Speed Reduction as a Surrogate for Accident Experience at Horizontal Curves on Rural Two-Lane Highways

2000 ◽  
Vol 1701 (1) ◽  
pp. 86-94 ◽  
Author(s):  
Ingrid B. Anderson ◽  
Raymond A. Krammes
Keyword(s):  
Linear Regression ◽  
Significant Relationship ◽  
Statistical Relationship ◽  
Speed Profile ◽  
Horizontal Curve ◽  
Accident Rate ◽  
Speed Reduction ◽  
Profile Model ◽  
Horizontal Curves ◽  
The Mean

A proposed speed profile model was used to estimate the reduction in 85th percentile speeds from the approach tangent to the midpoint of 1,126 horizontal curve sites on rural two-lane highways in three states. The sites were divided into eight speed-reduction intervals, the mean accident rate and mean speed reduction were computed for each category, and linear regression was performed to analyze the statistical relationship between mean accident rate and mean speed reduction. Similar analyses were performed with degree-of-curvature intervals to compare mean degree of curvature and mean speed reduction as predictors of accident experience. The results suggest that estimated speed reduction is a useful measure that helps explain how accident experience at horizontal curves on rural two-lane highways varies with degree of curvature. Horizontal curves that require speed reductions [generally, curves sharper than about 4°, a condition that corresponds with design speeds less than 100 km/h (60 mph) and estimated 85th percentile speeds less than drivers’ desired speeds on long tangents] have higher accident rates than curves that do not require speed reductions. When curve sites are grouped into speed-reduction intervals, there is a statistically significant relationship between the intervals’ mean accident rate and mean speed reduction. The mean accident rate increases approximately linearly with the mean speed reduction.

Preliminary Validation of a Speed-Profile Model for Design Consistency Evaluation

1996 ◽  
Vol 1523 (1) ◽  
pp. 11-21 ◽  
Author(s):  
Kent M. Collins ◽  
Raymond A. Krammes
Keyword(s):  
Speed Profile ◽  
Rural Highways ◽  
Speed Reduction ◽  
Profile Model ◽  
Horizontal Curves ◽  
Preliminary Validation ◽  
Design Consistency ◽  
Consistency Evaluation

The validity of a speed-profile model for design consistency evaluation was tested, including (a) the speed reduction estimation ability of the model and (b) assumptions about deceleration and acceleration characteristics approaching and departing horizontal curves. Detailed speed data were collected at a sample of 10 horizontal tangent-curve sections on two-lane rural highways in Texas. The results indicate that the model provides a reasonable, albeit simplified, representation of speed profiles on horizontal alignments consisting of long tangents and isolated curves. The model provides reasonable estimates of speed reductions from long approach tangents to curves but does not account for the effect of nearby intersections on speeds. The results also indicate that the assumed 0.85 m/sec2 value is reasonable for deceleration rates approaching curves that require speed reductions but may overestimate acceleration rates departing curves. The model's assumptions that deceleration occurs entirely on the approach tangent and that speeds are constant throughout a curve were not confirmed by observed speed behavior. The observations that deceleration continues after entering a curve and that speed adjustments occur throughout a curve are indicators of the difficulty drivers experience in judging appropriate speeds through curves.

Improved speed-profile model for two-lane rural highways

2003 ◽  
Vol 30 (6) ◽  
pp. 1055-1065 ◽  
Author(s):  
Said M Easa
Keyword(s):  
Highway Safety ◽  
Extended Model ◽  
Speed Profile ◽  
Rural Highways ◽  
Profile Model ◽  
Horizontal Curves ◽  
Sight Distance ◽  
Safety Design ◽  
Speed Change ◽  
Design Consistency

