Predicted 95th Percentile Speeds on Curved Alignments Approaching a Stop

2005 ◽  
Vol 1912 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Karen S. Schurr ◽  
Benjamin W. Spargo ◽  
Ryan R. Huff ◽  
Geza Pesti
Keyword(s):  
Prediction Models ◽  
Surface Condition ◽  
Vehicle Speed ◽  
Heavy Vehicles ◽  
Passenger Cars ◽  
Rural Highways ◽  
Horizontal Curves ◽  
Significant Difference ◽  
Study Sites ◽  
Horizontal Curvature

The objective of this project was to develop a model that describes design speed profiles of vehicles traversing horizontal curves on approaches to stop-controlled intersections on two-lane two-way rural highways. Once speed prediction models were determined, a procedure for the design of horizontal curves that would accommodate vehicles transitioning from high speeds to a stop was developed. Speed profiles were developed with the use of data from 15 study sites in Nebraska. The multiplicative model was used to provide prediction equations for speed profiles. Separate profiles were created for passenger cars and heavy vehicles because speeds were significantly different. The heavy vehicle data were separated further for alignments with and without horizontal curvature. It was concluded that posted speed, median type, presence of rumble bars, roadway surface condition, and degree of rutting did not significantly affect the vehicle speed profiles at these sites at a 95% confidence level. During the comparison of speeds, it was found that the intercepts of the regression lines for approaches with and without horizontal curves were significantly different in the case of heavy vehicles. The speed of heavy vehicles on tangent approaches was generally about 8 mph higher than on sites that exhibited horizontal curvature. The rate of deceleration remained almost the same on all approaches to intersections, except near the stop. For passenger cars, there was no statistically significant difference between curved and tangent alignments. A guidebook for the geometric design of intersection realignment Methods A through D, referred to in the 2004 Green Book, is also included in the project's report.

Speed Prediction Models for Trucks on Horizontal Curves of Two-Lane Rural Roads

2018 ◽  
Vol 2672 (17) ◽  
pp. 72-82 ◽  
Author(s):  
David Llopis-Castelló ◽  
Brayan González-Hernández ◽  
Ana María Pérez-Zuriaga ◽  
Alfredo García
Keyword(s):  
Road Safety ◽  
Prediction Models ◽  
Gps Tracking ◽  
Heavy Vehicle ◽  
Heavy Vehicles ◽  
Passenger Cars ◽  
Rural Roads ◽  
Horizontal Curves ◽  
Speed Prediction ◽  
Design Consistency

Road safety is closely related to geometric design consistency, which is usually assessed by examining operating speed. Most consistency models only consider passenger car speeds, even though the interaction between passenger cars and heavy vehicles plays a pivotal role in road safety. This is due to the fact that there are too few models to estimate heavy vehicle speeds. This study aims to develop speed prediction models for heavy vehicles on horizontal curves of two-lane rural roads. To do this, continuous speed profiles were collected by using Global Positioning System (GPS) tracking devices on 11 road sections. Truck speeds were analyzed on 105 horizontal curves. The results showed that the radius of the horizontal curve and the grade at the point of curvature have a significant influence on heavy vehicle speeds. In this regard, vertical alignment only has a significant effect on truck speeds along upgrades. In addition, different trends were identified for loaded and unloaded trucks, so different speed models were calibrated for each of them. As a result, heavy vehicle speeds were adversely affected by grades greater than 3%. This phenomenon was larger for loaded trucks than for unloaded ones. Finally, the calibrated 85th and 15th percentile speed models were compared with those developed previously. As a conclusion, the use of the proposed models in this study was recommended on Spanish two-lane rural roads due mainly to the different characteristics of heavy vehicles around the world.

scholarly journals OPERATING SPEED PREDICTION MODEL AS A TOOL FOR CONSISTENCY BASED GEOMETRIC DESIGN OF FOUR-LANE DIVIDED HIGHWAYS

Transport ◽  
2019 ◽  
Vol 34 (4) ◽  
pp. 425-436 ◽  
Author(s):  
Gourab Sil ◽  
Avijit Maji ◽  
Suresh Nama ◽  
Akhilesh Kumar Maurya
Keyword(s):  
Prediction Model ◽  
Lateral Position ◽  
Geometric Design ◽  
Operating Speed ◽  
Vehicle Speed ◽  
Horizontal Curve ◽  
Passenger Cars ◽  
Horizontal Curves ◽  
Speed Prediction ◽  
Design Consistency

