Investigating the different characteristics of weekday and weekend crashes

IntroductionThis study provides a systematic approach to investigate the different characteristics of weekday and weekend crashes.MethodWeekend crashes were defined as crashes occurring between Friday 9 p.m. and Sunday 9 p.m., while the other crashes were labeled as weekday crashes. In order to reveal the various features for weekday and weekend crashes, multi-level traffic safety analyses have been conducted. For the aggregate analysis, crash frequency models have been developed through Bayesian inference technique; correlation effects of weekday and weekend crash frequencies have been accounted. A multivariate Poisson model and correlated random effects Poisson model were estimated; model goodness-of-fits have been compared through DIC values. In addition to the safety performance functions, a disaggregate crash time propensity model was calibrated with Bayesian logistic regression model. Moreover, in order to account for the cross-section unobserved heterogeneity, random effects Bayesian logistic regression model was employed.ResultsIt was concluded that weekday crashes are more probable to happen during congested sections, while the weekend crashes mostly occur under free flow conditions. Finally, for the purpose of confirming the aforementioned conclusions, real-time crash prediction models have been developed. Random effects Bayesian logistic regression models incorporating the microscopic traffic data were developed. Results of the real-time crash prediction models are consistent with the crash time propensity analysis. Furthermore, results from these models would shed some lights on future geometric improvements and traffic management strategies to improve traffic safety.Impact on IndustryUtilizing safety performance to identify potential geometric improvements to reduce crash occurrence and monitoring real-time crash risks to pro-actively improve traffic safety.     

Examining teen driver crashes and the prevalence of distraction: Recent trends, 2007–2015

IntroductionTeen drivers crash at a much higher rate than adult drivers, with distractions found as a factor in nearly 6 out of 10 moderate-to-severe teen crashes. As the driving environment continues to rapidly evolve, it is important to examine the effect these changes may be having on our youngest and most vulnerable drivers.MethodThe purpose of this study was to identify types of vehicle crashes teens are most frequently involved in, as well as the distracting activities being engaged in leading up to these crashes, with a focus on identifying changes or trends over time. We examined 2,229 naturalistic driving videos involving drivers ages 16–19. These videos captured crashes occurring between 2007 and 2015. The data of interest for this study included crash type, behaviors drivers engaged in leading up to the collision, total duration of time the driver's eyes were off the forward roadway, and duration of the longest glance away from forward.ResultsRear-end crashes increased significantly (annual % change = 3.23 [2.40–4.05]), corresponding with national data trends. Among cell phone related crashes, a significant shift occurred, from talking/listening to operating/looking (annual % change = 4.22 [1.15–7.29]). Among rear-end crashes, there was an increase in the time drivers' eyes were off the road (β = 0.1527, P = 0.0004) and durations of longest glances away (β = 0.1020, P = 0.0014).ConclusionsFindings suggest that shifts in the way cell phones are being used, from talking/listening to operating/looking, may be a cause of the increasing number of rear-end crashes for teen drivers.Practical applicationsUnderstanding the role that cell phone use plays in teen driver crashes is extremely important. Knowing how and when teens are engaging in this behavior is the only way effective technologies can be developed for mitigating these crashes.     

School transportation mode,by distance between home and school,United States,ConsumerStyles 2012

