Characteristics of rear-end crashes involving passenger vehicles with automatic emergency braking

Abstract

Objectives: Automatic emergency braking (AEB) is a proven effective countermeasure for preventing front-to-rear crashes, but it has not yet fully lived up to its estimated potential. This study identified the types of rear-end crashes in which striking vehicles with AEB are overrepresented to determine whether the system is more effective in some situations than in others, so that additional opportunities for increasing AEB effectiveness might be explored.

Methods: Rear-end crash involvements were extracted from 23?U.S. states during 2009–2016 for striking passenger vehicles with and without AEB among models where the system was optional. Logistic regression was used to examine the odds that rear-end crashes with various characteristics involved a striking vehicle with AEB, controlling for driver and vehicle features.

Results: Striking vehicles were significantly more likely to have AEB in crashes where the striking vehicle was turning relative to when it was moving straight (odds ratio [OR]?=?2.35; 95% confidence interval [CI], 1.76, 3.13); when the struck vehicle was turning (OR = 1.66; 95% CI, 1.25, 2.21) or changing lanes (OR = 2.05; 95% CI, 1.13, 3.72) relative to when it was slowing or stopped; when the struck vehicle was not a passenger vehicle or was a special use vehicle relative to a car (OR = 1.61; 95% CI, 1.01, 2.55); on snowy or icy roads relative to dry roads (OR = 1.83; 95% CI, 1.16, 2.86); or on roads with speed limits of 70+ mph relative to those with 40 to 45?mph speed limits (OR = 1.49; 95% CI, 1.10, 2.03). Overall, 25.3% of crashes where the striking vehicle had AEB had at least one of these overrepresented characteristics, compared with 15.9% of strikes by vehicles without AEB.

Conclusions: The typical rear-end crash occurs when 2 passenger vehicles are proceeding in line, on a dry road, and at lower speeds. Because atypical crash circumstances are overrepresented among rear-end crashes by striking vehicles with AEB, it appears that the system is doing a better job of preventing the more typical crash scenario. Consumer information testing programs of AEB use a test configuration that models the typical rear-end crash type. Testing programs promoting good AEB performance in crash circumstances where vehicles with AEB are overrepresented could guide future development of AEB systems that perform well in these additional rear-end collision scenarios.     

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.     

Estimated benefit of automated emergency braking systems for vehicle–pedestrian crashes in the United States

Abstract

Objective: The objective of this research study is to estimate the benefit to pedestrians if all U.S. cars, light trucks, and vans were equipped with an automated braking system that had pedestrian detection capabilities.

Methods: A theoretical automatic emergency braking (AEB) model was applied to real-world vehicle–pedestrian collisions from the Pedestrian Crash Data Study (PCDS). A series of potential AEB systems were modeled across the spectrum of expected system designs. Both road surface conditions and pedestrian visibility were accounted for in the model. The impact speeds of a vehicle without AEB were compared to the estimated impact speeds of vehicles with a modeled pedestrian detecting AEB system. These impacts speeds were used in conjunction with an injury and fatality model to determine risk of Maximum Abbreviated Injury Scale of 3 or higher (MAIS 3+) injury and fatality.

Results: AEB systems with pedestrian detection capability, across the spectrum of expected design parameters, reduced fatality risk when compared to human drivers. The most beneficial system (time-to-collision [TTC]?=?1.5?s, latency = 0?s) decreased fatality risk in the target population between 84 and 87% and injury risk (MAIS score 3+) between 83 and 87%.

Conclusions: Though not all crashes could be avoided, AEB significantly mitigated risk to pedestrians. The longer the TTC of braking and the shorter the latency value, the higher benefits showed by the AEB system. All AEB models used in this study were estimated to reduce fatalities and injuries and were more effective when combined with driver braking.     

