Improvement of driver active interventions during automated driving by displaying trajectory pointers—A driving simulator study

Abstract

Objective: The handover of vehicle control from automated to manual operation is a critical aspect of interaction between drivers and automated driving systems (ADS). In some cases, it is possible that the ADS may fail to detect an object. In this event, the driver must be aware of the situation and resume control of the vehicle without assistance from the system. Consequently, the driver must fulfill the following 2 main roles while driving: (1) monitor the vehicle trajectory and surrounding traffic environment and (2) actively take over vehicle control if the driver identifies a potential issue along the trajectory. An effective human–machine interface (HMI) is required that enables the driver to fulfill these roles. This article proposes an HMI that constantly indicates the future position of the vehicle.

Methods: This research used the Toyota Dynamic Driving Simulator to evaluate the effect of the proposed HMI and compares the proposed HMI with an HMI that notifies the driver when the vehicle trajectory changes. A total of 48 test subjects were divided into 2 groups of 24: One group used the HMI that constantly indicated the future position of the vehicle and the other group used the HMI that provided information when the vehicle trajectory changed.

The following instructions were given to the test subjects: (1) to not hold the steering wheel and to allow the vehicle to drive itself, (2) to constantly monitor the surrounding traffic environment because the functions of the ADS are limited, and (3) to take over driving if necessary.

The driving simulator experiments were composed of an initial 10-min acclimatization period and a 10-min evaluation period. Approximately 10?min after the start of the evaluation period, a scenario occurred in which the ADS failed to detect an object on the vehicle trajectory, potentially resulting in a collision if the driver did not actively take over control and manually avoid the object.

Results: The collision avoidance rate of the HMI that constantly indicated the future position of the vehicle was higher than that of the HMI that notified the driver of trajectory changes, χ² = 6.38, P < .05. The steering wheel hands-on and steering override timings were also faster with the proposed HMI (t test; P < .05).

Conclusions: This research confirmed that constantly indicating the position of the vehicle several seconds in the future facilitates active driver intervention when an ADS is in operation.     

Fatal crash between a car operating with automated control systems and a tractor-semitrailer truck

Abstract

Objective: The objective of this investigation was to evaluate the interaction between an SAE level 2 automated vehicle and the driver, including the limitations imposed by the vehicle on the driver.

Methods: A case study of the first fatal crash involving a vehicle operating with an automated control system was performed using scene evidence, vehicle damage, and recorded data available from the vehicle, and information from both drivers, including experience, phone records, computer systems, and medical information, was reviewed.

Results: System performance data downloaded from the car indicated that the driver was operating it using the Traffic-Aware Cruise Control and Autosteer lane-keeping systems, which are automated vehicle control systems within Tesla’s Autopilot suite. As the car crested the hill, a tractor trailer began its left turn onto a crossing roadway. Although reconstruction of the crash determined that there was sufficient sight distance for both drivers to see each other and take action, neither responded to the circumstances leading to the collision. Further, based on the speeds of the vehicles and simulations of the truck’s path, the car driver had at least 10.4?s to detect the truck and take evasive action. Neither the car driver nor the Autopilot system changed the vehicle’s velocity.

?At the time of the crash, the system performance data indicated that the last driver interaction with the system was 1?min 51?s prior when the cruise control speed was set to 74?mph. The driver was operating the vehicle using the Autopilot system for 37 of the 41?min in the last trip. During this period, the vehicle detected the driver’s hands on the steering wheel for a total of 25?s; each time his hands were detected on the wheel was preceded by a visual alert or auditory warning.

Conclusions: The National Transportation Safety Board (NTSB) determined that the probable cause of the Williston, Florida, crash was the truck driver’s failure to yield the right of way to the car, combined with the car driver’s inattention due to overreliance on vehicle automation, which resulted in the car driver’s lack of reaction to the presence of the truck. Contributing to the car driver’s overreliance on the vehicle automation was the car’s operational design, which permitted the driver’s prolonged disengagement from the driving task and his use of the automation in ways inconsistent with guidance and warnings from the manufacturer.     

Exploring relationships between observed activation rates and functional attributes of lane departure prevention

Objective: Drivers’ use of lane departure warning and prevention systems is lower than use of other crash avoidance technologies and varies significantly by manufacturer. One factor that may affect use is how well a system prevents unintended departures. The current study evaluated the performance of systems that assist in preventing departures by providing steering or braking input in a 2016 Chevrolet Malibu, 2016 Ford Fusion, 2016 Honda Accord, and 2018 Volvo S90. These vehicles were selected because a prior observational study found that the percentage of privately owned vehicles that had lane departure prevention systems turned on varied among these 4 automakers.

Method: In each vehicle, a test driver induced 40 lane drifts on left and right curves by steering the vehicle straight into the curve so that vehicles departed in the opposite direction and 40 lane drifts on straightaways by slight steering input to direct the vehicle to left and right lane markers.

Results: Vehicles from automakers with higher observed lane departure prevention use rates (Volvo, Chevrolet) featured systems that provided steering input earlier and more often avoided crossing lane markers by more than 35?cm compared to vehicles from automakers with lower observed use rates (Ford, Honda).

