PERFORMANCE MEASURES FOR TRAFFIC SIGNAL SYSTEMS:AN OUTCOME-ORIENTED APPROACH This monograph is a synthesis of research carried out on traffic signal performance measures based on highresolution controller event data, assembled into a methodology for performance evaluation of traffic signal systems. High-resolution data consist of a log of discrete events such as changes in detector and signal phase states. A discussion is provided on the collection and management of the signal event data and on the necessary infrastructure to collect these data. A portfolio of performance measures is then presented, focusing on several different topics under the umbrella of traffic signal systems operation. System maintenance and asset management is one focus. Another focus is signal operations, considered from the perspectives of vehicle capacity allocation and vehicle progression. Performance measures are also presented for nonvehicle modes, including pedestrians, and modes that require signal preemption and priority features. Finally, the use of travel time data is demonstrated for evaluating system operations and assessing the impact of signal retiming activities.
Overview of Study LocationThe location used to demonstrate the use of the Abstract Graphical Performance Measures for Practitioners to Triage Split Failure Trouble CallsDetector occupancy is commonly used to measure traffic signal performance. Despite improvements in controller computational power, there have been relatively few innovations in occupancy-based performance measures or integration with other data. This paper introduces and demonstrates the use of graphical performance measures based on detector occupancy ratios to verify potential split failures and other signal timing shortcomings reported to practitioners by the public. The proposed performance measures combine detector occupancy during the green phase, detector occupancy during the first five seconds of the red phase, and phase termination cause (gap out or force off). These are summarized by time of day to indicate whether the phase is undersaturated, nearly saturated, or oversaturated. These graphical performance measures and related quantitative summaries provide a first-level screening and triaging tool for practitioners to assess user concerns regarding whether sufficient green times are being provided to avoid split failures. They can also provide outcome-based feedback to staff after making split adjustments to determine whether operation improved or worsened. The paper concludes by demonstrating how the information was used to make an operational decision to re-allocate green time that reduced the number of oversaturated cycles on minor movements from 304 to 222 during a Thursday 0900-1500 timing plan and from 240 to 180 during a Friday 0900-1500 timing plan.
Overview of Study LocationThe location used to demonstrate the use of the Abstract Graphical Performance Measures for Practitioners to Triage Split Failure Trouble CallsDetector occupancy is commonly used to measure traffic signal performance. Despite improvements in controller computational power, there have been relatively few innovations in occupancy-based performance measures or integration with other data. This paper introduces and demonstrates the use of graphical performance measures based on detector occupancy ratios to verify potential split failures and other signal timing shortcomings reported to practitioners by the public. The proposed performance measures combine detector occupancy during the green phase, detector occupancy during the first five seconds of the red phase, and phase termination cause (gap out or force off). These are summarized by time of day to indicate whether the phase is undersaturated, nearly saturated, or oversaturated. These graphical performance measures and related quantitative summaries provide a first-level screening and triaging tool for practitioners to assess user concerns regarding whether sufficient green times are being provided to avoid split failures. They can also provide outcome-based feedback to staff after making split adjustments to determine whether operation improved or worsened. The paper concludes by demonstrating how the information was used to make an operational decision to re-allocate green time that reduced the number of oversaturated cycles on minor movements from 304 to 222 during a Thursday 0900-1500 timing plan and from 240 to 180 during a Friday 0900-1500 timing plan.
Intersection crashes are a safety concern for many transportation agencies, and those related to red-light-running (RLR) vehicles are of particular interest. Many camera-based RLR detection systems are controversial with the public, and there is relatively little published literature on the methodologies. This study proposes a methodology that combines high resolution signal controller data with conventional stop bar loop detection to identify vehicles that enter the intersection after the start of red, when many of the most serious RLR crashes occur. The methodology is validated using on-site video collection at several locations, and the algorithm was refined to reduce the incidence of false RLR indications. One case study demonstrates that an increase in side street green split from 20% to 24% of cycle length is associated with a 34% reduction in daily RLR counts, and a reduction in the likelihood of RLR by a factor of 1.7 -a substantial safety improvement for minimal cost. Additionally, law enforcement and transportation agencies can utilize this technique to more efficiently manage and deploy safety resources, especially in cases where detailed crash histories are unknown or too infrequent.
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