In urban areas, confronted with the development of the epidemic and in a very short period of time, people are reconsidering their travel options. Cycling then appears in several respects as a resilient and reliable short- and long-term urban mobility option, compatible both with a context of health crisis and sustainable development objectives. As mobility habits are difficult to change, taking advantage of a change in behaviour during the health crisis to sustainably transform urban mobility practices and habits becomes an opportunity and a challenge for many cities. As the implementation of an efficient Bike Sharing System (BSS) has a positive impact on the general development of bicycle use in urban areas, the multidisciplinary project we are presenting proposes to study and characterise the impact of the pandemic on the use of BSSs by comparing the situations in Toulouse and Lyon. The methods used are based on the mathematical analysis of disaggregated data on BSS journeys, road traffic and public transport ticketing, and on interview surveys. The aim is to help operators and public authorities to quickly grasp these changes in use in order to respond as well as possible to an emergency situation created by the pandemic and to prepare for future crises, to understand the current opportunities in terms of bicycle use and to set up the conditions for the perpetuation of new cycling practices.

The main objective of the TRAFIPOLLU research project is the development of dynamic modeling tools that determine the location of pollutants generated by road traffic in an urban environment. Such tools require variable spatial and temporal scale resolutions (from very fine to coarse). To that purpose, modeling chains have to be implemented at the various urban scales (street, city and district) to predict (i) the behavior of traffic, (ii) the emissions of pollutants, (iii) the dispersion of pollutants in the atmosphere, (iv) deposition of pollutants and (v) transfer in water and soil. A key point of the modeling chains is the rescaling process. Proposed methods should be able to (i) refine the results produced by the modeling chains operating at large scale from the results produced by models with higher resolution (scale rising) and (ii) implement detailed models from existing on-field measures or from simulation results produced at larger scales (scale downing). More generally, the purpose of this project is to observe, analyze and model the pollutants across the different urban scales. Moreover, difficulty about collecting data that are required by the different modeling chain is stressed for each of the urban scale studied during the research project. Early reflections on this project showed the importance of producing a modeling chain at the finer scale (high resolution) for which the results would be validated. Therefore a part of this project is devoted to a wide-ranging experiment to measure the different involved physical behaviors and to track in space and in time the considered pollutants (NOx, COx, PAH, particles and metals). A first experimental site has been identified in the city of Noisy-Champs. It fulfills all the requirements related to the different studied systems (traffic, air, water and soil).

The SYMEXPO project aims to develop a systemic approach for assessing the impact of urban mobility on exposure to noise and atmospheric pollutants, based on a modelling framework where a city dweller is represented as a mobile agent evolving in a pollution field subject to spatial and temporal variations. The expected scientific advances are the following: • Use data analysis to advance knowledge on: (i) which individual mobility factors are associated with high exposures, (ii) which indicators reflect the effects of the temporal dynamics of exposures; • Build integrated open-source modelling chains (noise and atmospheric pollutants) based on traffic models capturing the effects of mobility policies, at the metropolitan and neighborhood scales, calibrated on the same study site in Lyon Metropolis; • Propose a multi-criteria assessment framework for mobility policies, integrating the health and environmental justice dimensions and accounting for the agent’s mobility.

The growing concentration of people in urban areas translates into increasing travel demand, degrading mobility experience and frequent unavailability or inaccessibility of the transport infrastructures, especially in presence of inclement or extreme weather events. Contextually, the urban environment is pervasively digitalizing and generates massive amounts of data that can be used to improve mobility and enable novel approaches for measuring and improving transport resilience. PROMENADE targets the development of a novel, systemic, real-time, data-driven platform towards sustainable and resilient multi-modal transportation. Firstly, PROMENADE proposes a novel, holistic modeling framework based on multi-layer networks to effectively represent multi-modal, large-scale urban transport systems. This model will allow for grasping the complex interplays that exist among different transport modes and are usually neglected in transportation studies. Secondly, PROMENADE aims at jointly mining multi-source, real-time, large-scale data to enrich the model with accurate and dynamic information on users’ mobility patterns and traffic performance. Big data fusion techniques will be exploited to fully leverage the power of such heterogeneous data and allow for more informed monitoring and decision making. Thirdly, PROMENADE aims at identifying novel resilience metrics and strategies for multi-modal urban transport networks by developing stress tests aimed at analyzing the impact of extreme weather events on multi-modal networks. Moreover, efficient implementations of the proposed resilience indicators will be studied to allow for continuous, real-time monitoring of large-scale network resilience. PROMENADE will deliver a software platform integrating all the models, analytics, algorithms and tools developed along the project. The platform will make the project achievements publicly accessible and re-usable to researchers, transport stakeholders and socio-economic actors. PROMENADE will therefore enable a breakthrough in the modeling of complex transport networks and in the capability to monitor and improve their resilience for sustainable operation.

ANNONA project (Decision making tool for sustainable city logistics) is an Industrial oriented research program. It aims at producing new knowledge and methods in the domain of city freight. This project is motivated by the need of decision making tools to help institutional decision makers when designing innovative logistics solutions in city centers. It addresses item ‘smart-cities’ within axis 1 of the ‘Ville et Bâtiments Durables’ call for projects. City freight is often seen as a need for necessary evil, although it has been constantly improved since a few decades. However, most approaches to implement urban logistics are based on benchmarks. This leads to systematize what has been decided for referent cities, and select on-shelves solutions. As a consequence, such empirical approaches rarely meet the needs of all the concerned stakeholders. There is a lack for methods and tools aiming at predicting the impacts of innovative freight solutions at the very early design step. To fill this gap, ANNONA will address a major lockup: evaluating ex ante the multi-criteria impacts of urban logistics strategies. It will focus on a principal question: where and how to design and implement freight facilities and logistics areas in cities, with respect to sustainable objectives. To do so, new theoretical models will be proposed to deal with complexity of urban freight. A prototype of dashboard to assess the performances of logistics scenarii will be built. This prototype will be based on Geographic Information Systems so as to be used in a very interactive and visual way by decision makers and stakeholders. It will predict the consequences of freight policies on economic, environmental and social dimensions. ANNONA project team is composed of scientists in logistics, environment sciences, economics of transports, and dynamic modeling of traffic. Multi-disciplinary has been favored so as to fully address the multiple dimensions of urban freight problematic. International partnership with South America is a contributing factor to enlarge the vision of cities beyond the borders of Europa. Last but not least, institutional partners will bring their own know how to make sure the proposed solutions are relevant in the field.