navigation tool for CAVs encompassing their own impacts, but also the marginal impacts on the other vehicles in the network. At the end of the project, a computational framework will be capable of determining effective actions for autonomous vehicles, taking into account diverse levels of market penetration and different levels of connectivity with the infrastructure. The results will be evaluated through a rigorous environmental (air quality) and economic evaluation of the various actions. InFLOWence will support policy-makers to prioritize cooperative ITS systems, whose impact is most beneficial from the environmental point of view.