Standard Deviation Of Speed Research Articles

Modeling decentralized mandatory lane change for connected and autonomous vehicles: An analytical method

Mandatory lane change (MLC) is the core of lane-specific motion planning for connected and autonomous vehicles (CAVs). To model the MLC for CAVs, this paper presented a decentralized cooperative MLC (DC-MLC) framework. The framework aimed to achieve a safe MLC maneuver with multiple-CAV cooperation, including the lane change times, positions, and trajectories for the CAVs, while minimizing the impacts of the MLC maneuver on overall traffic. This problem was rigorously formulated and solved by an analytical method that significantly decreases computational time and renders the methodology suitable for practical implementations. To evaluate the performance of the proposed DC-MLC framework, we built a CAV testing environment by referring to the next generation simulation program (NGSIM) US 101 dataset. A series of numerical experiments were conducted under the built CAV testing environment. The results showed that the proposed DC-MLC framework could achieve safe, traffic-efficient, and comfortable MLC maneuvers. Moreover, the trajectories generated by the proposed DC-MLC framework outperformed those of human drivers in terms of speed standard deviation, maximum acceleration/deceleration, and maximum acceleration jerk.

Safety Impact of Connected Vehicles on Driver Behavior in Rural Work Zones under Foggy Weather Conditions

Work zone safety is one of the paramount goals of the safety community. Safety in WZs is a particular concern under foggy conditions as they represent an exogenous factor contributing to high variability in driver behavior. In line with the Connected Vehicle (CV) Pilot Deployment Program on Interstate-80 (I-80) in Wyoming, this study investigates the safety benefits of CV Work Zone Warning (WZW) applications on driver behavior during foggy weather conditions. A work zone (WZ) was simulated using VISSIM in four sequential areas, including the advance warning, transition, activity, and termination area. The effect of drivers’ increased situational awareness under the effect of WZW was calibrated in VISSIM based on the results of a high-fidelity driving simulator experiment. Various Surrogate Measures of Safety (SMoS), including Time-To-Collision (TTC), Time Exposed Time-to-collision (TET), Time-Integrated Time-to-collision (TIT), and Modified Deceleration Rate to Avoid Crash (MDRAC), were employed to quantify the safety performance of CVs under varying CV Market Penetration Rates (MPRs). According to the results of TTC and MDRAC, it was found that an increase in CV-MPR enhances the safety performance of the WZ area. Findings showed that, under foggy weather conditions, the advance warning area had the highest TIT and TET values. Furthermore, it was revealed that an increase in MPR of up to 60% on I-80 would reduce mean speeds and the standard deviation of speed at each of the WZ areas, leading to more speed harmonization and minimizing the crash risk in WZs.

Investigating “Texting while Driving” Behavior at Different Roadway Configurations Using a Driving Simulator Setting

This study investigates the safety impact of distracted driving (texting while driving) for different roadway configurations (intersections, segments, freeways, and roundabouts; urban, suburban, and rural sections; and straight and curved road cross-sections) and various lighting conditions (nighttime and daytime) using a driving simulator. The study took place at Western Kentucky University in Bowling Green, KY. Fifty participants (30 young adults, 18 to 25 years old; 20 middle-/old age adults, 26 to 70 years old) drove the simulator, for approximately 10 min each. Video recordings and behavior observations (e.g., recording single longest off-road eye glance while texting and driving) were further documented. While texting and driving at the roundabout, significant differences were found between the mean lane positions of the young and middle-/old age groups. Additionally, a slightly higher speed variance for middle-/old age drivers existed while texting and driving on freeways during the daytime compared with their younger counterparts. Comparisons with the safe stopping sight distance revealed potential safety risks for all texting while driving situations for both age groups compared with nontexting situations. On average, participants with a higher distracted-driving crash-risk expended 0.676 more seconds glancing off-road than lower distracted-driving crash-risk participants. Furthermore, on average, lower-risk participants had a 3.99 mph speed standard deviation compared with the 5.34 mph speed standard deviation of higher-risk participants. It should be noted that the top five higher-risk drivers were from the middle/older population, whereas the top five lower-risk drivers were from the younger population.

