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17 CHAPTER THREE WORKING PRINCIPLES OF MAJOR ADAPTIVE TRAFFIC CONTROL SYSTEMS INTRODUCTION SCATS), whereas others are known for their adaptive opera- tions in grid networks (e.g., SCOOT and UTOPIA). However, This chapter summarizes some of the working principles of different concepts and operational features that drive these major ATCSs deployed worldwide. Detailed descriptions of ATCSs do not always result in significantly different field various ATCSs, based on information obtained from the sys- performances. The following paragraphs review the concep- tems' developer and/or vendors, are provided in Appendix A. tual differences of the systems described in this study. Each of the ATCS descriptions primarily follows a format with the following subsections: Each of the ATCSs is somewhat unique. Therefore, com- parison of the specific features of each of the ATCSs is almost Adaptive traffic control logic impossible. Instead, this study identified and compared several Hardware and software requirements principles that essentially describe various adaptive traffic System architecture and communications Detection requirements control logics. Among the potential principles to be considered Special features. it was found that the following are of particular interest for the scope of this study: Detailed descriptions of all ATCSs and their characteris- tics were beyond the scope of this study. This report could Detection, not address in detail all of the ATCSs that are currently used Type of action, around the world. For some of the ATCSs, literature (in Eng- Adjustment method, lish) is scarce (e.g., PRODYN, CRONOS, and ITACA). Some Time frame for adjustment, other U.S. brands have a limited deployment history in the Hierarchical levels, United States. Sometimes, the adaptiveness of these systems Estimation through traffic modeling, is claimed owing to the adaptive functionalities and features Adjustments to signal timings, of their local controllers. This study covers only systems that Flexibility to form regions, can be recognized as full adaptive traffic control packages, Support for vehicle-actuated operations, and with an identifiable adaptive framework (logic, detection, etc.), Transit operations. that have been deployed in the field. Some of the emerging or international technologies are still not properly described This list does not include at least a half dozen other prin- in the literature. Hence, Table 6 shows 10 ATCSs, with their ciples that are nearly as important. For example, handling developers and vendors that were found to be the most impor- pedestrian operations and the ability to provide a framework tant, to be described in this study. Selection of the systems for sustainable traffic signal operations have now become two presented in Table 6 is based on several criteria, of which the of the most important principles in traffic signal operations. most important are: However, although some ATCSs are very advanced in this regard (e.g., SCOOT for pedestrian facilities), others simply Length of the presence on the market, rely on operations provided by local field controllers whose Field deployments, comparison is beyond the scope of this study. Documented descriptions of the system (available liter- ature), and Credibility of developer/vendor in ATCS field. Detection Various ATCSs use different detection layouts to estimate SUMMARY OF ADAPTIVE TRAFFIC CONTROL the state of traffic, which is later used to develop strategies that SYSTEMS CHARACTERISTICS adjust traffic control in a network. There are generally four Operational Characteristics major detector location types used by most ATCSs: ATCSs can be categorized in numerous ways. Some are Stop-line detectors (e.g., as seen in common actuated known to operate best on arterial networks (ACS Lite and operations in the United States and SCATS).

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18 TABLE 6 ATCS DESCRIBED IN THE STUDY System Developer/Distributor ACS Lite FHWA/Siemens ITS BALANCE University of Hanover, Germany/Gevas Software, Germany InSync Rhythm Engineering LA ATCS Los Angeles DOT/McTrans MOTION Technical Universi ity Munich, Germany/Siemens, Germany OPAC U. of Massachusetts, Lowell/PB Farradyne RHODES U. of Arizona, Tucson /Siemens ITS SCATS Road Transit Authority, Sydney, NSW, Australia/TransCore SCOOT Transport Research Laboratory, UK/Siemens UK UTO PIA MIZAR Automazione, Italy/McCain Near-stop-line detectors located close to the stop-line Adjustment Method (1060 m), which cannot be used (owing to their prox- imity to the stop-line) to easily calculate queue length There is a widely accepted notion among traffic signal practi- by balancing inflows and outflows (e.g., as used in tioners that most ATCSs optimize signal timings. The reality Germany by BALANCE and MOTION). is that some of them perform some kind of optimization, which Upstream (mid-block) detectors, which can be used to is usually constrained by its domain or time allowed to con- estimate reasonably long queue lengths (e.g., as seen at duct the optimization process. Some of these optimizations use some Californian intersections). heuristic techniques, whereas others use extensive search tech- Upstream (far-side) detectors located at the exit point of niques, to find solutions. Others do not formally optimize (no the upstream intersection (as used by SCOOT, UTOPIA, search process and no objective function); instead, they adjust ACS Lite, and optionally by RHODES). signal timings by using some heuristic methods and common traffic engineering concepts. Essentially we have three major Each of these detection layouts dictates, to a certain extent, types of adjustment methods: the type of adaptive traffic control logic that is needed to use imperfect measurements of the current traffic state where Domain-constrained optimization, where an optimiza- imperfections are inherently caused by location, number of tion search domain is very much limited to avoid high detectors, and accuracy of detection technology. fluctuations of signal timings to prevent negative tran- sition effects (e.g., SCOOT--all parameters, ACS Lite-- Type of Action offsets). Time-constrained optimization, where the optimiza- Some ATCSs proactively adjust traffic control to meet esti- tion search process is constrained by time and/or struc- mated traffic demand at each intersection before vehicles tural boundaries set by local controller policies (e.g., arrive. Other ATCSs react by providing feedback to the traf- RHODES, OPAC, BALANCE, and MOTION). fic measured during the previous interval. These two con- Rule-based adjustment, which covers any methods used cepts are usually, but not necessarily, related to the location to develop a (simple) functional relationship between of detectors. If stop-line detectors are used alone, the ATCSs parameters that describe change of traffic conditions and will usually provide feedback and respond with certain delay. resulting signal timings. Upstream detectors usually allow for a certain degree of pro- activity, although systems that use these detectors rely more on traffic models and the estimation of traffic demand. In Time Frame for Implementing New Signal Timings spite of the common belief that proactive systems work bet- ter than reactive systems, there is no hard evidence to sup- Some ATCSs adjust some of their parameters every few sec- port such a hypothesis. Some of the major systems combine onds. Others adjust parameters every 10 to 15 min, similar to two concepts for various segments of their operations. For pattern-matching responsive traffic control systems. Some of example, SCOOT determines splits and offsets proactively, the ATCSs combine the two approaches. Again, there is no whereas the cycle length is computed reactively. ACS Lite is evidence that the systems that respond faster are (always) bet- similar: splits are determined reactively, whereas the offsets ter than the less responsive systems, although such a notion are determined proactively. can be found in the literature.

