Aleksandar Stevanovic

Optimizing Traffic Control to Reduce Fuel Consumption and Vehicular Emissions: Integrated Approach with VISSIM, CMEM, and VISGAOST

One way to reduce excessive fuel consumption and vehicular emissions on urban streets is to optimize signal timings. Historically, signal timing optimization tools were used to reduce traffic delay and stops. The concept of optimizing signal timings to reduce fuel consumption and emissions was addressed decades ago with tools that are now considered outdated. This study advocates a fresh approach to integrating existing state-of-the-art tools for reassessing and ultimately minimizing fuel consumption and emissions. VISSIM, CMEM, and VISGAOST were linked to optimize signal timings and minimize fuel consumption and CO2 emissions. As a case study, a 14-intersection network in Park City, Utah, was used. Signal timings were optimized for seven optimization objective functions to find the lowest fuel consumption and CO2 emissions. Findings show that a formula commonly used to estimate fuel consumption in traffic simulation tools inadequately estimates fuel consumption and cannot be used as a reliable objective function in signal timing optimizations. Some of the performance measures used as objective functions in the optimization process were proved to be ineffective. When CMEM-estimated fuel consumption is used as an objective function, estimated fuel savings are around 1.5%, a statistically significant decrease. Further research is needed to find an effective way to minimize fuel consumption and emissions by using the proposed approach.

Adaptive Traffic Control Systems: Domestic and Foreign State of Practice

Adaptive Traffic Control Systems (ATCSs), also known as real-time traffic control systems, adjust, in real time, signal timings based on the current traffic conditions, demand, and system capacity. Although there are at least 25 ATCS deployments in the United States, these systems may not be well understood by many traffic signal practitioners in the country. Their operational benefits are demonstrated, but there are still some reservations among the people in the traffic signal community. These systems are considered expensive and complex and they require high maintenance of detectors and communications. The study methodology included three sequential efforts. The first focused on the selection of ATCSs, which are typically deployed in the United States (and worldwide) and identification of ATCS agencies. The next effort undertaken was a literature review that gathered and reported information about ATCS operations and deployments from previous studies. Finally, two electronic surveys were conducted: a shorter e-mail survey for ATCS vendors and a longer website-based survey for ATCS users. Responses were obtained from 34 of 42 agencies in North America, an 81% response rate. Also, 11 responses from agencies in other countries were obtained. Municipal and county traffic operations agencies were the major contributors among the 45 agencies that responded to the survey.

VisSim-Based Genetic Algorithm Optimization of Signal Timings

Genetic algorithm optimizations of traffic signal timings have been shown to be effective, continually outperforming traditional optimization tools such as Synchro and TRANSYT-7F. However, their application has been limited to scholarly research and evaluations. Only one tool has matured to a commercial deployment: direct CorSim optimization, a feature of TRANSYT-7F. A genetic algorithm formulation, VisSim-based genetic algorithm optimization of signal timings (VISGAOST), is presented; it builds on the best of the recorded methods by extending their capabilities. It optimizes four basic signal timing parameters with VisSim microsimulation as an evaluation environment. The program brings new optimization features not available in the direct CorSim optimization, such as the optimization of phasing sequences, multiple coordinated systems and uncoordinated intersections, fully actuated isolated intersections, and multiple time periods. The formulation has two features that enhance and reduce computational time: optimization resumption and parallel computing. The program has been tested on two VisSim networks: a hypothetical grid network and a real-world arterial of actuated–coordinated intersections in Park City, Utah. The results show that timing plans optimized by the genetic algorithm outperformed the best Synchro plans in both cases, reducing delay and stops by at least 5%.

