A Hierarchical Approach in Deploying Traffic Lights Using Complex Network Analysis

We present a novel approach in designing and de- ploying traffic light systems by identifying key intersections of the road network. Based on techniques borrowed from Complex Network Analysis, our algorithm can be applied successively at different levels of granularity allowing a hierarchical clustering of the intersections and prioritization of the traffic lights. We illustrate our approach with a case study conducted over the city of Timisoara. from complex networks apply and influence traffic behavior. We believe that proven metrics for describing the structure of a complex network can be used successfully for finding the key intersections in any urban network. These intersections are subject to intense traffic flow and require careful regulation in order to maintain this flow. By consequence, optimal policies and strategies for deploying traffic lights are essential in an Intelligent Transportation System; this makes up for the core of this paper. The rest of the paper is organized as follows: Section 2 provides an overview of the most relevant research initiatives in the area of our study, while Section 3 consists of a short introduction in the field of Complex Network Analysis, pre- senting the key concepts and metrics used in our research. Section 4 describes the core of our investigations in the form of a novel strategy and its corresponding algorithm for identifying the key intersections of the city in order to place traffic lights. In Section 5 we present the application of this methodology over the city of Timisoara, while Section 6 presents our concluding remarks and provides some ideas for future work. II. STATE OF THE ART With the advent of modern tools and methodologies for com- puter aided urban planning and the rapid spread of (Geograph- ical Information Systems) GIS tools in the public services and administration, significant research has been carried towards finding alternative approaches in analyzing the structure of cities. The approach based on graph theory was a clear choice