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19 Hierarchical Levels ATCS into those regions or subsystems of intersections that usually need to be coordinated. In such a case, a bor- It is interesting to note that all of the ATCSs considered in dering intersection in one subsystem may sometimes ben- this report, in one way or another, operate on two or more efit from leaving its current subsystem and joining the hierarchical levels. Although some systems are seen as more neighboring subsystem. If an ATCS supports automatic hierarchical than others, they all have a component that uses reconfiguration of the subsystems it is said that the ATCS operations of local controllers and also some tactical (or strate- supports flexible regions. SCATS is well known for its gic) component that oversees the responsiveness of traffic "marriage and divorce" logic, which supports automatic control on a higher level, regardless of whether it is done in reconfiguration of the subsystems based on predefined cri- a centralized or in a distributive way. For example, SCOOT, teria. Although SCOOT can do something similar, most of which is often considered a major example of centralized the other ATCSs either do not support such operations or (and tactical) ATCS, also uses demand-dependent features of information about such a feature is not easily available in local controllers to skip phases with no demand. the public literature. Estimation Through Traffic Modeling Support for Actuated Operations The word "modeling" here refers to the use of macroscopic, By actuated operations it is meant common gap-out opera- mesoscopic, or microscopic models (by an ATCS) to estimate tions executed by local controllers. Most of the ATCSs will the current state of traffic, which is further used as an input set lower and upper boundaries for green splits. A lower to adjust signal timings. For example, analytical models that boundary is usually defined as minimum green for each express relationships between measured and derived traffic phase. Upper boundaries are usually defined by dynamic variables (such as degree of saturation, phase utilization, etc.) splits that are optimized by ATCS logic for each cycle do not conform to the definition of modeling as used in this section. SCOOT is famous for its model that estimates queue (or even for shorter intervals). What happens in between lengths based on flow-occupancy profiles from upstream detec- defines whether an ATCS supports actuated operations or tors. SCATS does not use any traffic modeling in its operations. not. To further clarify this concept a distinction needs to be Most of the other ATCSs use models extensively. In general, made between cases where an ATCS takes responsibility models help ATCSs perform more proactively, although they to end the green phase in the absence of traffic demand over also may introduce errors that can be propagated (spatially and a detector and where such a responsibility is transferred to a temporally) during the course of ATCS actions. An extreme local intersection controller. For example, RHODES does use of modeling is seen in the newly developed ATCS for not allow a local controller to make decisions based on local New York City, where data from traffic detectors are used to actuation. If RHODES is in its "Online" mode it will issue populate a microsimulation model that is then run under a vari- a force-off command to stop green for a phase. This com- ety of traffic control strategies (within a 15-min time frame). mand is based on RHODES traffic estimation and not on the In spite of its ultramodern approach of using a microsimulation common gap-out logic of a local controller. The RHODES model to investigate the quality of signal timings, the system concept does not transfer responsibility to gap-out opera- requires that a specified traffic control strategy be confirmed tions to a local controller. On the other hand, SCATS, as manually (Xin et al. 2008). well as some other ATCSs (e.g., BALANCE, MOTION, and ACS Lite), will allow the local controller to execute its gap-out logic in between the aforementioned lower and Adjusted Signal Timings upper boundaries. Most ATCSs adjust three major types of signal timings: green splits, cycle lengths, and offsets. However, there are a few Transit Signal Priority ATCSs that do not follow this rule either because they are still under development (e.g., ACS Lite) or because their operations It is interesting to note that most of the ATCSs presented here are not based on all of these timings (e.g., RHODES, InSync, provide some type of priority for transit vehicles. However, and some versions of OPAC do not use cycle lengths). Con- this priority is often provided at the local controller's level and versely, only a few ATCSs adjust or optimize phase sequenc- is not offered as a result of comprehensive optimization where ing in real time (e.g., BALANCE, MOTION, and InSync). This transit travel times (or delays) are integrated into the opti- is primarily because frequent alterations in phase sequencing mization structure that accounts for network-wide vehicular can cause negative impacts on traffic (frequent transitions). and transit performances. Flexibility to Form Regions Table 7 shows how each of the ten major ATCSs consid- ered in this study are categorized for each of the ten principles. For some of the ATCSs (e.g., SCOOT, SCATS, and LA The information provided here is based on a comprehensive ATCS) it is necessary to divide the entire area covered by the literature review and does not necessarily reflect how vendors