IntroductionMotor-vehicle crashes are a leading cause of death among children in the United States, and almost one-fourth of all trips by school-aged children are trips to and from school. This study sought to determine how children (5–18 years) travel to and from school and, among those living ≤ 1 mile of school, to explore the role of school bus service eligibility on school travel mode.MethodsWe used national 2012 survey data to determine prevalence of usual school travel mode, stratified by distance from school. For those living ≤ 1 mile of school, multivariable regression was conducted to assess the association between bus service eligibility and walking or bicycling.ResultsAlmost half (46.6%) of all children rode in passenger vehicles (PV) to school and 41.8% did so for the trip home. Results were similar among those living ≤ 1 mile (48.1%, PV to school; 41.3%, PV to home). Among those living ≤ 1 mile, 21.9% and 28.4% of children walked or bicycled to and from school, respectively. Ineligibility for school bus service was strongly associated with walking or bicycling to school [adjusted prevalence ratio (aPR: 5.36; p < 0.001)] and from school (aPR: 5.36; p < 0.001).ConclusionsRegardless of distance from school, passenger vehicles were a common mode of travel. For children who live close to school, the role that school bus service eligibility plays in walking or bicycling deserves further consideration.Practical applicationsGiven the large proportion of children who use passenger vehicles for school travel, effective interventions can be adopted to increase proper child restraint and seat belt use and reduce crash risks among teen drivers. Better understanding of conditions under which bus service is offered to children who live close to school could inform efforts to improve pedestrian and bicyclist safety for school travel.     

Access to trauma centers for road crashes in the United States

Introduction: Existing research indicates that around 90% of all U.S. residents have access to at least one level I or II trauma center within 60 min. However, a limitation of these estimates lies in that they are based on where people live and not where people are injured, which may overestimate the access to trauma centers for seriously injured patients in fatal crashes. Method: In this study, the Fatality Analysis Reporting System (FARS) data between 2013 and 2014 were collected and analyzed to quantify the access of injured patients to trauma centers for fatal crashes across states. Two types of distance, linear distance and route distance, were calculated using ArcGIS. The estimated transport time to the nearest level I/II trauma center was also calculated and compared to the recorded on-scene and transport time. Results and Conclusions: The Northeast region had the nearest average linear and route distance between fatal crash and trauma center (25.3 km and 31.7 km, respectively), followed by the Midwest (44.4 km and 54.1 km), the South (47.3 km and 57.0 km), and the West (50.9 km and 67.5 km). The comparison between the estimated and actual transport time revealed that the different states adopted different trauma triage protocols, resulting in different utilization rates of the level I/II trauma center among states. A linear regression analysis demonstrated that the longer the average route distance, the less the seriously injured patients in fatal crashes were taken to level I/II trauma center directly. Practical applications: These findings may help to identify the access to trauma centers for road crashes and the variation of delivery ratio to trauma center among the states, therefore a better utilization of trauma centers for road crashes can be achieved for the emergency medical services (EMS) systems.     

Older drivers’ involvement in fatal RTCs. Do crashes fatal to them differ from crashes involving them but fatal to others?

In several countries, older drivers are disproportionately involved in fatal road traffic crashes (RTCs) for various reasons. This study maps the circumstances of occurrence of crashes involving older drivers that are fatal to either them or other road users and highlights differences between them. Sweden’s national in-depth studies of fatal RTCs archive was used and focus was placed on crashes in which a driver aged 65 years or older was involved between 2002 and 2004 (n = 197). Thirteen driver and crash characteristics were analyzed simultaneously and typical crash patterns (classes) were highlighted. For each pattern, the proportions of crashes fatal to the older driver vs. to someone else were compared. Four patterns were identified: (1) crashes on low-speed stretches, involving left turn and intersections; (2) crashes involving very old drivers and older vehicles, (3) rear-end collisions on high-speed stretches; and (4) head-on and single-vehicle crashes in rural areas. Older drivers dying in the crash were over-represented in classes 2 and 4. The study shows that when older drivers are involved in fatal RTCs, they are often the ones who die (60%). Typical circumstances surrounding their involvement include manoeuvring difficulties, fast-moving traffic, and colliding in an old vehicle. Preventing fatal RTCs involving older drivers requires not only age-specific but also general measures.     