The speed-profile model has been suggested as a valuable tool for evaluating geometric design consistency for two-lane rural highways with isolated and combined horizontal and vertical alignments. The model determines the operating speeds on the speed-change (SC) segment, which is the distance between speed-limiting curves. The speed-limiting curves are the horizontal curves and the limited sight-distance crest vertical curves on horizontal tangents, where the sight distance required by the design guides is not satisfied. The model assumes that deceleration begins where required, which implies that the next curve is visible when deceleration starts. This paper presents an extension to the speed-profile model to incorporate the effect of sight obstruction on operating speeds and deceleration rates. The SC segment may include nonlimited sight–distance crest vertical and sag vertical curves. These curves may present sight obstruction. A procedure to determine whether the sight line is obstructed is developed. If it does, simple formulas are applied for revising the operating-speed profile. The extended model is suitable for inclusion in the design consistency module of the interactive highway safety design model.Key words: speed profile, model, two-lane highways, alignments, design consistency.

Speed-Profile Model for a Design-Consistency Evaluation Procedure in the United States

2000 ◽  
Vol 1701 (1) ◽  
pp. 76-85 ◽  
Author(s):  
Jeffery L. Ottesen ◽  
Raymond A. Krammes
Keyword(s):  
United States ◽  
The United States ◽  
Evaluation Procedure ◽  
Preliminary Evaluation ◽  
Speed Profile ◽  
Evaluation Tool ◽  
Rural Highways ◽  
Profile Model ◽  
Horizontal Curves ◽  
Design Consistency

A speed-profile model for estimating 85th percentile speeds along horizontal alignments of rural two-lane highways in the United States is documented. The model is an evaluation tool to check for speed consistency violations on alignments with design speeds less than 100 km/h (62.1 mph). The model was calibrated by using speed and geometry data collected for 138 horizontal curves and 78 approach tangents on 29 rural highways in 5 states. A preliminary evaluation suggests that the model provides reasonable estimates of the reductions in 85th percentile speeds from an approach tangent to a horizontal curve.

Evaluating Horizontal Alignment Design Consistency of Two-Lane Rural Highways: Development of New Procedure

2000 ◽  
Vol 1737 (1) ◽  
pp. 9-17 ◽  
Author(s):  
John McFadden ◽  
Lily Elefteriadou
Keyword(s):  
Primary Objective ◽  
Maximum Speed ◽  
Operating Speed ◽  
Speed Profile ◽  
Horizontal Curve ◽  
Rural Highways ◽  
Speed Reduction ◽  
Design Elements ◽  
The Difference ◽  
Design Consistency

Design consistency refers to the condition wherein the roadway geometry does not violate driver expectations. Operating-speed profile models are used to evaluate the consistency of a design by identifying locations with large speed variability between successive design elements. There is a direct correlation between safety and variability in speeds. Recent operating-speed models predict the 85th percentile speeds on horizontal curves and compare this value with the expected 85th percentile speed on the approach tangent. There is a direct correlation between speed variability between successive design elements and crash rates. Eighty-fifth percentile speeds, however, do not necessarily represent the speed reductions experienced by drivers. The primary objective of the research was to assess the efficacy of the use of 85th percentile speed by operating-speed profile models to evaluate the consistency of a design. Speed data were collected at 21 horizontal curve sites. These data were used to evaluate the implication of using 85th percentile speed for evaluating design consistency. A new parameter was investigated for analyzing design consistency: the 85th percentile maximum reduction in speed (85MSR). This parameter is calculated by using each driver’s speed profile from an approach tangent through a horizontal curve and determining the maximum speed reduction each driver experiences. These maximum speed reductions are sorted, and the 85th percentile value becomes the statistic of interest, or 85MSR. 85MSR was compared with the difference in 85th percentile speeds (85S), and it was found that 85MSR is significantly larger than 85S. The data showed that, on average, 85MSR is approximately two times larger than 85S. Models were developed that predict 85MSR as a function of geometric design elements, and these models could be used to complement existing operating-speed models.

