Investigating changes in travel behavior over time in response to the COVID-19 pandemic.

The COVID-19 pandemic has significantly affected travel behavior, including the frequency and mode of travel, with the magnitude and nature of these effects varying over time. This study investigates the nature of these relationships by examining changes in various measures of travel behavior, including weekly driving hours, as well as the frequency of telecommuting, use of ride-sharing services, travel for medical purposes, and use of food delivery services. Self-reported travel data from a representative statewide survey of Michigan residents were used to assess changes in these metrics during the early stages of the pandemic, as well as one year thereafter. Random effects linear regression and ordered logit regression models were estimated and the findings show that various changes in behavior had long-lasting effects, while other behaviors generally reverted back toward pre-pandemic levels. In addition, these changes were found to vary across individuals. For example, significant differences were observed based on socio-demographic characteristics, between urban and rural areas, and amongst individuals with differing views on COVID-19 and related government interventions. In general, the pandemic tended to have less pronounced and sustained effects among younger adults as compared to older age groups. Further, those individuals who were opposed to mandatory COVID-19 vaccines were less likely to change their travel behavior, during both the early and latter stages of the pandemic. Changes were observed consistently across most of the travel metrics of interest. Among these, overall driving hours, travel for medical purposes, and ride-sharing were still lower during the latter stages of the pandemic, while telecommuting and the use of food delivery services reverted nearer to pre-pandemic levels.

Examining Impacts of COVID-19-Related Stay-At-Home Orders through a Two-Way Random Effects Model.

The COVID-19 pandemic has had far-reaching impacts on public health and safety, economics, and the transportation system. To reduce the spread of this disease, federal and local governments around the world have introduced stay-at-home orders and other restrictions on travel to "non-essential" businesses to implement social distancing. Preliminary evidence suggests substantial variability in the impacts of these orders in the United States, both across states and over time. This study examines this issue using daily county-level vehicle miles traveled (VMT) data for the 48 continental U.S. states and the District of Columbia. A two-way random effects model is estimated to assess changes in VMT from March 1 to June 30, 2020 as compared with baseline January travel levels. The implementation of stay-at-home orders was associated with a 56.4 percent reduction in VMT on average. However, this effect was shown to dissipate over time, which may be attributable to "quarantine fatigue." In the absence of full shelter-in-place orders, travel was also reduced where restrictions on select businesses were introduced. For example, restrictions on entertainment, indoor dining, and indoor recreational activities corresponded to reductions in VMT of 3 to 4 percent while restrictions on retail and personal care facilities showed 13 percent lower traffic levels. VMT was also shown to vary based on the number of COVID case reports, as well as with respect to other characteristics, including median household income, political leanings, and how rural the county was in nature.

A comparison of freeway median crash frequency, severity, and barrier strike outcomes by median barrier type.

Median-crossover crashes are among the most hazardous events that can occur on freeways, often resulting in severe or fatal injuries. The primary countermeasure to reduce the occurrence of such crashes is the installation of a median barrier. When installation of a median barrier is warranted, transportation agencies are faced with the decision among various alternatives including concrete barriers, beam guardrail, or high-tension cable barriers. Each barrier type differs in terms of its deflection characteristics upon impact, the required installation and maintenance costs, and the roadway characteristics (e.g., median width) where installation would be feasible. This study involved an investigation of barrier performance through an in-depth analysis of crash frequency and severity data from freeway segments where high-tension cable, thrie-beam, and concrete median barriers were installed. A comprehensive manual review of crash reports was conducted to identify crashes in which a vehicle left the roadway and encroached into the median. This review also involved an examination of crash outcomes when a barrier strike occurred, which included vehicle containment, penetration, or re-direction onto the travel lanes. The manual review of crash reports provided critical supplementary information through narratives and diagrams not normally available through standard fields on police crash report forms. Statistical models were estimated to identify factors that affect the frequency, severity, and outcomes of median-related crashes, with particular emphases on differences between segments with varying median barrier types. Several roadway-, traffic-, and environmental-related characteristics were found to affect these metrics, with results varying across the different barrier types. The results of this study provide transportation agencies with important guidance as to the in-service performance of various types of median barrier.

