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The state of Michigan increased the maximum speed limit for passenger cars from 70 to 75 mph on 614 mi of rural freeways between May and June of 2017. The maximum speed limit for trucks was also increased from 60 to 65 mph on all freeways where the passenger car limit was 65 mph or above. This study examined the effects of these changes on traffic speed characteristics. Speed data were collected before the speed limit increases were introduced, as well as at several intervals afterward using three different data sources. Free-flow speed data were collected from spot-speed studies using light detection and ranging (LIDAR) devices whereas aggregate-level traffic speed data were obtained from both permanent traffic recorder (PTR) stations, as well as from probe vehicle data. These data were integrated with associated roadway and traffic characteristics and the impacts of the speed limit changes were evaluated using seemingly unrelated regression equations, which provide insights into how these increases affected the 15th, 50th, and 85th percentile speeds, as well as the standard deviation in speeds. Regardless of data source, the results consistently showed increases in each speed metric. However, the magnitude of these increases varied from 1.1 to 3.2 mph depending on the specific metric and data source. Marginal changes in speeds were observed at sites where speed limits were not changed, suggesting limited spillover effect. Several site-specific characteristics were also correlated with speed selection, with these effects being less pronounced when considering free-flow and probe vehicle data as compared to PTR.

Posted speed limits inform drivers of the legal maximum allowable speed. In contrast, advisory speeds provide recommendations to drivers based on highway design, operating characteristics, and conditions. Various studies have investigated the safety impacts of speed limit changes, particularly on high-speed rural highways. One area of particular concern on such roadways is the approach to exit ramps that require substantive speed reductions, such as loop ramps. To date, there has been limited research examining the safety impact of the differential between the mainline speed limit and the lower exit ramp advisory speeds. This study aims to evaluate this relationship through the estimate of a series of safety performance functions. Random effects negative binomial regression models were estimated using data from 187 exit ramps where advisory speed signs are present throughout Michigan. The analyses were conducted based on a five-year period from 2014 to 2019, excluding 2017 data because of speed limit increases. In addition to speed differentials, various roadway characteristics such as deceleration lane length and curve radius were also evaluated. Results indicate that crashes increased as the difference between mainline and ramp speed increased. Crashes were also shown to decrease on ramps where the upstream deceleration lane length was greater than the minimum recommendation as per current design guidance.

Alternative intersection designs can offer safety and operational benefits with potentially lower costs than conventional intersections when implemented in the proper setting. The Federal Highway Administration has previously identified a subset of alternative designs called reduced left-turn conflict intersections as a proven safety countermeasure. Median U-turn intersections (also known as “Michigan lefts” or “boulevard turnarounds”) are one such design that accommodates all left-turn movements via directional U-turn crossovers within the median. Prior work has consistently shown that median U-turn intersections can provide superior safety performance when used in the appropriate conditions. However, research that is specific to unsignalized reduced left-turn conflict intersections continues to be limited to work conducted before the Highway Safety Manual, or which includes restricted crossing U-turn intersections. This study included the evaluation of historical traffic crashes and volume data at 95 unsignalized intersections in the state of Michigan. This included the collection of data for 39 median U-turn sites and 56 reference group sites to estimate safety performance functions and crash modification factors that can be used when considering future conversions. Ultimately, crash modification factors for fatal and injury crashes of 0.438 and 0.686 are recommended when converting intersections with undivided two-lane two-way major approaches and four-lane divided boulevard major approaches, respectively. Although there was no significant difference in property damage only crashes associated with converting intersections with undivided, two-lane, two-way major approaches, a crash modification factor of 1.325 is recommended for property damage only crashes specific to conversions with four-lane, divided boulevard major approaches.

Automated Vehicles (AVs) must comply with traffic laws, including those requiring motorists to maintain safe distances when passing pedalcyclists. We review relevant U.S. legislation, statistics of traffic accidents in the U.S. resulting in pedalcyclists fatalities, and present “what if” scenarios for AV and pedalcyclist interactions to illustrate safety-preserving algorithms' necessary ethical considerations. We identify a need for pervasive cyclist identification to improve situational awareness and propose as a solution the concept of using AV-mounted Bluetooth receivers for identifying and localizing a pedalcyclist's "beaconing" Bluetooth device, e.g. a preexisting, low-cost performance monitoring system. This method estimates the distance-to-bicycle from the receivers' Received Signal Strength Indicator (RSSI). Experimental results prove its feasibility for coarse pedalcyclist localization. Such a system may augment contemporary vision-based detection systems, thereby improving detection resilience and safety, particularly in dark or poor weather conditions.

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.

Transportation agencies have increasingly been using dynamic message signs (DMS) to communicate safety messages in an effort to both increase awareness of important safety issues and to influence driver behavior. Despite their widespread use, evaluations as to potential impacts on driver behavior, and the resultant impacts on traffic crashes, have been very limited. This study addresses this gap in the extant literature and assesses the relationship between traffic crashes and the frequency with which various types of safety messages are displayed. Safety message data were collected from a total of 202 DMS on freeways across the state of Michigan between 2014 and 2018. These data were integrated with traffic volume, roadway geometry, and crash data for segments that were located downstream of each DMS. A series of random parameters negative binomial models were estimated to examine total, speeding-related, and nighttime crashes based on historical messaging data while controlling for other site-specific factors. The results did not show any significant differences with respect to total crashes. Marginal declines in nighttime crashes were observed at locations with more frequent messages related to impaired driving, though these differences were also not statistically significant. Finally, speeding-related crashes were significantly less frequent near DMS that showed higher numbers of messages related to speeding or tailgating. Important issues are highlighted with respect to methodological concerns that arise in the analysis of such data. Field research is warranted to investigate potential impacts on driving behavior at the level of individual drivers.