RELATIONSHIP BETWEEN HORIZONTAL CURVES DESIGN AND ACCIDENT RATE

2016 ◽  
Vol 78 (5-2) ◽  
Author(s):  
Michal Radimsky ◽  
Radka Matuszkova ◽  
Ondrej Budik
Keyword(s):  
Strong Correlation ◽  
Deflection Angle ◽  
Horizontal Curve ◽  
Accident Rate ◽  
Fatal Accidents ◽  
The Road ◽  
Horizontal Curves ◽  
Lower Correlation

Horizontal curves are very problematic elements of the road alignment. The danger of these spots is confirmed by the analysis of accidents, which showed that while on the tangents (straight sections) is an accident resulting in injury or death one of every five, at intersections and curve segments it is one of every three. Share of fatal accidents in curve segments compared to the intersections or direct segments is then more than doubled. The research aims to find potential correlations between different accident’s characteristics and horizontal curves design, which could help predict dangerousness of horizontal elements. Strong correlation was proven between radius of horizontal curve and relative accidental rate. Lower correlation was found between traffic lanes width and relative accidental rate. From gathered data wasn’t proven relationship between relative accidental rate and deflection angle.

Comfort thresholds for horizontal curve design

2009 ◽  
Vol 36 (9) ◽  
pp. 1391-1402 ◽  
Author(s):  
Dalia Said ◽  
Yasser Hassan ◽  
A.O. Abd El Halim
Keyword(s):  
Research Work ◽  
Lateral Acceleration ◽  
Horizontal Curve ◽  
Driver Behaviour ◽  
Rural Roads ◽  
Speed Reduction ◽  
Horizontal Curves ◽  
Friction Factors ◽  
Side Friction Factor ◽  
Side Friction

A key to better geometric design of highways is designing horizontal curves conforming to driver behaviour. The values of side friction factors in the point mass formula, used for the design of the minimum radius of a horizontal curve, are based on the upper threshold of driver comfort. In the current guidelines, these driver comfort levels were established in research work carried out back in the 1930s. Recently, it was found that faster drivers tend to accept higher comfort thresholds to maintain their speed and minimize speed reduction between curve and tangent. An experiment was designed at Carleton University to collect newer data on driver behaviour including speed and lateral acceleration. The results confirmed the need to revise the values of side friction demand especially for sharp curves. In addition, a model was developed to determine the side friction factor to be used in design or in consistency evaluation of horizontal curves on rural roads and ramps.

scholarly journals Comparison of consistency assessment models for isolated horizontal curves in two-lane rural highways

DYNA ◽  
2015 ◽  
Vol 82 (194) ◽  
pp. 57-65
Author(s):  
Danilo Cárdenas-Aguilar ◽  
Tomás Echaveguren
Keyword(s):  
Spatial Variation ◽  
Operating Speed ◽  
Speed Profile ◽  
Horizontal Curve ◽  
Spatial Variance ◽  
Middle Point ◽  
Rural Roads ◽  
Rural Highways ◽  
Horizontal Curves ◽  
The Difference

This consistency assessment of highways’ geometrical design has the objective of providing safer roads. There are two types of models for consistency assessment: aggregated and disaggregated. The first one considers the difference between design and operating speed at the middle point of isolated horizontal curves. The second one considers the spatial variation of the operating speed profile along the horizontal curve. This paper compares the two types of consistency assessment models, using naturalistic speed and geometry data obtained in 34 horizontal curves of two-lane rural roads in Chile, using a 10 Hz GPS. Results obtained showed that in only 19 cases both methods are equivalent. This equivalence occurred only when operating speed profiles have the lowest spatial variance along the curves. If the operating speed profile has a high variance the consistency level obtained using both methods is different and the better option is combine it.

scholarly journals P170 The validity and utility of the SLE-key® rule-out serological test when applied in a selected cohort of patients with SLE and other connective tissue diseases

Rheumatology ◽  
2021 ◽  
Vol 60 (Supplement_1) ◽  
Author(s):  
Sheilla Achieng ◽  
John A Reynolds ◽  
Ian N Bruce ◽  
Marwan Bukhari
Keyword(s):  
Linear Regression ◽  
Connective Tissue ◽  
Connective Tissue Disease ◽  
Negative Correlation ◽  
Connective Tissue Diseases ◽  
Inflammatory Myositis ◽  
The Mean ◽  
Negative Rule ◽  
Spearman’S Correlation ◽  
Rule Out

