Forward collision warning system impact

Abstract

Objective: The objective of this research is to use historical crash data to evaluate the potential benefits of both high- and low-speed automatic emergency braking (AEB) with forward collision warning (FCW) systems.

Methods: Crash data from the NHTSA’s NASS–General Estimates System (GES) and Fatality Analysis Reporting System (FARS) databases were categorized to classify crashes by the speed environment, as well as to identify cases where FCW systems would be applicable.

Results: Though only about 19% of reported crashes occur in environments with speeds greater than 45?mph, approximately 32% of all serious or fatal crashes occur in environments with speeds greater than 45?mph. The percentage of crashes where FCW systems would be relevant has remained remarkably constant, varying between about 21 and 26% from 2002 to 2015. In 2-vehicle fatal crashes where one rear-ends the other, the fatality rates are actually higher in the struck vehicle (33%) than the striking vehicle (26%). The disparity is even greater when considering size–class differences, such as when a light truck rear-ends a passenger car (15 vs. 42% fatality rates, respectively).

Conclusions: NHTSA and the Insurance Institute for Highway Safety (IIHS) proposed the Automatic Emergency Braking Initiative in 2015, which is intended to make AEB (also called crash-imminent braking) with FCW systems standard on nearly all new cars by September 2022. Twenty automakers representing 99% of the U.S. auto market voluntarily committed to the initiative. Though the commitment to safety is laudable, the AEB component of the agreement only covers low-speed AEB systems, with the test requirements set to 24?mph or optionally as low as 12?mph. The test requirements for the FCW component of the agreement include 2 tests that begin at 45?mph. Only 21% of relevant serious injury or fatal accidents occur in environments at speeds under 24?mph, whereas about 22% of serious or fatal crashes occur in environments with speeds greater than 45?mph. This means that the AEB with FCW systems as agreed upon will cover only 21% of serious or fatal crashes and will not cover 22% of serious or fatal crashes. Because these systems are protective not only for the occupants of the vehicle where they are installed but also other vehicles on the roads, the data indicate that these systems should be a standard feature on all cars for high-speed as well as low-speed environments for the greatest social benefit.     

Analyses of rear-end crashes based on classification tree models

OBJECTIVE: Signalized intersections are accident-prone areas especially for rear-end crashes due to the fact that the diversity of the braking behaviors of drivers increases during the signal change. The objective of this article is to improve knowledge of the relationship between rear-end crashes occurring at signalized intersections and a series of potential traffic risk factors classified by driver characteristics, environments, and vehicle types. METHODS: Based on the 2001 Florida crash database, the classification tree method and Quasi-induced exposure concept were used to perform the statistical analysis. Two binary classification tree models were developed in this study. One was used for the crash comparison between rear-end and non-rear-end to identify those specific trends of the rear-end crashes. The other was constructed for the comparison between striking vehicles/drivers (at-fault) and struck vehicles/drivers (not-at-fault) to find more complex crash pattern associated with the traffic attributes of driver, vehicle, and environment. RESULTS: The modeling results showed that the rear-end crashes are over-presented in the higher speed limits (45-55 mph); the rear-end crash propensity for daytime is apparently larger than nighttime; and the reduction of braking capacity due to wet and slippery road surface conditions would definitely contribute to rear-end crashes, especially at intersections with higher speed limits. The tree model segmented drivers into four homogeneous age groups: < 21 years, 21-31 years, 32-75 years, and > 75 years. The youngest driver group shows the largest crash propensity; in the 21-31 age group, the male drivers are over-involved in rear-end crashes under adverse weather conditions and the 32-75 years drivers driving large size vehicles have a larger crash propensity compared to those driving passenger vehicles. CONCLUSIONS: Combined with the quasi-induced exposure concept, the classification tree method is a proper statistical tool for traffic-safety analysis to investigate crash propensity. Compared to the logistic regression models, tree models have advantages for handling continuous independent variables and easily explaining the complex interaction effect with more than two independent variables. This research recommended that at signalized intersections with higher speed limits, reducing the speed limit to 40 mph efficiently contribute to a lower accident rate. Drivers involved in alcohol use may increase not only rear-end crash risk but also the driver injury severity. Education and enforcement countermeasures should focus on the driver group younger than 21 years. Further studies are suggested to compare crash risk distributions of the driver age for other main crash types to seek corresponding traffic countermeasures.     