Distracted driving is among the leading causes of motor vehicle crashes in the United States, though the magnitude of this problem is difficult to quantify given limitations of police-reported crash data. This study leveraged data from the second Strategic Highway Research Program Naturalistic Driving Study to gain important insights into the risks posed by driver distraction on both freeways and two-lane highways. More than 50 types of secondary tasks were aggregated into ten distraction type categories and mixed-effects logistic regression models were estimated to discern how the risks of near-crash events varied by distraction type while controlling for the effects of driver, roadway, and traffic characteristics. In general, the types of distractions that created the most pronounced risks were those that introduced a combination of cognitive, visual, and manual distractions. For example, drivers who used cell phones were subject to higher risks and these risks tended to be most pronounced when both visual and manual distractions were involved. Likewise, risks tended to be highest when drivers reached for other objects inside the vehicle, engaged in personal hygiene-related activities, or focused on activities occurring outside of the driving environment. Although the same factors tended to increase near-crash risk on both types of facilities, the impacts of several factors tended to be more pronounced on two-lane highways where interaction with other vehicles occurred more frequently. From a policy standpoint, the results of this study provide further motivation for more aggressive legislation and enforcement of distracted driving.

In recent years numerous transportation agencies have begun displaying creative safety messages like “get your head out of your apps” on dynamic message signs (DMS). DMS have been used traditionally to provide real-time information about travel times, weather conditions, construction, and incidents. Applying emotional and consequential concepts from protection motivation theory, which has a track record of leading to behavioral changes from public awareness campaigns, this study evaluates how the use of safety messages on DMS impacts driver perceptions. We find that emotions, but not consequences, impact self-reported driving behavior. Further, while drivers reported negative emotions would change their driving habits, positive messages were recalled far more often. Cell phone related messages were recalled most frequently despite being rarely displayed along roadways in Michigan where the study is conducted. Thus, the results support the use of positively themed messages with consequences that drivers perceive as realistic.

Move-over laws are intended to enhance the safety of road agency and law enforcement personnel who are working on or near the roadway. This study examined driver behavior through a series of field studies where these types of vehicles were located on the outside shoulder of a freeway with their lights activated. The study also evaluated the use of upstream dynamic message signs (DMS) to discern whether targeted safety messages had any impact on behavior under this scenario. Upstream and downstream speed and lane position data were collected from vehicles originally traveling in the rightmost lane upstream of the DMS and emergency/service vehicle at two locations in Michigan. Logistic regression models were estimated to assess driver compliance with the law while considering important contextual factors, such as the type of vehicle on the shoulder and the message displayed on the DMS. The results indicated that drivers were more likely to move over or reduce their speeds when a police car was located on the shoulder as compared to a transportation agency pickup truck. In general, the type of message displayed had minimal impact on driver behavior. The one exception showed that drivers were likely to drive at or below the speed limit when targeted move-over messages were shown as compared to standard travel time messages. For all message types, both speed and lane compliance improved if the roadside vehicle was a police car.

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

Research was conducted to assess the effectiveness of a dynamic speed feedback sign (DSFS) as a speed reduction strategy at speed transition zones along five high-speed rural highways in northern Michigan. The DSFS was positioned on the shoulder in advance of the reduced speed limit at each community and was programmed to display speeds of approaching vehicles alternating with the upcoming reduced speed limit. Using handheld LIDAR guns, vehicle speeds were tracked through each speed transition area before and after installation of the DSFS. The DSFS was found to have a significant speed reduction effect throughout each of the five speed transition zones. The speed reductions generally began when the DSFS came into the motorists’ view, and the speed reduction effect increased as motorists approached DSFS. The greatest speed reduction effects were observed at the DSFS location itself, where speeds were 3.2 to 7.8 mph lower with the DSFS present, and these reductions were sustained on entry to the community. Similarly, drivers were 78.8 to 92.4% less likely to exceed the reduced speed limit with the DSFS present. Positioning the DSFS further upstream typically resulted in earlier speed reductions, although this effect became negligible once vehicles reached the reduced speed zone entering the community. Based on the study findings, continued use of DSFS for speed management at speed transition zones entering communities on high-speed rural roadways is recommended. When used in this context, the DSFS should be positioned 250 to 650 ft upstream of the reduced speed limit.

Snow removal activities are performed by roadway agencies to enhance winter mobility and safety. Slower travel speeds during these operations, combined with low visibility and reduced pavement friction, mean that safety and collision avoidance remain a persistent concern. Many studies have implemented signing and lighting technologies to improve the visibility of snowplows. Although a few studies have evaluated the use of different colors on snowplows, there is no rigorous study that evaluates the potential impacts of using green warning lights for winter maintenance operations. This study, therefore, investigates the impacts of various warning light configurations on the visibility of snowplows, with the focus on green lights. To this end, 37 warning light configurations are designed using various color combinations (green and amber), and flashing patterns (single and quad) on the back (LED), the top (beacon), or both, of snowplows. These configurations are evaluated to identify the most effective configurations. Three sets of experiments are designed and implemented: static, dynamic, and weather to evaluate the visibility effectiveness in different contexts: day versus night, clear versus snowy weather, and static versus dynamic scenarios. Human subjects are employed to conduct the experiments and the test results are evaluated using statistical analyses. The conspicuity during the day time and glare during the night time are statistically different among various configurations. In addition, adding green lights with a single flash pattern to amber warning lights improves the conspicuity, while keeping the glare at an acceptable level relative to configurations using only amber.