Abstract Background/Aims  We aimed to establish the validity of the SLE-key® rule-out test and analyse its utility in distinguishing systemic lupus erythematosus (SLE) from other autoimmune rheumatic connective tissue diseases. Methods  We used data from the Lupus Extended Autoimmune Phenotype (LEAP) study, which included a representative cross-sectional sample of patients with a variety of rheumatic connective tissue diseases, including SLE, mixed connective tissue disease (MCTD), inflammatory myositis, systemic sclerosis, primary Sjögren’s syndrome and undifferentiated connective tissue disease (UCTD). The modified 1997 ACR criteria were used to classify patients with SLE. Banked serum samples were sent to Immune-Array’s CLIA- certified laboratory Veracis (Richmond, VA) for testing. Patients were assigned test scores between 0 and 1 where a score of 0 was considered a negative rule-out test (i.e. SLE cannot be excluded) whilst a score of 1 was assigned for a positive rule-out test (i.e. SLE excluded). Performance measures were used to assess the test’s validity and measures of association determined using linear regression and Spearman’s correlation. Results  Our study included a total of 155 patients of whom 66 had SLE. The mean age in the SLE group was 44.2 years (SD 13.04). 146 patients (94.1%) were female. 84 (54.2%) patients from the entire cohort had ACR SLE scores of ≤ 3 whilst 71 (45.8%) had ACR SLE scores ≥ 4. The mean ACR SLE total score for the SLE patients was 4.85 (SD 1.67), ranging from 2 to 8, with mean disease duration of 12.9 years. The Sensitivity of the SLE-Key® Rule-Out test in diagnosing SLE from other connective tissue diseases was 54.5%, specificity was 44.9%, PPV 42.4% and NPV 57.1 %. 45% of the SLE patients had a positive rule-out test. SLE could not be ruled out in 73% of the MCTD patients whilst 51% of the UCTD patients had a positive Rule-Out test and >85% of the inflammatory myositis patients had a negative rule-out test. ROC analysis generated an AUC of 0.525 illustrating weak class separation capacity. Linear regression established a negative correlation between the SLE-key Rule-Out score and ACR SLE total scores. Spearman’s correlation was run to determine the relationship between ACR SLE total scores and SLE-key rule-out score and showed very weak negative correlation (rs = -0.0815, n = 155, p = 0.313). Conclusion  Our findings demonstrate that when applied in clinical practice in a rheumatology CTD clinic setting, the SLE-key® rule-out test does not accurately distinguish SLE from other CTDs. The development of a robust test that could achieve this would be pivotal. It is however important to highlight that the test was designed to distinguish healthy subjects from SLE patients and not for the purpose of differentiating SLE from other connective tissue diseases. Disclosure  S. Achieng: None. J.A. Reynolds: None. I.N. Bruce: Other; I.N.B is a National Institute for Health Research (NIHR) Senior Investigator and is funded by the NIHR Manchester Biomedical Research Centre. M. Bukhari: None.

scholarly journals Correlation between fundus autofluorescence and visual function in patients with cone-rod dystrophy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Satoru Kanda ◽  
Takumi Hara ◽  
Ryosuke Fujino ◽  
Keiko Azuma ◽  
Hirotsugu Soga ◽  
...  
Keyword(s):  
Visual Field ◽  
Significant Relationship ◽  
Fundus Autofluorescence ◽  
Univariate Analysis ◽  
Retrospective Chart Review ◽  
Mean Deviation ◽  
Wide Field ◽  
The Mean ◽  
The Relationship ◽  
Field Imaging

