Larry Head

A real-time traffic signal control system: Architecture, algorithms, and analysis

Abstract 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 pro-active 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.

Data-Driven Algorithms for Real-Time Adaptive Tuning of Offsets in Coordinated Traffic Signal Systems

A real-time adaptive control algorithm for tuning traffic signal offsets in a coordinated traffic signal system is presented. The algorithm described here is used in the Adaptive Control Software-Lite (ACS-Lite) adaptive control system. The algorithm uses a statistical average flow profile of traffic on the coordinated approaches to an intersection to assess when vehicles are arriving during the signal cycle. Alternative offset adjustments are evaluated by calculating how much of this flow profile is being captured by the green phase serving each coordinated approach. The algorithm considers the impact of the offset adjustment on traffic at the local intersection as well as on traffic at adjacent intersections that are also under ACS-Lite control. Simulation tests have quantitatively shown that this tuning approach can improve arterial progression performance relative to the quality of the initial baseline fixed offsets used in a traffic pattern. Several issues and areas for improvement of the algorithm are also identified and discussed.

Hybrid simulation and optimization-based design and operation of integrated photovoltaic generation, storage units, and grid

Abstract Unlike fossil-fueled generation, solar energy resources are geographically distributed and highly intermittent, which makes their direct control extremely difficult and requires storage units as an additional concern. The goal of this research is to design and develop a flexible tool, which will allow us to obtain (1) an optimal capacity of an integrated photovoltaic (PV) system and storage units and (2) an optimal operational decision policy considering the current and future market prices of the electricity. The proposed tool is based on hybrid (system dynamics model and agent-based model) simulation and meta-heuristic optimization. In particular, this tool has been developed for three different scenarios (involving different geographical scales), where PV-based solar generators, storage units (compressed-air-energy-storage (CAES) and super-capacitors), and grid are used in an integrated manner to supply energy demands. Required data has been gathered from various sources, including NASA and TEP (utility company), US Energy Information Administration, National Renewable Energy Laboratory, commercial PV panel manufacturers, and publicly available reports. The constructed tool has been demonstrated to (1) test impacts of several factors (e.g. demand growth, efficiencies in PV panel and CAES system) on the total cost of the integrated generation and storage system and an optimal mixture of PV generation and storage capacity, and to (2) demonstrate an optimal operational policy.

Decision Model for Priority Control of Traffic Signals

This paper presents a model of the core logic of a traffic signal controller. The model is formulated on the basis of the traditional North American ring, phase, and barrier construct and includes phase intervals such as minimum and maximum times, pedestrian service, alternative minimum times, and a priority service extension. The mathematical model is based on precedence graphs that are familiar to engineers involved with project management techniques such as Gantt charts, the critical path method, and the program evaluation and review technique. The model presents an analytical framework for the analysis of complex controller behaviors and is demonstrated for the case of multiple priority requests. An example shows that a first-come, first-served policy for serving priority requests can result in more delay than will a multiple-priority-request policy generated by the model developed in this paper. Additional controller behaviors, such as preemption, coordination, and offset transition, can be analyzed with this model.

Long Green Times and Cycles at Congested Traffic Signals

Field data were collected and simulation experiments based on traffic at an intersection in Virginia were conducted to test the hypothesis that headways increase with long green times and to test the common assumption that throughput increases with longer cycles. The results showed that headways increased with long green times as a result of departing turning vehicles and that this effect could cause a significant increase in overall average approach headways. The results also showed that maximum throughput, defined as the point where additional offered load could not be served, did not increase with longer cycles. With values derived from the field data, increasing the cycle did not increase throughput. In simulation, increasing the cycle caused a reduction in throughput as a result of increasing the effect of departing turning traffic on the average headway.

Effective Coordinated Optimization Model for Transit Priority Control Under Arterial Progression

With the goal of providing effective priority control for transit while minimizing adverse impacts on general traffic movements along the arterial, this paper presents a coordinated transit priority control optimization model with the following features: (a) the control unit is defined as the coordinated intersection group between two successive bus stops; (b) buses are detected after leaving the upstream stop before their arrival at the first intersection of a control unit; (c) the dynamic interactions of priority strategies between adjacent intersections within a control unit are modeled by using a bus delay model and an ineffective priority time model; and (d) a linear program model is developed to generate the optimal priority strategies to reduce bus travel time when priority is necessary and to ensure that every priority treatment implemented at each intersection is effective. Extensive experimental analyses, including time–space diagram-based deterministic analysis and simulation-based analysis, were performed, and results were compared with conventional transit signal priority strategy and no-priority scenarios. The proposed model presents promising outcomes in the design of transit priority signal control in terms of decreasing bus delay, improving bus schedule adherence, and minimizing the negative impacts on general traffic under different traffic demand patterns.

