Use of Decision Assistance Curves in Advanced Warrant Analysis for Indirect Left-Turn Intersections

This paper develops decision assistance curves (DAC) to compare delay-based performance measures for three indirect left turn (ILT) intersections, namely median U-turn (MUT), continuous flow intersection (CFI), and jughandle, relative to a conventional signalized intersection. The DACs consist of two graphical tools: (i) DAC-classifier and (ii) two sets of DAC-contours. DAC-classifier plots are used to select the intersection type that produces the minimum system average delay for a specified main and cross-street volume configuration. DAC-contour plots are used to estimate the system average delay difference between a chosen ILT and a conventional signalized intersection as well as to estimate the increase in average delay as compared to a conventional signalized intersection for the most negatively impacted movement. These tools can be used by planners, engineers, or other decision makers to visually identify the intersection type that provides the least average system delay under given volume conditions as well as estimated tradeoffs for choosing a specific intersection type. It was found that the conventional signalized intersection, with protected left turns, was never optimal under studied scenarios. This implies that, for all the studied conditions, there exists at least one ILT or permitted left turn alternative that produces lower delay than the conventional signalized intersection

International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways.

Primary biliary cirrhosis (PBC) is a classical autoimmune liver disease for which effective immunomodulatory therapy is lacking. Here we perform meta-analyses of discovery data sets from genome-wide association studies of European subjects (n=2,764 cases and 10,475 controls) followed by validation genotyping in an independent cohort (n=3,716 cases and 4,261 controls). We discover and validate six previously unknown risk loci for PBC (Pcombined<5 × 10(-8)) and used pathway analysis to identify JAK-STAT/IL12/IL27 signalling and cytokine-cytokine pathways, for which relevant therapies exist

A new decision making approach for indirect left turn treatments by utilizing decision assistance curves

This study developed decision assistance curves (DAC) for unconventional intersections, including median U-turns (MUT), continuous flow intersections (CFI), and jughandle intersections, based on their operational performance relative to a conventional intersection. An economic analysis was performed to compute the net present value (NPV) of benefits and the benefit to cost ratio (B/C) with the development of a spreadsheet tool. The DAC classified the region of optimal performance of isolated unconventional intersections. For 5% left turn traffic conditions, MUT was warranted for all volume criteria. For 10% and 15% left turn traffic conditions, jughandle was warranted for the major street approach traffic volumes greater than or equal to 2200 vph, and greater than 1800 vph, respectively. However, the warranty decreased with the increase of minor streets for all of the conditions except at balanced and nearly balanced conditions under 10% left turn traffic. For 10% and 15% left turn traffic conditions with an unbalanced flow, CFI was warranted for major street approach traffic volumes greater than or equal to 2200 vph, and greater than 1800 vph, respectively. The warranty expanded with the increase of minor street approach traffic volumes. The standard signalized intersection with left turn permitted was warranted for minor street approach traffic volumes less than 200 vph and the major street approach traffic volumes of 700 vph to 1350 vph. The high presence of trucks favored the use of CFI. Additionally, a case study performed on a 24-hour rural pattern volume indicated the highest NPV of benefits and the highest B/C related to new MUT construction. Though the MUT-retrofit had the highest NPV, since the construction cost of MUT-retrofit was high, a jughandle-retrofit was found to have the highest B/C. In this manner, the developed method provided an integrated decision support system utilizing both operational performance and economic aspects as an improved method over the current practice. Some possible extensions of study were also recommended as further studies

LCCA-based Decision Assistance Tool for Indirect Left Turn (ILT) Intersections using Excel-driven Highway Capacity Software

This paper explains the principles involved in the development of an MS Excel - based decision assistance tool for indirect left (ILT) intersections. this tool, termed Signalized Intersection Life Cycle Cost Analysis (SILCC), analyzes three types of ILT intersections; (i) MUt, (ii) CFl, and (iii) jughandles. SO far, no tools have been developed that are capable of analyzing ILT intersections while incorporating cost and benefit aspects. In contrast, SILCC is designed to incorporate cost and benefit aspects in the evaluation of ILT intersections. It is interfaced with the Highway Capacity Software (HCS) and hence can perform macro-level operational analysis. It considers delay, fuel consumption, and emissions as operational performance measures. It is capable of performing life cycle cost analysis (LCCA) and providing net present value (NPV) and benefit-to-cost ratio (B/C) as surrogate measures of performance. Planners can use NPV or B/C for decision support while deciding among several alternatives for economic and efficiently operating ILT intersections. Additionally, SILCC feature the flexibility to alter input values so that it can be used for multiple conditions and criteria. A case study of rual traffic volume conditions indication that a MUT intersection had the highest NPV of benefits for both new construction and retrofits. However, because the construction cost for MUT retrofits was high for the particular condition, an MUT intersection had the highest B/C for new construction an a jughandle had the highest B/C for retrofits.This paper was peer-reviewed by TRB and presented at the Annual Meeting of the Transportation Research Board, Washington, D.C. and can be cited as Gyawali, Sunil, Anuj Sharma, and Aemal J. Khattak. "LCCA-based Decision Assistance Tool for Indirect Left Turn (ILT) Intersections using Excel-driven Highway Capacity Software." Transportation Research Board 94th Annual Meeting, no. 15-4912. 2015. Posted with permission.</p

