This chapter on on-line traffic assignment and network loading is from a book of essays published in honor of David Boyce for his contributions to the fields of transportation modeling and regional science. The authors first consider the use of equilibrium modeling to estimate current and future use of traffic networks; static traffic assignment (STA) is a model where, for given origin-destination predicted flow volumes, an equilibrium concept is utilized to assign routes and load flows on these routes. To model the route travel times and the speed profiles during the trip actually experienced by the traveler, researchers have developed the dynamic traffic assignment (DTA) approaches. The authors then propose a model that captures the dynamics of route-choice equilibration, provide an analytical traffic assignment approach to manage an impacted neighborhood network (INN) when count detectors and traffic probes are available, and demonstrate the feasibility and applicability of the approach. The model considers the dynamics of travel through the network, as well as day-to-day congestion-forming processes, rather than the use of explicit Bureau of Public Roads (BPR) functions. Analysis of the results from the assignment/simulation model indicate that the dynamic equilibrium process does behave as expected in the field: the process exhibits dynamic travel times and day-to-day convergence to a steady state; the routes most used for an origin-destination pair, at steady state, have nearly equal travel times; and if a long route is chosen for an origin-destination pair then only a very small fraction of travelers choose it.

The article discusses a strategy, referred to as Categorized Arrivals-based Phase Reoptimization at Intersections (CAPRI), which integrates transit signal priority and rail/emergency preemption within a dynamic programming-based real-time traffic adaptive signal control system. The system takes as input sensor data, from detectors, automatic vehicle locators, transponders, etc., for real-time predictions of traffic flow, and “optimally” controls the flow through the network using signal phasing. The system utilizes a traffic adaptive signal control architecture that (1) decomposes the traffic control problem into several subproblems that are interconnected in a hierarchical fashion, (2) predicts traffic flows, at appropriate resolution levels (individual vehicles, platoons of vehicles, transit vehicles, emergency response units, and trains) to enable proactive control, (3) supports various optimization modules for solving the hierarchical subproblems, and (4) utilizes data structure and computer/communication approaches that allow for fast solution of the subproblems, so that each decision can be implemented in the field within an appropriate rolling time horizon of the corresponding subproblem. Simulation-based analyses illustrate the effectiveness of the CAPRI system.

A new approach is presented to the estimation of travel times (in real time) on arterials on the basis of second-by-second data from detectors that count vehicles. Unlike most approaches, which attempt to track individual vehicles as they move throughout the network, the proposed approach tracks clusters, or platoons, of vehicles. This approach offers several advantages over existing methods and provides good travel time estimates for arterial networks. Although other methods of estimating travel times have varying degrees of success, they each suffer from limitations ranging from processing, equipment, and infrastructure requirements to personnel cost for probe vehicles, sociopolitical issues of surveillance, and the perceived loss of privacy. The proposed method attempts to overcome some of these limitations. Because existing detection and controller infrastructure is used, additional equipment is not required. Second-by-second detector data are used to identify platoons of vehicles but not individual vehicles. The platoons, and not individual vehicles, are then tracked as they travel from upstream detectors to downstream detectors on a route segment, producing travel time estimates for this segment. In addition, since the proposed method captures the aggregate flow of vehicles, it should better measure the central tendencies of the driver population and current traffic conditions as reflected by travel times at the prevailing congestion levels.

According to the salving-principle of self-organization theory, the primary parameter in traffic flow is found. By simulation, a criterion for traffic light setting at an intersection based on the primary parameter is obtained. Then, by analyzing the important effect of the primary parameter on this criterion, the practicability of using self-organization theory in traffic flow research is confirmed.

RHODES is a traffic-adaptive signal control system that optimally controls the traffic that is observed in real time. The RHODES-ITMS Program is the application of the RHODES strategy for the two intersections of a freeway-arterial diamond interchange. This report addresses the latest phase of the RHODES-ITMS Program that resulted in a field test in the City of Tempe, Arizona. In summary, this phase involved: (i) the integration of the RHODES logic within the signal controller; (ii) the validation of the RHODES logic using hardware-in-the-loop simulation; (iii) the integration of the RHODES algorithms within Tempe's traffic management system; (iv) the deployment of RHODES for the field test; and (v) the data gathering and evaluation of traffic performance with and without the RHODES logic. The objectives of this project were: (i) to see if a communication/computation infrastructure could be designed and implemented for second-by-second detector data collection and signal phase commands; (ii) to see if a traffic-adaptive signal control system could be implemented on an off-the-shelf Advanced Traffic Controller; (iii) to determine whether the RHODES strategy is viable in the field; and (iv) to evaluate the traffic performance of RHODES. The answers for the first three objectives were positive: that is, the communication/computation infrastructure was designed and implemented, and RHODES control strategy was integrated within the infrastructure and proved to be viable. With regard to the fourth objective, RHODES was able to match the performance of the current well-tuned semi-actuated control being used by the City of Tempe. The major contributions of the RHODES-ITMS Program can be categorized into the development and implementation (i) of new integrated hardware/software infrastructure that includes a new communication system, and (ii) of a traffic-adaptive signal control system. The infrastructure (i) integrates traffic-adaptive features within the 2070 Advanced Traffic Controllers, (ii) deploys, for the first time, a 2070 Controller within a TS2 cabinet, and (iii) implements a communication system for second-by-second decision making. The traffic-adaptive system has the following attributes and benefits: (i) it is second-by-second responsive; (ii) it has a hierarchical and distributed modular architecture that allows additional traffic control features; and (iii) it requires low maintenance of timing plans by traffic engineers. Last, but not least, the effort has extended the cutting edge in systems engineering methodology for the design of real-time decision-making systems and has expanded the workforce in traffic systems engineering by graduating several students through this research effort.

Simulation is a valuable tool for evaluating the effects of various changes in a transportation system. This is especially true in the case of real-time traffic-adaptive control systems, which must undergo extensive testing in a laboratory setting before being implemented in a field environment. Various types of simulation environments are available, from software-only to hardware-in-the-loop simulations, each of which has a role to play in the implementation of a traffic control system. The RHODES (real-time hierarchical optimized distributed effective system) real-time traffic-adaptive control system was followed as it progressed from a laboratory project toward actual field implementation. The traditional software-only simulation environment and extensions to a hardware-in-the-loop simulation are presented in describing the migration of RHODES onto the traffic controller hardware itself. In addition, a new enhancement to the standard software-only simulation that allows remote access is described. The enhancement removes the requirement that both the simulation and the traffic control scheme reside locally. This architecture is capable of supporting any traffic simulation package that satisfies specific input-output data requirements. This remote simulation environment was tested with several different types of networks and was found to perform in the same manner as its local counterpart. Remote simulation has all of the advantages of its local counterpart, such as control and flexibility, with the added benefit of distribution. This remote environment could be used in many different ways and by different groups or individuals, including state or local transportation agencies interested in performing their own evaluations of alternative traffic control systems.