Comparision of speed and endurance between short and long distance runner of Kashmir Division

The main idea and aim of this comparative study is to assess and compare the speed and endurance among long distance and short distance athletes of Kashmir division. For this comparative study (60) subjects were selected, 30 athletes were long distance runner and 30 were short distance runner all were selected from Kashmir division city which were selected randomly from various disticte of Kashmir division for the study. The the statistical criteria used for selecting the subjects was through simple random sampling. All the athletes from both the categories were of the age ranged between 25-35 years. To compare and analyze the speed and endurance among long distance and short distance athletes of Kashmir division. Of the athletes of both the groups two different tests or equipments were used. For speed A digital Stop watch for recording the distance covered per unit time and for endurance Heart Rate count. Vo2max. Bench for Cardiovascular was used. The comparison analysis of data was done by using statistical technique ‘t’- test for finding the significance difference speed and endurance of long and short distance runner of Kashmir division the level of significance was set at 0.05 levels (p<0.05). The calculated means and standard deviation of speed and endurance of long distance distance athletes of Kashmir division selected variables of industrial inhabitants viz. speed( 12.82 ± 1.07 endurance VO2 Max is ( 58.24 ± 7.25 ) and the findings means and standard deviation of selected variables of short distance atheletes of Kashmir division in speed (13.87± 2.93), endurance (448 ± 66.39), Hence the Non-industrial inhabitants were found with sound cardio respiratory capacities as compared to Industrial Inhabitants the difference might be due to the pollution of industries which directly or indirectly affects the population (people) residing in industrial area.

Influence of prompt timing and messages of an audio navigation system on driver behavior on an urban expressway with five exits

An audio navigation system is a very useful tool for driving path guidance with less distraction. However, the influence of the audio navigation system on driver behavior, especially in complicated road environments, is still not entirely clear. This study aims to investigate navigation prompt timing (NPT), navigation prompt message (NPM), and their combination in an audio navigation system on driving behavior on an urban expressway with five exits. Driving simulator technology was used to reproduce the experimental environment and obtain driver behavior data. Four indicators-speed, standard deviation of speed, absolute values of acceleration, and depth of accelerator-were selected to examine the main and interactive effects of NPT, NPM, and their combination based on repeated measures analysis of variance. The results show that the driver’s psychological state and operation of the vehicle on the urban expressway were affected by the prompt timing and messages of the audio navigation system. An interaction effect existed between prompt timing and prompt messages of the system, and this effect adjusted the effect on the driver’s psychological state and vehicle operation caused by these two important factors. This study contributes to our understanding of the influence of audio navigation systems on driver behavior in complex road environments and thus lays a foundation for developing standard audio navigation broadcast guidelines to improve drivers’ acceptance of navigation systems, reduce drivers’ cognitive workload, and improve the level of vehicle operation safety.

A Simulation-Based Comprehensive Analysis for Traffic Efficiency and Spatial Distribution of Risks in Short Weaving Area of Municipal Interchange

The weaving area is an important junction that affects the efficiency and traffic safety at the municipal interchanges. To explore the factors affecting traffic efficiency and the spatial distribution characteristics of traffic risks in the weaving areas of municipal interchanges, this study employed a microscopic traffic software of Vissim to construct a simulation model of weaving areas and evaluate the impact of road and traffic design parameters in the short weaving on traffic efficiency and risks, which includes ramp delay, mainline through lane (TL) traffic delay, average ramp speed, TL average speed, and collision rate. Through variance analysis via a large number of simulation scenarios, the weaving length is identified as the most important factor affecting traffic efficiency and risks in the short weaving area. Subsequently, three different types of weaving lengths with 350 m, 450 m, and 550 m were set to conduct the sensitivity analysis based on four performance indexes of mean acceleration and deceleration, acceleration range, deceleration range, and speed standard deviation as the representative variables of spatial risk distribution. The simulation results illustrate that a shorter weaving length has a significant influence on risk distribution, especially the highest risk probability at the positions after three-quarters of the inner and outer lanes in the short weaving area at the municipal interchange. Finally, this study verified the traffic risk reduction method of having traffic safety facilities and traffic organization at the complex interchange with double-entry and single-exit weaving areas in the city of Guangzhou, China. The research proposed a method to analyze the influence of the design parameters in the short weaving area on traffic efficiency and safety and provided a reference for the risk spatial distribution analysis and improvement in the short weaving area.