Researchers have studied two-lane rural highways to predict the operating speed on horizontal curves and correlated it with safety. However, the driving characteristics of four-lane-divided highways are different. Weak lane discipline is observed in these facilities, which influences vehicle speed in adjacent lane or space. So, irrespective of its lane or lateral position, vehicles in four-lane divided highways are considered free flowing only when it maintains the minimum threshold headway from any lead vehicle. Examination of two conditions is proposed to ensure the free flow. Vehicles meeting both conditions, when tracked from the preceding tangent section till the centre of the horizontal curve, are considered as free flowing. The speed data of such free flowing passenger cars at the centre of eighteen horizontal curves on four-lane divided highways is analysed to develop a linear operating speed prediction model. The developed model depends on curve radius and preceding tangent length. The operating speed of passenger car in four-lane divided highways is influenced by horizontal curve of radius 360 m or less. Further, longer tangent would yield higher operating speed at the centre of the curve. Finally, two nomograms are suggested for conventional design, consistency based design and geometric design consistency evaluation of four-lane divided horizontal curves.

scholarly journals Evaluation of Minimum Preparation Sampling Strategies for Sugarcane Quality Prediction by vis-NIR Spectroscopy

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2195
Author(s):  
Lucas de Paula Corrêdo ◽  
Leonardo Felipe Maldaner ◽  
Helizani Couto Bazame ◽  
José Paulo Molin
Keyword(s):  
Sample Preparation ◽  
Prediction Models ◽  
Spectral Response ◽  
Nir Spectroscopy ◽  
Quality Parameters ◽  
Partial Least Square ◽  
Least Square ◽  
Sample Type ◽  
Sampling Strategies ◽  
Significant Difference

Proximal sensing for assessing sugarcane quality information during harvest can be affected by various factors, including the type of sample preparation. The objective of this study was to determine the best sugarcane sample type and analyze the spectral response for the prediction of quality parameters of sugarcane from visible and near-infrared (vis-NIR) spectroscopy. The sampling and spectral data acquisition were performed during the analysis of samples by conventional methods in a sugar mill laboratory. Samples of billets were collected and four modes of scanning and sample preparation were evaluated: outer-surface (‘skin’) (SS), cross-sectional scanning (CSS), defibrated cane (DF), and raw juice (RJ) to analyze the parameters soluble solids content (Brix), saccharose (Pol), fibre, pol of cane and total recoverable sugars (TRS). Predictive models based on Partial Least Square Regression (PLSR) were built with the vis-NIR spectral measurements. There was no significant difference (p-value > 0.05) between the accuracy SS and CSS samples compared to DF and RJ samples for all prediction models. However, DF samples presented the best predictive performance values for the main sugarcane quality parameters, and required only minimal sample preparation. The results contribute to advancing the development of on-board quality monitoring in sugarcane, indicating better sampling strategies.

scholarly journals Evaluating the Impacts of Speed Limit Increases on Rural Two-Lane Highways Using Quantile Regression

2021 ◽  
pp. 036119812110197
Author(s):  
Md Shakir Mahmud ◽  
Nischal Gupta ◽  
Babak Safaei ◽  
Hisham Jashami ◽  
Timothy J. Gates ◽  
...  
Keyword(s):  
Quantile Regression ◽  
Spillover Effects ◽  
Speed Limit ◽  
Passenger Cars ◽  
Cross Sectional ◽  
Speed Limits ◽  
Site Specific ◽  
Rural Highways ◽  
Speed Selection ◽  
Numerous Site

Understanding speed selection behavior of drivers following speed limit increases is critically important. To date, the literature has largely focused on freeways and the effects of speed limit changes on two-lane highways remains under researched. Prior research has generally focused on changes to mean speeds, although the speeds of both the highest and lowest drivers are also of great interest. This study investigates trends in free-flow travel speeds following 2017 legislation that increased the posted speed limit from 55 to 65 mph on 943 mi of rural highways in Michigan. Speed data were collected for over 46,000 drivers at 67 increase segments where speed limit increased and 28 control segments where speed limits remained unchanged, before and during each of the two successive years following the speed limit increases. Site-specific traffic, geometric, and cross-sectional information was also collected. Impacts of the speed limit increases on the 15th, 50th, and 85th percentile speeds were evaluated using quantile regression. Separate analyses were conducted for passenger cars and heavy vehicles. Locations where the speed limits were raised experienced increases in travel speeds ranging from 2.8 to 4.8 mph. The control sites experienced marginal changes in speeds, which suggests that any spillover effects of the higher speed limits have been limited. Significant differences were observed across the quantiles with respect to the effects of the speed limit increases, as well as numerous site-specific variables of interest. The results provide important insights about the nature of driver speed selection and the impacts of speed limit increases.