Creating Pedestrian Crash Scenarios in a Driving Simulator Environment

Objective: In 2012 in the United States, pedestrian injuries accounted for 3.3% of all traffic injuries but, disproportionately, pedestrian fatalities accounted for roughly 14% of traffic-related deaths (NHTSA 2014 NHTSA. Traffic Safety Facts 2012 Pedestrians. Washington, DC: Author; 2014. DOT HS 811 888. [Google Scholar]). In many other countries, pedestrians make up more than 50% of those injured and killed in crashes. This research project examined driver response to crash-imminent situations involving pedestrians in a high-fidelity, full-motion driving simulator. This article presents a scenario development method and discusses experimental design and control issues in conducting pedestrian crash research in a simulation environment. Driving simulators offer a safe environment in which to test driver response and offer the advantage of having virtual pedestrian models that move realistically, unlike test track studies, which by nature must use pedestrian dummies on some moving track.

Methods: An analysis of pedestrian crash trajectories, speeds, roadside features, and pedestrian behavior was used to create 18 unique crash scenarios representative of the most frequent and most costly crash types. For the study reported here, we only considered scenarios where the car is traveling straight because these represent the majority of fatalities. We manipulated driver expectation of a pedestrian both by presenting intersection and mid-block crossing as well as by using features in the scene to direct the driver's visual attention toward or away from the crossing pedestrian. Three visual environments for the scenarios were used to provide a variety of roadside environments and speed: a 20–30 mph residential area, a 55 mph rural undivided highway, and a 40 mph urban area.

Results: Many variables of crash situations were considered in selecting and developing the scenarios, including vehicle and pedestrian movements; roadway and roadside features; environmental conditions; and characteristics of the pedestrian, driver, and vehicle. The driving simulator scenarios were subjected to iterative testing to adjust time to arrival triggers for the pedestrian actions. This article discusses the rationale behind creating the simulator scenarios and some of the procedural considerations for conducting this type of research.

Conclusions: Crash analyses can be used to construct test scenarios for driver behavior evaluations using driving simulators. By considering trajectories, roadway, and environmental conditions of real-world crashes, representative virtual scenarios can serve as safe test beds for advanced driver assistance systems. The results of such research can be used to inform pedestrian crash avoidance/mitigation systems by identifying driver error, driver response time, and driver response choice (i.e., steering vs. braking).     

AEB effectiveness evaluation based on car-to-cyclist accident reconstructions using video of drive recorder

Objective: Though autonomous emergency braking (AEB) systems for car-to-cyclist collisions have been under development, an estimate of the benefit of AEB systems based on an analysis of accident data is needed for further enhancing their development. Compared to the data available from in-depth accident data files, data provided by drive recorders can be used to reconstruct car-to-cyclist collisions with greater accuracy because the position of cyclists can be observed from the videos. In this study, using data from drive recorders, the performance and limitations of AEB systems were investigated.

Method: Data of drive recorders involving taxi-to-cyclist collisions were collected. Using the images collected from the drive recorders of those taxis, 40 cases of 90° car-to-cyclist intersection collisions were reconstructed using PC-Crash. Then, the collisions were reconstructed again utilizing car models with AEB systems installed while changing the sensor’s field of view (FOV) and the delay time of initiating vehicle deceleration.

Results: The angle of FOV has a significant influence on avoiding car-to-cyclist collisions. Using a 50° FOV with a braking delay time of 0.5?s resulted in avoiding 6 collisions, and using a 90° FOV resulted in avoiding an additional 14 collisions. Even when installing an ideal AEB system providing 360° FOV and no delay time for braking, 8 collisions were not avoided, though the impact velocities were reduced for all of these remaining collisions. These collisions were caused by the cyclists’ sudden appearance in front of cars, and the time-to-collision (TTC) when the cyclists appeared was less than 0.9?s.

Conclusion: The AEB systems were effective for mitigating collisions that occurred due to driver perception delay. Because cyclists have a traveling velocity, a wide-angle FOV is effective for reduction of car-to-cyclist intersection collisions. The reduction of delay time in braking can reduce the number of collisions that are close to the braking performance limit. The collisions that remained even with an ideal AEB system in the PC-Crash simulation indicate that such collisions could still occur for autonomous cars if the traffic environment does not change.     

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.     

