A Case for Feedback Control to Prevent Delay

Abstract

This study was motivated by the work of researchers who conducted field experiments on roadways with no bottlenecks. The ring roads are circular roadways where passing was restricted. All drivers who took part in these field studies promised to maintain the same constant speed. They were unable to do so. The field tests showed the importance in the variability in speed, i.e., traffic noise. Like the field test, traffic noise plays a prominent role in this simulation study. First, the focus is on triggering traffic breakdown and queue formation. Stochastic car-following models are developed. They feature Brownian motion models that help explain the connection between driver behavior and traffic noise. Second, the focus is on preventing traffic breakdown and queuing. State-space modeling and feedback control using Kalman filtering are featured. Real-time noisy data are collected and recursively passed through a system that tracks a target that is a function of time. All simulations in this study imitate the instructions given to the drivers in the ring-road field experiments. The drivers start from rest, accelerate to the same constant speed, and then attempt to hold that speed through the duration of the experiment. In the first part, the drivers fail. In the second part, they succeed. To demonstrate the effectiveness of the feedback control approach, a worse-case scenario is investigated. A ring road is assumed to operate at capacity; thus, queuing and breakdown are expected. Testing and implementing the feedback control system in a smart city environment and its fate are discussed.