Effect of Freeway Level of Service and Driver Education on Truck Driver Stress - Phase 1

This research primarily deals with truck driver stress and its nature, stressors, and their mutual relationship. During the study, the different demands of driving that are related to roads, vehicle, traffic conditions, driver predisposition to stress and the surrounding environmental conditions were explored. The two distinct clusters of ―Low Stress level‖ and ―High Stress level‖ were identified in the stress distribution. The binary logistic regression method was used to relate these two conditions of stress with wide range of stressors. The result found that truck driver training was a statistically significant factor in predicting the low stress level. Other statistically significant factors increasing the likelihood of high stress levels were right turning maneuvers, passive overtaking and the traffic control related factors, such as the presence of a STOP sign as a control of the intersection. The drivers own personal dispositions to the stress were highly correlated with stress levels. The driving duration, the vehicle parameters like lateral velocity and co-axial acceleration were also significant variables in explaining stress levels. The study clearly identified that the provision of driving training could lower the driving stress level. Additionally, the significance of surrogate factors for level of service like passive overtaking, controls, acceleration and turn maneuvers also implied that the improvement of Level of Services (LOSs) of Freeway segments and intersections would play an important role in reducing driver stress

Use of Decision Assistance Curves in Advanced Warrant Analysis for Indirect Left-Turn Intersections

This paper develops decision assistance curves (DAC) to compare delay-based performance measures for three indirect left turn (ILT) intersections, namely median U-turn (MUT), continuous flow intersection (CFI), and jughandle, relative to a conventional signalized intersection. The DACs consist of two graphical tools: (i) DAC-classifier and (ii) two sets of DAC-contours. DAC-classifier plots are used to select the intersection type that produces the minimum system average delay for a specified main and cross-street volume configuration. DAC-contour plots are used to estimate the system average delay difference between a chosen ILT and a conventional signalized intersection as well as to estimate the increase in average delay as compared to a conventional signalized intersection for the most negatively impacted movement. These tools can be used by planners, engineers, or other decision makers to visually identify the intersection type that provides the least average system delay under given volume conditions as well as estimated tradeoffs for choosing a specific intersection type. It was found that the conventional signalized intersection, with protected left turns, was never optimal under studied scenarios. This implies that, for all the studied conditions, there exists at least one ILT or permitted left turn alternative that produces lower delay than the conventional signalized intersection.This is a manuscript of an article from Transportation Research Record 2486 (2015): 54, doi: 10.3141/2486-07. Posted with permission.</p

Structure-Property-Performance Relationships of Cuprous Oxide Nanostructures for Dielectric Mie Resonance-Enhanced Photocatalysis

Nanostructured metal oxides, such as Cu2O, CeO2, {\alpha}-Fe2O3, and TiO2 can efficiently mediate photocatalysis for solar-to-chemical energy conversion and pollution remediation. In this contribution, we report a novel approach, dielectric Mie resonance-enhanced photocatalysis, to enhance the catalytic activity of metal oxide photocatalysts. Specifically, we demonstrate that Cu2O nanostructures exhibiting dielectric Mie resonances can exhibit up to an order of magnitude higher photocatalytic rate as compared to Cu2O nanostructures not exhibiting dielectric Mie resonances. Our finite-difference time-domain (FDTD) simulation and experimental results predict a volcano-type relationship between the photocatalytic rate and the size of Cu2O nanospheres and nanocubes. Using transient absorption measurements, we reveal that a coherent electronic process associated with dielectric Mie resonance-mediated charge carrier generation is dominant in Cu2O nanostructures that exhibit higher photocatalytic rates. Although we experimentally demonstrate dielectric Mie resonance-enhanced photocatalysis using Cu2O particles here, based on our FDTD simulations, we anticipate the same can be achieved with other metal oxide photocatalysts, including CeO2, {\alpha}-Fe2O3, and TiO2