Connected and Automated Vehicles

A viability algorithm is developed to compute the constrained minimum time function for general dynamical systems. The algorithm is instantiated for a specific dynamics (Dubin's vehicle forced by a flow field) in order to numerically solve the minimum time problem. With the specific dynamics considered, the framework of hybrid systems enables us to solve the problem efficiently. The algorithm is implemented in C using epigraphical techniques to reduce the dimension of the problem. The feasibility of this optimal trajectory algorithm is tested in an experiment with a light autonomous...

The vulnerability of Mobility-as-a-Service (MaaS) systems to Denial-of-Service (DoS) attacks is studied. We use a queuing-theoretical framework to model the re-dispatch process used by operators to maintain a high service availability, as well as potential cyber-attacks on this process. It encompasses a customer arrival rate model at different sections of an urban area to pick up vehicles traveling within the network. Expanding this re-balance model, we analyze DoS cyber-attacks of MaaS systems by controlling a fraction of the cars maliciously through fake reservations (so called Zombies)...

Traffic dynamics are often modeled by complex dynamical systems for which classical analysis tools can struggle to provide tractable policies used by transportation agencies and planners. In light of the introduction of automated vehicles into transportation systems, there is a new need for understanding the impacts of automation on transportation networks. The present article formulates and approaches the mixed-autonomy traffic control problem (where both automated and human-driven vehicles are present) using the powerful framework of deep reinforcement learning (RL). The resulting...