Research has consistently demonstrated that seatbelt use is critically important in reducing the likelihood of fatal and serious injuries resulting from traffic crashes. However, after years of nationwide increases in seatbelt use, these rates have largely plateaued, motivating the need for research to better understand those circumstances under which seatbelt use remains relatively low. At an aggregate level, research has shown that occupants in the same vehicle tend to exhibit correlation in seatbelt use or non-use. This suggests that social dynamics may play a role in occupants’ decisions as to whether or not to wear a seatbelt. To that end, this study examines trends in seatbelt use among pairs of drivers and front-seat passengers using data from direct observation roadside surveys. Bivariate probit models are estimated to examine the relationship between seatbelt use and various demographic, vehicle, and site-specific factors. The bivariate framework is also able to account for correlation among important unobserved factors associated with seatbelt use. The results show significantly better fit as compared with independent univariate probit models. The results also suggest both direct and indirect relationships between seatbelt use and various demographic, vehicle, and site characteristics. Seatbelt use rates are found to vary based on occupants’ age, gender, and race. Furthermore, seatbelt use by both the driver and front-seat passenger is also shown to vary based on the other occupant’s age. Heterogeneity is also shown across various geographic regions and roadway functional classes.

Since the mid-2000s, Public-Private Partnerships (PPP) have been established in transportation infrastructure projects as an effective alternative to the traditional procurement process, such as design-bid-build where the design and construction are awarded separately and sequentially to private firms. PPP contracts ensure both greater participation of the private sector, as well as shared responsibility in project delivery. However, the interrelationship between various PPP approaches and the status of traffic safety during the project implementation has not been thoroughly explored to date. This paper seeks to provide new insights into the performance of different PPP contracting approaches by investigating them from the perspective of transportation safety. To that end, a statistical analysis is conducted in order to distinguish differences with respect to the characteristics of crashes that occurred during the contractual period of roadway projects. Using data from 645 PPP contracts that were executed across multiple States of the US between 1996 and 2011, count data models of crash frequencies are developed. To take into account the effect of unobserved factors on crash frequencies, correlated random parameter models with heterogeneity in the means are estimated. The results of the statistical analysis overall show that the determinants of crash frequencies and the magnitude of their impacts vary across PPP types. Contracts with higher cost, shorter duration, fewer lane-miles to be covered, more asset work activities, as well as contracts for roadways featuring better pavement and drainage conditions, low to medium AADT, and higher width of shoulder are more likely to observe fewer crashes. Additionally, several variables resulted in correlated random parameters (such as, contract size in lane-miles and truck percentage), with their distributional characteristics being affected by other exogenous factors (such as pavement characteristics), thus unveiling the heterogeneous patterns underpinning the safety performance of different PPP approaches.

Research was undertaken to determine effective messaging strategies and sign positions for dynamic speed feedback signs (DSFS) when used for speed management at freeway ramp curves. A field evaluation was performed in this setting to assess the impacts of a DSFS on driver speed selection and braking characteristics while approaching and entering the curve. Three feedback messaging strategies were evaluated at three sign positions in advance of the curve. Compared with the existing site (without the DSFS), the DSFS reduced curve entry speeds and improved brake response across all test conditions, particularly for heavy trucks. Overall, considering the combination of both sign position and feedback messaging strategy, the greatest benefits to driver behavior were attained when the DSFS was positioned 255 ft upstream of the curve and the feedback message included the speed number alternating with a SLOW DOWN message. The inclusion of an advisory speed panel with the DSFS did not have a substantive impact on driver behavior. Based on the findings, the continued use of DSFS as a speed reduction treatment at freeway ramp curves is recommended. Specifically, the sign should be positioned to provide adequate time for drivers to perceive and react to the message, such that comfortable braking can be accommodated while approaching the curve. However, the sign should not be placed too far in advance of the curve, as drivers may be more likely to disregard such a premature warning message. Further evaluation of DSFS under various alternative ramp configurations is recommended.

Cell phone use is among the most prevalent types of in-vehicle distractions. Studies have shown cell phones to have a negative impact on driving performance, with the magnitude of these impacts varying based on the level of engagement required for phone use, as well as the complexity of the driving environment. The development of effective policies and programs to mitigate distracted driving is contingent on an improved understanding of the nature of these relationships. To this end, this study investigates the rate of cell phone use under various settings through a statewide direct observation survey. Data were collected from 200 roadside locations throughout the State of Michigan and a random effects multinomial logit model was estimated to assess how the prevalence of cell phone use varies across drivers. While several studies have investigated the prevalence of cell phone use, this study distinguishes differences in the manner of cell phone use (i.e., talking on a handheld device versus manual manipulation of the device) across drivers while controlling for important contextual factors. The results show cell phone use is generally higher among female drivers and use rates consistently decrease with age. The prevalence of cell phone use is also shown to vary significantly depending on the manner of use. Use rates are shown to differ based on changes in the driving environment, suggesting potential risk compensation on the part of motorists. The results also show a significant correlation in use rates at the same sites over time, which is reflective of important unobserved site-specific factors.

The installation of “active” warning devices, such as crossing signals and gates, is a principal element of state and federal railroad crossing safety programs, and their effectiveness in preventing vehicle–train collision is well documented. While most active crossings are occupied by trains only a few minutes each day, non-crashworthy items are frequently present at active crossings including crossing signal masts, crossing gate mechanisms, cantilever supports, and signal controller bungalows. Various agencies utilize longitudinal guardrail systems to protect errant motorists from striking non-frangible crossing signal hardware. This study sought to determine whether such guardrails influence the prevalence and severity of motor vehicle strikes involving crossing hardware. A review of 10 years of police crash-report narratives in Iowa, United States (U.S.) indicates an average of 15.6 crashes per year at 1,853 crossings involving signal masts, signal guardrails, or related infrastructure. Over this period, one fatality and five serious injuries occurred as a result of these crashes. The crash-injury severity distributions appeared similar in crashes with and without guardrail, and regression models showed that guardrail presence did not affect the rate of crashes involving railroad apparatus. Although the use of longitudinal guardrail systems did not appear to have a strong effect on crash rates or severity at active grade crossings, other methods for reducing crash prevalence and severity could be explored in future research, such as the development of crashworthy signal assemblies for flashing-signal-only crossings and the redesign of gate and cantilever supports to increase separation from the traveled way.