Field effectiveness evaluation of advanced driver assistance systems

Abstract

Objective: Advanced driver assistance systems (ADAS) are a class of vehicle technologies designed to increase safety by providing drivers with timely warnings and autonomously intervening to avoid hazardous situations. Though laboratory testing suggests that ADAS technologies will greatly impact crash involvement rates, real-world evidence that characterizes their effectiveness is still limited. This study evaluates and quantifies the association of ADAS technologies with the likelihood of a moderate or severe crash for new-model BMWs in the United States.

Methods: Vehicle ADAS option information for the cohort of model year 2014 and later BMW passenger vehicles sold after January 1, 2014 (n?=?1,063,503), was coded using VIN-identified options data. ADAS technologies of interest include frontal collision warning with autonomous emergency braking, lane departure warning, and blind spot detection. BMW Automated Crash Notification system data (from January 2014 to November 2017) were merged with vehicle data by VIN to identify crashed vehicles (n?=?15,507), including date, crash severity (delta V), and area of impact. Using Cox proportional hazards regression modeling, the study calculates the adjusted hazard ratio for crashing among BMW passenger vehicles with versus without ADAS technologies. The adjusted percentage reduction in moderate and severe crashes associated with ADAS is interpreted as one minus the hazard ratio.

Results: Vehicles equipped with both autonomous emergency braking and lane departure warning were 23% less likely to crash than those not equipped (hazard ratio [HR]?=?0.77; 95% confidence interval [CI], 0.73–0.81), controlling for model year, vehicle size and body type. Autonomous emergency braking and lane departure warning generally occur together, making it difficult to tease apart their individual effects. Blind spot detection was associated with a 14% reduction in crashes after controlling for the presence of autonomous emergency braking and lane departure warning (HR =0.86; 95% CI, 0.744–0.99). Differences were observed by vehicle type and crash type. The combined effect of autonomous emergency braking and lane departure warning was greater in newer model vehicles: Equipped vehicles were 13% less likely to crash (HR =0.87; 95% CI, 0.79–0.95) among 2014 model year vehicles versus 34% less likely to crash (HR =0.66; 95% CI, 0.57–0.77) among 2017 model year vehicles.

Conclusion: This robust cohort study contributes to the growing evidence on the effectiveness of ADAS technologies.     

Multi-agent traffic simulations to estimate the impact of automated technologies on safety

Abstract

Objective: The objective of this article was to develop a multi-agent traffic simulation methodology to estimate the potential road safety improvements of automated vehicle technologies.

Methods: We developed a computer program that merges road infrastructure data with a large number of vehicles, drivers, and pedestrians. Human errors are induced by modeling inattention, aimless driving, insufficient safety confirmation, misjudgment, and inadequate operation. The program was applied to simulate traffic in a prescribed area in Tsukuba city. First, a 100% manual driving scenario was set to simulate traffic for a total preset vehicle travel distance. The crashes from this simulation were compared with real-world crash data from the prescribed area from 2012 to 2017. Thereafter, 4 additional scenarios of increasing levels of automation penetration (including combinations of automated emergency braking [AEB], lane departure warning [LDW], and SAE Level 4 functions) were implemented to estimate their impact on safety.

Results: Under manual driving, the system simulated a total of 859 crashes including single-car lane departure, car-to-car, and car-to-pedestrian crashes. These crashes tended to occur in locations similar to real-world crashes. The number of crashes predicted decreased to 156 cases with increasing level of automation. All of the technologies considered contributed to the decrease in crashes. Crash reductions attributable to AEB and LDW in the simulations were comparable to those reported in recent field studies. For the highest levels of automation, no assessment data were available and hence the results should be carefully treated. Further, in modeling automated functions, potentially negative aspects such as sensing failure or human overreliance were not incorporated.

Conclusions: We developed a multi-agent traffic simulation methodology to estimate the effect of different automated vehicle technologies on safety. The crash locations resulting from simulations of manual driving within a limited area in Japan were preliminary assessed by comparison with real-world crash data collected in the same area. Increasing penetration levels of AEB and LDW led to a large reduction in both the frequency and severity of rear-end crashes, followed by car-to-car head-on crashes and single-vehicle lane departure crashes. Preliminary estimations of the potential safety improvements that may be achieved with highly automated driving technologies were also obtained.     

Crash risk of ESC-fitted passenger cars

Objective: We examined both fatal and injury at-fault crashes of a population of passenger cars fitted with electronic stability control (ESC). Crash rates were calculated in relation to both registration years and mileage. Crash rates were also calculated for a non-ESC car population and crash rate ratios were calculated to compare the crash risk between ESC-fitted and non-ESC-fitted passenger cars.