Driver speed selection and crash risk: Insights from the naturalistic driving study.

INTRODUCTION: This study investigates how speed limits affect driver speed selection, as well as the related crash risk, while controlling for various confounding factors such as traffic volumes and roadway geometry. Data from a naturalistic driving study are used to examine how driver speed selection varies among freeways with different posted speed limits, as well as how the likelihood of crash/near-crash events change with respect to mean speed and standard deviation. METHOD: Regression models are estimated to assess three measures of interest: the average speed of vehicles during the time preceding crash/near-crash and baseline (i.e., normal) driving events; the variation in travel speeds leading up to each event as quantified by the standard deviation in speeds over this period; and the probability of a specific event resulting in a crash/near-crash based on speed selection and other factors. RESULTS: Speeds were relatively stable across levels-of-service A and B, within a range of 1.5mph on average. Speeds were marginally lower (3.3mph) on freeways posted at 65mph versus 70mph. In comparison, speeds were approximately 10.2 to 13.4mph lower on facilities posted at 55mph or 60mph. Speeds were shown to be 2.5mph lower in rainy weather and 11mph lower under snow or sleet. CONCLUSIONS: Significant correlation was observed with respect to speed selection behavior among the same individuals. Mean speeds are shown to increase with speed limits. However, these increases are less pronounced at higher speed limits. Drivers tend to reduce their travel speeds in presence of junctions and work zones, under adverse weather conditions, and particularly under heavy congestion. Crash risk increased with the standard deviation in speed, as well as on vertical curves and ramp junctions, and among the youngest and oldest age groups of drivers.

Driver speed selection on high-speed two-lane highways: Comparing speed profiles between uniform and differential speed limits.

OBJECTIVE: Although a considerable amount of prior research has investigated the impacts of speed limits on traffic safety and operations, much of this research, and nearly all of the research related to differential speed limits, has been specific to limited access freeways. The unique safety and operational issues on highways without access control create difficulty relating the conclusions from prior freeway-related speed limit research to 2-lane highways, particularly research on differential limits due to passing limitations and subsequent queuing. Therefore, the objective of this study was to assess differences in driver speed selection with respect to the posted speed limit on rural 2-lane highways, with a particular emphasis on the differences between uniform and differential speed limits. METHODS: Data were collected from nearly 59,000 vehicles across 320 sites in Montana and 4 neighboring states. Differences in mean speeds, 85th percentile speeds, and the standard deviation in speeds for free-flowing vehicles were examined across these sites using ordinary least squares regression models. RESULTS: Ultimately, the results of the analysis show that the mean speed, 85th percentile speed, and variability in travel speeds for free-flowing vehicles on 2-lane highways are generally lower at locations with uniform 65 mph speed limits, compared to locations with differential limits of 70 mph for cars and 60 mph for trucks. CONCLUSIONS: In addition to posted speed limits, several site characteristics were shown to influence speed selection including shoulder widths, frequency of horizontal curves, percentage of the segment that included no passing zones, and hourly volumes. Differences in vehicle speed characteristics were also observed between states, indicating that speed selection may also be influenced by local factors, such as driver population or enforcement.

Examination of factors associated with use rates after transition from a universal to partial motorcycle helmet use law.

