Crash proximity and equivalent property damage calculation techniques: An investigation using a novel horizontal curve dataset.

Despite the numerous breakthroughs in crash analytics, there remains a lack of consensus among safety practitioners as to the optimal method for locating high crash locations. Two critical components in the traffic safety analysis process not agreed upon are 1) how the crash distance to a target location is included in the analysis and 2) how crashes are weighted based on crash-related characteristics. For example, the commonly used buffering technique to determine which crashes are associated with a specific target road segment does not associate crashes that are closer to a target road segment with any additional weight, even though it is likely to be more greatly associated with the characteristics of the target location. Additionally, the commonly used equivalent property damage only (EPDO) crash weight method has been found to weigh fatal crashes significantly more than serious injury crashes, even if the difference between the two outcomes was a single factor. This study proposes more robust crash weighting techniques for use in high-risk location identification using an application of a novel horizontal curve dataset. Specifically, a heteroscedastic censored regression approach was used to investigate the impact of different crash proximity weighting techniques and crash severity weighting methods on model outcomes. The results demonstrate that the use of a linear distance weighting factor used in conjunction with the buffering technique as well as a less precise EPDO weighting factor method results in more robust safety analysis outcomes. The improved results have the potential to improve hot spot identification and resource allocation at both the federal and regional levels by employing models that more accurately link specific crash segments with contributing crash characteristics.

Driver behavior and performances on in-vehicle display based speed compliance.

Traffic safety, and the inherent risks associated with speeding, continue to remain a national priority. Advances in both roadway and vehicle technology have created potential mechanisms to mitigate speeding behaviors. This driving simulator study evaluated the effects of alternative ways to increase driver safety by investigating the characteristics of specific driving cues and drivers' response rates to those cues. The study builds upon existing approaches to symbolically deliver Traffic Control Devices (TCDs), specifically speed alerts, at different locations within the vehicle to reduce cognitive distraction and prevent visual crowding so that drivers can properly select their speed and focus upon the roadway environment. Twenty-three participants received five visual treatments (e.g., combinations of speed alert style, presentation, and location) in a simulated environment. Participants also responded to a set of survey questions following the simulated drive. Participants were evaluated on various response factors to each visual treatment. Results showed that younger participants of the age group 18-23 responded to the visual treatment and stayed within speed limits as compared to other older and more experienced participants. Results also showed that alerts falling in the mid-peripheral visual region and alerts that flashed received an increased response rate for observing speed limits.

Using a novel data linkage approach to investigate potential reductions in motor vehicle crash severity - An evaluation of strategic highway safety plan emphasis areas.

INTRODUCTION: With the significant number of motor-vehicle fatalities occurring on the nation's roadways in recent years, there exists a need to integrate a more complete range of data sources, available at a regional or statewide level, to effectively evaluate existing safety concerns and quantify their impacts. Crash data alone does not provide ample crash-associated citation, injury, and roadway characteristics; therefore, a more cohesive dataset is required to accurately and completely analyze the true impacts of motor-vehicle crashes. Previously developed strategies linked crash data with citation and roadway inventory data to enhance the identification and optimization of highway safety strategies. METHOD: The main objective of this research focused on developing a new deterministic linkage between crash and Emergency Medical Services (EMS) data, by utilizing the Massachusetts Crash Data System (CDS) and the Massachusetts Ambulance Trip Record Information System (MATRIS). RESULTS: After several iterations of match criterion, the validated linkage successfully matched 58.3% of MATRIS records (containing an Injury Cause of Motor Vehicle Crash) to a CDS person record (55011 linked pairs, between 2014 and 2016). The data linkage provided significant insight into injury trends in several highway safety emphasis areas such as roadway departure, speeding-related, and distraction-affected crashes. The findings from this research are twofold: (1) an established process for linking previously separate data sets, and (2) a mechanism for analysis that provides decision-makers and safety professionals with a better measure of crash outcomes.

A Wizard-of-Oz experimental approach to study the human factors of automated vehicles: Platform and methods evaluation.

OBJECTIVES: Driving simulation is an important platform for studying vehicle automation. There are different approaches to using this platform - with most using scripting or programmatic tools to simulate vehicle automation. A less frequently used approach, the Wizard-of-Oz method, has potential for increased flexibility and efficiency in designing and conducting experiments. This study designed and evaluated an experimental setup to examine the feasibility of this approach as an alternative for conducting automation studies. METHODS: Twenty-four participants experienced simulated vehicle automation in two platforms, one where the automation was controlled by algorithms, and the other where the automation was simulated by an external operator. Surveys were administered after each drive and the drivers' takeover performance after the automation disengaged was measured. RESULTS: Results indicate that while the kinematic parameters of the driving differed significantly for the two platforms, there were no significant differences in the perceptions of participants and in their takeover performance between the two platforms. CONCLUSION: These results provide evidence for the use of alternative approaches for the conduct of human factors studies on vehicle automation, potentially lowering barriers to undertaking such experiments while increasing flexibility in designing more complex studies.

The use of a driving simulator to determine how time pressures impact driver aggressiveness.