Interactive Influence Analysis of Tunnel Lateral Clearance on Driving Behavior Using Expressway Field Data

Changes in lateral clearance are prone to drastic changes in the driving environment at the entrance and exit of the tunnel, which can cause a driver to become psychologically stressed and deviate from the center of a lane, thus creating a greater security risk. However, most of the existing regulations and studies only focus on the horizontal and vertical alignment of the tunnel entrances and exits, and there are few studies on the influence of lateral clearance on driving behavior. This study hired 15 random subjects to conduct real vehicle tests in eight tunnels on expressways with 3 design speeds by using a CAN-OBD analyzer and steering wheel angle meter. First, in five lateral clearance variation schemes, different speed characteristic indicators and steering wheel angles were selected as the indicators of driving behavior. Second, the interactive influence of the design speed, lateral clearance, operating speed, steering wheel angle, and other indicators were analyzed. Finally, paired t-test analysis and Wilcoxon and Friedman nonparametric tests were used to compare the differences in various indicators among different lateral clearance schemes. The results showed that when the left lateral clearance is 1.5 meters, the operating speed is increased by 3.9%, while the standard deviation of speed is small, and the driving performance is higher. When the right lateral clearance is 1.75 and 2.00 meters, the operating speed is not much different. However, the latter’s speed standard deviation is smaller. By contrast, when the right lateral clearance is up to 2.25 m, the operating speed increases by 3.7%. However, the speed standard deviation also increases. Different lateral clearances have little effect on the steering wheel angle. The operating speed on the right side is higher and more stable when the design speed is 100 km/h. This study provides scientific suggestions for the setting of the lateral clearance of the tunnels.

Risk Distribution Characteristics and Optimization of Short Weaving Area for Complex Municipal Interchanges

This paper is focused on analyzing the risk distribution characteristics in short weaving areas of urban interchanges. The study was carried out on merge-diverge weaving areas with different lengths of 350 m, 450 m, and 550 m. To evaluate and identify the risk, the average speed, speed standard deviation, acceleration range, and average absolute value of acceleration were selected as indicators. Vissim simulation was applied to collect the identification indicator value of 21 typical lane sections. The results show that the risk is concentrated at the 3/4 section and exit section of the outer lane. The vehicle-operating status of the inner and middle lanes is almost unaffected. The operating speed of the outer lane is approximately 4/5 of the same position in the inner lane at 3/4 of the length of the weaving segment, while the speed standard deviation is approximately 2 times greater, and the acceleration range is approximately 2–3 times greater. Moreover, the acceleration of the average absolute value is also approximately 2–3 times greater. To balance the risk distribution, an optimization method is proposed based on the result analysis. Compared with the original design, the results show that a reasonable method of traffic organization for the complex weaving area can effectively improve the risk distribution in the weaving area and reduce the high peak of risk concentration. These results provide a basis for the optimization method and traffic organization of short weaving areas of municipal interchanges.

Impact of connected vehicle environment on driving performance: A case of an extra‐long tunnel scenario

In view of the benefits and a promising prospect of the emerging connected vehicles (CV), more and more vehicles will be equipped with the in-vehicle human-machine interface (HMI). This study aims to assess the comprehensive impacts of HMIs on individual driving performance, traffic safety, and eco-driving behaviour based on a driving simulator. In order to explore how a driver responds to warnings when approaching a tunnel, this study divided the experimental road into five zones according to warning positions. A comparative analysis was conducted to examine the changes in driving comfort, speeding behaviour, the standard deviation of speed, time headway (THW), fuel consumption, and emissions. Results showed that the HMI could be beneficial to speed adjustment before entering a tunnel. Meanwhile, HMI may affect the THW of vehicles. Drivers were usually more cautious when the HMI was on. However, no significant effects of the HMI for driving comfort and eco-driving behaviour can be observed. It is expected that more efficient technology and different warning strategies can be developed to enhance eco-safe driving for different zones because they have different effects. The findings of this study are also helpful for active safety management and for evaluating the effectiveness of CV systems.

