Effect of shoulder width,guardrail and roadway geometry on driver perception and behavior

Roadway design is one of the most significant factors that affect driving behavior and perceived safety. The current study tests the combined effects of three roadway design elements – shoulders width, guardrail existence and roadway geometry (curvature) – on objective driving measures (speed and lane position), and subjective measures (perceived safe driving speed and estimated road safety).Twenty two drivers participated in an experiment with a driving simulation. In the first part objective driving data were collected, and in the second part subjective paper–pencil evaluations were requested of the perceived safety of 30 different scenarios that were previously experienced in the simulator. The scenarios consisted of the various combinations of the three roadway design elements.The results showed a significant effect of roadway geometry on both objective and subjective measures. The shoulders width had a significant effect on actual speed, on lane position, and on perceived safe driving speed, but only when a guardrail was present.These findings illustrate the perceptual role of a guardrail in defining the perceived safety margins that various shoulder widths provide. When a guardrail is absent, the width of the shoulder loses much of its benefits and effects on driving behavior. The results also demonstrate that roadway geometry can be used to reduce driving speeds, but at the same time it can have a negative effect on maintaining a stable lane position in sharp curves. Thus, controlling the width of road shoulders and the placement of guardrails seems to be a safer approach to speed and lane position control.     

轴肩结构对搅拌摩擦焊过程中材料流动的影响

考虑材料参数随温度的变化关系以及搅拌头的实际结构形式,利用ANSYS FLUENT软件对搅拌摩擦焊过程中材料的流动行为进行了数值分析,研究了轴肩结构分别为平面、内凹与同心圆时的材料流动规律.研究表明,当轴肩结构发生变化时,焊件表面及内部的材料流动趋势基本相同;靠近焊件表面的材料流动速度在轴肩结构为同心圆时最大,在轴肩结构为平面时最小.从避免搅拌摩擦焊根部缺陷的角度看,同心圆轴肩的搅拌头优于内凹轴肩,这一规律得到了试验证实.     

Aggressive driving: an observational study of driver, vehicle, and situational variables

Over 2000 aggressive driving behaviors were observed over a total of 72 h at six different sites. The behaviors selected for observation were those that are commonly included in "aggressive driving" lists, and they consisted of honking, cutting across one or more lanes in front of other vehicles, and passing on the shoulders. In addition, an exposure sample of 7200 drivers were also observed at the same times and places. Relative risks (RRs) and odds ratios (ODs) were calculated to show the relative likelihood that different drivers under different conditions will commit aggressive behaviors. The rate of aggressive actions observed in this study decreased from the most frequent behavior of cutting across a single lane, through honking, and to the least frequent behaviors of cutting across multiple lanes and passing on the shoulders. Relative to their proportion in the driving population, men were more likely than women to commit aggressive actions, and the differences increased as the severity of the action increased. Drivers who were 45 years old or older were less likely to drive aggressively than younger ones. The presence of passengers was associated with a slight but consistent reduction in aggressive driving of all types; especially honking at other drivers. There was a strong linear association between congestion and the frequency of aggressive behaviors, but it was due to the number of drivers on the road. However, when the value of time was high (as in rush hours), the likelihood of aggressive driving--after adjusting for the number of drivers on the road--was higher than when the value of time was low (during the non-rush weekday or weekend hours). The results have implications for driver behavior modifications and for environmental design.     

Effects of fog,driver experience and gender on driving behavior on S-curved road segments

Driving on curved roads has been recognized as a significant safety issue for many years. However, driver behavior and the interactions among variables that affect driver performance on curves is complicated and not well understood. Previous studies have investigated various factors that influence driver performance on right- or left-turn curves, but have paid little attention to the effects of foggy weather, driver experience and gender on driver performance on complex curves. A driving simulator experiment was conducted in this study to evaluate the relationships between driving behavior on a continuous S-curve and foggy weather, driver experience and gender. The process of negotiating a curve was divided into three stages consisting of a straight segment, the transition from the straight segment to the S-curve and the S-curve. The experimental results indicated that drivers tended to drive more cautiously in heavy fog, but the driving risk was still increased, especially in the transition stage from the straight segment to the S-curve. The non-professional (NP) drivers were less sensitive to the impending change in the road geometry, and less skilled in both longitudinal and lateral vehicle control than the professional drivers. The NP female drivers in particular were found to be the most vulnerable group in S-curve driving.     

