Centralized Traffic Control via Small Fleets of Connected and Automated Vehicles

Abstract

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Macroscopic traffic flow modelling: from kinematic waves to autonomous vehicles

“…In particular, the multi-scale models presented in Section 3.2 can be used to quantify the gain that can be obtained by controlling the desired speed of small fleets of CAVs in mixed traffic flows. As an example, we illustrate in Figure 12 the result of total fuel consumption minimization algorithms using a centralized control of a small fleet of CAVs [69], supporting the perspective of regulating traffic flow by means of a small number of controlled vehicles. , where Vmax = 140 km/h and Rmax = 400 veh/km, and inflow and outflow boundary conditions are given by f in (t) = 1400χ([0, 0.5]) veh/h and f out (t) = 700χ([0, 1]) veh/h respectively.…”

Sustainability Opportunities and Ethical Challenges of AI-Enabled Connected Autonomous Vehicles Routing in Urban Areas

“…However, the routing and exploitation of sensing potential of CAVs is beyond the capabilities of human traffic controller, hence the need for optimised and tailored AI-based approaches (see, e.g., [1]- [3]). In particular, AI enables the centralised distribution of traffic [4], which is where significant sustainability benefits are expected to come from [5]. It should also be noted that intervehicular (V2V) and with infrastructure (V2X) communication capabilities enable vehicles to make independent decisions based on shared data received from fellow vehicles and roadside units, facilitating short-term decisions to further improve efficiency and safety [6].…”