Driver Behavior During Overtaking Maneuvers from the 100-Car Naturalistic Driving Study

Objective: Lane changes with the intention to overtake the vehicle in front are especially challenging scenarios for forward collision warning (FCW) designs. These overtaking maneuvers can occur at high relative vehicle speeds and often involve no brake and/or turn signal application. Therefore, overtaking presents the potential of erroneously triggering the FCW. A better understanding of driver behavior during lane change events can improve designs of this human–machine interface and increase driver acceptance of FCW. The objective of this study was to aid FCW design by characterizing driver behavior during lane change events using naturalistic driving study data.

Methods: The analysis was based on data from the 100-Car Naturalistic Driving Study, collected by the Virginia Tech Transportation Institute. The 100-Car study contains approximately 1.2 million vehicle miles of driving and 43,000 h of data collected from 108 primary drivers. In order to identify overtaking maneuvers from a large sample of driving data, an algorithm to automatically identify overtaking events was developed. The lead vehicle and minimum time to collision (TTC) at the start of lane change events was identified using radar processing techniques developed in a previous study. The lane change identification algorithm was validated against video analysis, which manually identified 1,425 lane change events from approximately 126 full trips.

Results: Forty-five drivers with valid time series data were selected from the 100-Car study. From the sample of drivers, our algorithm identified 326,238 lane change events. A total of 90,639 lane change events were found to involve a closing lead vehicle. Lane change events were evenly distributed between left side and right side lane changes. The characterization of lane change frequency and minimum TTC was divided into 10 mph speed bins for vehicle travel speeds between 10 and 90 mph. For all lane change events with a closing lead vehicle, the results showed that drivers change lanes most frequently in the 40–50 mph speed range. Minimum TTC was found to increase with travel speed. The variability in minimum TTC between drivers also increased with travel speed.

Conclusions: This study developed and validated an algorithm to detect lane change events in the 100-Car Naturalistic Driving Study and characterized lane change events in the database. The characterization of driver behavior in lane change events showed that driver lane change frequency and minimum TTC vary with travel speed. The characterization of overtaking maneuvers from this study will aid in improving the overall effectiveness of FCW systems by providing active safety system designers with further understanding of driver action in overtaking maneuvers, thereby increasing system warning accuracy, reducing erroneous warnings, and improving driver acceptance.     

Motorcycle active safety systems: Assessment of the function and applicability using a population-based crash data set

Objective: Motorcycles and mopeds, often referred to as powered 2-wheelers (PTWs), play an important role in personal mobility worldwide. Despite their advantages, including low cost, space occupancy, and fuel efficiency, the risk of sustaining serious or fatal injuries is higher than that for occupants of passenger cars. The development of safety systems specific for PTWs represents a potential way to reduce casualties among riders. With the proliferation of new active and passive safety technologies, the question as to which might offer the most value is important. In this context, a prioritization process was applied to a set of PTW active safety systems to evaluate their applicability to crash scenarios alone and in combination. The systems included in the study were antilock braking (ABS), autonomous emergency braking (AEB), collision warning, curve warning, and curve assist.

Methods: With the functional performance of the 5 safety systems established, the relevance of each system to specific crash configurations and vehicle movements defined by a standardized accident classification system used in Victoria, Australia, was rated by 2 independent reviewers, with a third reviewer acting as a moderator where disagreements occurred. Ratings ranged from 1 (definitely not applicable) to 4 (definitely applicable). Using population-based crash data, the number and percentage of crashes that each safety system could potentially influence, or be relevant for, was defined. Applying accepted injury costs permitted the derivation of the societal economic cost of PTW crashes and the potential reductions associated with each safety system given a theoretical crash avoidance effectiveness of 100%.

Results: In the 12-year period 2000–2011, 23,955 PTW riders and 1292 pillion passengers were reported to have been involved in a road crash, with over 500 killed and more than 10,000 seriously injured; only 3.5% of riders/pillion passengers were uninjured. The total economic cost associated with these injured riders and pillion passengers was estimated to be AU$11.1 billion (US$7.70 billion; €6.67 billion). The 5 safety systems, as single solutions or in combination, were relevant to 57% of all crashes and to 74% of riders killed. Antilock braking was found to be relevant to the highest number of crashes, with incremental increases in coverage when combined with other safety systems.

