Traffic Operations and Management

This study focuses on the comprehensive investigation of stop-and-go waves appearing in closed-circuit ring road traffic wherein we evaluate various longitudinal dynamical models for vehicles. It is known that the behavior of human-driven vehicles, with other traffic elements such as density held constant, could stimulate stop-and-go waves, which do not dissipate on the circuit ring road. Stop-and-go waves can be dissipated by adding automated vehicles (AVs) to the ring. Thorough investigations of the performance of AV longitudinal control algorithms were carried out in Flow, which is an...

In an ideal world, all cars along a congested roadway would travel at the same constant average speed; however, this is hardly the case. As soon as one driver brakes, trailing cars must also brake to compensate, leading to “stop and go” traffic waves. This unnecessary braking and accelerating increases fuel consumption (and greenhouse gas emissions) by as much as 67 percent.1 Fortunately, automated vehicles (AVs) — even Level 2 AVs2 which are commercially available today — have the potential to mitigate this problem. By accelerating less than a human would, an AV with flow smoothing...

The rise of vehicle automation has generated significant interest in the potential role of future automated vehicles (AVs). In particular, in highly dense traffic settings, AVs are expected to serve as congestion-dampeners, mitigating the presence of instabilities that arise from various sources. However, in many applications, such maneuvers rely heavily on non-local sensing or coordination by interacting AVs, thereby rendering their adaptation to real-world settings a particularly difficult challenge. To address this challenge, this paper examines the role of imitation learning in...

We develop reinforcement learning (RL) boundary controllers to mitigate stop-and-go traffic congestion on a freeway segment. The traffic dynamics of the freeway segment are governed by a macroscopic Aw–Rascle–Zhang (ARZ) model, consisting of 2 \times 2 quasi-linear partial differential equations (PDEs) for traffic density and velocity. The boundary stabilization of the linearized ARZ PDE model has been solved by PDE backstepping, guaranteeing spatial L² norm regulation of the traffic state to uniform density and velocity and ensuring that traffic oscillations are...