Developing safety performance functions for freeways at different aggregation levels using multi-state microscopic traffic detector data

Safety Performance Functions (SPFs) have been widely used by researchers and practitioners to conduct roadway safety evaluation. Traditional SPFs are usually developed by using annual average daily traffic (AADT) along with geometric characteristics. However, the high level of aggregation may lead to a failure to capture the temporal variation in traffic characteristics (e.g., traffic volume and speed) and crash frequencies. In this study, SPFs at different aggregation levels were developed based on microscopic traffic detector data from California, Florida, and Virginia. More specifically, five aggregation levels were considered: (1) annual average weekday hourly traffic (AAWDHT), (2) annual average weekend hourly traffic (AAWEHT), (3) annual average weekday peak/off-peak traffic (AAWDPT), (4) annual average day of the week traffic (AADOWT), and (5) annual average daily traffic (AADT). Model estimation results showed that the segment length and volume, as exposure variables, are significant across all the aggregation levels. Average speed is significant with a negative coefficient, and the standard deviation of speed was found to be positively associated with the crash frequency. It is noteworthy that the operation of the high occupancy vehicle (HOV) lanes was found to have a positive effect on crash frequency across all the aggregation levels. The model results also showed that the AAWDPT and AADOWT models consistently performed better (the improvements range from 3.14%–16.20%) than the AADT-based SPF, which implies that the differences between the day of the week and peak/off-peak periods should be considered in the development of crash prediction models. The model transferability results indicated that the SPFs between Florida and Virginia are transferrable, while the models between California and the other two states are not transferrable.

Experimental research on the effectiveness of navigation prompt messages based on a driving simulator: a case study

In China, F-type-5 m intersections are not uncommon. One approach of these intersections usually includes a driveway closely followed by an intersecting street, and the driveway and the intersecting street are parallel and approximately 5 m apart. Nowadays, drivers often rely on the navigation systems for directions. However, it is found that the navigation systems sometimes mislead or confuse drivers to make wrong turns or miss their turns at such F-type-5 m intersections. This study proposed to employ driving simulation to identify the appropriate prompt message delivered at the right prompt timing to help drivers navigate through such F-type-5 m intersections. First, a within-subjects two-factor experiment was designed. One factor was the Prompt Timing Mode (PTM), representing a set of three sequential messages broadcast by the navigation system at varying distances to the intended intersection; the other factor was the Prompt Message Type (PMT), representing various sets of three sequential messages broadcast by the navigation system. Three Prompt Timing Modes were used: PTM1 = {− 400 m, -200 m, − 30 m}, PTM2 = {− 300 m, − 150 m, − 30 m}, and PTM3 = {− 200 m, − 100 m, − 30 m}. Three Prompt Message Types were defined: PMT-A = {Turn right at the traffic light XXm ahead; Turn right at the traffic light XXm ahead; Turn right}, PMT-B = {Turn right at the traffic light XXm ahead, enter YY street; Turn right at the traffic light XXm ahead, enter YY street; Turn right}, PMT-C = {Turn right at the traffic light XXm ahead, enter YY street, and please use the second right turn lane; Turn right at the traffic light XXm ahead, enter YY street, and please use the second right turn lane; Turn right}. The combinations of the two factors generated nine experimental intersections which were randomly assigned to three experimental routes. Then, a total of 37 drivers were recruited, and participated in the driving simulation experiment from which vehicle operation data were collected under different prompt timing modes and message types. Next, the repeated Analysis of Variance (rANOVA) was performed to examine the effects of different prompt timing modes and prompt message types on vehicle operation indicators, such as Driving Time, Standard Deviation of Speed, Absolute Value of Acceleration, and Standard Deviation of Acceleration. Finally, the grey near-optimal method was adopted to evaluate the effectiveness of three prompt message types under each prompt timing mode. The rANOVA results showed the vehicle operation in the F-type-5 m intersection was affected by prompt timing modes and prompt message types; the evaluation results indicated that PMT-C made drivers perform better in PTM1 and PTM3, while PMT-B made drivers perform better inPTM2. However, the effectiveness of PMT-A was the lowest in each prompt timing mode. The research results provide valuable guidance to design the human machine interface of navigation systems, which can help drivers safely navigate through F-type-5 m intersections. This research also has laid solid foundations for establishing navigation messaging design guidelines.