Tracking progress in teenage driver crash risk in the United States since the advent of graduated driver licensing programs

IntroductionThis study examined U.S. teenagers' crash rates since 1996, when the first graduated driver licensing (GDL) program in the United State was implemented.MethodsPassenger vehicle driver crash involvement rates for 16–19 and 30–59 (middle-aged) year-olds were examined, using data from the Fatality Analysis Reporting System, National Automotive Sampling System General Estimates System, Census Bureau, and National Household Travel Surveys.ResultsPer capita fatal and police-reported crash rates in 2012 were lower for 16 year-olds than for middle-aged drivers but older teenagers' rates were higher. Mileage-based fatal and police-reported crash rates in 2008 were higher for teenagers than for middle-aged drivers and higher for 16–17 year-olds than for older teenagers. In 1996–2012, teenagers' per capita fatal and police-reported crash rates declined sharply, especially for 16–17 year-olds, and more so than for middle-aged drivers. Substantial declines also occurred in teenagers' mileage-based fatal and police-reported crash rates from 1995–96 to 2008, generally more so than for middle-aged drivers. Regarding factors in fatal crashes in 1996 and 2012, proportions of young teenagers' crashes occurring at night and with multiple teenage passengers declined, more so than among older teenagers and middle-aged drivers. The proportion of fatally injured drivers who had been drinking declined for teenagers but changed little for middle-aged drivers. Improvements were not apparent in rates of driver errors or speeding among teenage drivers in fatal crashes.ConclusionsTeenage drivers' crash risk dropped during the period of implementation of GDL laws, especially fatal crash types targeted by GDL. However, teenagers' crash risk remains high, and important crash factors remain unaddressed by GDL.Practical applicationsAlthough this study was not designed to examine the role of GDL, the results are consistent with the increased presence of such laws. More gains are achievable if states strengthen their laws.     

Safety effects of automated section speed control on the Italian motorway network

Introduction: Automated Section Speed Control (ASSC) has been identified as an effective countermeasure to reduce speeds and improve speed limit compliance. Method: An Empirical Bayes (EB) before-and-after study was performed in this research in order to evaluate the impact of the ASSC system on the expected crash frequency. The study was carried out on a sample of 125 ASSC sites of the Italian motorway network covering 1252 km, where a total of 21,721 crashes were recorded during a 10-year analysis period from 2004 to 2013. Results: Overall, the EB analysis estimated a significant 22% reduction in the expected crash frequency due to the implementation of the ASSC system. The analysis indicated that the effect is slightly larger on property damage only (PDO) crashes (− 23%) than on fatal injury (FI) crashes (− 18%) and that the highest reductions in crash frequency are expected for multi-vehicle FI crashes (− 25%) and multi-vehicle PDO crashes (− 31%). Furthermore, the results indicated that the ASSC system is more effective in reducing crash rates when traffic volume increases and it is therefore strongly recommended as a countermeasure to improve safety on high-traffic-volume motorway sections.     

Efficacy of roll stability control and lane departure warning systems using carrier-collected data

IntroductionLarge truck crashes have significantly declined over the last 10 years, likely due, in part, to the increased use of onboard safety systems (OSS). Unfortunately, historically there is a paucity of data on the real-world efficacy of these devices in large trucks. The purpose of this study was to evaluate the two OSSs, lane departure warning (LDW) and roll stability control (RSC), using data collected from motor carriers.MethodA retrospective cohort approach was used to assess the safety benefits of these OSSs installed on Class 7 and 8 trucks as they operated during normal revenue-producing deliveries. Data were collected from 14 carriers representing small, medium, and large carriers hauling a variety of commodities. The data consisted of a total of 88,112 crash records and 151,624 truck-years that traveled 13 billion miles over the observation period.ResultsThe non-LDW cohort had an LDW-related crash rate that was 1.917 times higher than the LDW cohort (p = 0.001), and the non-RSC cohort had an RSC-related crash rate that was 1.555 times higher than the RSC cohort (p < 0.001).ConclusionsThe results across analyses indicated a strong, positive safety benefit for LDW and RSC under real-world conditions.Practical applicationsThe results support the use of LDW and RSC in reducing the crash types associated with each OSS.     