Access management strategies, such as the introduction of minimum access point spacing criteria and turning movement restrictions, have been shown to be important elements in optimizing the operational and safety performance of roadway segments. The relationship between safety and these types of access policies is a complex issue, and the impacts of such features on traffic crashes is critical to the development of appropriate access management strategies. The purpose of this study was to provide a quantitative evaluation of how crash risk on multilane and two-lane highways varies with respect to access spacing in support of the development of a revised access management policy. Data were obtained for approximately 1,247 and 5,795 mi of segments across multilane and two-lane highways, respectively. Crash data were obtained for a five-year period from 2012 to 2016 and a series of random effect negative binomial regression models were estimated for each facility to examine the association between crash frequency, access point spacing, and traffic volume. For both facility types, crashes were found to increase consistently as the average spacing of access points along road segments decreased. Crash rates were highest when consecutive accesses were within 150 ft of one another and the frequency of crashes decreased substantively as spacing was increased to 300 ft and, particularly, 600 ft. With spacing beyond 600 ft, crash rates continued to decrease, although these improvements were less pronounced than at the lower range of values. These findings were generally consistent on multilane and two-lane highways.

Motorcycle crashes and fatalities remain a significant public health problem as fatality rates have increased substantially as compared to other vehicle types in the United States. Analysis of causal factors for motorcycle crashes is often challenging given a lack of reliable traffic volume data and the fact that such crashes comprise a relatively small portion of all traffic crashes. Given these limitations, on-scene crash investigations represent an ideal setting through which to investigate the precipitating factors for motorcycle-involved crashes. This study examines motorcycle crash risk factors by employing data recently made available from the Federal Highway Administration Motorcycle Crash Causation Study (MCCS). The MCCS represents a comprehensive investigative effort to determine the causes of motorcycle crashes and involved the collection of in-depth data from 351 crashes, as well as the collection of comparison data from 702 paired control observations in Orange County, California. This dataset provides a unique opportunity to understand how the risk of crash involvement varies across different segments of the riding population. Logistic regression models are estimated to identify the rider and vehicle attributes associated with motorcycle crashes. The results of the study suggest that motorcycle crash risks are related to rider age, physical status, and educational attainment. In addition to such factors outside of the rider’s control, several modifiable risk factors, which arguably affect the riders’ proclivity to take risks, were also found to be significantly associated with motorcycle crash risk, including motorcycle type, helmet coverage, motorcycle ownership, speed, trip destination, and traffic violation history.

The relationship between traffic safety and speed limits has been an area of significant research. Since the repeal of the National Maximum Speed Law in 1995, states have full autonomy in establishing maximum statutory speed limits. Since 2001, at least 25 states have increased their maximum limits to speeds as high as 85 mph. This study examines changes in rural interstate fatalities from 2001 to 2016 in consideration of such increases. Speed limit policy data include the maximum speed limit for each state–year combination, as well as the proportion of rural interstate mileage posted at each speed limit in each state. Random parameter negative binomial models are estimated to control for unobserved heterogeneity, as well as time-invariant effects unique to each state. The results show that increasing the mileage of rural interstates posted at 70, 75, or 80 mph by 1% is associated with fatality increases of 0.2%, 0.5%, and 0.6%, respectively. These increases are more pronounced than when considering only the maximum statutory limits in each state. The study also examines the influence between these higher limits and the frequency of fatal crashes involving speeding and driver distraction. At the highest limits of 75 and 80 mph, the increases among these subsets of crashes are greater than the increases in total fatalities. Ultimately, this study provides important empirical evidence in support of continuing speed limit policy discussions, in addition to identifying salient analytical concerns that should be considered as a part of longitudinal analyses of state-level fatality data.

Access control remains an important concern to roadway agencies as the spacing of at-grade access points significantly affects both the safety and operational performance of highways. Significant variability exists with respect to policies dictating where the first access points may occur in the vicinity of interchanges. This study examines two important spacing criteria, which include: (1) the distance from the freeway off-ramp to the first access on the interchanging arterial roadway; and (2) the distance from a freeway on-ramp to the first at-grade intersection in areas with partial access control. To investigate these relationships, a series of crash prediction models were estimated that examined how crash risk changed with respect to access spacing while controlling for the effects of traffic volume and other pertinent characteristics. The results illustrate that at cross-streets near ramp terminal intersections, the crash rate generally increases as the distance to the nearest access point decreases. The same trend was also true of freeway transition areas. Ultimately, this research illustrates a complex relationship that exists among the proximity of the exit point of the controlled access facility and the adjacent access point, the volume of traffic along the roadway, and the volume of traffic at the access point.

Effective access management is critical to the safe and efficient operation of roadway corridors. Access management is particularly important near signalized intersections, where adjacent driveways exacerbate the crash risks created by conflict points at the primary intersection. This study examines the relationship between crash risk and access spacing in the vicinity of 415 signalized urban intersections. The frequency of access points near each signalized intersection of interest was collected to examine the differences in experienced crash frequency over a five-year period. Additional information about each access point was collected, including details of turning movement restrictions and estimated driveway volumes. A series of buffers of varying radii were considered to examine how crash rates varied based upon the spatial proximity of access points to each signalized intersection. In addition, traffic volume and roadway geometric information was collected and utilized as a part of this evaluation. A series of crash prediction models were estimated to discern how crash rates varied based upon the access point density on the intersection approaches along the major (i.e., higher volume) roadway. As the number of access points increased, the crash rates also increased. This relationship was consistent in direction, but varied in magnitude, depending on the size of the buffers, which varied in radius from 50 ft to 600 ft at 50-ft intervals. The number of crashes by location was also shown to vary based upon the number of travel lanes, the number of intersection legs, and the land use type of the adjacent driveways.

