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Co-Design to Enable User-Friendly Tools to Assess the Impact of Future Mobility Solutions

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Document pages: 11 pages

Abstract: The design of future mobility solutions (autonomous vehicles, micromobilitysolutions, etc.) and the design of the mobility systems they enable are closelycoupled. Indeed, knowledge about the intended service of novel mobilitysolutions would impact their design and deployment process, whilst insightsabout their technological development could significantly affect transportationmanagement policies. This requires tools to study such a coupling and co-designfuture mobility systems in terms of different objectives. This paper presents aframework to address such co-design problems. In particular, we leverage therecently developed mathematical theory of co-design to frame and solve theproblem of designing and deploying an intermodal mobility system, wherebyautonomous vehicles service travel demands jointly with micromobility solutionssuch as shared bikes and e-scooters, and public transit, in terms of fleetssizing, vehicle characteristics, and public transit service frequency. Ourframework is modular and compositional, allowing one to describe the designproblem as the interconnection of its individual components and to tackle itfrom a system-level perspective. Moreover, it only requires very generalmonotonicity assumptions and it naturally handles multiple objectives,delivering the rational solutions on the Pareto front and thus enabling policymakers to select a policy. To showcase our methodology, we present a real-worldcase study for Washington D.C., USA. Our work suggests that it is possible tocreate user-friendly optimization tools to systematically assess the costs andbenefits of interventions, and that such analytical techniques might informpolicy-making in the future.

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