The PoC aims to develop a prototype for an optimal route guidance system that improves traffic conditions in urban areas. Urban traffic management at large-scale is very challenging but may lead to significant travel time savings by better-distributing drivers among the network. Existing navigation apps or routing systems provide the shortest-path in time to users resulting in the network user equilibrium. However, traffic engineers know that total travel times may be reduced by 10 to 30% if user routes comply with the system optimum. There is no actual traffic management system that can achieve such a goal because of computational (determining the optimal route for all current users in NP-hard), privacy (optimality requires that all users share their destination with a centralized controller) and compliance issues (users may not follow routing instructions). The optimal route guidance system we have designed within the MAGnUM project can quickly solve the two first issues. A centralized controller produces real-time avoidance maps, i.e., the definition of how many users should avoid each subsection of the road network to alleviate congestion in this area. Such maps are derived by monitoring of overall traffic conditions. Each user transforms this information into individual route guidance through its navigation system. This privacy is guaranteed by design as the users share no information with the controller but only take benefit from avoidance maps. The PoC will not only develop the prototype but also implement the system in the field to run experiments over three months. The experiments aim to (i) test the proper system functioning, (ii) derive optimal controller settings in particular concerning the network partitioning, and (iii) investigate users’ reactions to the guidance and determine the natural compliance rate. All the studies will permit us to assess the potential of the full system better and prepare the next steps before introduction to the market.

The 5-year CLEAR-Doc project aims at attracting PhD students (ESR) from around the world, in order to strengthen their research capacity and soft skills through high standards and fair selection. The trainees will benefit from a unique research environment of excellence thanks to 22 research labs focusing on Urban Research, so as to create the “City of tomorrow”. ESRs will contribute to address major societal challenges in climate-neutral, resource-efficient, resilient, safe and smart cities. The programme includes a choice among 6 interdisciplinary curricula in addition to a mandatory secondment among a comprehensive network of academic, non-academic and international partners of Université Gustave Eiffel, as a means to facilitate professional integration and international experience. In the context of booming urbanization, the richness of the research options offered is expected to meet the most demanding career plans of ESRs in terms of interdisciplinarity, intersectorality and international experience. The project strengths rely on unique excellent competences and experimental platforms available on each of the 7 university campuses as well as historical strong local cooperation with regional and private partners, with the support of European and international networks. The programme originality is to introduce interdisciplinarity and intersectorality from the start, promoting an approach through three cross-disciplinary challenges shared at international level. These challenges are as follows :1-Design and develop resource-efficient urban spaces; 2- Understand and manage ʺurban risks" for safe and resilient cities; 3-Develop the digital city and turn it into a catalyst for social, environmental and economic performance. The CLEAR Doc programme will also provide to the ESRs cohorts the opportunity to work together and within a scientific community and take full advantage of such environment.

Moving towards sustainable mobility will require improved understanding of the gendering processes across cycling mobility as the bicycle is a vector of sustainable lifestyles but gender norms still restrict its development. Research on gender and mobility neglects the sensitive materiality through which gender is constructed, and aesthetical approach of mobility infrastructure takes little interest so far in gender. To investigate how gender intersects with aesthetics in the ongoing formation of bicycling practices, equipment and infrastructure will lead to a better understanding of the potential of gender dynamics as an agent of change in creating more sustainable cities. The aesthetical experience of the bicycle has a key role in the continuous infrastructuring processes of bicycling practices, equipment and infrastructure. My main hypothesis is that the aesthetical experience also creates a tension with the dominant norms of feminity/masculinity, impacting the ongoing gender formation and deconstruction. The deconstruction of these unequal political categories constitutes an important step towards the development of more systemically sustainable cities. Focusing on French and Swiss cities at different stages in the implementation of their cycling policies, the research will develop an original interdisciplinary, comparative and multi-scale approach that deploys the concept of social imaginary to explore the spatial (micro)practices in relation to cycling materialities and ambiances, embodied experiences, meanings and representations, drawing on object-based, visual and mobile methodologies. It will cast light on affective and sensible resonances between infrastructure, environment, equipment and gendered bodies. In the longer term, to investigate the aesthetical dimension of mobility participates in the effort in research to overcome the curiously immaterial and disembodied conceptions of sustainability.

Rapid growth in the demand for urban transportation networks has underlined the urgent need for sophisticated management of multimodal transportation networks due to the significant costs associated with traffic congestion and CO2 emissions. Addressing these challenges requires a dual focus: alleviating congestion and minimizing CO2 emissions. A significant step towards achieving environmentally sustainable urban transportation networks, SMART-ROUTE is dedicated to optimizing large-scale urban multimodal transportation networks and has four objectives: (i) capturing the evolution of large-scale multimodal network dynamics; (ii) design and train machine learning models to predict the dynamic network state; (iii) design Deep Reinforcement Learning (DRL) methods to refine demand and supply management; (iv) validate the proposed algorithms at large-scale multimodal transport networks. Calculation of the real transportation network state is defined as an equilibrium that corresponds to modeling and solving Dynamic network equilibrium (DNE). It addresses the challenges posed by DNE, with increasingly fluctuating demand and supply, particularly in light of the health crisis and the spread of teleworking. Utilizing machine learning approaches, such as physics-informed machine learning (PIML) and graph neural networks (GNNs), we aim to capture intricate DNE features (e.g., path/link flow patterns), enabling more efficient predictive modeling. Graph-based machine learning models will be designed for forecasting DNE, while DRL techniques optimize these solution spaces by applying various control strategies. SMART-ROUT will evaluate and validate the methods on multiple multimodal test cases. In particular, real test cases of Paris and Lyon, provided by Consortium members, will be employed, ensuring their robustness and efficacy. By integrating the DNE mathematical foundations with the power of ML, SMART-ROUTE aims to create new efficient tools to optimize agent-based simulators. This integration leads to more adaptive, efficient, and environmentally conscious urban transport networks that are responsive to a variety of conditions, advancing the transition to smart, sustainable cities. The tool will offer time, energy, cost, and CO2 emission savings for professionals in the transportation and urban mobility sectors. The project will offer a set of models and tools available to all researchers, policymakers, and transportation stakeholders.