Scatterometer Sea Surface Wind Product Validation for HY-2C

The Chinese HY-2C satellite was launched on Sep. 21, 2020, carrying the new Ku-band scatterometer (HSCAT-C). Different from the other currently operating scatterometers, the HSCAT-C is in a nonsun-synchronous orbit and as such it will be useful for the cross-calibration of sea surface wind products from current space-borne scatterometers and radiometers. In this article, the HSCAT-C wind products are validated by comparing to collocated winds from buoys, European Centre for Medium-Range Weather Forecasts model, and several other scatterometers. The results show that the quality of HSCAT-C winds is very good: in comparison with buoy winds, the wind speed standard deviation and direction root-mean-square error are 1.03 m/s and 15.9°, respectively. The HSCAT-C winds show very good agreements with the HSCAT-B winds, especially in the range of [4, 17] m/s. In addition, as HSCAT-C is a rotating pencil-beam scatterometer, some common error characteristics are also clearly found in the wind products. Based on the validation results and existing scatterometer application experience, it is believed that the availability of the HSCAT-C wind product would greatly benefit the scientific and user community.

Influence of the tunnel retro-reflective arch in freeway tunnels on driving behavior: A driving simulator study

In this study, a driving simulator experiment was conducted to investigate the influence of tunnel retro-reflective arch (TA) on driving behavior, through the employment and analysis of TAs with disparate spacing alternatives (no TAs, TAs with a spacing of 200 m, and TAs with a spacing of 300 m) and tunnel lengths (800 m, 1800 m, 3500 m, and 5800 m). The performances of a total of 32 drivers were collected and assessed. The tunnels and TAs were accurately replicated in the driving simulator. On the basis of the experimental data, four behavioral variables, namely, average speed, the standard deviation of speed, the standard deviation of acceleration, and lateral position were obtained. A series of linear mixed models with random effects were estimated to reveal the contributing factors of driving behavior subjected to TAs variation. The results demonstrate that drivers showed significantly higher consciousness of speed control and lower mental stress, coupled with less risky driving behavior, under the condition of TAs in long and extra-long tunnels. Furthermore, drivers are more comfortable subjected to TAs with a spacing of 300 m.

Application of Connected and Automated Vehicles in a Large-Scale Network by Considering Vehicle-to-Vehicle and Vehicle-to-Infrastructure Technology

Application of connected and automated vehicles (CAVs) is expected to have a significant impact on traffic safety and mobility. Although several studies evaluated the effectiveness of CAVs in a small roadway segment, there is a lack of studies analyzing the impact of CAVs in a large-scale network by considering both freeways and arterials. Therefore, the objective of this study is to analyze the effectiveness of CAVs at the network level by utilizing both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication technologies. Also, the study proposed a new signal control algorithm through V2I technology to elevate the performance of CAVs at intersections. A car-following model named cooperative adaptive cruise control was utilized to approximate the driving behavior of CAVs in the Aimsun Next microsimulation environment. For the testbed, the research team selected Orlando central business district area in Florida, U.S. To this end, the impacts of CAVs were evaluated based on traffic efficiency (e.g., travel time rate [TTR], speed, and average approach delay, etc.) and safety surrogates (e.g., standard deviation of speed, real-time crash-risk models for freeways and arterials, time exposed time-to-collision). The results showed that the application of CAVs reduced TTR significantly compared with the base condition even with the low market penetration level. Also, the proposed signal control algorithm reduced the approach delay for 94% of the total intersections present in the network. Moreover, safety evaluation results showed a significant improvement of traffic safety in the freeways and arterials under CAV conditions with different market penetration rates.

Identification of driving simulator sessions of depressed drivers: A comparison between aggregated and time-series classification

Depression has been found to significantly increase the probability of risky driving and involvement in traffic collisions. The majority of studies correlating depressive symptoms with driving, pursue to predict the differences in driving behavior if the driver has already been diagnosed. Little evidence can be found, however, on how mental and psychological disorders can be identified from driving data, and usually analyses utilize simple models and aggregated data. This study aims at utilizing microscopic data from a driving simulator to detect sessions belonging to “depressed” drivers by utilizing powerful machine learning classifiers. Driving simulator sessions from 11 older drivers with symptoms of depression and 65 healthy drivers were utilized towards that aim. Random Forests, an ensemble classifier, with proven efficiency among transportation applications, are then trained on highly disaggregated data describing the mean and standard deviation of speed and lateral or longitudinal acceleration of drivers in the simulator. The kinematic data were aggregated in 30-seconds, 1-minute and 5-minute intervals, but the corresponding time-series of the measurements were also taken into account. Furthermore, classifiers were treated with imbalanced learning techniques to address the scarcity of depressed drivers among the healthy. Time-series of mean speed and the standard deviation of longitudinal acceleration even with a duration of 30-seconds have proven to be the best predictors of driving sessions belonging to depressed drivers with a very low rate of false alarms. The results outperform previous approaches, and indicate that naturalistic driving data or deep learning could prove even more efficient in detecting depression.