Comparative Evaluation of Adaptive Traffic Control System Assessments Through Field and Microsimulation

Usually, benefits from deploying an adaptive traffic control system are measured by comparing data collected in the field before the system is installed with those collected after the system is fully operational. Such an approach is costly because it requires installation of a system before potential benefits can be observed. Nowadays to investigate effectiveness of many alternatives that were traditionally investigated in field, microsimulation is used. However, how much can one rely on results from microsimulation? There has not been a single study in which benefits of adaptive traffic control systems measured in the field are compared with those obtained through microsimulation. This study presents such a research effort. The authors compared performance measures from a field evaluation of Sydney Coordinated Adaptive Traffic System in Park City, Utah, to their counterparts from microsimulation. They collected a significant amount of data to assess system performance in the field and to help build a microsimulation model. A 14-intersection model of the Park City network was developed, calibrated, and validated on the basis of multiple data sources. The results show that a validated microsimulation model can accurately reflect field conditions although such an effort can be very challenging.

Microscopic Modeling of Traffic Signal Operations: Comparative Evaluation of Hardware-in-the-Loop and Software-in-the-Loop Simulations

Currently, there are three different methods to model traffic signal operations in microscopic simulation models: the simulation models controller emulator, hardware-in-the-loop simulation, and software-in-the-loop simulation. Although all three methods can be based on the same industry standard code, their different implementations suggest potential operational differences. This study investigates operational differences of the three methods by examining how each method operates in five experimental scenarios. Each of the scenarios differs from the others in network size (one intersection to five intersections) and operational strategies (pretimed, actuated, actuated–coordinated, and two different signal transition logics). Ten 75-min simulation runs with 100-ms simulation resolution were executed for each experiment with the three signal control modeling alternatives. The results showed that for basic signal control operations, such as pretimed and isolated actuated operations, the three alternatives provided similar results as indicated by the average green time allocation and different operational measures of effectiveness. When advanced controller operations were used, such as signal transition logic, the simulation model emulator showed significantly different behavior than that observed in hardware-in-the-loop and software-in-the-loop simulations.

Comparison of Before–After Versus Off–On Adaptive Traffic Control Evaluations: Park City, Utah, Case Study

An adaptive traffic control system, the Sydney Coordinated Adaptive Traffic System (SCATS), was installed in Park City, Utah, to improve traffic performance at its network of signalized intersections. A field evaluation of the previous time-of-day actuated–coordinated signal timings was conducted before SCATS installation to compare the two systems. However, the post-SCATS field evaluation could not occur until two additional signals were installed and several other changes were made to the network. Two years after the original pre-SCATS field evaluation, the network was reevaluated with an off–on technique analogous to a before–after study. The signal timings and parameters in the off condition forced SCATS to use time-of-day actuated–coordinated control, similar to the before study but with timings readjusted for the additional signals and changed traffic conditions. The performance gains with SCATS on were measurably greater than those with SCATS off for travel time and number of stops and greater overall for stopped delay. These data provided the transportation agency with results anticipated by its traffic engineers. However, the original field evaluation data from 2 years earlier provided a less distinct conclusion. A methodology is presented to determine the relevance of an off–on study in place of a before–after study. The results show that “before” and “off ” data sets behave consistently 62.5% of the time. This value provides a basis of support for using off data, which better represent before signal timings on an after network. It also quantifies sensitivity to changes in the network, which are substantial in this case.

Development and Evaluation of Algorithm for Resolution of Conflicting Transit Signal Priority Requests

The goal of this study was the development and evaluation of an algorithm for resolving conflicting requests for transit signal priority (TSP). This algorithm was designed to work with actual traffic controllers without the need for new hardware or software installations. The algorithm was tested in VISSIM microsimulation and ASC/3 software-in-the-loop controllers on an intersection that will be upgraded to serve two conflicting bus rapid transit (BRT) lines. The ASC/3 logic processor was used to control built-in TSPs in the case of conflicting requests and to develop custom-TSP strategies that would not rely on built-in TSP. Custom TSP provides a much higher level of TSP for transit vehicles than built-in TSP, and it creates opportunities for more adaptable TSP control. The results showed that the widely used first-come, first-served policy for resolution of conflicting TSP requests was not the best solution. Such a policy could perform worse than a policy that provided no priority. For the analyzed intersection, the first-come, first-served option even increased BRT delays by 13% more than did the no-TSP option. The presented algorithm can help resolve the problem of the conflicting TSP requests. The algorithm worked best when combined with several TSP strategies. For the custom-TSP strategies, the application of the algorithm reduced BRT delays by more than 30%, with minimal impact on vehicular traffic. The algorithm shows promising results, and with small upgrades, it can be applied to any type of TSP.