OBJECTIVES: Motorcycle riders account for a disproportionately high number of traffic injuries and fatalities compared to occupants of other vehicle types. Though research has demonstrated the benefits of helmet use in preventing serious and fatal injuries in the event of a crash, helmet use has remained relatively stable in the United States, where the most recent national estimates show a 64% use rate. Use rates have been markedly lower among those states that do not have a universal helmet law for all riders. In 2012, the state of Michigan repealed its longstanding mandatory helmet use law. In order to gain insights as to the effects of this legislative change, a study was conducted to examine short-term changes in helmet use and identify factors associated with use rates. METHODS: A statewide direct observation survey was conducted 1 year after the transition from a universal helmet law to a partial helmet law. A random parameters logistic regression model was estimated to identify motorcyclist, roadway, and environmental characteristics associated with helmet use. This modeling framework accounts for both intravehicle correlation (between riders and passengers on the same motorcycle) as well as unobserved heterogeneity across riders due to important unobserved factors. RESULTS: Helmet use was shown to vary across demographic segments of the motorcyclist population. Use rates were higher among Caucasian riders, as well as among those age 60 and above. No significant difference was observed between male and female riders. Use was also found to vary geographically, temporally, and with respect to various environmental characteristics. Geographically, helmet use rates tended to be correlated with historical restraint use trends, which may be reflective of riding environment and general differences in the riding population. To this end, rates were also highly variable based upon the type of motorcycle and whether the motorcyclist was wearing high-visibility gear. CONCLUSIONS: The study results demonstrate the short-term reduction in helmet use following transition from a universal to partial motorcycle helmet law. The reduction in use is somewhat less pronounced than has been experienced in other states, which may be reflective of general differences among Michigan motorcyclists because the state has also generally exhibited higher use rates of seat belts and other forms of occupant protection. The study results also highlight potential target areas for subsequent education and public awareness initiatives aimed at increasing helmet use.

A comparison of contributing effects on 2-vehicle alcohol-related crashes between impaired and nonimpaired operators.

OBJECTIVE: Driving under the influence of alcohol is a crime that places the lives of all motorists in danger. Though it is a largely preventable act, impaired driving has accounted for 31 to 38% of fatal crashes across the country over the last decade. When an impaired operator crashes his or her vehicle, there is often a second unit, of which the operator is not impaired, involved in the crash. METHODS: This research looks at approximately 14,000 2-unit crashes involving an impaired operator in the State of Ohio from 2008 through 2012. The research is focused on determining the effects of crash and operator characteristics in 2-unit alcohol-related crashes through the use of 2 mixed logit models. RESULTS: It is found that several factors have similar effects on the injury severities of both the impaired and nonimpaired operators, including head-on crashes, the use of seat belts, and the deployment of airbags. There are, however, several factors that affect the 2 operators differently. It is found that the impaired operator's injury severity is based on the type and, more important, the size of the vehicle he or she is driving, the roadway geometry, and the speed of the vehicle driven by the nonimpaired operator. The nonimpaired operator is equally affected by the speed of the impaired vehicle as much as his or her own speed, and the nonimpaired operator's injury severity is virtually independent of the type of vehicle being driven. CONCLUSIONS: Researchers may disseminate the results to community groups such as Mothers Against Drunk Driving and Safe Communities to increase awareness of the dangers of drunk driving in an effort to reduce the number of alcohol-related crashes.

Examining driver behavior at the onset of yellow in a traffic simulator environment: Comparisons between random parameters and latent class logit models.

This study involves an examination of driver behavior at the onset of a yellow signal indication. Behavioral data were obtained from a driving simulator study that was conducted through the National Advanced Driving Simulator (NADS) laboratory at the University of Iowa. These data were drawn from a series of events during which study participants drove through a series of intersections where the traffic signals changed from the green to yellow phase. The resulting dataset provides potential insights into how driver behavior is affected by distracted driving through an experimental design that alternated handheld, headset, and hands-free cell phone use with "normal" baseline driving events. The results of the study show that male drivers ages 18-45 were more likely to stop. Participants were also more likely to stop as they became more familiar with the simulator environment. Cell phone use was found to some influence on driver behavior in this setting, though the effects varied significantly across individuals. The study also demonstrates two methodological approaches for dealing with unobserved heterogeneity across drivers. These include random parameters and latent class logit models, each of which analyze the data as a panel. The results show each method to provide significantly better fit than a pooled, fixed parameter model. Differences in terms of the context of these two approaches are discussed, providing important insights as to the differences between these modeling frameworks.

Driver decision-making in the dilemma zone - Examining the influences of clearance intervals, enforcement cameras and the provision of advance warning through a panel data random parameters probit model.