How to identify the key factors that affect driver perception of accident risk. A comparison between Italian and Spanish driver behavior

Road crashes can be caused by different factors, including infrastructure, vehicles, and human variables. Many research studies have focused solely on identifying the key factors that cause road crashes. From these studies, it emerged that human factors have the most relevant impact on accident severity. More specifically, accident severity depends on several factors related directly to the driver, i.e., driving experience, driver's socio-economic characteristics, and driving behavior and attitudes. In this paper, we investigate driver behaviors and attitudes while driving and specifically focus on different methods for identifying the factors that most affect the driver's perception of accident risk. To this end, we designed and conducted a survey in two different European contexts: the city of Cosenza, which is located in the south of Italy, and the city of Granada, which is located in the south of Spain. Samples of drivers were contacted for their opinions on certain aspects of driving rules and attitudes while driving, and different types of questions were addressed to the drivers to assess their judgments of these aspects. Consequently, different methods of data analysis were applied to determine the aspects that heavily influence driver perception of accident risk. An experiment based on the stated preferences (SP) was carried out with the drivers, and the SP data were analyzed using an ordered probit (OP) model. Interesting findings emerged from different analyses of the data and from the comparisons among the data collected in the two different territorial contexts. We found that both Italian and Spanish drivers consider driving in an altered psychophysical state and violating the overtaking rules to be the most risky behaviors.     

Development of crash modification factors for changing lane width on roadway segments using generalized nonlinear models

This study evaluates the effectiveness of changing lane width in reducing crashes on roadway segments. To consider nonlinear relationships between crash rate and lane width, the study develops generalized nonlinear models (GNMs) using 3-years crash records and road geometry data collected for all roadway segments in Florida. The study also estimates various crash modification factors (CMFs) for different ranges of lane width based on the results of the GNMs. It was found that the crash rate was highest for 12-ft lane and lower for the lane width less than or greater than 12 ft. GNMs can extrapolate this nonlinear continuous effect of lane width and estimate the CMFs for any lane width, not only selected lane widths, unlike generalized linear models (GLMs) with categorical variables. The CMFs estimated using GNMs reflect that crashes are less likely to occur for narrower lanes if the lane width is less than 12 ft whereas crashes are less likely to occur for wider lanes if the lane width is greater than 12 ft. However, these effects varied with the posted speed limits as the effect of interaction between lane width and speed limit was significant. The estimated CMFs show that crashes are less likely to occur for lane widths less than 12 ft than the lane widths greater than 12 ft if the speed limit is higher than or equal to 40 mph. It was also found from the CMFs that crashes at higher severity levels (KABC and KAB) are less likely to occur for lane widths greater or less than 12 ft compared to 12-ft lane. The study demonstrates that the CMFs estimated using GNMs clearly reflect variations in crashes with lane width, which cannot be captured by the CMFs estimated using GLMs. Thus, it is recommended that if the relationship between crash rate and lane width is nonlinear, the CMFs are estimated using GNMs.     

Driver perception of roadside configurations on two-lane rural roads: Effects on speed and lateral placement

This paper reports the results of a driving simulator study which sought to analyze the effect that: (a) three roadside configurations on a two-lane rural road lined with trees have on speed and lateral position of the driver, depending on different cross-sections as well as geometric elements; (b) the beginning of the guardrail barrier has upon the driver's behavior whenever this occurs on the left curve, right curve or tangent.     

Overly cautious and dangerous: An empirical evidence of the older driver stereotypes

Negative comments regarding the competency of older drivers are frequently heard in the general population. While negative stereotypes of older drivers seem to be present, their existence has yet to be empirically validated. We thus investigated the stereotypes pertaining to older drivers in two experiments. In both experiments young adults viewed 12 simulated clips of three categories of driving behaviors (i.e., younger adults’ unsafe behaviors, older drivers’ unsafe behaviors and appropriate-safe driving behaviors) without knowing the driver's age. They were asked to rate how representative the behaviors were of a typical younger, middle-aged, or older driver. Experiment 1 showed that older drivers’ unsafe behaviors were rated as significantly more representative of the typical older driver, while young adults’ unsafe behaviors were perceived as significantly more representative of the typical younger driver. In Experiment 2, younger participants viewed the same clips but were only asked to indicate whether the observed behavior was representative or not of the typical older driver. The main findings were replicated. When asked to describe the main features of the typical older drivers, participants qualified them as being overly cautious, uncomfortable behind the wheel, and unsafe and dangerous. The potential implications on driving performance of older drivers and on driving cessation and are discussed.     

