IE Decision Systems Engineering Fall ’20 Seminar Series: Framework for Loss Distribution of the Operational Risk of Vehicle-to-Vehicle Cooperation to Marshal Traffic via Monetization of Highway Space, October 23

In this work, we develop a framework for loss distribution of the operational risk of vehicle-to-vehicle cooperation to marshal traffic via monetization of highway space. As a motivating technological solution, we consider the Cooperatively Managed Merge and Pass (CMMP) system proposed by Ford Motor Company. In the USA alone, traffic congestion in terms of time lost imposes substantial opportunity costs, afflicts commuters with stress, and contributes to air pollution. Acting in concert, a vehicle-to-vehicle In this work, we develop a framework for loss distribution of the operational risk of vehicle-to-vehicle cooperation to marshal traffic via monetization of highway space. As a motivating technological solution, we consider the Cooperatively Managed Merge and Pass (CMMP) system proposed by Ford Motor Company. In the USA alone, traffic congestion in terms of time lost imposes substantial opportunity costs, afflicts commuters with stress, and contributes to air pollution. Acting in concert, a vehicle-to-vehicle communications infrastructure, blockchain, smart contracts, and digital assets technologies allow for novel solutions to this long-standing problem. So far, leading automobile manufacturers have offered several technological solutions for real-time monetization of highway space. Unfortunately, often the technology stack required has cyber vulnerabilities leaving these solutions open to misuse. In that context, understanding the operational risk via its loss distribution is of high importance for operators and insurers. That is why we pioneer the approach that contextualizes the problem in the probabilistic graph theoretical framework by using percolation models. In the case of adverse materialization of cyber risk and its spread through a vehicular network, we allow for spatially heterogeneous loss topology. In the context of the USA, we provide instructive numerical examples. communications infrastructure, blockchain, smart contracts, and digital assets technologies allow for novel solutions to this long-standing problem. So far, leading automobile manufacturers have offered several technological solutions for real-time monetization of highway space. Unfortunately, often the technology stack required has cyber vulnerabilities leaving these solutions open to misuse. In that context, understanding the operational risk via its loss distribution is of high importance for operators and insurers. That is why we pioneer the approach that contextualizes the problem in the probabilistic graph theoretical framework by using percolation models. In the case of adverse materialization of cyber risk and its spread through a vehicular network, we allow for spatially heterogeneous loss topology. In the context of the USA, we provide instructive numerical examples.