Exploring the impact of autonomous vehicles in urban networks and potential new capabilities for perimeter control

Recently there has been an enormous effort towards the development and field deployment of autonomous vehicles (AV). These developments have a direct impact on road traffic characteristics, as AV can also be used as sensors, actuators, and generally as effective components of an online traffic management system. In this work, we explore through microsimulation how AV can affect the network performance on urban networks. It is demonstrated through simulation experiments, that for mixed traffic (i.e. AV and conventional vehicles), different penetration rates of AV can reduce the density (i.e. congestion) and increase the capacity (i.e. throughput) of the network. Furthermore, new emerging capabilities for perimeter control in urban regions are explored, by utilizing new sources of data that can become available. A new feedback-based regulator is developed, which uses AV speed measurements as the state-feedback variables. The regulator is demonstrated to work equivalently well with a well fine-tuned regulator that uses loop detectors occupancy measurements (i.e. accumulation estimates) from all the links of the network. The speed-based feedback perimeter flow regulator performs significantly well even for very low penetration rates of AV (e.g. 5%), resulting in reduced delays for the users and less congestion in the urban region. Although the regulator has sparse measurements only from AV it can achieve the same improvement with the accumulation-based regulator that has the whole picture of the network.