Experimental research on safety impacts of the inside shoulder based on driving simulation

Statistical data shows that single-vehicle crashes account for half of all traffic crashes on expressways in China, and previous research has indicated that main contributing factors were related to whether and how the inside shoulder was paved. The inside shoulder provides space for drivers to make evasive maneuvers and accommodate driver errors. However, lower-cost construction solutions in China have resulted in the design of numerous urban expressway segments that lack inside shoulders.     

An on-road assessment of cognitive distraction: impacts on drivers' visual behavior and braking performance

In this on-road experiment, drivers performed demanding cognitive tasks while driving in city traffic. All task interactions were carried out in hands-free mode so that the 21 drivers were not required to take their visual attention away from the road or to manually interact with a device inside the vehicle. Visual behavior and vehicle control were assessed while they drove an 8 km city route under three conditions: no additional task, easy cognitive task and difficult cognitive task. Changes in visual behavior were most apparent when performance between the No Task and Difficult Task conditions were compared. When looking outside of the vehicle, drivers spent more time looking centrally ahead and spent less time looking to the areas in the periphery. Drivers also reduced their visual monitoring of the instruments and mirrors, with some drivers abandoning these tasks entirely. When approaching and driving through intersections, drivers made fewer inspection glances to traffic lights compared to the No Task condition and their scanning of intersection areas to the right was also reduced. Vehicle control was also affected; during the most difficult cognitive tasks there were more occurrences of hard braking. Although hands-free designs for telematics devices are intended to reduce or eliminate the distraction arising from manual operation of these units, the potential for cognitive distraction associated with their use must also be considered and appropriately assessed. These changes are captured in measures of drivers' visual behavior.     

Modeling driver stop/run behavior at the onset of a yellow indication considering driver run tendency and roadway surface conditions

The ability to model driver stop/run behavior at signalized intersections considering the roadway surface condition is critical in the design of advanced driver assistance systems. Such systems can reduce intersection crashes and fatalities by predicting driver stop/run behavior. The research presented in this paper uses data collected from two controlled field experiments on the Smart Road at the Virginia Tech Transportation Institute (VTTI) to model driver stop/run behavior at the onset of a yellow indication for different roadway surface conditions. The paper offers two contributions. First, it introduces a new predictor related to driver aggressiveness and demonstrates that this measure enhances the modeling of driver stop/run behavior. Second, it applies well-known artificial intelligence techniques including: adaptive boosting (AdaBoost), random forest, and support vector machine (SVM) algorithms as well as traditional logistic regression techniques on the data in order to develop a model that can be used by traffic signal controllers to predict driver stop/run decisions in a connected vehicle environment. The research demonstrates that by adding the proposed driver aggressiveness predictor to the model, there is a statistically significant increase in the model accuracy. Moreover the false alarm rate is significantly reduced but this reduction is not statistically significant. The study demonstrates that, for the subject data, the SVM machine learning algorithm performs the best in terms of optimum classification accuracy and false positive rates. However, the SVM model produces the best performance in terms of the classification accuracy only.     

Size and geometry dependent tensile behavior of ultra-high-performance fiber-reinforced concrete

This research investigated direct tensile stress versus strain response of ultra-high-performance fiber-reinforced concrete (UHPFRC) with various sizes and geometries. The UHPFRC in this research contained 1% macro twisted and 1% micro smooth steel fibers by volume. The effects of gauge length, section area, volume and thickness of the specimens on the measured tensile response of the UHPFRC were experimentally discovered. The different sizes and geometries of specimens did not generate significant influence on the post cracking strength of UHPFRC whereas they produced clear effects on the strain capacity, energy absorption capacity and multiple cracking behavior of UHPFRC. The strain capacity, energy absorption capacity and the number of multiple micro cracks within unit length obviously decreased as the gauge length, section area and volume of UHPFRC specimens increased. In contrast, as the thickness of the specimen increased, different tendency was observed.     

