Rhodes: a Real-time Traffic Signal Control System: Architecture, Algorithms, and Analysis

The paper discusses a real-time traffic adaptive signal control system referred to as RHODES. The system takes as input detector data for real-time measurement of traffic flow, and “optimally” controls the flow through the network. The system utilizes a control architecture that (1) decomposes the traffic control problem into several subproblems that are interconnected in an hierarchical fashion, (2) predicts traffic flows, at appropriate resolution levels (individual vehicles and platoons) to enable proactive control, (3) allows various optimization modules for solving the hierarchical subproblems, and (4) utilizes a data structure and computer/communication approaches that allow for fast solution of the subproblems, so that each decision can be downloaded in the field appropriately within the given rolling time horizon of the corresponding subproblem. The RHODES architecture, algorithms, and its analysis are presented. Laboratory test results, based on implementation of RHODES on simulation models of actual scenarios, illustrate the effectiveness of the system. 1. THE SYSTEM Over the last six years, the authors, with some students, faculty and researchers have proposed and developed a real-time traffic-adaptive signal control system, referred to as RHODES1. The system takes input from the surface street detectors (allowing whatever technology that is being utilized: induction loops, video, etc.), predicts the future traffic streams at various hierarchical levels of aggregation, both spatially and temporally, and outputs “optimal” signal control settings that respond to these predictions. The optimization criterion can be any that is provided by the jurisdiction using the system but must be based on traffic measures of effectiveness (average delays, stops, throughput, etc.). The RHODES architecture for surface streets is depicted in Figure 1(from Head et al, 1992). At the highest level of RHODES is a "dynamic network loading" model that captures the slow-varying characteristics of traffic. These characteristics pertain to the network geometry (available routes including road closures, construction, etc.) and the typical route selection of travelers. Based on the slow-varying characteristics of the network traffic loads, estimates of the load on each particular link, in terms of vehicles per hour, can be calculated. The load estimates then allow RHODES to allocate "green time" for each different demand pattern and each phase (North-South through movement, North-South left turn, East-West left turn, and so on). These decisions are made at the middle level of the hierarchy, referred to as "network flow control". Traffic flow characteristics at this level are measured in terms of platoons of vehicles and their speeds. Given the approximate green times, the "intersection control” at the third level selects the appropriate phase change epochs based on observed and predicted arrivals of individual vehicles at each intersection. Essentially, at each level of the hierarchy there is an estimation/prediction component and a control component. These components are discussed in discussed in Sections 2 and 3 respectively. Currently, we have not done much model development at the highest level (dynamic network loading) so we will not include much discussion of level 1 of the RHODES hierarchy. There are three aspects of the RHODES philosophy that make it a viable and effective systems to adaptively control traffic signals. First, it recognizes that recent technological advances in communication, control, and computation (a) make it possible to move data quickly from the street to the computing processors (even now most current systems have communication capabilities that are not utilized to their potential), (b) make processing of this data to 1 The authors also acknowledge the significant support received from the Arizona Department of Transportation, City of Tucson and other local agencies in Arizona, and the Federal Highway Administration, without which the authors would not have been able to develop RHODES up to the field testing phases.