Speeding greatly attributes to traffic safety with approximately a third of fatal crashes in the United States being speeding-related. Previous research has identified being late as a primary cause of speeding. In this driving simulator study, a virtual drive was constructed to evaluate how time pressures, or hurried driving, affected driver speed choice and driver behavior. In particular, acceleration profiles, gap acceptance, willingness to pass, and dilemma zone behavior were used, in addition to speed, as measures to evaluate whether being late increased risky and aggressive driving behaviors. Thirty-six drivers were recruited with an equal male/female split and a broad distribution of ages. Financial incentives and completion time goals calibrated from a control group were used to generate a Hurried and Very Hurried experimental group. As compared to the control group, Very Hurried drivers selected higher speeds, accelerated faster after red lights, accepted smaller gaps on left turns, were more likely to pass a slow vehicle, and were more likely to run a yellow light in a dilemma zone situation. These trends were statistically significant and were also evident with the Hurried group but a larger sample would be needed to show statistical significance. The findings from this study provide evidence that hurried drivers select higher speeds and exhibit riskier driving behaviors. These conclusive results have possible implications in areas such as transportation funding and commercial motor vehicle safety.

An investigation of the speeding-related crash designation through crash narrative reviews sampled via logistic regression.

Speed is one of the most important factors in traffic safety as higher speeds are linked to increased crash risk and higher injury severities. Nearly a third of fatal crashes in the United States are designated as "speeding-related", which is defined as either "the driver behavior of exceeding the posted speed limit or driving too fast for conditions." While many studies have utilized the speeding-related designation in safety analyses, no studies have examined the underlying accuracy of this designation. Herein, we investigate the speeding-related crash designation through the development of a series of logistic regression models that were derived from the established speeding-related crash typologies and validated using a blind review, by multiple researchers, of 604 crash narratives. The developed logistic regression model accurately identified crashes which were not originally designated as speeding-related but had crash narratives that suggested speeding as a causative factor. Only 53.4% of crashes designated as speeding-related contained narratives which described speeding as a causative factor. Further investigation of these crashes revealed that the driver contributing code (DCC) of "driving too fast for conditions" was being used in three separate situations. Additionally, this DCC was also incorrectly used when "exceeding the posted speed limit" would likely have been a more appropriate designation. Finally, it was determined that the responding officer only utilized one DCC in 82% of crashes not designated as speeding-related but contained a narrative indicating speed as a contributing causal factor. The use of logistic regression models based upon speeding-related crash typologies offers a promising method by which all possible speeding-related crashes could be identified.

Measurement of spatial and temporal variation in volatile hazardous air pollutants in Tacoma, Washington, using a mobile membrane introduction mass spectrometry (MIMS) system.

The objective of this study was to use membrane introduction mass spectrometry (MIMS), implemented on a mobile platform, in order to provide real-time, fine-scale, temporally and spatially resolved measurements of several hazardous air pollutants. This work is important because there is now substantial evidence that fine-scale spatial and temporal variations of air pollutant concentrations are important determinants of exposure to air pollution and adverse health outcomes. The study took place in Tacoma, WA during periods of impaired air quality in the winter and summer of 2008 and 2009. Levels of fine particles were higher in winter compared to summer, and were spatially uniform across the study area. Concentrations of vapor phase pollutants measured by membrane introduction mass spectrometry (MIMS), notably benzene and toluene, had relatively uniform spatial distributions at night, but exhibited substantial spatial variation during the day-daytime levels were up to 3-fold higher at traffic-impacted locations compared to a reference site. Although no direct side-by-side comparison was made between the MIMS system and traditional fixed site monitors, the MIMS system typically reported higher concentrations of specific VOCs, particularly benzene, ethylbenzene and naphthalene, compared to annual average concentrations obtained from SUMA canisters and gas chromatographic analysis at the fixed sites.

The influence of clear zone size and roadside vegetation on driver behavior.

INTRODUCTION: Roadside vegetation provides numerous environmental and psychological benefits to drivers. Previous studies have shown that natural landscapes can effectively lower crash rates and cause less frustration and stress to the driver. However, run-off-the-road crashes resulting in a collision with a tree are twice as likely to result in a fatality, reinforcing the need to examine the placement of vegetation within the clear zone. METHOD: This study explores the relationship between the size of the clear zone and the presence of roadside vegetation on vehicle speed and lateral position. A static evaluation, distributed electronically to 100 licensed drivers, was utilized to gather speed selections for both real and virtual roads containing four combinations of clear zone sizes and roadside vegetation densities. A case study was included in the static evaluation to investigate the presence of utility poles near the edge of the road on speed selection. Validation of the static evaluation was performed by a field data collection on the same roadways shown to participants in the evaluation. RESULTS: The speeds observed in the field for roadways with medium clear zone/dense vegetation or large clear zone/spare vegetation correlated with the speeds chosen by static evaluation participants. Further field data were obtained on vehicle speeds and lateral positions for additional roads demonstrating the same clear zone size/vegetation density combinations. PRACTICAL APPLICATION: This study successfully demonstrates the relationship between clear zone design and driver behavior, which could improve clear zone design practices and thus roadway safety.