In recent years, there have been a series of innovations in the field of vehicle detection at intersection approaches. Modern radar-based smart sensors make it possible to track individual vehicles in close proximity to an intersection. These advancements in technology potentially enable the provision of vehicle- and site-specific decision dilemma zone protection at the onset of the yellow indication at signalized intersections. To exploit this opportunity, it is critical to develop an in-depth understanding of those factors influencing a driver's decision to stop or go at the onset of yellow. This study investigates how signal timing strategies such as yellow interval durations, all-red clearance intervals, advance warning flashers, and automated camera enforcement affect driver decision-making. Data from 87 intersection approaches across five regions of the United States are used to develop a series of decision (i.e., probability of stopping) curves using vehicle trajectory and signal phasing data. A panel data random parameters probit model is used to account for heterogeneity across locations, as well as correlation in driver decision-making, due to unobserved factors that are unique to each signalized intersection. The results demonstrate drivers are more likely to stop at locations where enforcement cameras or flashers are present. Stopping was also more prevalent at intersections with lower speed limits, longer crossing distances, and where pedestrian crosswalks were present.

Toxic effects of combined stressors on Daphnia pulex: Interactions between diazinon, 4-nonylphenol, and wastewater effluent.

Contaminant exposure in aqueous systems typically involves complex chemical mixtures. Given the large number of compounds present in the environment, it is critical to identify hazardous chemical interactions rapidly. The present study utilized a prototype for a novel high-throughput assay to quantify behavioral changes over time to identify chemical interactions that affect toxicity. The independent and combined effects of 2 chemicals, diazinon (an insecticide) and 4-nonylphenol (a detergent metabolite), on the swimming behavior of the freshwater crustacean Daphnia pulex were examined. Cumulative distance and change in direction were measured repeatedly via optical tracking over 90 min. Exposure to low concentrations of diazinon (0.125-2 µM) or 4-nonylphenol (0.25-4 µM) elicited significant concentration- and time-dependent effects on swimming behavior. Exposure to 0.5 µM 4-nonylphenol alone did not significantly alter mean cumulative distance but did elicit a small, significant increase in mean angle, the measure of change in direction. When 0.5 µM 4-nonylphenol was used in combination with diazinon (0.125-0.5 µM), it augmented the adverse impact of diazinon on the swimming behavior of Daphnia. Additionally, enhanced sensitivity to diazinon was observed in animals exposed to treated wastewater effluent for 24 h prior to a diazinon challenge. The present experiments demonstrate that exposure to 4-nonylphenol and complex chemical mixtures (e.g., treated wastewater) can enhance the toxicity of exposure to the insecticide diazinon.

A comparison of contributing factors between alcohol related single vehicle motorcycle and car crashes.

INTRODUCTION: Alcohol related crashes have accounted for approximately 35% of fatal crashes per year since 1994 nationwide, with approximately 30% involving impairment over the legal blood alcohol content limit of 0.08%. Educational campaigns and law enforcement efforts are two components of multi-faceted programs aimed toward reducing impaired driving. It is crucial that further research be conducted to guide the implementation of enforcement and educational programs. METHOD: This research attempts to provide such guidance by examining differences in alcohol-involved crashes involving motorcycles and passenger cars. Prior safety research has shown that motorcyclists follow a significantly different culture than the average passenger car operator. These cultural differences may be reflected by differences in the contributing factors affecting crashes and the severity of the resulting injuries sustained by the driver or motorcyclist. This research is focused on single-vehicle crashes only, in order to isolate modal effects from the contribution of additional vehicles. The crash data provided for this study are from the Ohio Department of Public Safety from 2009 through 2012. RESULTS: The injury severity data are analysed through the development of two mixed logit models, one for motorcyclists and one for passenger car drivers. The models quantify the effects of various factors, including horizontal curves, speeds, seatbelt use, and helmet use, which indicate that the required motor skills and balance needed for proper motorcycle operation compounded with a lack of mechanical protection make motorcyclists more prone to severe injuries, particularly on curves and in collisions with roadside objects. PRACTICAL APPLICATIONS: The findings of this study have been incorporated into combined motorcycle and sober driving educational safety campaigns. The results have shown to be favorable in supporting national campaign messages with local justification and backing.