A study of relationships in traffic oscillation features based on field experiments

• Collect field trajectory data with periodic oscillation settings. • Propose a new time-domain method to estimate oscillation features. • Quantitatively reveal the relationships between traffic oscillation features. • Estimate a time gap function to improve the performance of car following models. Despite numerous theoretical models, only limited field experiments have been conducted to investigate traffic oscillation propagation, and the relationships between traffic oscillation features (e.g., period, speed variation, spacing and headway) have not received quantitative analysis. This study conducts a set of field experiments designed to inspect such relationships. In these experiments, 12 vehicles equipped with high-resolution global positioning system (GPS) devices following one another on public roads, and the lead vehicle was asked to move with designed trajectory profiles incorporating various parameters. Measurements of five features are extracted from processing the field vehicle trajectory data with a time-domain method. Frequency analysis is also proposed with the Fourier transform method to verify the effectiveness of the features measured by the time-domain method. Compared to the frequency-domain method, the time-domain method yields more measurements with comparable quality and is more robust on trajectories with a small number of oscillation cycles. Then, a series of linear regression analyses reveal a number of new findings on the relationships between these features. For example, the time gap between two consecutive vehicles is negatively correlated with the speed standard deviation of the preceding vehicle and the initial speed of the following vehicle. It is also positively correlated with the average speed of the preceding vehicle and the initial spacing. The findings are helpful in constructing new microscopic traffic models better describing traffic oscillation dynamics. To illustrate this benefit, revised car following models are proposed to capture the relationship between time gap and other features. The simulation results show that the revised models yield better prediction accuracy (in range of 18% to 40% with the oscillation experiment dataset and in range of 30–63% with the stationary experiment dataset) than the classical models on reproducing real-world trajectories.

Accident Prediction based on Integrated Design Consistency with the Lower Number of Vehicles/Traffic Volumes (due to Health Disaster/COVID-19)

Purpose: Malaysia is one of the developing countries that facing high road accident in Asia. The most common accident happens is between motorcyclist and cars. A motorcyclist is 17 times more dangerous than passenger cars. Analysis shows the three main types of accidents in Malaysia is collision with passenger cars, collisions with other motorcycles and single-motorcycle accidents. Road accidents keep rising in Malaysia, because lacks of road geometric design consistency where the drivers make mistakes errors due to the road geometric features. 
 Design/methodology/approach: The study was conducted at F0050 from km 21 until km 25. By using GPS (DG -200), the continuous speed profile data were using new analysis method to develop road design consistency profile of motorcycle and cars and determined the value of the index the integrated road design consistency (IC).
 Findings: The developments of consistency model are based on parameter: the bounded area between the profile and the average speed, standard deviation of speed along a segment. Hence, use ACAD software for develops consistency model’s profile. The integrated-consistency model is the impact of the speed profile on design consistency in traffic and safety evaluations. The highest areas of an accident at km 24 are justified based on the design consistency of the area and integrated design consistency model between of car and motorcycle is poor design. The study shows that crashes and fatalities are fully effected by traffic volumes but road design performances and driving behavior.
 Research limitations/implications: However, the traffic volumes are relatively low in the whole country regarding to the Movement Control Order (MCO) due to the pandemic COVID-19 since March 2020. In contrast to the reduction of the volumes, the number of crashes still shows relatively high. Therefore, it shows that crashes and fatalities are influenced by other factors. Geometric factors such as access point, tangent length, curve length, shoulder width, and lane width are influencing an operating speed profile for developed tangents and curves of motorcycle and cars.
 Practical implications: The result of this study can be used as references to solve accident problems in Malaysia.
 Paper type: This study is categorized as a case study.