Methods: Passenger car models with and without ESC were identified (ESC-equipped cars: 3,352,813 registration years; non-ESC-equipped: 5,839,946 registration years) and their vehicle information for the period 2009–2013, including mileage (ESC-equipped vehicles: 89.3 billion kilometers; non-ESC-equipped: 72.4 billion kilometers), was drawn from the national Vehicular and Driver Data Register.

The registry of Finnish road accident investigation teams was accessed and all fatal at-fault crashes among the cars in the study populations (ESC 97; non-ESC 377) for the period 2009–2013 were analyzed. The motor insurance database includes at-fault crashes leading to injuries and was utilized for analyses (ESC: N?=?8,827, non-ESC: N?=?21,437).

Crash rates and crash rate ratios were calculated to evaluate crash risk of both ESC-equipped and non-ESC-equipped passenger cars. Poisson regression was used to model crash involvement rate ratios both per registration year and per mileage for vehicles with ESC and without ESC, controlling for age and gender of the vehicle owner and vehicle mass.

Results: Passenger cars fitted with ESC showed lower crash rates than non-ESC-equipped cars in all crash types studied. In general, the difference in crash rates between ESC-equipped and non-ESC-equipped vehicles was greater when the crashes were compared to the mileage rather than registration years. The mileage-proportional crash rate of ESC-equipped cars was 64% (95% confidence interval, 61%; 67%) lower in run-off-road crashes resulting in injury and as much as 82% (65%; 91%) lower in fatal run-off-road crashes when suicides and disease attacks were not taken into account.

Conclusions: Our results show that modern passenger cars provide a significant crash risk reduction, which depends on both ESC and passive safety features introduced. Results also show that exposure evaluation in terms of registration years (or vehicle population) instead of true mileage can provide an overly pessimistic view of the crash risk.     

Intersection AEB implementation strategies for left turn across path crashes

Abstract

Objective: Left turn across path with traffic from the opposite direction (LTAP/OD) is the second most frequent car-to-car intersection crash type after straight crossing path (SCP) in Germany and the United States. Intersection automated emergency braking (AEB) for passenger cars can address these crashes.

This study investigates 2 implementation strategies of intersection AEB addressing LTAP/OD crashes: (1) only the turning car is equipped with an intersection AEB and (2) turning and straight-heading cars are equipped with an intersection AEB. For each strategy, the influence of a safety zone around the vehicles that should not be entered is evaluated in terms of accident avoidance, injury mitigation, and change in velocity (delta-V) of remaining accidents. Results are given as a function of market penetration.

Methods: A total of 372 LTAP/OD crashes from the time series precrash matrix (PCM), a subsample of the German In-Depth Accident Study (GIDAS), were resimulated in the PRediction of Accident Evolution by Diversification of Influence factors in COmputer simulation (PRAEDICO) simulation framework. A Kudlich-Slibar rigid-body impact model and an injury risk curve derived from GIDAS were used to predict remaining moderate to fatal (Maximum Abbreviated Injury Scale [MAIS] 2?+?F) injuries among car occupants.

Results: With a safety zone of 0.2 m, when the turning vehicle only was equipped with an intersection AEB, 59% of the crashes were avoided at a 100% market penetration. With both vehicles equipped the percentage increased to 77%. MAIS 2?+?F injured occupants were reduced by 60 and 76%, respectively. Considering both the turning and the straight-heading vehicles, the delta-V decreased strongly with market penetration in remaining left-side impacts but only slightly in remaining frontal and right-side impacts. Eliminating the safety zone substantially decreases effectiveness in all conditions.

Conclusions: Implementation strategy and safety zone definition strongly influence the real-life performance of intersection AEB. AEB should be applied not only for the turning vehicle but also for the straight-going vehicle to benefit from the full potential. Situationally appropriate safety zone definitions, in line with human hazard perception, need more attention and are a key to balance true positive and false positive performance. Remaining delta-V does not decrease broadly; hence, there is no evidence that future LTAP/OD crashes will be generally of lower severity. This highlights the need for continuous development of in-crash protection.     

Motorcycle crashes potentially preventable by three crash avoidance technologies on passenger vehicles

Objective: The objective of this study was to identify and quantify the motorcycle crash population that would be potential beneficiaries of 3 crash avoidance technologies recently available on passenger vehicles.