Simulation-Based Optimization of Maximum Green Setting Under Retrospective Approximation Framework

Most traffic signal systems work under highly dynamic traffic conditions, and they can be studied adequately only through simulation. As a result, how to optimize traffic signal system parameters in a stochastic framework has become increasingly important. Retrospective approximation (RA) represents the latest theoretical development in stochastic simulation. Under the RA framework, the solution to a simulation-based optimization problem can be approached with a sequence of approximate optimization problems. Each of these problems has a specific sample size and is solved to a specific error tolerance. This research applied the RA concept to the optimal design of the maximum green setting of the multidetector green extension system. It also designed a variant of the Markov monotonic search algorithm that can accommodate the requirements of the RA framework, namely, the inheritable Markov monotonic search algorithm, and implemented the RA-based optimization engine within VISSIM. The results show that the optimized maximum green can considerably increase composite performance (reducing delay and increasing safety) compared with traditional designs. The optimization methodology presented in this paper can easily be expanded to other signal parameters.

Hybrid simulation and optimization-based capacity planner for integrated photovoltaic generation with storage units

Unlike fossil-fueled generation, solar energy resources are geographically distributed and highly intermittent, which makes their direct control difficult and requires storage units. The goal of this research is to develop a flexible capacity planning tool, which will allow us to obtain a most economical mixture of capacities from solar generation as well as storage while meeting reliability requirements against fluctuating demand and weather conditions. The tool is based on hybrid (system dynamics and agent-based models) simulation and meta-heuristic optimization. In particular, the proposed tool has been developed for scenarios, where photovoltaic generators and storage units (compressed-air-energy-storage and super-capacitors) are used to supply energy demands in a region characterized by different house-holds considering different times and seasons. The constructed tool has been used to test impact of several factors (e.g. demand growth, efficiencies in PV panel and storage techniques) on the total cost of the system. Initial results look quite promising.

Performance Analysis of Coordinated Traffic Signals During Transition

Coordinated traffic signals can improve progression and delay times by switching timing plans as traffic conditions change. As cycle and split changes shift capacity where needed, signals shift offsets to maintain or to reestablish progressive flow. Signal offsets dictate, for each main-street green phase, where that green starts in each cycle with the intention of promoting nonstop green waves. To start it earlier or later at a given signal, the options are to shorten one or more intermediate phases or to lengthen one or more intermediate phases (or the main-street phase itself or both phases). Such phase time changes may create a temporary lack of capacity or impose extra delay time. Controllers from all vendors offer transition options to choose from that are differentiated by the amount of offset correction possible per cycle, whether they use a short or a long cycle, and by the distribution of time added to or subtracted from the set of phases. Common transition methods include dwell, maximum dwell, add, subtract, and shortway—all of which were recently incorporated into the CorSim actuated–controller logic. A transient profile analysis method is introduced and demonstrated with a model of a major arterial in Tucson, Arizona, and an additional hypothetical network model. The resulting transient profiles highlight the performance transition behavior that occurs during traffic signal plan transition and that contrasts with assertions previously reported in the literature.

Coordinated Optimization of Signal Timings for Intersection Approach with Presignals

Many congested intersections have heavy traffic volume on movements for which there is insufficient capacity because of geometric limitations. Installing presignals at midblock locations and reorganizing traffic upstream of the approach of an intersection combine to be a promising and cost-effective method for addressing these capacity limitations. A coordinated optimization model was developed for an isolated intersection approach with presignals to increase the protected left-turn phase capacity. The presignal model was based on two principles: (a) explicitly capture the interaction between the presignal and the main signal by modeling the queuing process and capacity constraints of temporal and spatial limitations of the intersection and (b) optimize the signal timings of both the presignal and the main signal as well as the offset between them to produce the best operational strategy for the approach. The minimum green time required and the delay-minimization problems are considered. Extensive experimental analysis has shown that the presignal model outperforms the conventional control method (without presignal). Sensitivity analysis of the signal timing method that will assist traffic engineers with selecting the appropriate length of the sorting area, phase sequence, and early starting time of presignals was conducted. The results from the study offer a basis for traffic practitioners, researchers, and authorities on which to design and utilize presignals in locations where there is a need to increase intersection capacity for congested movements.