Development of a unique multi-contaminant air sampling device for a childhood asthma cohort in an agricultural environment.

This research describes the design, deployment, performance, and acceptability of a novel outdoor active air sampler to provide simultaneous measurements of multiple contaminants at timed intervals for the Aggravating Factors of Asthma in Rural Environment (AFARE) study-a longitudinal cohort of 50 children in Yakima Valley, Washington. The sampler was constructed of multiple sampling media connected to individual critical orifices and a rotary vane vacuum pump. It was connected to a timed control valve system to collect 24 hours samples every six days over 18 months. We describe a spatially representative approach with both quantitative and qualitative location criteria to deploy a network of 14 devices at participant residences in a rural region (20 × 60 km). Overall the sampler performed well, as the concurrent mean sample flow rates were within or above the ranges of recommended sampling rates for each exposure metric of interest. Acceptability was high among the study population of Hispanic farmworker participant households. The sampler design may prove useful for future urban and rural community-based studies with aims at collecting multiple contaminant data during specific time periods.

Biomonitoring of estrogen and melatonin metabolites among women residing near radio and television broadcasting transmitters.

OBJECTIVES: Metabolites of estrogen (estrone-3-glucuronide [E1G]) and melatonin (6-hydroxymelatonin sulfate [6-OHMS]) were characterized among women living in a community with increased radiofrequency (RF) exposure from radio and television transmitters. METHODS: RF spot measurements, and personal 60-Hz magnetic field and residential parameters were collected. Overnight urine samples were assayed for E1G and 6-OHMS excretion. RESULTS: Among premenopausal women, there were no associations between RF or 60-Hz nonionizing radiation and E1G or 6-OHMS excretion. Among postmenopausal women, increased residential RF exposures, transmitter proximity and visibility, and temporally stable 60-Hz exposures were significantly associated with increased E1G excretion. This association was strongest among postmenopausal women with low overnight 6-OHMS levels. CONCLUSIONS: RF and temporally stable 60-Hz exposures were associated with increased E1G excretion among postmenopausal women. Women with reduced nocturnal 6-OHMS excretion may represent a sensitive subgroup.

Comparison of global positioning system (GPS) tracking and parent-report diaries to characterize children's time-location patterns.

Respondent error, low resolution, and study participant burden are known limitations of diary timelines used in exposure studies such as the National Human Exposure Assessment Survey (NHEXAS). Recent advances in global positioning system (GPS) technology have produced tracking devices sufficiently portable, functional and affordable to utilize in exposure assessment science. In this study, a differentially corrected GPS (dGPS) tracking device was compared to the NHEXAS diary timeline. The study also explored how GPS can be used to evaluate and improve such diary timelines by determining which location categories and which respondents are least likely to record "correct" time-location responses. A total of 31 children ages 3-5 years old wore a dGPS device for all waking hours on a weekend day while their parents completed the NHEXAS diary timeline to document the child's time-location pattern. Parents misclassified child time-location approximately 48% of the time using the NHEXAS timeline in comparison to dGPS. Overall concordance between methods was marginal (kappa=0.33-0.35). The dGPS device found that on average, children spent 76% of the 24-h study period in the home. The diary underestimated time the child spent in the home by 17%, while overestimating time spent inside other locations, outside at home, outside in other locations, and time spent in transit. Diary data for time spent outside at home and time in transit had the lowest response concordance with dGPS. The diaries of stay-at-home mothers and mothers working unskilled labor jobs had lower concordance with dGPS than did those of the other participants. The ability of dGPS tracking to collect continuous rather than categorical (ordinal) data was also demonstrated. It is concluded that automated GPS tracking measurements can improve the quality and collection efficiency of time-location data in exposure assessment studies, albeit for small cohorts.

Radio frequency nonionizing radiation in a community exposed to radio and television broadcasting.

Exposure to radio frequency (RF) nonionizing radiation from telecommunications is pervasive in modern society. Elevated disease risks have been observed in some populations exposed to radio and television transmissions, although findings are inconsistent. This study quantified RF exposures among 280 residents living near the broadcasting transmitters for Denver, Colorado. RF power densities outside and inside each residence were obtained, and a global positioning system (GPS) identified geographic coordinates and elevations. A view-shed model within a geographic information system (GIS) characterized the average distance and percentage of transmitters visible from each residence. Data were collected at the beginning and end of a 2.5-day period, and some measurements were repeated 8-29 months later. RF levels logged at 1-min intervals for 2.5 days varied considerably among some homes and were quite similar among others. The greatest differences appeared among homes within 1 km of the transmitters. Overall, there were no differences in mean residential RF levels compared over 2.5 days. However, after a 1- to 2-year follow-up, only 25% of exterior and 38% of interior RF measurements were unchanged. Increasing proximity, elevation, and line-of-sight visibility were each associated with elevated RF exposures. At average distances from > 1-3 km, exterior RF measurements were 13-30 times greater among homes that had > 50% of the transmitters visible compared with homes with < or = 50% visibility at those distances. This study demonstrated that both spatial and temporal factors contribute to residential RF exposure and that GPS/GIS technologies can improve RF exposure assessment and reduce exposure misclassification.