Methods: Two-vehicle crashes between a motorcycle and a passenger vehicle that occurred in the United States during 2011–2015 were classified by type, with consideration of the functionality of 3 classes of passenger vehicle crash avoidance technologies: frontal crash prevention, lane maintenance, and blind spot detection. Results were expressed as the percentage of crashes potentially preventable by each type of technology, based on all known types of 2-vehicle crashes and based on all crashes involving motorcycles.

Results: Frontal crash prevention had the largest potential to prevent 2-vehicle motorcycle crashes with passenger vehicles. The 3 technologies in sum had the potential to prevent 10% of fatal 2-vehicle crashes and 23% of police-reported crashes. However, because 2-vehicle crashes with a passenger vehicle represent fewer than half of all motorcycle crashes, these technologies represent a potential to avoid 4% of all fatal motorcycle crashes and 10% of all police-reported motorcycle crashes.

Discussion: Refining the ability of passenger vehicle crash avoidance systems to detect motorcycles represents an opportunity to improve motorcycle safety. Expanding the capabilities of these technologies represents an even greater opportunity. However, even fully realizing these opportunities can affect only a minority of motorcycle crashes and does not change the need for other motorcycle safety countermeasures such as helmets, universal helmet laws, and antilock braking systems.     

Comparison of Expected Crash and Injury Reduction from Production Forward Collision and Lane Departure Warning Systems

Objectives: The U.S. New Car Assessment Program (NCAP) now tests for forward collision warning (FCW) and lane departure warning (LDW). The design of these warnings differs greatly between vehicles and can result in different real-world field performance in preventing or mitigating the effects of collisions. The objective of this study was to compare the expected number of crashes and injured drivers that could be prevented if all vehicles in the fleet were equipped with the FCW and LDW systems tested under the U.S. NCAP.

Methods: To predict the potential crashes and serious injury that could be prevented, our approach was to computationally model the U.S. crash population. The models simulated all rear-end and single-vehicle road departure collisions that occurred in a nationally representative crash database (NASS-CDS). A sample of 478 single-vehicle crashes from NASS-CDS 2012 was the basis for 24,822 simulations for LDW. A sample of 1,042 rear-end collisions from NASS-CDS years 1997–2013 was the basis for 7,616 simulations for FCW. For each crash, 2 simulations were performed: (1) without the system present and (2) with the system present. Models of each production safety system were based on 54 model year 2010–2014 vehicles that were evaluated under the NCAP confirmation procedure for LDW and/or FCW. NCAP performed 40 LDW and 45 FCW tests of these vehicles.

Results: The design of the FCW systems had a dramatic impact on their potential to prevent crashes and injuries. Between 0 and 67% of crashes and 2 and 69% of moderately to fatally injured drivers in rear-end impacts could have been prevented if all vehicles were equipped with the FCW systems. Earlier warning times resulted in increased benefits. The largest effect on benefits, however, was the lower operating speed threshold of the systems. Systems that only operated at speeds above 20 mph were less than half as effective as those that operated above 5 mph with similar warning times. The production LDW systems could have prevented between 11 and 23% of drift-out-of-lane crashes and 13 and 22% of seriously to fatally injured drivers. A majority of the tested LDW systems delivered warnings near the point when the vehicle first touched the lane line, leading to similar benefits. Minimum operating speed also greatly affected LDW effectiveness.

Conclusions: The results of this study show that the expected field performance of FCW and LDW systems are highly dependent on the design and system limitations. Systems that delivered warnings earlier and operated at lower speeds may prevent far more crashes and injuries than systems that warn late and operate only at high speeds. These results suggest that future FCW and LDW evaluation should prioritize early warnings and full-speed range operation. A limitation of this study is that additional crash avoidance features that may also mitigate collisions—for example, brake assist, automated braking, or lane-keeping assistance—were not evaluated during the NCAP tests or in our benefits models. The potential additional mitigating effects of these systems were not quantified in this study.     

Ticketing aggressive cars and trucks (TACT): How does it work on city streets?

Objective: The purpose of this study was to determine the feasibility of modifying the Ticking Aggressive Cars and Trucks (TACT) program, originally designed to work on state highways, within a metropolitan area to reduce unsafe interactions and their related crashes between drivers of large trucks and passenger vehicles.