AbstractThis study aimed to investigate the relationship between autofluorescence (AF) signal measured with ultra-wide field imaging and visual functions in patients with cone-rod dystrophy (CORD). A retrospective chart review was performed for CORD patients. We performed the visual field test and fundus autofluorescence (FAF) measurement and visualized retinal structures with optical coherence tomography (OCT) on the same day. Using binarised FAF images, we identified a low FAF area ratio (LFAR: low FAF/30°). Relationships between age and logMAR visual acuity (VA), central retinal thickness (CRT), central choroidal thickness (CCT), mean deviation (MD) value, and LFAR were investigated. Thirty-seven eyes of 21 CORD patients (8 men and 13 women) were enrolled. The mean patient age was 49.8 years. LogMAR VA and MD were 0.52 ± 0.47 and − 17.91 ± 10.59 dB, respectively. There was a significant relationship between logMAR VA and MD (p = 0.001). LogMAR VA significantly correlated with CRT (p = 0.006) but not with other parameters. Conversely, univariate analysis suggested a significant relationship between MD and LFAR (p = 0.001). In the multivariate analysis, LFAR was significantly associated with MD (p = 0.002). In conclusion, it is useful to measure the low FAF area in patients with CORD. The AF measurement reflects the visual field deterioration but not VA in CORD.

scholarly journals The Relationship between Inflammation Markers (CRP, IL-6, sCD40L) and Colorectal Cancer Stage, Grade, Size and Location

Diagnostics ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 1382
Author(s):  
Olga Martyna Koper-Lenkiewicz ◽  
Violetta Dymicka-Piekarska ◽  
Anna Justyna Milewska ◽  
Justyna Zińczuk ◽  
Joanna Kamińska
Keyword(s):  
Colorectal Cancer ◽  
Linear Regression ◽  
Tumor Size ◽  
Distal Colon ◽  
Proximal Colon ◽  
Model Parameters ◽  
Grade Group ◽  
Who Grade ◽  
The Mean ◽  
Mean Concentration

The aim of the study was the evaluation whether in primary colorectal cancer (CRC) patients (n = 55): age, sex, TNM classification results, WHO grade, tumor location (proximal colon, distal colon, rectum), tumor size, platelet count (PLT), mean platelet volume (MPV), mean platelet component (MCP), levels of carcinoembryonic antigen (CEA), cancer antigen (CA 19-9), as well as soluble lectin adhesion molecules (L-, E-, and P-selectins) may influence circulating inflammatory biomarkers: IL-6, CRP, and sCD40L. We found that CRP concentration evaluation in routine clinical practice may have an advantage as a prognostic biomarker in CRC patients, as this protein the most comprehensively reflects clinicopathological features of the tumor. Univariate linear regression analysis revealed that in CRC patients: (1) with an increase in PLT by 10 × 103/μL, the mean concentration of CRP increases by 3.4%; (2) with an increase in CA 19-9 of 1 U/mL, the mean concentration of CRP increases by 0.7%; (3) with the WHO 2 grade, the mean CRP concentration increases 3.631 times relative to the WHO 1 grade group; (4) with the WHO 3 grade, the mean CRP concentration increases by 4.916 times relative to the WHO 1 grade group; (5) with metastases (T1-4N+M+) the mean CRP concentration increases 4.183 times compared to non-metastatic patients (T1-4N0M0); (6) with a tumor located in the proximal colon, the mean concentration of CRP increases 2.175 times compared to a tumor located in the distal colon; (7) in patients with tumor size > 3 cm, the CRP concentration is about 2 times higher than in patients with tumor size ≤ 3 cm. In the multivariate linear regression model, the variables that influence the mean CRP value in CRC patients included: WHO grade and tumor localization. R2 for the created model equals 0.50, which indicates that this model explains 50% of the variance in the dependent variable. In CRC subjects: (1) with the WHO 2 grade, the mean CRP concentration rises 3.924 times relative to the WHO 1 grade; (2) with the WHO 3 grade, the mean CRP concentration increases 4.721 times in relation to the WHO 1 grade; (3) with a tumor located in the rectum, the mean CRP concentration rises 2.139 times compared to a tumor located in the distal colon; (4) with a tumor located in the proximal colon, the mean concentration of CRP increases 1.998 times compared to the tumor located in the distal colon; if other model parameters are fixed.

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