Raising the speed limit from 75 to 80 mph on Utah rural interstates: Effects on vehicle speeds and speed variance

IntroductionIn November 2010 and October 2013, Utah increased speed limits on sections of rural interstates from 75 to 80 mph. Effects on vehicle speeds and speed variance were examined.MethodsSpeeds were measured in May 2010 and May 2014 within the new 80 mph zones, and at a nearby spillover site and at more distant control sites where speed limits remained 75 mph. Log-linear regression models estimated percentage changes in speed variance and mean speeds for passenger vehicles and large trucks associated with the speed limit increase. Logistic regression models estimated effects on the probability of passenger vehicles exceeding 80, 85, or 90 mph and large trucks exceeding 80 mph.ResultsWithin the 80 mph zones and at the spillover location in 2014, mean passenger vehicle speeds were significantly higher (4.1% and 3.5%, respectively), as were the probabilities that passenger vehicles exceeded 80 mph (122.3% and 88.5%, respectively), than would have been expected without the speed limit increase. Probabilities that passenger vehicles exceeded 85 and 90 mph were non-significantly higher than expected within the 80 mph zones. For large trucks, the mean speed and probability of exceeding 80 mph were higher than expected within the 80 mph zones. Only the increase in mean speed was significant. Raising the speed limit was associated with non-significant increases in speed variance.ConclusionsThe study adds to the wealth of evidence that increasing speed limits leads to higher travel speeds and an increased probability of exceeding the new speed limit. Results moreover contradict the claim that increasing speed limits reduces speed variance.Practical applicationsAlthough the estimated increases in mean vehicle speeds may appear modest, prior research suggests such increases would be associated with substantial increases in fatal or injury crashes. This should be considered by lawmakers considering increasing speed limits.     

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

IntroductionThis 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.MethodRegression 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.ResultsSpeeds were relatively stable across levels-of-service A and B, within a range of 1.5 mph on average. Speeds were marginally lower (3.3 mph) on freeways posted at 65 mph versus 70 mph. In comparison, speeds were approximately 10.2 to 13.4 mph lower on facilities posted at 55 mph or 60 mph. Speeds were shown to be 2.5 mph lower in rainy weather and 11 mph lower under snow or sleet.ConclusionsSignificant 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.     

Temporal factors in motor-vehicle crash deaths: Ten years later

ObjectiveTo assess trends in traffic fatalities on several temporal scales: year to year, by month, by day of week, and by time of day, to determine why some times correspond with higher rates of crash deaths, and to assess how these trends relate to age, the role of the deceased, and alcohol consumption.MethodTraffic fatalities were identified using the Fatality Analysis Reporting System (FARS) for 1998 through 2014 and assessed for their time of occurrence. Three days that, on average, contained particularly high numbers of crash deaths were then assessed in greater detail, considering the age of the deceased, role of the deceased (vehicle occupant, bicyclist, motorcyclist, or pedestrian), and the blood alcohol content of either the driver (for passenger vehicle occupants) or the deceased.ResultsAnnual crash fatality totals were much lower in 2014 than in 1998, but the decrease was not steady; a marked drop in crash deaths occurred after 2007 and continued until 2014. On average the most fatalities per day occurred in July and August (116 per day), followed closely by June, September, and October. During the week, the greatest number of fatalities on average occur on weekend days, and during the day the most fatalities tend to occur between the hours of 3 p.m. and 7 p.m. Holidays like Independence Day and New Year's Day show elevated crash fatalities, and a greater percentage of these crashes involved alcohol, when compared with adjacent days.ConclusionCertain days and times of year stand out as posing an elevated crash risk, and even with the decrease in average daily fatalities over the past decade, these days and times of year have remained consistent.Practical applicationThese results indicate focused areas for continued efforts to reduce fatal crashes.     