Safety performance functions (SPFs) were developed for rural two-lane county roadway segments in Michigan. Five years of crash data (2011 to 2015) were analyzed for greater than 6,500 mi of rural county roadways, covering 29 of Michigan’s 83 counties and representing all regions of the state. Three separate models were developed to estimate annual deer-excluded total and injury crashes on rural county roadways: 1) paved federal-aid segments, 2) paved non-federal-aid segments, and 3) paved and gravel non-federal-aid segments with fewer than 400 vpd. To account for the unobserved heterogeneity associated with differing county design standards, mixed effects negative binomial models with a county-specific random effect were utilized. Not surprisingly, the county segment SPFs generally differed from traditional models generated using data from state-maintained roadways. County federal-aid roadways general showed greater crash occurrence than county non-federal-aid roadways, the Highway Safety Manual (HSM) two-lane rural roadways model, and rural state highways in Michigan. County non-federal-aid paved roadways showed crash occurrence rates that were remarkably similar to the HSM base rural two-lane roadway model, whereas gravel roadways showed greater crash occurrence rates. The presence of horizontal curves with design speeds below 55 mph had a strong association with the occurrence of total and injury crashes across all county road classes. Increasing driveway density was also found to be associated with increased crash occurrence. However, lane width, roadway surface width, and paved shoulder width had little to no impact on total or injury crashes.

Limited access facilities, such as freeways and expressways, are generally designed to the highest standards among public roads. Consequently, these facilities demonstrate crash, injury, and fatality rates that are significantly lower than other road facility types. However, these rates are generally elevated in the immediate vicinity of interchanges because of increases in traffic conflicts precipitated by weaving, merging, and diverging traffic. Given the extensive costs involved in interchange construction, it is important to discern the expected operational and safety impacts of various design alternatives. To this end, the objective of this study was to analyze safety performance within the functional areas of interchanges. The study involves the integration of traffic crash, volume, and roadway geometric data from 2010 to 2014 in the state of Iowa. Separate analyses were conducted for the freeway mainline and ramp connections. A series of safety performance functions (SPFs) were estimated for both the mainline and ramps. Random effects negative binomial models were estimated, which account for correlation in crash counts at the same location over time. The results show the frequency of crashes to vary based on traffic volume, interchange configuration, speed limit, and traffic control at the ramp terminal. The random effects models are shown to significantly outperform pooled models, which suggest there are several important location-specific factors that are not included in the analysis dataset. The SPFs from this study are also compared with several reference models from the extant research literature.

Introduction Prior research has shown the probability of a crash occurring on horizontal curves to be significantly higher than on similar tangent segments, and a disproportionally higher number of curve-related crashes occurred in rural areas. Challenges arise when analyzing the safety of horizontal curves due to imprecision in integrating information as to the temporal and spatial characteristics of each crash with specific curves. Methods The second Strategic Highway Research Program(SHRP 2) conducted a large-scale naturalistic driving study (NDS),which provides a unique opportunity to better understand the contributing factors leading to crash or near-crash events. This study utilizes high-resolution behavioral data from the NDS to identify factors associated with 108 safety critical events (i.e., crashes or near-crashes) on rural two-lane curves. A case-control approach is utilized wherein these events are compared to 216 normal, baseline-driving events. The variables examined in this study include driver demographic characteristics, details of the traffic environment and roadway geometry, as well as driver behaviors such as in-vehicle distractions. Results Logistic regression models are estimated to discern those factors affecting the likelihood of a driver being crash-involved. These factors include high-risk behaviors, such as speeding and visual distractions, as well as curve design elements and other roadway characteristics such as pavement surface conditions. Conclusions This paper successfully integrated driver behavior, vehicle characteristics, and roadway environments into the same model. Logistic regression model was found to be an effective way to investigate crash risks using naturalistic driving data. Practical Applications This paper revealed a number of contributing factors to crashes on rural two-lane curves, which has important implications in traffic safety policy and curve geometry design. This paper also discussed limitations and lessons learned from working with the SHRP 2 NDS data. It will benefit future researchers who work with similar type of data.

Autonomous vehicles (AVs) typify the nexus of smart Internet-based technology and prior innovations in transportation. A challenge with AV research is that the technology is not yet readily available for consumers to experience. Thus, public perceptions of AVs are often assessed through survey research which has uncovered demographic and socio-economic differences in the willingness to adopt and pay for AVs. It has also provided information about the perceived benefits and risks associated with AVs and how these perceived benefits and risks affects support for self-driving car technology. More recently, studies have found that political ideology is linked to perceived concerns about self-driving cars but have not yet assessed whether this link extends to the intent to adopt AVs. Given this gap in our knowledge, the contributions of the present paper our twofold. One, we will assess whether political ideology impacts the intention to adopt AVs. Two, we will assess whether political ideology directly or indirectly affects the intention to adopt AVs. As regards the latter, we will conduct a mediation analysis with a path model to assess the extent that political ideology indirectly affects the intention to adopt via the perceived benefits and concerns survey respondents expressed about AVs. Our results reveal political ideology is an important predictor of individuals’ intent to adopt AVs, as characterized by both willingness to ride in and to own AVs. Specifically, compared to conservative participants, moderates and liberals reported higher AV adoption intentions. We also find that the effect of political ideology on AV adoption intention is mediated by participants’ perceived benefits and concerns about AVs. Compared to conservatives, political moderates reported AV adoption intention via higher perceived benefits about AVs. Compared to conservatives, liberals reported higher AV adoption intention through both higher perceived benefits and lower perceived concerns about AVs.