Effects of major-road vehicle speed and driver age and gender on left-turn gap acceptance

Because the driver's gap-acceptance maneuver is a complex and risky driving behavior, it is a highly concerned topic for traffic safety and operation. Previous studies have mainly focused on the driver's gap acceptance decision itself but did not pay attention to the maneuver process and driving behaviors. Using a driving simulator experiment for left-turn gap acceptance at a stop-controlled intersection, this study evaluated the effects of major traffic speed and driver age and gender on gap acceptance behaviors. The experiment results illustrate relationships among drivers' left-turn gap decision, driver's acceleration rate, steering action, and the influence of the gap-acceptance maneuver on the vehicles in the major traffic stream. The experiment results identified an association between high crash risk and high traffic speed at stop-controlled intersections. The older drivers, especially older female drivers, displayed a conservative driving attitude as a compensation for reduced driving ability, but also showed to be the most vulnerable group for the relatively complex driving maneuvers.     

The effects of on-street parking and road environment visual complexity on travel speed and reaction time

On-street parking is associated with elevated crash risk. It is not known how drivers’ mental workload and behaviour in the presence of on-street parking contributes to, or fails to reduce, this increased crash risk. On-street parking tends to co-exist with visually complex streetscapes that may affect workload and crash risk in their own right. The present paper reports results from a driving simulator study examining the effects of on-street parking and road environment visual complexity on driver behaviour and surrogate measures of crash risk. Twenty-nine participants drove a simulated urban commercial and arterial route. Compared to sections with no parking bays or empty parking bays, in the presence of occupied parking bays drivers lowered their speed and shifted their lateral position towards roadway centre to compensate for the higher mental workload they reported experiencing. However, this compensation was not sufficient to reduce drivers’ reaction time on a safety-relevant peripheral detection task or to an unexpected pedestrian hazard. Compared to the urban road environments, the less visually complex arterial road environment was associated with speeds that were closer to the posted limit, lower speed variability and lower workload ratings. These results support theoretical positions that proffer workload as a mediating variable of speed choice. However, drivers in this study did not modify their speed sufficiently to maintain safe hazard response times in complex environments with on-street parking. This inadequate speed compensation is likely to affect real world crash risk.     

狭缝宽度及坩埚半径对分离结晶法制备CdZnTe晶体的影响

借助有限元法,在常重力条件下对分离结晶过程进行全局数值模拟,研究了狭缝宽度及坩埚半径对CdZnTe晶体生长过程中整体传热与流动特性的影响。模拟结果表明系统内传热特性、熔体流型与狭缝宽度及坩埚半径密切相关:(1)狭缝宽度对分离结晶有决定性的作用,当狭缝宽度较小时,气-液弯界面两端的温差很小,导致增大晶体重新粘附于坩埚壁面的风险;随着狭缝宽度的增大,流动不稳定性增加,很难保持稳定的气-液弯界面形状,增加了实现晶体稳定生长的难度;(2)随着坩埚半径增大,Marangoni对流对熔体流动影响逐渐增大,结晶界面附近的熔体流动不稳定性增加,这不利于晶体的稳定生长。     

纤维对混凝土裂缝宽度、曲折度及渗透性的影响

为研究不同纤维（钢纤维（SF）、聚丙烯长纤维（Macro-PP）、聚丙烯短纤维（Micro-PP））对荷载作用下带裂缝混凝土渗透性能的影响,通过劈裂试验引入不同宽度的结构裂缝（50~200 μm）,比较不同纤维对卸载后混凝土裂缝宽度及曲折度的影响。利用自主研发的渗透装置,分析了不同纤维类型、掺量及混杂方式对荷载作用下不同裂缝宽度混凝土渗透性的影响。研究发现:单掺55 kg/m3 SF比25 kg/m3渗透系数降低95.7%。与单掺SF相比,SF和Macro-PP的掺入具有正混杂效应;Micro-PP与SF混杂体系中渗透系数基本无变化,研究表明Micro-PP对结构裂缝间桥接作用甚微,对渗透性的作用不明显。SF和Macro-PP可有效限制裂缝的扩展,增大表面曲折度,降低开裂后混凝土的渗透性。      