Assessing characteristics related to the use of seatbelts and cell phones by drivers: application of a bivariate probit model.

INTRODUCTION: The effects of cell phone use and safety belt use have been an important focus of research related to driver safety. Cell phone use has been shown to be a significant source of driver distraction contributing to substantial degradations in driver performance, while safety belts have been demonstrated to play a vital role in mitigating injuries to crash-involved occupants. METHOD: This study examines the prevalence of cell phone use and safety belt non-use among the driving population through direct observation surveys. A bivariate probit model is developed to simultaneously examine the factors that affect cell phone and safety belt use among motor vehicle drivers. RESULTS: The results show that several factors may influence drivers' decision to use cell phones and safety belts, and that these decisions are correlated. PRACTICAL APPLICATIONS: Understanding the factors that affect both cell phone use and safety belt non-use is essential to targeting policy and programs that reduce such behavior.

Driver behavior during bicycle passing maneuvers in response to a Share the Road sign treatment.

The interaction of motorists and bicyclists, particularly during passing maneuvers, is an area of concern to the bicycle safety community as there is a general perception that motor vehicle drivers may not share the road effectively with bicyclists. This is a particular concern on road sections with centerline rumble strips where motorists are prone to crowd bicyclists during passing events. One potential countermeasure to address this concern is the use of a bicycle warning sign with a "Share the Road" plaque. This paper presents the results of a controlled field evaluation of this sign treatment, which involved an examination of driver behavior while overtaking bicyclists. A series of field studies were conducted concurrently on two segments of a high-speed, rural two-lane highway. These segments were similar in terms of roadway geometry, traffic volumes, and other relevant factors, except that one of the segments included centerline rumble strips while the other did not. A before-and-after study design was utilized to examine changes in motor vehicle lateral placement and speed at the time of the passing event as they relate to the presence of centerline rumble strips and the sign treatment. Centerline rumble strips generally shifted vehicles closer to the bicyclists during passing maneuvers, though the magnitude of this effect was marginal. The sign treatment was found to shift motor vehicles away from the rightmost lane positions, though the signs did not significantly affect the mean buffer distance between the bicyclists and passing motorists or the propensity of crowding events during passing. The sign treatment also resulted in a 2.5miles/h (4.0km/h) reduction in vehicle speeds. Vehicle type, bicyclist position, and the presence of opposing traffic were also found to affect lateral placement and speed selection during passing maneuvers.

Optical bioassay for measuring sublethal toxicity of insecticides in Daphnia pulex.

Many emerging contaminants tend to be biologically active at very low concentrations, occur in water as part of complex mixtures, and impact biota in ways that are not detected using traditional toxicity tests (e.g., median lethal concentration). To evaluate emerging contaminants, the authors developed a method for detecting sublethal behavioral effects by quantifying the swimming behavior of Daphnia pulex, a model organism for studying aquatic toxicity. This optical tracking technique is capable of measuring many swimming parameters, 2 of which-cumulative distance and angular change-are presented. To validate this technique, 2 prototypical compounds that exhibit different modes of action as well as corresponding insecticides that are commonly found in surface waters were investigated. The acetylcholinesterase (AChE) inhibitor physostigmine was used as the prototypical compound for the large number of AChE inhibitor insecticides (e.g., chlorpyrifos). Nicotine was used as the prototypical compound for neonicotinoid insecticides (e.g., imidacloprid). Results demonstrate that this assay is capable of detecting sublethal behavioral effects that are concentration-dependent and that insecticides with the same mode of action yield similar results. The method can easily be scaled up to serve as a high-throughput screening tool to detect sublethal toxic effects of a variety of chemicals. This method is likely to aid in enhancing the current understanding of emerging contaminants and to serve as a novel water-quality screening tool.

Examination of factors determining fault in two-vehicle motorcycle crashes.