Assessing the risk of secondary crashes on highways

IntroductionThe occurrence of “secondary crashes” is one of the critical yet understudied highway safety issues. Induced by the primary crashes, the occurrence of secondary crashes does not only increase traffic delays but also the risk of inducing additional incidents. Many highway agencies are highly interested in the implementation of safety countermeasures to reduce this type of crashes. However, due to the limited understanding of the key contributing factors, they face a great challenge for determining the most appropriate countermeasures.MethodTo bridge this gap, this study makes important contributions to the existing literature of secondary incidents by developing a novel methodology to assess the risk of having secondary crashes on highways. The proposed methodology consists of two major components, namely: (a) accurate identification of secondary crashes and (b) statistically robust assessment of causal effects of contributing factors. The first component is concerned with the development of an improved identification approach for secondary accidents that relies on the rich traffic information obtained from traffic sensors. The second component of the proposed methodology is aimed at understanding the key mechanisms that are hypothesized to cause secondary crashes through the use of a modified logistic regression model that can efficiently deal with relatively rare events such as secondary incidents. The feasibility and improved performance of using the proposed methodology are tested using real-world crash and traffic flow data.ResultsThe risk of inducing secondary crashes after the occurrence of individual primary crashes under different circumstances is studied by employing the estimated regression model. Marginal effect of each factor on the risk of secondary crashes is also quantified and important contributing factors are highlighted and discussed.Practical applicationsMassive sensor data can be used to support the identification of secondary crashes. The occurrence mechanism of these secondary crashes can be investigate by the proposed model. Understanding the mechanism helps deploy appropriate countermeasures to mitigate or prevent the secondary crashes.     

Traffic environment and demographic factors affecting impaired driving and crashes

IntroductionData availability has forced researchers to examine separately the role of alcohol among drivers who crashed and drivers who did not crash. Such a separation fails to account fully for the transition from impaired driving to an alcohol-related crash.MethodIn this study, we analyzed recent data to investigate how traffic-related environments, conditions, and drivers’ demographics shape the likelihood of a driver being either involved in a crash (alcohol impaired or not) or not involved in a crash (alcohol impaired or not). Our data, from a recent case–control study, included a comprehensive sampling of the drivers in nonfatal crashes and a matched set of comparison drivers in two U.S. locations. Multinomial logistic regression was applied to investigate the likelihood that a driver would crash or would not crash, either with a blood alcohol concentration (BAC) = .00 or with a BAC ≥ .05.ConclusionsTo our knowledge, this study is the first to examine how different driver characteristics and environmental factors simultaneously contribute to alcohol use by crash-involved and non-crash-involved drivers. This effort calls attention to the need for research on the simultaneous roles played by all the factors that may contribute to motor vehicle crashes.     

Heavy trucks, conspicuity treatment, and the decline of collision risk in darkness

IntroductionThe influence of amendments to Federal Motor Vehicle Safety Standard (FMVSS) 108, requiring conspicuity treatments on heavy tractors and trailers, was determined in analyses of the odds of fatal collisions in darkness.MethodComparisons were made between crashes in which conspicuity treatment was likely relevant, and those in which it was likely irrelevant.ResultsOver 23 years, the odds that a fatal collision involving a heavy truck occurred in darkness declined by 58% among relevant crashes, while little decline was observed for irrelevant crashes. Disaggregation into crash types revealed the largest declines occurred in fatal rear-end and angle collisions. A parallel analysis of light vehicles also found declines but no differences among crash type. Similar trends were also observed for nonfatal rear end collisions.ConclusionThe results suggest that detection failure may have contributed to the risk of striking a tractor-semitrailer in darkness, and that conspicuity treatments have reduced this risk.Impact on IndustryConspicuity treatments appear to reduce risk of collision into heavy trucks in darkness. It is likely that this benefit would also extend to other vehicles that are not included in the FMVSS 108 regulation (e.g., buses, single unit trucks, recreational vehicles), although many are so equipped, regardless of the regulation.     

