LEVITATE aims to develop a wide-ranging evaluation framework to assess the impact of connected and automated transport (CAT) on all aspects of transport and individual mobility as well as at societal level.
This framework will be used to evaluate the impacts of CAVs on individuals, the mobility system and society using a wide range of indicators. The timescales for the forecasting will include
• short term – CAT at an early stage of implementation, technological capability is broadly in line with present day
• medium term – CAT becoming more widespread, increasing capability of technologies. Increasing penetration of more highly automated vehicles in fleet
• long term – ubiquitous highly integrated transport systems, vehicle fleet is predominantly automated, personal mobility, vehicles and infrastructure have adapted to the new technologies.
The outcomes of Levitate will include a set of validated methods to measure the impacts of existing technologies and forecast that of future systems. The methods will be applied to a series of scenarios including those of the present day to provide a range of impact studies of new and future mobility technologies. Based on the Levitate approach a new Connected and automated mobility decision support tool will be developed to provide an evidential basis for future mobility policy-making.
Aimsun has provided a range of new models to the project to enable partners to investigate a range of Cooperative, Connected and Automated Mobility (CCAM) systems from electro-mobility (through a battery charging model), through Green Light Optimized Speed Advisory (GLOSA), to Automated vehicles.
A key part in this has been the use of the Macroscopic Fundamental Diagram (MFD) method to investigate how localised operational impacts of AVs can be scaled up to the City level. This has involved conducting Microscopic simulations to measure changes in network capacities at different AV penetration rates. The resulting capacities are used to estimate the effects on the Passenger Car Units (PCU) and derive functional relationships, which are further introduced to travel demand models to forecast the macroscopic impacts on network performance.
Analysis of three different urban networks, Barcelona, Bilbao (Spain) and Athens (Greece), has revealed consistent trends.