Conclusions: The findings demonstrate that ABS, alone and in combination with other safety systems, has the potential to mitigate or possibly prevent a high percentage of PTW crashes in the considered setting. Other safety systems can influence different crash scenarios and are also recommended. Given the high cost of motorcycle crashes and the increasing number of PTW safety technologies, the proposed approach can be used to inform the process of selection of the most suitable interventions to improve PTW safety.     

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.     

Simulating the relative influence of tire,vehicle and driver factors on forward collision accident rates

Introduction: There is currently a strong focus within the automotive industry centered on traffic safety, with topics such as distracted driving, accident avoidance technologies, and autonomous vehicles. These papers tend to focus on the possible improvements from a single factor. However, there are many factors that are present in each accident, and it is important to understand the influence of each factor on the relative accident risk in order to identify the most effective approaches for improving driver safety. Rear-end accidents tend to be the most common accident type with approximately 1.8 M cases, or 31% of all accidents, in 2012, according to NHTSA. Of the rear-end accident scenarios, approximately 18–23% occur on wet surfaces. Method: A Monte Carlo Forward Collision Simulation models the conditions of a wet rear-end accident and estimates the relative impact of various vehicle collision parameters. The model takes distributions of these parameters as inputs, and outputs a risk of collision relative to a known reference case. The parameters that can be studied include: tire grip level, road grip level, vehicle velocity, following distances, and the presence of vehicle technologies (ABS, FCW & AEB). Distributions of some of these parameters have been improved thanks to Naturalistic Driving Study data from SHRP2. Results: This study shows that these vehicle systems have a large impact on safety and can change the amount of influence attributed to other parameters such as tire grip levels. As the use of automated vehicle systems expands, so will the influence of tire grip performance levels on collision risks. Practical Applications: It is more important than ever for consumers and auto manufacturers to consider tire performance levels. Therefore, the tire industry should continue to focus on wet grip as a key performance related to safety and should strive to continue to improve tire performance.     

Autonomous emergency braking systems adapted to snowy road conditions improve drivers' perceived safety and trust

Objective: This study investigated drivers' evaluation of a conventional autonomous emergency braking (AEB) system on high and reduced tire–road friction and compared these results to those of an AEB system adaptive to the reduced tire–road friction by earlier braking. Current automated systems such as the AEB do not adapt the vehicle control strategy to the road friction; for example, on snowy roads. Because winter precipitation is associated with a 19% increase in traffic crashes and a 13% increase in injuries compared to dry conditions, the potential of conventional AEB to prevent collisions could be significantly improved by including friction in the control algorithm. Whereas adaption is not legally required for a conventional AEB system, higher automated functions will have to adapt to the current tire–road friction because human drivers will not be required to monitor the driving environment at all times. For automated driving functions to be used, high levels of perceived safety and trust of occupants have to be reached with new systems. The application case of an AEB is used to investigate drivers' evaluation depending on the road condition in order to gain knowledge for the design of future driving functions.

Methods: In a driving simulator, the conventional, nonadaptive AEB was evaluated on dry roads with high friction (μ = 1) and on snowy roads with reduced friction (μ = 0.3). In addition, an AEB system adapted to road friction was designed for this study and compared with the conventional AEB on snowy roads with reduced friction. Ninety-six drivers (48 males, 48 females) assigned to 5 age groups (20–29, 30–39, 40–49, 50–59, and 60–75 years) drove with AEB in the simulator. The drivers observed and evaluated the AEB's braking actions in response to an imminent rear-end collision at an intersection.

Results: The results show that drivers' safety and trust in the conventional AEB were significantly lower on snowy roads, and the nonadaptive autonomous braking strategy was considered less appropriate on snowy roads compared to dry roads. As expected, the adaptive AEB braking strategy was considered more appropriate for snowy roads than the nonadaptive strategy. In conditions of reduced friction, drivers' subjective safety and trust were significantly improved when driving with the adaptive AEB compared to the conventional AEB. Women felt less safe than men when AEB was braking. Differences between age groups were not of statistical significance.