Validation of the principles of injury risk zones for motorcycle protective clothing

IntroductionThe distributions of motorcycle crash impacts and injuries were compared to the four impact risk zones and protective performance specified in the European Standard for motorcycle clothing (EN 13595).MethodsCrashed motorcyclists' (n = 117) injuries and clothing damage were categorized by body area into the four risk zones. Three levels of protection were defined: protective clothing with impact protection, protective clothing only and non-protective clothing.ResultsThe distribution of impact/injury sites corresponded to the predictions of EN 13595, with the proportion of all injuries decreasing from 43.9% in Zone 1, to 18.0%, 16.7%, and 11.5% in Zones 2 to 4, respectively. Protective clothing modified the distribution of injuries with substantially more injuries (OR = 2.69, 95% CL: 20.1–3.59) at unprotected impact sites.Practical applicationThese findings support an appropriate framework for determining performance specifications for the manufacture of motorcycle clothing that will effectively reduce the risk of injury in crashes.     

Conscientious personality and young drivers' crash risk

Introduction: Personality characteristics are associated with many risk behaviors. However, the relationship between personality traits, risky driving behavior, and crash risk is poorly understood. The purpose of this study was to examine the association between personality, risky driving behavior, and crashes and near-crashes, using naturalistic driving research methods. Method: Participants' driving exposure, kinematic risky driving (KRD), high-risk secondary task engagement, and the frequency of crashes and near-crashes (CNC) were assessed over the first 18 months of licensure using naturalistic driving methods. A personality survey (NEO-Five Factor Inventory) was administered at baseline. The association between personality characteristics, KRD rate, secondary task engagement rate, and CNC rate was estimated using a linear regression model. Mediation analysis was conducted to examine if participants' KRD rate or secondary task engagement rate mediated the relationship between personality and CNC. Data were collected as part of the Naturalistic Teen Driving Study. Results: Conscientiousness was marginally negatively associated with CNC (path c = − 0.034, p = .09) and both potential mediators KRD (path a = − 0.040, p = .09) and secondary task engagement while driving (path a = − 0.053, p = .03). KRD, but not secondary task engagement, was found to mediate (path b = 0.376, p = .02) the relationship between conscientiousness and CNC (path c′ = − 0.025, p = .20). Conclusions: Using objective measures of driving behavior and a widely used personality construct, these findings present a causal pathway through which personality and risky driving are associated with CNC. Specifically, more conscientious teenage drivers engaged in fewer risky driving maneuvers, and suffered fewer CNC. Practical Applications: Part of the variability in crash risk observed among newly licensed teenage drivers can be explained by personality. Parents and driving instructors may take teenage drivers' personality into account when providing guidance, and establishing norms and expectations about driving.     

Distracting behaviors among teenagers and young,middle-aged,and older adult drivers when driving without and with warnings from an integrated vehicle safety system

IntroductionNegative reinforcement from crash warnings may reduce the likelihood that drivers engage in distracted driving. Alternatively, drivers may compensate for the perceived safety benefit of crash warnings by engaging in distractions more frequently, especially at higher speeds. The purpose of this study was to examine whether warning feedback from an integrated vehicle-based safety system affected the likelihood that various secondary behaviors were present among drivers ages 16–17, 20–30, 40–50, and 60–70.MethodParticipants drove an instrumented sedan with various collision warning systems for an extended period. Ten 5-second video clips were randomly sampled from driving periods at speeds above 25 mph and below 5 mph each week for each driver and coded for the presence of 11 secondary behaviors.ResultsAt least one secondary behavior was present in 46% of video clips; conversing with a passenger (17%), personal grooming (9%), and cellphone conversation (6%) were the most common. The likelihood that at least one secondary behavior was present was not significantly different during periods when drivers received warnings relative to periods without warnings. At least one secondary behavior was 21% more likely to be present at speeds below 5 mph relative to speeds above 25 mph; however, the effect of vehicle speed was not significantly affected by warning presence. Separate models for each of the five most common secondary behaviors also indicated that warnings had no significant effect on the likelihood that each behavior was present.ConclusionsCollision warnings were not associated with significant increases or decreases in the overall likelihood that teen and adult drivers engaged in secondary behaviors or the likelihood of the behaviors at speeds above 25 mph or below 5 mph.Practical applicationsThere was no evidence that forward collision warning and other technologies like those in this study will increase or decrease distracted driving.     

