This content is not included in your SAE MOBILUS subscription, or you are not logged in.
Traffic Control Strategies for Congested Heterogeneous Multi-Vehicle Networks
ISSN: 0148-7191, e-ISSN: 2688-3627
To be published on April 14, 2020 by SAE International in United States
The primary goal of this paper is to pioneer and develop robust and adaptive algorithms for controlling autonomous vehicles in heterogeneous networks with the aim of maximizing the performance (in terms of mobility) and minimizing variation in the network. While the fundamental approaches and models proposed in this research can be applied to any heterogeneous multi-agent system, we select heterogeneous traffic networks as a set-up for exploring the proposed research. We consider the heterogeneity in the system in the form of a mix of autonomous and human-driven vehicles (different levels of autonomous vehicle penetration). We propose a two-level hierarchical controller wherein the upper-level controller, an optimization problem using the concept of macroscopic fundamental diagram is formulated to deal with the traffic demand balance problem. At the lower level, using the microscopic models of the network, the control actions for each vehicle will be determined such that he optimal flow received from the upper-level controllers can be tracked.