Conclusions: Drivers notice the adaptation of the autonomous braking strategy on snowy roads with reduced friction. On snowy roads, they feel safer and trust the adaptive system more than the nonadaptive automation.     

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.     

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.     

Using SHRP2 naturalistic driving data to examine driver speeding behavior

Problem: Speeding-related crashes continue to be a serious problem in the United States. According to the National Highway Traffic Safety Administration, 26% of all fatal crashes in 2017 had speeding as a contributing factor. Method: Vehicle speed data recorded during the Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study were analyzed to identify the frequency of speeding episodes. Up to 100 trips were sampled from 2,910 individual drivers aged 16–64. Vehicle speed data from individual trips were parsed into continuous speeding episodes (SEs) and Free-Flow Episodes (FFEs), which approximated opportunities to speed. Results & Discussion: Driving 10 mph above the posted speed limit (PSL) was common, and 99.8% of drivers had at least one occurrence SE within their trip sample, yielding an average of 2.75 SEs per trip (623,202 SEs in total). The analysis focused on a subset of higher-speed SEs in which the vehicle reached speeds of at least 15 mph above the PSL during the SE (71,113 SEs in total). Average maximum speeds for most higher-speed SEs ranged between 12 mph to 15 mph above the PSL, and most also lasted less than 2 min. Most drivers spent less than 5% of the FFE time speeding, and only a small number of drivers spent more than 10% of the time speeding. There was also a clear trend towards the younger group having higher overall percentages of SE time relative to FFE time. Practical Applications: The methods and measures developed in this study provide the foundation for future analyses to determine if there are different types of speeding that vary in terms of risky characteristics, and further, if certain drivers are more likely to engage in riskier speeding behavior. Identifying higher-risk speeders is an important step for developing countermeasures and strategies targeting drivers that are at greatest risk of speed-related crashes.     

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.     

Prevalence of driver physical factors leading to unintentional lane departure crashes

Objective: Some lane-keeping assist systems in development and production provide autonomous braking and steering to correct unintentional lane drift but otherwise require drivers to fully control their vehicles. The goal of this study was to quantify the proportion of drivers involved in unintentional lane drift crashes who would be unable to regain control of their vehicles to inform the design of such systems.

Methods: The NHTSA's National Motor Vehicle Crash Causation Survey collected in-depth, on-scene data for a nationally representative sample of 5,470 U.S. police-reported passenger vehicle crashes during 2005–2007 that occurred between 6 a.m. and midnight and for which emergency medical services were dispatched. The physical states of drivers involved in the 631 lane drift crashes in the sample, which represented 259,034 crashes nationally, were characterized.

Results: Thirty-four percent of drivers who crashed because they drifted from their lanes were sleeping or otherwise incapacitated. These drivers would be unlikely to regain full control of their vehicles if an active safety system prevented their initial drift. An additional 13% of these drivers had a nonincapacitating medical issue, blood alcohol concentration (BAC) ≥ 0.08%, or other physical factor that may not allow them to regain full vehicle control. When crashes involved serious or fatal injuries, 42% of drivers who drifted were sleeping or otherwise incapacitated, and an additional 14% were impacted by a nonincapacitating medical issue, BAC ≥ 0.08%, or other physical factor.

Conclusions: Designers of active safety systems that provide autonomous lateral control should consider that a substantial proportion of drivers at risk of lane drift crashes are incapacitated. Systems that provide only transient corrective action may not ultimately prevent lane departure crashes for these drivers, and drivers who do avoid lane drift crashes because of these systems may be at high risk of other types of crashes when they attempt to regain control. Active lane-keeping assist systems may need to be combined with in-vehicle driver monitoring to identify incapacitated drivers and safely remove them from the roadway if the systems are to reach their maximum potential benefit.     

Quantifying Vision Zero: Crash avoidance in rural and motorway accident scenarios by combination of ACC,AEB, and LKS projected to German accident occurrence

Abstract

Objective: The Vision Zero initiative pursues the goal of eliminating all traffic fatalities and severe injuries. Today’s advanced driver assistance systems (ADAS) are an important part of the strategy toward Vision Zero. In Germany in 2018 more than 26,000 people were killed or severely injured by traffic accidents on motorways and rural roads due to road accidents. Focusing on collision avoidance, a simulative evaluation can be the key to estimating the performance of state-of-the-art ADAS and identifying resulting potentials for system improvements and future systems.