Methods: Using crash data, the driving behaviors most commonly associated with large truck and passenger vehicle crashes were identified. A public awareness campaign using media messaging and increased law enforcement was created targeting these associated behaviors. The frequency of these behaviors both before and after the public awareness campaign was determined through observation of traffic at 3 specific locations within the city. Each location had a sufficient volume of large truck and passenger traffic to observe frequent interactions. Pre- and postintervention data were compared using negative binomial regression with generalized estimating equations to evaluate whether the campaign was associated with a reduction in the identified driving behaviors.

Results: A comparison between crash data from before, during, and after the campaign and crashes during the same time periods in previous years did not show a significant difference (P =.081). The number of large trucks observed in traffic remained the same during pre- and postintervention periods (P =.625). The rates of negative interactions per 100 large trucks decreased for both large trucks and passenger vehicles after the intervention, with calculated rate ratios of 0.58 (95% confidence interval [CI], 0.48, 0.70) and 0.31 (95% CI, 0.20, 0.47). The greatest reduction was seen in passenger vehicles following too close, with a rate ratio of 0.21 (95% CI, 0.15, 0.30).

Conclusions: Although designed for reducing crashes on highways, the TACT program can be an effective approach for improving driver behaviors on city streets.     

Characteristics of vehicle-animal crashes in which vehicle occupants are killed

During the past 10 years almost 1,500 people have been killed in motor vehicle collisions with animals. Police reports on 147 fatal vehicle-animal crashes during 2000-2002 were obtained from nine states. The goal was to determine common crash types, types of animals involved, and steps that could be taken to reduce the crashes and injuries. Seventy-seven percent of the struck animals were deer, but six other types of animals were involved including small ones such as dogs. Eighty percent of the crashes were single-vehicle events. In most of these cases a motorcycle struck an animal and the rider came off the vehicle, or a passenger vehicle struck an animal and then ran off the road; in a few cases the animal went through the windshield. Multiple-vehicle crashes included vehicles striking deer that went through the windshields of oncoming vehicles, vehicles striking animals and then colliding with other vehicles, and vehicles striking animals that subsequently were struck by other vehicles. Crashes occurred primarily in rural areas, on roads with 55 mph or higher speed limits, during evening or nighttime hours, and in darkness. Greater application of deer-vehicle collision countermeasures known to be effective is needed, but it is noteworthy that a majority of fatalities occurred from subsequent collisions with other vehicles or objects, not from animal contacts. Sixty-five percent of motorcyclists killed were not wearing helmets, and 60% of vehicle occupants killed were unbelted; many of these fatalities would not have occurred with proper protection.     

Risk of motor vehicle crash for older adults after receiving a traffic charge: A case–crossover study

Objective: After the age of 65, the number of motor vehicle crashes per mile driven increases. Traffic-related charges issued by law enforcement can help identify drivers who are at a higher risk of having a crash. This study examines the relationship between motor vehicle crashes and traffic-related charges among older adult drivers.

Methods: Iowa Department of Transportation crash data from 2011–2012 were linked with Iowa Court Information System data for moving violations that occurred during 2009–2012 for drivers over the age of 50. A time-stratified case–crossover design was used matching on time periods 1 year apart. Case exposure was defined as having a traffic-related charge 30 days before the crash. Control exposure was the same 30-day time period 1 year before the crash for each individual. Conditional logistic regression was used to analyze the self-matched pairs. Additional time periods of 31–60, 61–90, 91–120, 121–150, 151–180, and 181–210 days before the crash were also assessed.

Results: There were 38,171 adults at least 50 years of age with an Iowa driver's license who were involved in a crash in Iowa between 2011 and 2012. In addition, 13,129 adults over the age of 50 received a charge during 2009–2012. Relative to the control time period, experiencing a traffic-related charge in the 30-day time period before the crash increased the risk of a crash by 21% (odds ration [OR] = 1.21, 95% confidence interval [CI], 1.03–1.42) for all drivers included in the study. This crash risk was similar for adults aged 50–64 (OR = 1.20, 95% CI, 1.00–1.45) and adults 65 and older (OR = 1.24, 95% CI, 0.90–1.72). In the 30 days after receiving a traffic-related charge, the risk of a crash was also increased for crashes occurring in adverse weather (OR = 1.79, 95% CI, 1.12–2.84) or during night, dawn, or twilight (OR = 1.89, 95% CI, 1.31–2.72).