Evaluation of Transit Signal Priority Options for Future Bus Rapid Transit Line in West Valley City, Utah

This paper presents an analysis of different transit signal priorities (TSPs) for a future bus rapid transit (BRT) corridor in West Valley City, Utah. The goal was to find the optimal TSP strategy for estimated and planned traffic and transit operations. The study used VISSIM microsimulation software in combination with ASC/3 software-in-the-loop simulation. Four models were used in the analysis: no TSP, TSP, TSP with phase rotation, and custom TSP. The results showed that TSP with phase rotation and custom TSP could both be considered for implementation. TSP with phase rotation would provide significant benefits for BRT, with minimum impacts on vehicular traffic. Custom TSP would provide major benefits for BRT in travel times, delays, and stops. However, this strategy has more impact on vehicular traffic. Custom TSP is an advanced strategy that still needs examination and improvement. The study provides a set of instructions on how the described strategies can be implemented in field traffic controllers.

Predictive Priority for Light Rail Transit: University Light Rail Line in Salt Lake County, Utah

The goal of this paper is to assess the operational implementation of strategies for predictive light rail priority through microsimulation. A 2-mi corridor in Salt Lake County, Utah, where the University Line of light rail line operates, was studied. The study used VISSIM microsimulation models to analyze light rail operations and the effects that light rail priority has on transit and vehicular traffic. Results showed that although the existing priority strategies had no effects on vehicular traffic along the corridor, they reduced train travel times by 20% to 30%. Left turns along the main corridor were slightly affected by the priority. Although the priority strategies could have minor to major effects on vehicular traffic along side streets through increased delays, they reduced train delays by 2.5 min along the corridor. Enabling priority at the 700 E intersection (where the priority was currently not active) would help reduce delays for trains by an additional 10%, with a small increase in vehicle delays. However, the coordinated north–south through movements would experience minimum impacts. Three recommendations emerged from the study: enable priority at 700 E to improve transit without major effects on vehicular traffic; reset priority parameters at intersections adjacent to light rail stations so that the priority call encompasses station dwell times; and consider removing the queue jump strategies, so as to reduce delays for the corridor through movements and help preserve coordination patterns.

Cross-Evaluation of Signal Timing Optimized by Various Traffic Simulation and Signal Optimization Tools

The most popular tools for traffic simulation and signal timing optimization are macroscopic and deterministic in structure. Microscopic tools are also available and are gaining popularity because they simulate the stochastic nature of traffic flow. Performance of the optimized signal timing developed by any tool depends on the fidelity of the traffic models embedded in it. This study evaluates the performance of signal timing developed by the most popular signal-timing optimization tools. It examines signal timing from each tool in various macroscopic and microscopic simulation environments and includes statistical tests to find which tool produces signal timing of the highest quality. Each of the four tools selected (two macroscopic and two microscopic) can both optimize and evaluate signal timing. A real-world arterial with 12 signalized intersections serves as the test bed. To eliminate skewness and bias in the results, all experiments were performed under the same geometric and traffic characteristics in each tool. Saturation flow rates from each calibrated model were assessed to ensure that all the tools processed traffic demand consistently. The results indicate that, overall, VISSIM-based genetic algorithm optimization of signal timing and the Synchro programs produce signal timing of the highest quality and provide extremely similar performance.