scholarly journals A Novel Approach for Operating Speed Continuous Predication Based on Alignment Space Comprehensive Index

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Ying Yan ◽  
Gengping Li ◽  
Jinjun Tang ◽  
Zhongyin Guo
Keyword(s):  
Field Experiments ◽  
Prediction Models ◽  
Three Dimensional ◽  
Safety Evaluation ◽  
Driving Safety ◽  
Operating Speed ◽  
Passenger Cars ◽  
Comprehensive Index ◽  
Novel Approach ◽  
Lane Width

Operating speed is a critical indicator for road alignment consistency design and safety evaluation. Although extensive studies have been conducted on operating speed prediction, few models can finish practical continuous prediction at each point along alignment on multilane highways. This study proposes a novel method to estimate the operating speed for multilane highways in China from the aspect of the three-dimensional alignment combination. Operating speed data collected in field experiments on 304 different alignment combination sections are detected by means of Global Positioning System. First, the alignment comprehensive index (ACI) is designed and introduced to describe the function accounting for alignment continuity and driving safety. The variables used in ACI include horizontal curve radius, change rate of curvature, deflection angle of curve, grade, and lane width. Second, the influence range of front and rear alignment on speed is determined on the basis of drivers’ fixation range and dynamical properties of vehicles. Furthermore, a prediction model based on exponential relationships between road alignment and speeds is designed to predict the speed of passenger cars and trucks. Finally, three common criteria are utilized to evaluate the effectiveness of the prediction models. The results indicate that the prediction models outperform the other two operating speed models for their higher prediction accuracy.

scholarly journals Analysis of Nonsevere Crashes on Two- and Four-Lane Urban and Rural Highways: Effects of Wet Pavement Surface Condition

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Aschalew Kassu ◽  
Michael Anderson
Keyword(s):  
Negative Binomial ◽  
Surface Condition ◽  
Negative Binomial Regression ◽  
Segment Length ◽  
Mean Values ◽  
Rural Highways ◽  
Explanatory Variables ◽  
Crash Data ◽  
Pavement Surface ◽  
Binomial Regression

This study examines the effects of wet pavement surface conditions on the likelihood of occurrences of nonsevere crashes in two- and four-lane urban and rural highways in Alabama. Initially, sixteen major highways traversing across the geographic locations of the state were identified. Among these highways, the homogenous routes with equal mean values, variances, and similar distributions of the crash data were identified and combined to form crash datasets occurring on dry and wet pavements separately. The analysis began with thirteen explanatory variables covering engineering, environmental, and traffic conditions. The principal terms were statistically identified and used in a mathematical crash frequency models developed using Poisson and negative binomial regression models. The results show that the key factors influencing nonsevere crashes on wet pavement surfaces are mainly segment length, traffic volume, and posted speed limits.

scholarly journals Clinical, virological and epidemiological characterization of dengue outbreak in Myanmar, 2015

2017 ◽  
Vol 145 (9) ◽  
pp. 1886-1897 ◽  
Author(s):  
A. K. KYAW ◽  
M. M. NGWE TUN ◽  
M. L. MOI ◽  
T. NABESHIMA ◽  
K. T. SOE ◽  
...  
Keyword(s):  
Primary Infection ◽  
Phylogenetic Analyses ◽  
Molecular Techniques ◽  
Severe Dengue ◽  
Envelope Gene ◽  
Mosquito Vector ◽  
Serum Samples ◽  
Denv Serotypes ◽  
Significant Difference ◽  
Study Sites

SUMMARYHospital-based surveillance was conducted at two widely separated regions in Myanmar during the 2015 dengue epidemic. Acute phase serum samples were collected from 332 clinically diagnosed dengue patients during the peak season of dengue cases. Viremia levels were measured by quantitative real-time PCR and plaque assays using FcγRIIA-expressing and non-FcγRIIA-expressing BHK cells to specifically determine the infectious virus particles. By serology and molecular techniques, 280/332 (84·3%) were confirmed as dengue patients. All four serotypes of dengue virus (DENV) were isolated from among 104 laboratory-confirmed patients including two cases infected with two DENV serotypes. High percentage of primary infection was noted among the severe dengue patients. Patients with primary infection or DENV IgM negative demonstrated significantly higher viral loads but there was no significant difference among the severity groups. Viremia levels among dengue patients were notably high for a long period which was assumed to support the spread of the virus by the mosquito vector during epidemic. Phylogenetic analyses of the envelope gene of the epidemic strains revealed close similarity with the strains previously isolated in Myanmar and neighboring countries. DENV-1 dominated the epidemic in 2015 and the serotype (except DENV-3) and genotype distributions were similar in both study sites.