Association of intersection approach speed with driver characteristics, vehicle type and traffic conditions comparing urban and suburban areas

A mobile recording system, with integrated laser speed gun, video from CCD-cameras and auxiliary battery system, was used to observe driving behavior at an urban intersection and a suburban analog. After removal of instances of interference, 1538 driving behaviors were recorded. Multiple regression was then utilized to examine the factors affecting approaching speed. Speed limit violation was considered a dichotomous variable with two categories, violation and compliance. Binary logistic regression was also used to examine the risk of speeding as a function of covariates and interaction terms. The results of analysis revealed that the major contributing factors for approaching speed were site, rush-hour-status, traffic light condition, vehicle type and driver gender. In particular, light status was the highest contributor to speed. In addition, the results of logistic regression showed significant sites and rush-hour effects on speeding, with the risk of limit violation in the suburbs nearly six-fold that in urban areas. The relative risk of speeding for travelling in non-rush hours is three times higher than that for rush-hour. In terms of driver characteristics, male drivers under 55 years of age had the greatest speeding propensity in our sample. The results of the present study may provide meaningful information applicable to the design and operation of signalized intersections.     

Effect of finite grating, waveguide width, and end-facet geometry on resonant subwavelength grating reflectivity

Resonant subwavelength gratings (RSGs) offer narrowband high reflectivity with low-reflectivity sidebands. Analysis with the commonly used rigorous coupled-wave analysis assumes an RSG with infinite lateral extent and illumination by plane waves. This analysis is performed with a finite-difference semivectorial high-order accurate two-dimensional Helmholtz code that is able to simulate the entire finite RSG structure in the dimension of the grating vector. We study the effect of finite beam size on RSG reflectivity, resonant wavelength, and spectral response width. Independently, we study the effect of a finite RSG by varying the waveguide length and number of grating periods while fixing the beam size. We show that the placement of the waveguide end facets relative to the termination of the grating has a significant effect on the reflectivity and response width.     

Effects of practice, age, and task demands, on interference from a phone task while driving

Experimental research on the effects of cellular phone conversations on driving indicates that the phone task interferes with many driving-related functions, especially with older drivers. Unfortunately in past research (1) the dual task conditions were not repeated in order to test for learning, (2) the 'phone tasks' were not representative of real conversations, and (3) most often both the driving and the phone tasks were experimenter-paced. In real driving drivers learn to time-share various tasks, they can pace their driving to accommodate the demands of a phone conversation, and they can even partially pace the phone conversation to accommodate the driving demands. The present study was designed to better simulate real driving conditions by providing a simulated driving environment with repeated experiences of driving while carrying two different hands-free 'phone' tasks with different proximities to real conversations. In the course of five sessions of driving and using the phone, there was a learning effect on most of the driving measures. In addition, the interference from the phone task on many of the driving tasks diminished over time as expected. Finally, the interference effects were greater when the phone task was the often-used artificial math operations task than when it was an emotionally involving conversation, when the driving demands were greater, and when the drivers were older. Thus, the deleterious effects of conversing on the phone are very real initially, but may not be as severe with continued practice at the dual task, especially for drivers who are not old.     

The stability of driver acceleration behavior, and a replication of its relation to bus accidents

The reliability over time of a method for measuring driver acceleration behavior was tested on bus drivers in regular traffic. Also, a replication of an earlier finding of a correlation between driver acceleration behavior and accident frequency for the individual drivers was made. It was found that the split-half correlation is probably around 0.50 for the mean (of accelerations) of a 30-min drive, and similar for the test-retest of 2.5h measured about a month apart. With such reliability, the sample was probably too small to reliably determine any association with accidents, but some significant correlations were found. Some ways of holding constant the differences in exposure and driving environment were tried with mixed success. Alternate ways of analyzing the data and several methodological problems were briefly discussed. It was concluded that the measurements of acceleration behavior, for bus drivers, are fairly reliable over at least a few months. However, some strange discrepancies between samples make all interpretations concerning the link to accidents tentative.