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MAGnUM Report Summary

Project ID: 646592
Funded under: H2020-EU.1.1.

Periodic Reporting for period 1 - MAGnUM (A Multiscale and Multimodal Modelling Approach for Green Urban Traffic Management)

Reporting period: 2015-09-01 to 2017-02-28

Summary of the context and overall objectives of the project

The MAGnUM project aims to (i) create a consistent set of interrelated dynamic and multimodal traffic models able to capture driver behaviours at the different urban scales and (ii) apply this variety of models to design efficient and green traffic management strategies.
Traffic flow dynamics is well reproduced at a local urban scale by the kinematic wave model and its numerous extensions. Even if this model is parsimonious compared to other modelling approaches, it can hardly be applied at larger urban scales for traffic control applications. Very recently, a new modelling approach has been proposed to represent congestion dynamics at large scales. It relates the total travel production to the vehicle accumulation in a traffic network with for now a restrictive condition about network homogeneity. This approach is very promising for designing new traffic management systems but heterogeneous situations should be handled by properly connecting with the local scale to account for the effects of the local distributions and variations of the driver behaviour (demand) and the network structure (supply). Investigating these relationships and proposing a full set of consistent models representing traffic dynamics at several relevant scales (successive spatial and temporal integration) is very challenging with high potential gains for traffic control applications. This is the primary goal of MAGnUM and will be achieved by mixing analytical investigations on idealized but insightful test cases with explanatory approaches based on data gained from dynamic simulations or serious game sessions on more realistic and complex cases.
The second goal of the project concerns the design of innovative traffic management strategies at multiple urban scales. Breakthroughs will be achieved by considering multiple and competitive objectives when optimizing with a tight focus on environment issues and multi-modality.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

From the beginning of the project the main results achieved so far are:
• Preparation of a playground representing 25% of the Lyon Metropolis spatial area with realistic simulation of all trips during the peak hour. This playground will be used to design simulation game sessions to investigate how users take actions in transportation network (departure time, route and mode choise);
• A clustering method has been set-up to split a transportation network into spatio-temporal areas with homogeneous speed. The concept of 3D speed map has never been proposed before and appears very promising for lots of application from travel-time prediction to large-scale simulation;
• Numerical and analytical investigations of trip-based reservoir model. In particular, we designed a very efficient numerical scheme (event-based) for the trip-based formulation of the reservoir traffic model that permits to easily simulate large urban areas but also to account for heterogeneous user preferences when considering the dynamic traffic assignment models (choice models). Further investigations are undergoing to define a complete multi-reservoir approach that looks very promising.
• The trip-based reservoir approach has been successfully used to assess the impacts of parking search processes on the global network performance.
• We start investigating the impacts of heterogeneous network loadings at large scale when reservoir-based models are used.
• We start investigating how to couple reservoir-based models with dynamic traffic assignment models. We tested classical stochastic formulation but also proposed an analytical framework that is able to solve the two reservoir problems (like a freeway and the side urban network).
• We start working on heuristic methods to improve the calculation of network equilibriums.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

"We launched a lot of actions during the first period but for now it is difficult to provide a clear description of the potential impacts of the results. We should have a clearer vision for period report #2.
What appears for now is that the trip-based reservoir framework looks very promising as it permits to simplified the description of traffic dynamics without aggregating individual users. This formulation looks also well-adapted to include multimodal options and to quickly calculate network equilibriums at large scale. This should be of great use for the second part of the project about designing innovative traffic management strategies.

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