Conclusions: A traffic-related charge for an adult over the age of 50 indicates an increased risk of experiencing a crash in the 30 days following the charge. The risk for crashes occurring in adverse conditions or outside of daylight hours was also increased in the 30 days after receiving a traffic-related charge. The risk of experiencing a crash decreases as time passes after receiving a charge. Measures to restrict or increase driving safety during these conditions could help reduce the crash risk for older adults who receive a traffic-related charge.     

Characteristics of crashes and injuries among 14 and 15 year old drivers,by rurality

Purpose: Motor-vehicle crashes continue to be the leading cause of death for teenagers in the United States. The United States has some of the youngest legal driving ages worldwide. The objective of this study was to determine rates and factors associated with injury crashes among 14- and 15-year-old drivers and how these varied by rurality. Methods: Data for this cross-sectional study of 14- and 15-year-old drivers were obtained from the Iowa Department of Transportation from 2001 to 2013. Crash and injury crash rates were calculated by rurality. The relationship between crash and driver factors and injury was assessed using logistic regression. Findings: Teen drivers, aged 14 and 15 years, had a statewide crash rate of 8 per 1,000 drivers from 2001 to 2013. The majority of crashes occurred in urban areas (51%), followed by in town (29%), remote rural areas (13%), and suburban areas (7%). Crash and injury crash rates increased as level of rurality increased. The odds of an injury crash increased more than 10-fold with the presence of multiple other teens as passengers, compared to no passengers (OR = 10.7, 95% CI: 7.1–16.2). Conclusions: Although 14- and 15-year-old drivers in Iowa have either limited unsupervised (school permits) or supervised only driving restrictions, they are overrepresented in terms of crashes and injury crashes. Rural roads and multiple teen passengers are particularly problematic in terms of injury outcomes. Practical applications: Results from this study support passenger restrictions and teen driving interventions designed with a rural focus.     

Antilock Brake Systems and Risk of Different Types of Crashes in Traffic

While antilock braking systems (ABS) have been convincingly demonstrated to enhance test track braking performance, their effect on crash risk in actual driving remains less clear. This paper examines how ABS influences crash risk using mainly two published studies which used police-reported crashes. The published findings are augmented by including new data and additional results. All the work is based on seven General Motors (GM) passenger vehicles having ABS as standard equipment for 1992 models but not available for 1991 models. The ratio of crashes under an adverse condition (say, when the pavement is wet) to under a normal condition (say, when the pavement is dry) is compared for ABS and non-ABS vehicles. After correcting for such factors as model year effects not linked to ABS, the following associations between ABS and crash risk were found by averaging data from the five states Texas, Missouri, North Carolina, Pennsylvania and Indiana (the errors are one standard error): a (10 ± 3)% relative lower crash risk on wet roads compared to the corresponding comparison on dry roads; a (22 ± 11)% lower risk of a pedestrian crash compared to the risk of a non-pedestrian crash; a (39 ± 16)% increase in rollover crash risk compared to the risk of a non-rollover crash. Data from the same Ave states were used to examine two-vehicle rear-end collisions. Using the assumption that side-impact crashes estimate exposure, it was found that for wet roads ABS reduces the risk of crashing into a lead vehicle by (32 ± 8)%, but increases the risk of being struck in the rear by (30 ± 14)%. The results from this study and from all available reported studies are summarized in tabular form.     

Using medico-legal data to investigate fatal older road user crash circumstances and risk factors

Objective: This study used medico-legal data to investigate fatal older road user (ORU, aged 65 years and older) crash circumstances and risk factors relating to 4 key components of the Safe System approach (e.g., roads and roadsides, vehicles, road users, and speeds) to identify areas of priority for targeted prevention activity.

Method: The Coroners' Court of Victoria's (CCOV) Surveillance Database was searched to identify and describe the frequency and rate per 100,000 population of fatal ORU crashes in the Australian state of Victoria for 2013–2014. Information relating to the deceased ORU, crash characteristics and circumstances, and risk factors was extracted and analyzed.

Results: One hundred and thirty-eight unintentional fatal ORU crashes were identified in the CCOV Surveillance Database. Of these fatal ORU crashes, most involved older drivers (44%), followed by older pedestrians (32%), older passengers (17%), older pedal cyclists (4%), older motorcyclists (1%), and older mobility scooter users (1%). The average annual rate of fatal ORU crashes per 100,000 population was 8.1 (95% confidence interval [CI], 6.0–10.2). In terms of the crash characteristics and circumstances, most fatal ORU crashes involved a counterpart (98%), of which the majority were passenger cars (50%) or fixed/stationary objects (25%), including trees (46%) or embankments (23%). In addition, most fatal ORU crashes occurred close to home (73%), on-road (87%), on roads that were paved (94%), on roads with light traffic volume (37%), and during low-risk conditions: between 12 p.m. and 6 p.m. (44%), on weekdays (80%), during daylight (75%), and under dry/clear conditions (81%). Road user (RU) error was identified by the police and/or the coroner for the majority of fatal crashes (55%), with a significant proportion of deceased ORUs deemed to have failed to yield (54%) or misjudged (41%).