This project deals with the effectiveness assessment of a combination of ADAS for longitudinal and lateral intervention based on German accident data. Considered systems are adaptive cruise control (ACC), autonomous emergency braking (AEB), and lane keeping support (LKS).

Methods: As an approach for benefit estimation of ADAS, the method of prospective effectiveness assessment is applied. Using the software rateEFFECT, a closed-loop simulation is performed on accident scenario data from the German In-Depth Accident Study (GIDAS) precrash matrix (PCM). To enable projection of results, the simulative assessment is amended with detailed single case studies of all treated cases without PCM data.

Results: Three categories among today’s accidents on German rural roads and motorways are reported in this study: Green, grey, and white spots.

Green spots identify accidents that can be avoided by state-of-the-art ADAS ACC, AEB, and LKS. Grey spots contain scenarios that require minor system modifications, such as reducing the activation speed or increasing the steering torque. Scenarios in the white category cannot be addressed by state-of-the-art ADAS. Thus, which situations demand future systems are shown. The proportions of green, grey, and white spots are determined related to the considered data set and projected to the entire GIDAS.

Conclusions: This article describes a systematic approach for assessing the effectiveness of ADAS using GIDAS PCM data to be able to project results to Germany. The closed-loop simulation run in rateEFFECT covers ACC, AEB, and LKS as well as relevant sensors for environment recognition and actuators for longitudinal and lateral vehicle control.

Identification of green spots evaluates safety benefits of state-of-the-art level 0–2 functions as a baseline for further system improvements to address grey spots. Knowing which accidents could be avoided by standard ADAS helps focus the evolution of future driving functions on white spots and thus aim for Vision Zero.     

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.     

Effect of automated versus manual emergency braking on rear seat adult and pediatric occupant precrash motion

Abstract

Objective: Emergency braking can potentially generate precrash occupant motion that may influence the effectiveness of restraints in the subsequent crash, particularly for rear-seated occupants who may be less aware of the impending crash. With the advent of automated emergency braking (AEB), the mechanism by which braking is achieved is changing, potentially altering precrash occupant motion. Further, due to anatomical and biomechanical differences across ages, kinematic differences between AEB and manual emergency braking (MEB) may vary between child and adult occupants. Therefore, the objective of this study was to quantify differences in rear-seated adult and pediatric kinematics and muscle activity during AEB and MEB scenarios.

Methods: Vehicle maneuvers were performed in a recent model year sedan traveling at 50?km/h. MEB (acceleration ～1?g) was achieved by the driver pressing the brake pedal with maximum effort. AEB (acceleration ～0.8?g) was triggered by the vehicle system. Inertial and Global Positioning System data were collected. Seventeen male participants aged 10–33 were restrained in the rear right passenger seat and experienced each maneuver twice. The subjects’ kinematics were recorded with an 8-camera 3D motion capture system. Electromyography (EMG) recorded muscle activity. Head and trunk displacements, raw and normalized by seated height, and peak head and trunk velocity were compared across age and between maneuvers. Mean EMG was calculated to interpret kinematic findings.

Results: Head and trunk displacement and peak velocity were greater in MEB than in AEB in both raw and normalized data (P?≤?.01). No effect of age was observed (P?≥?.21). Peak head and trunk velocities were greater in repetition 1 than in repetition 2 (P?≤?.006) in MEB but not in AEB. Sternocleidomastoid (SCM) mean EMG was greater in MEB compared to AEB, and muscle activity increased in repetition 2 in MEB.

Conclusions: Across all ages, head and trunk excursions were greater in MEB than AEB, despite increased muscle activity in MEB. This observation may suggest an ineffective attempt to brace the head or a startle reflex. The increased excursion in MEB compared to AEB may be attributed to differences in the acceleration pulses between the 2 scenarios. These results suggest that AEB systems can use specific deceleration profiles that have potential to reduce occupant motion across diverse age groups compared to sudden maximum emergency braking applied manually.