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The speeds of traffic and freeway throughputs at the merge, diverge, and weaving areas are reduced significantly due to vehicle lane changes and increased traffic volumes. This study proposes a solution, referred to as split design (i.e. split merge, diverge, and weaving). The key concept is to make geometric changes to the existing ramp designs to create two merge or diverge points, such that potential conflicts of the mainline and ramp traffic can be distributed apart spatially. This potentially decreases unnecessary interactions between the mainline and ramp vehicles. This study also uses microscopic traffic simulation to assess operational efficiency of the proposed alternative geometric design; and to develop managerial insights for state DOTs to better design, enhance, and manage their freeway systems in the future. We find that, overall, the split design can potentially increase throughput by 6% to 9% and reduce delay by 35% to 80% across different scenarios. [ABSTRACT FROM AUTHOR]

High-occupancy vehicle (HOV) lanes have been widely deployed in freeways with high demands and traffic congestion. This paper discusses how an alternative design with the HOV lane on the right side of the freeway could effectively mitigate congestion problems at freeway merge, diverge, and weaving areas as compared with the benchmark design of HOV lanes on the left. Simulation experiments show that the alternative design will result in a reduction in average delay by 5% to 10% and increase in throughput by 10% to 30% for all traffic. While the alternative design generally improves performance for the general purpose (GP) lanes, it will degrade HOV lane performance. Nonetheless, HOV lane vehicles enjoy a higher level of service than GP lane vehicles under the same background settings. The study suggests that it is practical to implement the alternative design on freeways, especially for areas with low HOV traffic volumes. [ABSTRACT FROM AUTHOR]

Simultaneous Perturbation Stochastic Approximation (SPSA) has gained favor as an efficient optimization method for calibrating computationally intensive, “black box” traffic flow simulations. Few recent studies have investigated the efficiency of SPSA for traffic signal timing optimization. It is important for this to be investigated, because significant room for improvement exists in the area of signal optimization. Some signal timing methods and products perform optimization very quickly, but deliver mediocre solutions. Other methods and products deliver high-quality solutions, but at a very slow rate. When using commercialized desktop signal timing products, engineers are often forced to choose between speed and solution quality. Real-time adaptive control products, which must optimize timings within seconds on a cycle-by-cycle basis, have limited time to reach a high-quality solution. The existing literature indicates that SPSA provides the potential for upgrading both off-line and on-line solutions alike, by delivering high-quality solutions within seconds. This article describes an extensive set of optimization tests involving SPSA and genetic algorithms (GAs). The final results suggest that GA was slightly more efficient than SPSA. Moreover, the results suggest today's signal timing solutions could be improved significantly by incorporating GA, SPSA, and “playbooks” of preoptimized starting points. However, it may take another 5-10 years before our computers become fast enough to simultaneously optimize coordination settings (i.e., cycle length, phasing sequence, and offsets) at numerous intersections, using the most powerful heuristic methods, at speeds that are compatible with real-time adaptive solutions. [ABSTRACT FROM AUTHOR]

Urban congestion is being increased by a rapid growth in travel demand and a limited ability to expand physical infrastructure. If transportation agencies could accurately quantify the impacts of various congestion causes, they would be able to prioritize their strategies more efficiently. The Federal Highway Administration developed a well-known congestion causal pie chart in 2004, but this development process did not have extensive access to field data. Recent advancements in both traffic measurement technologies and data-driven analysis are making it possible to quantify congestion impacts more accurately. However, an assessment of congestion causes on signalized arterials presents many challenges, due to complexity of the required data and the interaction of traffic demand and control. The objective of this study is to create congestion pie charts which demonstrate the proportion of average experienced delay components on arterial corridors. A multivariate linear regression model of observed delay is used to demonstrate contributing factors to arterial street congestion. The methodology is explained using a section of Broward Boulevard in Fort Lauderdale, FL. The findings from the model demonstrate that a considerable part of arterial congestion can be attributed to travel demands and intersection signals. [ABSTRACT FROM AUTHOR]

Adaptive traffic-signal control (ATSC) is a traffic management strategy in which traffic-signal timings change, or adapt, based on observed traffic demand. Although ATSC can improve mobility, it also has the potential to reduce crashes because mainline stops should be reduced. This paper aims to evaluate the safety effectiveness of ATSC using the empirical Bayes method. This analysis examines 47 urban or suburban intersections where ATSC was deployed in Virginia using 235 site-years of before data and 66 site-years of after data. Installing ATSC was found to produce a crash modification factor (CMF) for total intersection crashes of 0.83 with a standard error of 0.05. This CMF was statistically significant at a 95 percent confidence level. Fatal and injury crashes did not change by a statistically significant amount, indicating that the primary safety benefit of ATSC was reduction in property damage crashes. Analyses of ATSC safety effects by crash type, by traffic volume level, and by operational improvement magnitude were also performed. All crash types were found to be reduced, but safety benefits varied from corridor to corridor and by volume levels. It was concluded that ATSC installation can potentially reduce total crashes at highway intersections and that public agencies should consider ATSC’s safety and mobility benefits when justifying ATSC projects. [ABSTRACT FROM AUTHOR]

The article discusses the emerging methods of signal timing optimization. It notes the benefits of using Automated Signal Performance Metrics (SPM) in terms of simplified troubleshooting, and assessment of historical operation of traffic signals. It cites that faster computing speeds using High Capacity Manual (HCM) based analysis and transparent heuristic methods can help traffic engineers improve signal timing performance, calibration, and data collection.