Changes in six domains of cognitive function with reproductive and chronological ageing and sex hormones: a longitudinal study in 2411 UK mid-life women

BackgroundThere may be changes in cognitive function in women going through the menopause. The current evidence remains unclear, however, whether these changes occur over and above those of general ageing. We aimed to evaluate the potential impact of the menopause (assessed by reproductive age and hormone levels) on cognitive function in women in mid-life accounting for the underlying effects of ageing.MethodsThe study was based on the follow up of women originally enrolled in pregnancy in a birth cohort when resident in the South West of England, UK between 1991 and 1992. Using up to three repeated measurements in 2411 women (mean age 51 at first assessment), we modelled changes in six cognitive function domains: immediate and delayed verbal episodic memory, working memory, processing speed, verbal intelligence and verbal fluency. The exposures of interest were reproductive age measured as years relative to the final menstrual period (FMP), chronological age and reproductive hormones (follicle-stimulating hormone (FSH), luteinizing hormone (LH) and anti-Müllerian hormone (AMH)).ResultsProcessing speed (− 0.21 (95% CI − 0.36 to − 0.06) standard deviation (SD) difference per 10 years since FMP), immediate verbal episodic memory (− 0.15 (95% CI − 0.35 to 0.06)) and delayed verbal episodic memory (− 0.17 (95% CI − 0.37 to 0.03)) declined with reproductive age. Reproductive hormones were not robustly associated with processing speed, but FSH and LH were both negatively associated with immediate (− 0.08 (95% CI − 0.13 to − 0.02) SD difference per SD difference in hormone level) and delayed verbal episodic memory (− 0.08 (95% CI − 0.13 to − 0.03)). There was little consistent evidence of cognitive function declining with menopause in other cognitive domains.ConclusionsOf the cognitive domains tested only verbal episodic memory declined both in relation to age since the menopause and in conjunction with the reproductive hormones that reflect the menopause. This decline was independent of normal ageing and suggests that the menopause is associated with a mild impact on this specific domain of cognitive function.

Driving after pediatric traumatic brain injury: Impact of distraction and executive functioning.

The objective of the current study was to examine the driving performance of young drivers with a history of moderate to severe traumatic brain injury (TBI) compared with an uninjured control group. The impact of cell phone related distraction (conversation and texting) and executive functioning (EF) were also explored. Individuals aged 16-25 years with (n = 19) and without (n = 19) a history of TBI engaged in a simulated drive under 3 distraction conditions (no distraction, cell phone conversation, and texting). Mean speed, maximum speed, standard deviation of speed, standard deviation of lane position, and crash rates were used as outcomes. The Global Executive Composite (GEC) from the Behavior Rating Inventory of Executive Functioning (BRIEF) was used to measure EF. Significant Injury × Distraction × GEC interaction effects were noted on max speed and speed variability, with a trending Distraction × GEC interaction noted for lane position variability. The effect of distraction was most notable among individuals with greater GEC scores, across both injury groups. A history of pediatric TBI did not specifically impact driving performance independent of EF, with EF playing a central role in functioning across domains of driving performance. Consistent effect of EF suggests that deficits in driving performance may be associated with EF specifically, with individuals with EF difficulties following TBI at greater risk for poor driving performance. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Atmospheric turbulence and land - atmosphere energy transfer characteristics in the surface layer of the Northern slope of Mt. Qomolangma area : abstract

Based on the turbulent data collected at Quzong site, on the northern slope of Mt. Qomolangma, from April 2005 to March 2006, macro-scale turbulent statistical characteristics and land-atmosphere energy transfer before and after the onset of southwest monsoon were acquired by the eddy correlation method. It was found that Monin-Obukhov similarity theory is applicable for Mt. Qomolangma area. The relationship between normalized wind speed standard deviation and atmospheric stability, variances of normalized temperature and humidity standard deviation with atmospheric stability were simulated in the study. It was also found that energy balance components (net radiation flux, sensible heat flux, latent heat flux and soil heat flux) and surface heating filed had evident diurnal and seasonal changes. Especially under the influence of southwest monsoon, the sensible heat flux and latent heat flux in Quzong area have evident opposite changing trends. The variation characteristics of other surface parameters (surface reflectance and Bowen ratio) is very clear before and after the breakout of southwest monsoon.