Conclusions: RU error was the most significant factor identified in fatal ORU crashes, which suggests that there is a limited capacity of the road system to fully accommodate RU errors. Initiatives related to safer roads and roadsides, vehicles, speed zones, as well as behavioral approaches are key areas of priority for targeted activity to prevent fatal ORU crashes in the future.     

The effectiveness of lane departure warning systems—A reduction in real-world passenger car injury crashes

Objective: The objective of this study was to estimate the safety benefits of in vehicle lane departure warning (LDW) and lane keeping aid (LKA) systems in reducing relevant real-world passenger car injury crashes.

Methods: The study used an induced exposure method, where LDW/LKA-sensitive and nonsensitive crashes were compared for Volvo passenger cars equipped with and without LDW/LKA systems. These crashes were matched by car make, model, model year, and technical equipment; that is, low-speed autonomous emergency braking (AEB) called City Safety (CS). The data were extracted from the Swedish Traffic Accident Data Acquisition database (STRADA) and consisted of 1,853 driver injury crashes that involved 146 LDW-equipped cars, 11 LKA-equipped cars, and 1,696 cars without LDW/LKA systems.

Results: The analysis showed a positive effect of the LDW/LKA systems in reducing lane departure crashes. The LDW/LKA systems were estimated to reduce head-on and single-vehicle injury crashes on Swedish roads with speed limits between 70 and 120 km/h and with dry or wet road surfaces (i.e., not covered by ice or snow) by 53% with a lower limit of 11% (95% confidence interval [CI]). This reduction corresponded to a reduction of 30% with a lower limit of 6% (95% CI) for all head-on and single-vehicle driver injury crashes (including all speed limits and all road surface conditions).

Conclusions: LDW/LKA systems were estimated to lower the driver injury risk in crash types that the systems are designed to prevent; that is, head-on and single-vehicle crashes. Though these are important findings, they were based on a small data set. Therefore, further research is desirable to evaluate the effectiveness of LDW/LKA systems under real-world conditions and to differentiate the effectiveness between technical solutions (i.e., LDW and LKA) proposed by different manufacturers.     

Factors associated with motorcycle traffic crash fatalities among active duty U.S. Army personnel

Objective: Research on factors associated with motorcycle fatalities among active duty U.S. Army personnel is limited. This analysis describes motorcycle crash–related injuries from 1995 through 2014 and assesses the effect of alcohol use and helmet use on the risk of fatal injury among active duty U.S. Army motorcycle operators involved in a traffic crash, controlling for other factors shown to be potentially associated with fatality in this population.

Methods: Demographics, crash information, and injury data were obtained from safety reports maintained in the Army Safety Management Information System. Traffic crashes were defined as crashes occurring on a paved public or private roadway or parking area, including those on a U.S. Army installation. Analysis was limited to motorcycle operators. Odds ratios (ORs) and 95% confidence intervals (95% CIs) from a multivariable analysis estimated the effect of alcohol use and helmet use on the risk of a fatal injury given a crash occurred, controlling for operator and crash characteristics.

Results: Of the 2,852 motorcycle traffic crashes, most involved men (97%), operators aged 20–29 years of age (60%), and operators who wore helmets (95%) and did not use alcohol (92%). Two thirds of reported crashes resulted in injuries requiring a lost workday; 17% resulted in fatality. Controlling for operator and crash characteristics, motorcycle traffic crashes involving operators who had used alcohol had a 3.1 times higher odds of fatality than those who did not use alcohol (OR =3.14; 95% CI, 2.17–4.53). Operators who did not wear a helmet had 1.9 times higher odds of fatality than those who did wear a helmet (OR =1.89; 95% CI, 1.24–2.89).

Conclusions: Among U.S. Army motorcycle operators, alcohol use and not wearing a helmet increased the odds of fatality, given that a crash occurred, and additional modifiable risk factors were identified. Results will help inform U.S. Army motorcycle policies and training.     