The flipped-classroom approach has gained increasing popularity and interest in engineering education. The purpose of this study was to investigate (a) student perspectives on the flipped-classroom approach in a transportation-engineering course and (b) how students used the in-class time dedicated to collaborative problem solving. To this end, the study adopted a mixed-methods approach. Quantitative data included an end-of-semester survey and student course grades. Qualitative data included information from focus-group interviews with students and video recordings that demonstrated selected groups’ problem-solving processes. The results indicated that students found their flipped-classroom experience to be generally positive. Students were shown to engage in five types of behaviors during collaborative problem solving: problem analysis or understanding, individually working on problems, comparing individual work, interacting with peers, and interacting with the instructor.

Work zone temporary traffic control strategies generally affect both traffic safety and operations. However, there is a substantial gap in the knowledge base with respect to the safety impacts of various work zone characteristics. The Highway Safety Manual provides crash modification functions that account for the effects of project length and duration on crash frequency as compared with normal road operations. However, these methods do not allow for explicit comparisons of expected safety performance among different work or closure types. This research examined the safety impacts of various temporary traffic control strategies on freeways, including shoulder closures, lane closures, and lane shifts. Data were collected for the periods during which these treatments were in effect and during similar nonconstruction periods from the preceding year. Safety performance functions were estimated that account for segment length, duration, traffic volume, and closure type. Random parameter count data models were estimated to accommodate segment-specific temporal correlation and unobserved heterogeneity. Crash rates were shown to vary roughly in proportion to traffic volumes. In contrast, segment length and project duration showed inelastic effects; this finding implies that crash rates increase more rapidly in work zones that are shorter in length or duration. Single-lane closures, multilane closures, and lane shifts were associated with an increase in crashes, whereas shoulder closures did not show a significant difference compared with similar, non-work-zone conditions. Ultimately, the study results provide important information that can be used to assess the crash risk for various temporary traffic control strategies.

Speed limits on rural highways have recently been on an upward trend nationwide as 25 states have increased speed limits on such roadways between 2011 and 2016. In January 2017, Michigan House Bill 4423 (Public Act 445) was signed into law, which required speed limits to be raised from 55 to 65 mph on at least 900 mi of Michigan’s state-maintained nonfreeways. The specific highway segments were to be selected by the Michigan Department of Transportation (DOT) within 1 year of enactment on the basis of an assessment of travel speeds and safety. Research was undertaken to develop a process to select candidate highway segments for speed limit increases in Michigan. The primary objective was to identify rural highway segments with comparatively low safety risks for which costly geometric upgrades, specifically horizontal or vertical realignment, would be avoided. Ultimately, 12 factors and associated selection criteria were used to identify the candidate segments. These factors included segment length, total crash rate, injury crash rate, severe (fatal and A-injuries) crash rate, horizontal curvature, speed reduction zones, no-passing zones, schools (kindergarten through eighth grade), driveway density, lane width, paved shoulder width, and signalized intersections. Application of the candidate selection criteria to the Michigan DOT nonfreeway network yielded 772.8 centerline miles along 33 candidate segments, which represented approximately one-eighth of the network mileage currently posted at 55 mph. To avoid substantial geometric upgrade costs, speed limit increases were specifically not recommended for segments that would require horizontal or vertical realignment to achieve design speed compliance with the increased speed limit.

As of November 2016, Montana was the only state to maintain a differential speed limit on two-lane two-way rural highways, with a daytime statutory speed limit of 70 mph for cars and light trucks and 60 mph for trucks exceeding a 1-ton payload capacity. Although differential speed limits are common on freeways, the use of differential limits on two-lane roadways presents unique safety and operational issues because of passing limitations and the resultant platooning that occurs. Given these concerns, the speed limit was changed from the differential 70 mph to 60 mph speed limit to a uniform 65 mph limit for all vehicles along 55 mi of two-lane highway in April 2013. This study evaluated the short-term operational and safety impacts associated with this transition. Given the limited time period over which data were available following the speed limit change, surrogate safety measures were investigated to provide immediate feedback as to these impacts. A series of field studies was performed on two-lane rural highways in Montana, which predominantly possessed the 70 mph to 60 mph differential speed limit, as well as on selected locations along the 55 mi where the uniform speed limit was implemented. The locations with 65 mph speed limits generally exhibited shorter platoon lengths and less high-risk passing behavior. Overall, the preliminary findings provide some general support for transitioning to a uniform 65 mph speed limit on two-lane rural highways.

Intersections experience a disproportionate share of traffic crashes, injuries, and fatalities because of the increased number of conflicting traffic movements at these locations. These issues are particularly pronounced at rural locations where speeds are generally higher and most intersections are either stop- or yield-controlled. Ideally, intersecting roadways should be oriented at as close to a 90-degree angle as possible. However, intersection design can diverge from this preferred configuration and result in a skewed intersection. Skewed intersections have been found to cause safety and operational issues for road users. To determine the effect of intersection skewness on crash frequency, crash prediction models were estimated for rural stop-controlled intersections on high-speed two-lane highways throughout the state of Iowa. Separate analyses were conducted for three-leg and four-leg intersections. In both cases, crash frequency was estimated as a function of annual average daily traffic, skew angle, and other salient geometric characteristics. The results consistently showed crash frequency to increase with skew angle. A 10-degree deviation from 90 degrees would result in 3% more crashes at three-leg intersections and 4% more crashes at four-leg intersections. In addition, crashes were affected by the volume of heavy vehicles, whether the approaches were paved or unpaved and whether intersection lighting was present.