Motorcycle crashes frequently involve a combination of high-risk behaviors by the motorcyclist or the other crash-involved driver. Such behaviors may include riding or driving without appropriate licensure or while under the influence of alcohol, as well as deciding not to use a safety device such as a helmet or safety belt. Given that these factors frequently occur in combination with one another, it is difficult to untangle the specific effects of individual factors leading up to the crash outcome. This study assesses how various rider-, driver-, and other crash-specific factors contribute to at-fault status in two-vehicle motorcycle crashes, as well as how these same factors affect the propensity for other high-risk behaviors. Furthermore, the interrelationships among fault status and these other behaviors are also examined using a multivariate probit model. This model is developed using police-reported crash data for the years 2006-2010 from the State of Ohio. The results show that younger motorcyclists are more likely to be at-fault in the event of a collision, as are riders who are under the influence of alcohol, riding without insurance, or not wearing a helmet. Similarly, motorcyclists were less likely to be at-fault when the other driver was of younger age or was driving under the influence of alcohol, without insurance, or not wearing their safety belt. Crash-involved parties who engaged in one high-risk behavior were more likely to engage in other such behaviors, as well, and this finding was consistent for both motorcyclists and drivers. The results of this study suggest that educational and enforcement strategies aimed at addressing any one of these behaviors are likely to have tangential impacts on the other behaviors, as well.

The statistical analysis of highway crash-injury severities: a review and assessment of methodological alternatives.

Reducing the severity of injuries resulting from motor-vehicle crashes has long been a primary emphasis of highway agencies and motor-vehicle manufacturers. While progress can be simply measured by the reduction in injury levels over time, insights into the effectiveness of injury-reduction technologies, policies, and regulations require a more detailed empirical assessment of the complex interactions that vehicle, roadway, and human factors have on resulting crash-injury severities. Over the years, researchers have used a wide range of methodological tools to assess the impact of such factors on disaggregate-level injury-severity data, and recent methodological advances have enabled the development of sophisticated models capable of more precisely determining the influence of these factors. This paper summarizes the evolution of research and current thinking as it relates to the statistical analysis of motor-vehicle injury severities, and provides a discussion of future methodological directions.

Mixed logit analysis of bicyclist injury severity resulting from motor vehicle crashes at intersection and non-intersection locations.

Standard multinomial logit (MNL) and mixed logit (MXL) models are developed to estimate the degree of influence that bicyclist, driver, motor vehicle, geometric, environmental, and crash type characteristics have on bicyclist injury severity, classified as property damage only, possible, nonincapacitating or severe (i.e., incapacitating or fatal) injury. This study is based on 10,029 bicycleinvolved crashes that occurred in the State of Ohio from 2002 to 2008. Results of likelihood ratio tests reveal that some of the factors affecting bicyclist injury severity at intersection and non-intersection locations are substantively different and using a common model to jointly estimate impacts on severity at both types of locations may result in biased or inconsistent estimates. Consequently, separate models are developed to independently assess the impacts of various factors on the degree of bicyclist injury severity resulting from crashes at intersection and non-intersection locations. Several covariates are found to have similar impacts on injury severity at both intersection and non-intersection locations. Conversely, six variables were found to significantly influence injury severity at intersection locations but not non-intersection locations while four variables influenced bicyclist injury severity only at non-intersection locations. In crashes occurring at intersection locations, the likelihood of severe bicyclist injury increases by 14.8 percent if the bicyclist is not wearing a helmet, 82.2 percent if the motorist is under the influence of alcohol, 141.3 percent if the crash-involved motor vehicle is a van, 40.6 percent if the motor vehicle strikes the side of the bicycle, and 182.6 percent if the crash occurs on a horizontal curve with a grade. Results from non-intersection locations show the likelihood of severe injuries increases by 374.5 percent if the bicyclist is under the influence of drugs, 150.1 percent if the motorist is under the influence of alcohol, 53.5 percent if the motor vehicle strikes the side of the bicycle and 99.9 percent if the crash-involved motor vehicle is a heavy-duty truck.