01660230

Component

The authors propose a novel traffic control algorithm that can be used in oversaturated road networks in large cities. For sophisticated traffic control, it is important to consider the dynamic behavior of vehicle queues. Such queues obstruct traffic flow in various directions, making the traffic situation chaotic. This results in severe traffic congestion, or so-called gridlock. In this study, the authors focus on closed-loop structures in road networks and vehicle queue advancement in these loops. The authors formalize the occurrence of gridlock in one-way road networks, and propose a traffic control algorithm called Z-control, which prevents gridlock and minimizes the total time spent based on a model predictive scheme. Moreover, the authors evaluated some algorithms for dynamic traffic control, including their proposed Z-control and some benchmarks. To do so, the authors conducted numerical experiments,considering two extreme scenarios pertaining to the behavior of drivers. In a “non-reactive” scenario, where drivers do not react to traffic conditions in the network, the authors showed that the proposed Z-control outperformed other benchmark algorithms. However, in a “reactive” scenario, where drivers are assumed to have perfect information about the traffic conditions in the network and react to it, no algorithm performed better than the situation without any control. The authors' research shows that to treat oversaturated traffic in cities suitably, it is important to control, or at least consider, the route-choice behavior of drivers, which may be achieved with automated vehicles.

This paper was sponsored by TRB committee AHB25 Standing Committee on Traffic Signal Systems.

18-01132

English

24p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; References; Tables

Algorithms; Evaluation; Feedback control; Networks; Queuing; Route choice; Traffic control; Traffic flow

Highways; Operations and Traffic Management

Transportation Research Board Annual Meeting 2018 Paper #18-01132

TRIS, TRB, ATRI

Jan 8 2018 10:17AM