Recently, several states have revisited their laws governing cannabis possession and consumption. Whereas some states have legalized cannabis use at different levels (i.e., legal recreational use, decriminalized possession, or legal medical use), others have zero tolerance. This study used 5 years of data (2010 to 2014) from the Fatality Analysis Reporting System to assess differences across states with various laws for cannabis use. Random parameter logistic regression models were estimated to examine differences in the prevalence of positive cannabis tests across states while controlling for other salient factors, including driver and roadway characteristics. The findings demonstrate that drivers in states with more lenient laws for cannabis possession and consumption were more likely to test positive compared with drivers in states with zero tolerance. In addition, ordinal logistic regression models were estimated to assess the relationships between injury severity, cannabis laws, and other factors associated with crash injury outcomes. The results suggest driver injuries were more severe when the driver tested positive for cannabis. A strong association was also observed between blood alcohol content and cannabis test results. Ultimately, the results provide evidence in support of continuing research to better understand the public health impacts of cannabis use as more states consider changes to the laws governing possession and consumption.

Field studies were performed to compare the effectiveness of traffic control countermeasures commonly used at uncontrolled midblock crosswalks. Various crosswalk treatments were evaluated at 31 low-speed midblock crosswalks located near three public universities. The study locations included unmarked crosswalks, in addition to standard and continental crosswalk markings, some including an additional enhancement device such as the pedestrian hybrid beacon (PHB), rectangular rapid flashing beacon (RRFB), or an in-street R1–6 sign. Driver yielding compliance during staged pedestrian crossing events was used as the measure of effectiveness. To isolate the crosswalk treatment effects, several roadway and traffic characteristics were included in the analysis, including the crossing distance, median presence, vehicular and pedestrian volumes, travel lane of the subject vehicle, and the subject vehicle’s position in a queue. A mixed effects logistic regression model was used to account for correlation in yielding rates within the same sites as well as for unobserved heterogeneity across locations. The results indicate that the type of crosswalk treatment has a strong influence over driver yielding compliance. While yielding compliance improved substantially when crosswalk markings were used, the highest compliance rates were achieved when an additional enhancement device (i.e., RRFB, PHB, or R1–6 sign) was also provided. Yielding compliance showed little sensitivity to the particular travel lane of the subject vehicle at locations where a crosswalk enhancement device was used, further validating the effectiveness of these treatments. Finally, yielding compliance rates were generally higher across each of the crosswalk enhancement devices compared with prior studies performed in the same areas, suggesting compliance improves as drivers become more familiar with these devices.

Design practices in the United States generally allow substantial flexibility in the design of cross-sectional elements of urban and suburban arterial roadways. The operational and safety performance of such facilities is influenced by a variety of design controls, which influence the selection of important cross-sectional components, such as the number of lanes, lane widths, and the presence of shoulders, medians, or on-street parking. This study assesses the effects of lane width on the safety performance of urban and suburban arterial segments in the State of Nebraska. Ten years of traffic crash, volume, and roadway geometry data are analyzed to discern differences in the frequency of sideswipe-same direction and rear-end collisions across four functional classes of urban arterials. Crashes generally decreased as lane width increased, with 10-ft. lanes experiencing 18.1% more rear-end crashes and 27% more same-direction sideswipe collisions. In general, 12-ft. lanes showed fewer crashes than 11...

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.

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.

The objectives of this study were to assess the in-service safety performance of roadside culverts and evaluate the potential impacts of installing various safety treatments to mitigate the severity of culvert-involved crashes. Such crashes were identified using standard fields on police crash report forms, as well as through a review of pertinent keywords from the narrative section of these forms. These crashes were then linked to the nearest cross-drainage culvert, which was associated with the nearest road segment. A negative binomial regression model was then estimated to discern how the risk of culvert-involved crashes varied as a function of annual average daily traffic, speed limit, number of travel lanes, and culvert size and offset. The second stage of the analysis involved the use of the Roadside Safety Analysis Program to estimate the expected crash costs associated with various design contexts. A series of scenarios were evaluated, culminating in guidance as to the most cost-effective treatments for different combinations of roadway geometric and traffic characteristics. The results of this study provide an empirical model that can be used to predict the risk of culvert-involved crashes under various scenarios. The findings also suggest that the installation of safety grates on culvert openings provides a promising alternative for most of the cases where the culvert is located within the clear zone. In general, a guardrail is recommended when adverse conditions are present or when other treatments are not feasible at a specific location.

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.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.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.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.

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.

Recently, nationwide speed limit policy modifications have resulted in a general upward trend in many states, including Michigan. In Michigan legislation has been proposed to raise posted speed limits on limited access freeways for passenger vehicles and for trucks and buses. In response, research was performed to assess the economic impacts associated with speed limit policy alternatives under consideration. The economic assessment included estimation of the agency costs and user benefits and disbenefits for each proposed policy alternative, including those related to infrastructure modifications, fuel consumption, travel time, and fatal crash occurrence. Calculation of the benefit–cost ratios indicated several findings. First, scenarios that increased only the freeway truck and bus speed limit from 60 mph to 65 or 70 mph had favorable benefit–cost ratios (i.e., greater than 1) as long as diesel prices remained below approximately $3 per gallon and fatal crashes did not increase by more than one per year systemwide. However, implementation of the 75 or 80 mph maximum freeway speed limit for passenger vehicles (70 mph for trucks and buses) in general resulted in unfavorable benefit–cost ratios. The reasons in large part were the expected increase in fatal crash occurrence, coupled with substantial infrastructure costs associated with geometric modifications that ultimately would be necessary to achieve compliance with state and federal design speed requirements. Therefore, freeway speed limit increases should be considered only for segments that have low historical crash rates and where design speed compliance can be maintained in general without costly geometric upgrades.