Rage against the machine? Google's self-driving cars versus human drivers

IntroductionAutomated driving represents both challenges and opportunities in highway safety. Google has been developing self-driving cars and testing them under employee supervision on public roads since 2009. These vehicles have been involved in several crashes, and it is of interest how this testing program compares to human drivers in terms of safety.MethodsGoogle car crashes were coded by type and severity based on narratives released by Google. Crash rates per million vehicle miles traveled (VMT) were computed for crashes deemed severe enough to be reportable to police. These were compared with police-reported crash rates for human drivers. Crash types also were compared.ResultsGoogle cars had a much lower rate of police-reportable crashes per million VMT than human drivers in Mountain View, Calif., during 2009–2015 (2.19 vs 6.06), but the difference was not statistically significant. The most common type of collision involving Google cars was when they got rear-ended by another (human-driven) vehicle. Google cars shared responsibility for only one crash.ConclusionsThese results suggest Google self-driving cars, while a test program, are safer than conventional human-driven passenger vehicles; however, currently there is insufficient information to fully examine the extent to which disengagements affected these results.Practical applicationResults suggest that highly-automated vehicles can perform more safely than human drivers in certain conditions, but will continue to be involved in crashes with conventionally-driven vehicles.     

The influence of rear turn-signal characteristics on crash risk

IntroductionThe relationship between the relative risk of a rear-end collision during a turn, merge, or lane change maneuver and the characteristics of the rear turn-signal configuration was examined using crash data from seven states in the United States.MethodRear turn-signal characteristics—including color, optics, separation, and light source—were identified for 55 vehicle models and used in a logistic regression analysis to model the odds of a rear-end collision. Additional variables including driver demographics (gender, age), vehicle age, and light condition were also modeled. Risk was assessed using a contrast group of striking vehicles in similar collisions.ResultsThe results suggest that the odds of being the struck vehicle were 3% to 28% lower among vehicles equipped with amber versus red turn signals. Although the analysis suggests that there may be a safety benefit associated with amber rear turn signals, it is unclear whether turn-signal color alone is responsible.Impact on IndustryThe results suggest that aspects of a vehicle's rear signal characteristics may influence crash risk.     

The Real-World Safety Potential of Connected Vehicle Technology

Objective: This article estimates the safety potential of a current commercially available connected vehicle technology in real-world crashes.

Method: Data from the Centre for Automotive Safety Research's at-scene in-depth crash investigations in South Australia were used to simulate the circumstances of real-world crashes. A total of 89 crashes were selected for inclusion in the study. The crashes were selected as representative of the most prevalent crash types for injury or fatal crashes and had potential to be mitigated by connected vehicle technology. The trajectory, speeds, braking, and impact configuration of the selected in-depth cases were replicated in a software package and converted to a file format allowing “replay” of the scenario in real time as input to 2 Cohda Wireless MK2 onboard units. The Cohda Wireless onboard units are a mature connected vehicle technology that has been used in both the German simTD field trial and the U.S. Department of Transport's Safety Pilot project and have been tuned for low false alarm rates when used in the real world. The crash replay was achieved by replacing each of the onboard unit Global Positioning System (GPS) inputs with the simulated data of each of the involved vehicles. The time at which the Cohda Wireless threat detection software issued an elevated warning was used to calculate a new impact speed using 3 different reaction scenarios and 2 levels of braking.

Results: It was found that between 37 and 86% of the simulated crashes could be avoided, with highest percentage due a fully autonomous system braking at 0.7 g. The same system also reduced the impact speed relative to the actual crash in all cases. Even when a human reaction time of 1.2 s and moderate braking of 0.4 g was assumed, the impact speed was reduced in 78% of the crashes. Crash types that proved difficult for the threat detection engine were head-on crashes where the approach angle was low and right turn–opposite crashes.

Conclusions: These results indicate that connected vehicle technology can be greatly beneficial in real-world crash scenarios and that this benefit would be maximized by having the vehicle intervene autonomously with heavy braking. The crash types that proved difficult for the connected vehicle technology could be better addressed if controller area network (CAN) information is available, such as steering wheel angle, so that driver intent can be inferred sooner. More accurate positioning in the real world (e.g., combining satellite positioning and accelerometer data) would allow the technology to be more effective for near-collinear head-on and rear-end crashes, because the low approach angles that are common in such crashes are currently ignored in order to minimize false alarms due to positioning uncertainty.