Peer influence predicts speeding prevalence among teenage drivers

Impact on IndustryPreventing speed-related crashes could reduce costs and improve efficiency in the transportation industry.ObjectiveThis research examined the psychosocial and personality predictors of observed speeding among young drivers.MethodSurvey and driving data were collected from 42 newly-licensed teenage drivers during the first 18 months of licensure. Speeding (i.e., driving 10 mph over the speed limit; about 16 km/h) was assessed by comparing speed data collected with recording systems installed in participants' vehicles with posted speed limits.ResultsSpeeding was correlated with elevated g-force event rates (r = 0.335, pb0.05), increased over time, and predicted by day vs. night trips, higher sensation seeking, substance use, tolerance of deviance, susceptibility to peer pressure, and number of risky friends. Perceived risk was a significant mediator of the association between speeding and risky friends.ConclusionThe findings support the contention that social norms may influence teenage speeding behavior and this relationship may operate through perceived risk.     

Evaluation of an in-vehicle monitoring system (IVMS) to reduce risky driving behaviors in commercial drivers: Comparison of in-cab warning lights and supervisory coaching with videos of driving behavior

ProblemRoadway incidents are the leading cause of work-related death in the United States.MethodsThe objective of this research was to evaluate whether two types of feedback from a commercially available in-vehicle monitoring system (IVMS) would reduce the incidence of risky driving behaviors in drivers from two companies. IVMS were installed in 315 vehicles representing the industries of local truck transportation and oil and gas support operations, and data were collected over an approximate two-year period in intervention and control groups. In one period, intervention group drivers were given feedback from in-cab warning lights from an IVMS that indicated occurrence of harsh vehicle maneuvers. In another period, intervention group drivers viewed video recordings of their risky driving behaviors with supervisors, and were coached by supervisors on safe driving practices.ResultsRisky driving behaviors declined significantly more during the period with coaching plus instant feedback with lights in comparison to the period with lights-only feedback (ORadj = 0.61 95% CI 0.43–0.86; Holm-adjusted p = 0.035) and the control group (ORadj = 0.52 95% CI 0.33–0.82; Holm-adjusted p = 0.032). Lights-only feedback was not found to be significantly different than the control group's decline from baseline (ORadj = 0.86 95% CI 0.51–1.43; Holm-adjusted p > 0.05).ConclusionsThe largest decline in the rate of risky driving behaviors occurred when feedback included both supervisory coaching and lights.Practical applicationsSupervisory coaching is an effective form of feedback to improve driving habits in the workplace. The potential advantages and limitations of this IVMS-based intervention program are discussed.     

A combined frequency–severity approach for the analysis of rear-end crashes on urban arterials

Analysis of both the crash count and the severity of injury are required to provide the complete picture of the safety situation of any given roadway. The randomness of crashes, the one-way dependency of injury on crash occurrence and the difference in response types have typically led researchers into developing independent statistical models for crash count and severity classification. The Genetic Programming (GP) methodology adopts the concepts of evolutionary biology such as crossover and mutation in effectively giving a common heuristic approach to model the development for the two different modeling objectives. The chosen GP models have the highest hit rate for rear-end crash classification problem and the least error for function fitting (regression) problems. Higher Average Daily Traffic (ADT) is more likely to result in more crashes. Absence of on-street parking may result in diminished severity of injuries resulting from crashes as they may provide “soft” crash barrier in contrast to fixed road side objects. Graphical presentation of the frequency of crashes with varying input variables shed new light on the results and its interpretation. Higher friction coefficient of roadways result in reduced frequency of crashes during the morning peak hours, with the trend being reversed during the afternoon peak hours. Crash counts have been observed to be at a maximum at a surface width of 30 ft. Sensitivity analysis results reflect that ADT is responsible for the largest variation in crash counts on urban arterials.