scholarly journals Comparative Analysis of Effects of Heavy Vehicles on Roads in Southern and Northern Nigeria

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
C. C. Osadebe ◽  
H. A. Quadri
Keyword(s):  
Northern Region ◽  
Design Guidelines ◽  
Traffic Volume ◽  
Southern Region ◽  
Heavy Vehicle ◽  
Heavy Vehicles ◽  
Passenger Cars ◽  
The Road ◽  
Equivalency Factors ◽  
On The Road

The prevalence of flexible pavement deterioration in the country has been adduced largely by highway researchers to trucks or heavy vehicles carrying much in excess of permitted legal limits. This study investigated levels of deterioration of Abuja-Kaduna-Kano road (Northern region) and Port Harcourt-Enugu road (Southern region) caused by heavy vehicles through a 14 day traffic counts conducted at 5 strategic points each in the Northern and Southern regions. Traffic data generated were analyzed with AASHTO Design Guidelines (1993) to evaluate Equivalent Single Axle Loads (ESALs) and Vehicle Damage effects on the road. The Traffic Volume, Average Daily Traffic (ADT), and Heavy Vehicle per day (HV/day) were estimated to be 2,063,977; 147,427; and 12,246 respectively in the Northern region, while in the Southern region they were estimated to be 750,381; 53,670; and 20,951 respectively. Motorcycles, Passenger cars, Mini-buses/Pick-ups, and Heavy vehicles constitute 18.7%, 49.7%, 23.3% and 8.31% of the total traffic volume respectively in the Northern region while in the South they constitute 4.6%, 30.1%, 26.2% and 39.1% respectively. ESALs were estimated according to AASHTO Design Guidelines in the Northern and Southern regions as 547,730 and 836,208 respectively. An average Load Equivalency Factors (LEFs) of 3.43 and 3.02 were estimated for each heavy vehicle plying the Northern and Southern roads respectively and this could explain some failures (alligator cracks, potholes, depressions, linear or longitudinal cracks along the centre line amongst others) inherent on the road.

scholarly journals The effect of invasive species Lantana Camara L. on soil nutrients at Ol-Donyo Sabuk National Park, Kenya

2020 ◽  
Vol 1 (1) ◽  
pp. 25-32
Author(s):  
M N Wekhanya ◽  
P. K. Mbugua ◽  
J. K. Mworia
Keyword(s):  
Soil Nutrients ◽  
National Park ◽  
Soil Samples ◽  
Lantana Camara ◽  
Preventive Strategy ◽  
Native Plant ◽  
Organic C ◽  
Anova Test ◽  
Significant Difference ◽  
Study Sites

The aim of this study was to establish whether the invasive plant Lantana camara L. alters the soil chemical properties at Ol-Donyo Sabuk National Park. The key objective was to evaluate the soil nutrient composition in areas invaded by L. camara and how these differ from areas without L. camara. Five study sites were selected by purposeful sampling, out of the existing 10 blocks. Soil samples were collected randomly from L. camara invaded areas and similarly from adjacent areas free from L. camara. The soil samples were subjected to determination of the following nutrients and parameters: pH, potassium (K), calcium (Ca) magnesium (Mg), total nitrogen (N), phosphorus (P), total organic carbon (TOC), manganese (Mn), copper (Cu), iron (Fe), zinc (Zn) and sodium (Na). The data obtained was analysed using Two-way ANOVA test to determine difference in nutrients composition in L. camara invaded and non-invaded areas. Three-way ANOVA test was used to gauge the interactions between wet and dry season, invaded and non-invaded areas and study sites. A post-ANOVA test, Tukey’s Honest Significant Difference was done to separate the means. The results from the study indicated L. camara invaded areas had a significant difference in pH, P, N, Mn, Fe and total organic C compared to the patches that had native plants and not invaded by L. camara. High pH also makes P to be more available to plants that is why P was high in the L. camara invaded areas. This study revealed that L. camara remarkably changes the concentration and balance of soil nutrients resulting to a change in chemistry of soil nutrients. This is in a bid to suit its survival to the detriment of the native plant species. This study is hence vital for designing an effective eradication and preventive strategy of L. camara in Ol-Donyo Sabuk National Park and other protected ecological habitats in Kenya.

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