Cross-median crashes are among the most hazardous collision types on freeways. The primary countermeasure to reduce such crashes is the installation of a median barrier, with a cable barrier being a widely used alternative. As of 2014, approximately 317 mi of cable median barriers had been installed on freeways throughout Michigan. To assess the safety impacts of this installation program, a comprehensive before-and-after crash analysis was conducted; this analysis included a manual crash report review to identify all median-related crashes. Safety performance functions were developed for roadway segments before and after cable barrier installation, as well as for similar control segments where no barrier had been installed. The empirical Bayes (EB) method was used to develop crash modification factors as a function of median width. To explore the effects of regression to the mean (RTM), the EB results were compared with those from a naïve before–after analysis. The results showed that cable barriers significantly reduced the frequency of fatal and severe injury crashes, although substantial increases in less severe crashes were also observed. The cable barrier was found to have greater impacts on crashes across nearly all severity levels when used on narrow medians (i.e., 26 to 50 ft) compared with wider medians (50 to 94 ft). In addition, reductions in fatal and serious injuries were less pronounced when compared with prior research (especially for wider medians), which was largely attributed to RTM effects. Ultimately, this study provides important guidance to deal with the expected safety impacts (and related costs) associated with cable median barrier installation.

Speed management has been a long-standing concern of transportation agencies. Recently, nationwide speed limit policy modifications have resulted in a general upward trend in many states. In Michigan, legislation was proposed to raise the maximum speed limits on state-owned, rural, nonfreeway highways from 55 to 65 mph. In response to this proposed speed limit policy change, research was performed to assess the associated economic impacts through the use of benefit–cost analysis. Several potential implementation scenarios of the proposed speed limit policy were investigated; these included a limited subset of roadways with favorable geometry and full statewide implementation. A primary research task was to estimate the costs for infrastructure upgrades necessary to achieve compliance with state and federal design speed requirements for the cohort of roadways included within each 65 mph implementation scenario. User benefits and disbenefits associated with the proposed speed limit increase also were estimated, which included reduced travel times, increased fuel consumption, and increased traffic crashes. Although the travel time savings were estimated to exceed the fuel consumption costs, the resulting benefit was far outweighed by crash-related disbenefits and agency infrastructure costs for roadways that required major geometric modifications (e.g., vertical or horizontal realignment). Consequently, an increase in the speed limit to 65 mph on rural, nonfreeway highways should be considered only if the critical geometric elements can maintain design speed compliance without major modification. However, even for roadways on which design speed compliance is maintained, careful, site-specific consideration must be given to the potential safety impacts, particularly with respect to fatal and injury crashes, which may result after the speed limit is increased.

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. Environ Toxicol Chem 2015;34:1145–1153. © 2015 SETAC

Lane departures are a precipitating event in most fatal crashes in the United States. This problem is particularly pronounced on high-speed undivided highways, which are prone to cross-centerline crashes. A common countermeasure to reduce such crashes involves installing centerline rumble strips (CLRS), which provide an audible and tactile warning to alert drivers of an impending lane departure event. This study assessed the safety effects of a statewide CLRS implementation program conducted by the Michigan Department of Transportation (DOT) between 2008 and 2010. This program included the installation of CLRS across the Michigan DOT–maintained network of rural, high-speed nonfreeway facilities. Shoulder rumble strips (SRS) were installed in combination with the CLRS at locations with paved shoulders at least 6 ft in width. The empirical Bayes method was used to assess the effectiveness of 4,077 mi of two-lane highways where CLRS were installed as part of this initiative. CLRS were found to reduce target cross-centerline crashes by 27.3% and by 32.8% when used in combination with SRS. Rumble strips were also effective in reducing crashes that occurred under adverse pavement conditions or involved passing maneuvers or driver impairment. This study also provides important insights as to the identification of target (i.e., cross-centerline) crashes. A comprehensive manual review of more than 70,000 crash report forms demonstrated that approximately 10% of target crashes were misclassified by crash type, which is the predominant field typically used to identify such crashes.

The purpose of this study was to examine the travel speed characteristics of passenger vehicles, trucks, and buses in states with different speed limit policies, primarily to ascertain the effects of differential speed limits (DSLs) versus those of uniform speed limits (USLs) for large vehicles. Spot-speed studies were conducted in the neighboring states of Indiana, Michigan, and Ohio; these studies permitted examination of speed characteristics under several speed limit settings along the same freeways. The sites included urban and rural locations, with speed limits at individual locations that varied from 55 to 70 mph. These sites included USLs and DSLs, with 5 mph differentials on rural freeways in Indiana and 10 mph differentials at rural locations in Michigan. Spot-speed data were collected at 157 freeway sites in the three states along flat, tangent segments. Regression models were estimated to ascertain differences in the mean speeds, the 85th percentile speeds, and the standard deviation in speeds across locations. The results showed passenger vehicle speeds to be quite consistent across the three states where a common 70 mph limit was in effect. Speeds varied more at locations with lower posted limits and between trucks and buses. Speeds were most consistent in Ohio at locations with higher USLs. The variability in travel speeds for all vehicles was found to be highest on freeways with DSLs, followed by urban freeways with USLs of 55 mph.

Existing research literature has shown that traffic fatalities increase at higher speed limits. A related issue is the establishment of maximum speed limits for trucks and buses. As of 2014, eight states have a differential speed limit in place that establishes a higher limit for passenger vehicles than for trucks and buses. This study aimed to inform the continuing debate regarding the safety impacts of speed limits by comparing states with various speed limit policies. The study included a longitudinal comparison of state-level rural Interstate fatalities in the United States from 1999 through 2011. In addition to an examination of differences in traffic fatalities as a function of maximum speed limits, comparisons were also made between states with differential limits for truck and buses. Random parameter negative binomial models were estimated for annual total and truck-involved fatalities. A random parameter framework allowed for consideration of temporal correlation in annual fatality counts within states as well as for unobserved heterogeneity across states. The results of this study provided further evidence that both overall and truck-involved fatalities increased with maximum speed limits. States with differential speed limits were found to have marginal differences in total fatalities as compared with states with uniform speed limits. However, truck-involved fatalities were significantly lower in states where differential limits were in place. The effects of speed limit policies as well as other covariates were found to vary significantly across states. The random parameter models demonstrated significantly improved goodness of fit as compared with standard Poisson and negative binomial models.