COmpetition models and cross-Subsidies for equitable and green MObility - COSMO

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Mobility systems are on the brink of revolution as they suffer from an overloaded infrastructure causing users' dissatisfaction, pollution, increased inequality, health dangers. In London alone, exposure to NO2 accounts for 5900 fatalities/year, with healthcare costs of 1.4BGBP/year. For these reasons, the UK Government identified Future Mobility as one of the four Grand Challenges.At the same time, the advent of new forms of mobility and big data provides remarkable opportunities. In this context, Intermodal Mobility -- where different modes of transport provide complementary services -- is a promising paradigm, as it combines efficient long-distance transport with last-mile services.However, their operation has resulted in equally many challenges. Most notably, transportation authorities struggle to understand how new mobility solutions should be integrated within the existing infrastructure, how to orchestrate and regulate them in a cohesive way, and how to identify those that will ultimately improve equitability and reduce system-wide congestion. At its core, these challenges stems from the fact that privately-owned mobility providers often have objectives that are misaligned with those of the transportation authority (e.g., maximise profit vs minimise congestion/inequity), and result in competing with existing modes of transport as opposed to complementing them.To address these challenges, COSMO aims to develop mathematical models to describe the competition between mobility providers, to analyse these models, and to exploit them to design optimisation-based and cooperation-inducing subsidies to reconcile the providers interest with that of improving equitability, minimising congestion, or a combination thereof.More in details, the first component will deliver a threefold set of cohesive contributions: i) the development of a concise game-theoretic model for competition between different mobility providers, ii) the study of the resulting equilibria, and iii) the design of efficient equilibrium computing algorithms. Building atop the first, the second component will leverage recent breakthroughs in optimization and game theory to design optimization-based cross-subsidies that trade-off between maximising equitability and minimising congestion/emissions.These two components will culminate in the release of an open-access algorithmic suite, whose effectiveness will be tested on synthetic and real-world case studies on US cities and the Borough of Greenwich, shared and developed jointly with project partners. In the spirit of this call, the research will be carried out in close collaboration with leaders in smart mobility (Dr. Pavone, Stanford University & NVIDIA Research) and transportation (Dr. Osorio, HEC Montreal & Google Research), with whom a number of networking activities have been co-designed including an extended visit at Stanford University and HEC Montreal, daily visits and invited talks at NVIDIA Research and Google Research.