No abstract

The simulation of local signal controllers has become increasingly sophisticated in recent years and has been paralleled by improvements in the integration of adaptive systems into simulation. This paper describes and demonstrates an emerging methodology for the evaluation of adaptive signal control that is termed “system-in-the-loop simulation.” This methodology extends existing software-in-the-loop simulation by linking virtualized traffic controllers with real-world adaptive-control systems. In addition, the authors propose an analysis methodology that fuses data on simulated probe vehicles with data on high-resolution controller events. Through this data fusion, traditional measures of simulation performance such as delay can be enhanced with operational measures of performance that characterize quality of progression and capacity utilization. In addition, adaptive-control performance can be characterized in relation to overall impact on traveler delay and also described in terms that are meaningful for improvement of control schemes. An example case study is presented: the ACS-Lite adaptive system was tested on a 19-intersection system in Morgantown, West Virginia, under a special-event scenario. Free, fully actuated control was compared with traditional time-of-day and traffic-responsive control both with and without the use of the adaptive-control system ACS-Lite. Overall delay results are presented and contrasted with more detailed analysis of event-based performance measures at a single intersection and on a networkwide basis.

Probe data are emerging as an important source for characterizing transportation systems. Travel time distributions have traditionally been characterized by the mean and standard deviation. These statistics work well to characterize uncongested freeway systems, which have travel time distributions that are approximately normal. When congested conditions or interrupted-flow facilities are encountered, the travel time distributions become more complex. Recently some additional travel time reliability indexes have been developed to quantify these travel time distribution characteristics. This study develops mathematical techniques for determining the sample size required for estimating the underlying travel time distributions that can be used for assessing changes in travel time distributions associated with operational changes of traffic signal controller offsets. The example provided shows that while gross changes in offsets require approximately 7 probe vehicle samples per study interval, subtle changes in offsets require approximately 80 probe vehicle data samples per study interval. Although these guidelines were developed for evaluating offset changes, the mathematical framework can be applied for evaluating the impact of other parameters, such as split times and cycle lengths. Further research on applying these mathematical techniques to a broader cross section of traffic conditions is warranted to assess their transferability to oversaturated conditions and freeways.

The increasing connectivity in transportation infrastructure is driving a need for additional security in transportation systems. For security decisions in a budget-constrained environment, the possible effect of a cyberattack must be numerically characterized. The size of an effect depends on the level of access and the vehicular demand on the intersections being controlled. This paper proposes a framework for better understanding of the levels of access and the effect that can be had in scenarios with varying demand. Simulations are performed on a simplistic corridor to provide numerical examples of the possible effects. The paper concludes that the possibility of some levels of cyberthreat may be acceptable in locations where traffic volumes would not be able to create an unmanageable queue. The more intimate levels of access can cause serious safety concerns by modifying the settings of the traffic controller in ways that encourage red-light running and accidents. The proposed framework can be used by transportation professionals and cybersecurity professionals to prioritize the actions to be taken to secure the infrastructure.

is the Arbutus Professor of Electrical and Computer Engineering at Georgia Tech, where he directs the Arbutus Center for the Integration of Research and Education and is the founder of the Vertically-Integrated Projects (VIP) Program. Dr. Coyle is a Georgia Research Alliance Eminent Scholar and was a co-recipient of the National Academy of Engineering's 2005 Bernard M. Gordon Award for Innovation in Engineering and Technology Education. He is a Fellow of the IEEE and his research interests include wireless networks, digital signal processing, and engineering education.