Conclusion: The study identified functional characteristics (i.e., timing of steering input, prevention of departures more than 35?cm) of lane departure prevention systems that were strongly associated with observed activation of these systems in privately owned vehicles. Although this relationship does not imply causation, the findings support the hypothesis that functional characteristics of lane departure prevention systems affect their use. Designers may be able to use these results to maximize driver acceptance of future implementations of lane departure prevention.     

Analysis of Driver Evasive Maneuvering Prior to Intersection Crashes Using Event Data Recorders

Objective: Intersection crashes account for over 4,500 fatalities in the United States each year. Intersection Advanced Driver Assistance Systems (I-ADAS) are emerging vehicle-based active safety systems that have the potential to help drivers safely navigate across intersections and prevent intersection crashes and injuries. The performance of an I-ADAS is expected to be highly dependent upon driver evasive maneuvering prior to an intersection crash. Little has been published, however, on the detailed evasive kinematics followed by drivers prior to real-world intersection crashes. The objective of this study was to characterize the frequency, timing, and kinematics of driver evasive maneuvers prior to intersection crashes.

Methods: Event data recorders (EDRs) downloaded from vehicles involved in intersection crashes were investigated as part of NASS-CDS years 2001 to 2013. A total of 135 EDRs with precrash vehicle speed and braking application were downloaded to investigate evasive braking. A smaller subset of 59 EDRs that collected vehicle yaw rate was additionally analyzed to investigate evasive steering. Each vehicle was assigned to one of 3 precrash movement classifiers (traveling through the intersection, completely stopped, or rolling stop) based on the vehicle's calculated acceleration and observed velocity profile. To ensure that any significant steering input observed was an attempted evasive maneuver, the analysis excluded vehicles at intersections that were turning, driving on a curved road, or performing a lane change. Braking application at the last EDR-recorded time point was assumed to indicate evasive braking. A vehicle yaw rate greater than 4° per second was assumed to indicate an evasive steering maneuver.

Results: Drivers executed crash avoidance maneuvers in four-fifths of intersection crashes. A more detailed analysis of evasive braking frequency by precrash maneuver revealed that drivers performing complete or rolling stops (61.3%) braked less often than drivers traveling through the intersection without yielding (79.0%). After accounting for uncertainty in the timing of braking and steering data, the median evasive braking time was found to be between 0.5 to 1.5 s prior to impact, and the median initial evasive steering time was found to occur between 0.5 and 0.9 s prior to impact. The median average evasive braking deceleration for all cases was found to be 0.58 g. The median of the maximum evasive vehicle yaw rates was found to be 8.2° per second. Evasive steering direction was found to be most frequently in the direction of travel of the approaching vehicle.

Conclusions: The majority of drivers involved in intersection crashes were alert enough to perform an evasive action. Most drivers used a combination of steering and braking to avoid a crash. The average driver attempted to steer and brake at approximately the same time prior to the crash.     

Evaluation of the safety performance of highway alignments based on fault tree analysis and safety boundaries

Objectives: To overcome the limitations of previous highway alignment safety evaluation methods, this article presents a highway alignment safety evaluation method based on fault tree analysis (FTA) and the characteristics of vehicle safety boundaries, within the framework of dynamic modeling of the driver–vehicle–road system.

Methods: Approaches for categorizing the vehicle failure modes while driving on highways and the corresponding safety boundaries were comprehensively investigated based on vehicle system dynamics theory. Then, an overall crash probability model was formulated based on FTA considering the risks of 3 failure modes: losing steering capability, losing track-holding capability, and rear-end collision.

Results: The proposed method was implemented on a highway segment between Bengbu and Nanjing in China. A driver–vehicle–road multibody dynamics model was developed based on the 3D alignments of the Bengbu to Nanjing section of Ning-Luo expressway using Carsim, and the dynamics indices, such as sideslip angle and, yaw rate were obtained. Then, the average crash probability of each road section was calculated with a fixed-length method. Finally, the average crash probability was validated against the crash frequency per kilometer to demonstrate the accuracy of the proposed method. The results of the regression analysis and correlation analysis indicated good consistency between the results of the safety evaluation and the crash data and that it outperformed the safety evaluation methods used in previous studies.

Conclusion: The proposed method has the potential to be used in practical engineering applications to identify crash-prone locations and alignment deficiencies on highways in the planning and design phases, as well as those in service.     

Residual road departure crashes after full deployment of LDW and LDP systems

Abstract

Objective: Road departures are one of the most severe crash modes in the United States. To help reduce this risk, vehicles are being introduced in the United States with lane departure warning (LDW) systems, which warn the driver of a departure, and lane departure prevention (LDP) systems, which assist the driver in steering back to the roadway. Previous studies have estimated that LDW/LDP systems may prevent one third of drift-out-of-lane road departure crashes. This study investigates the crashes that were not prevented, to potentially set research priorities for next-generation road departure prevention systems.

Methods: The event data recorder (EDR) data from 128 road departure crashes in the National Automotive Sampling System Crashworthiness Data System (NASS-CDS) from 2011 to 2015 were mapped onto the vehicle trajectory and simulated with LDW/LDP to assess the potential for crash avoidance. The model predicted that 63–83% of single-vehicle road departure crashes may not be prevented by an LDW system and 49% may not be prevented by an LDP system.

Results and Conclusions: For LDP systems, which were assumed to have zero latency, no crashes were avoided if the time-to-collision (TTC) from lane crossing to impact was less than 0.55?s. Obstacles such as guardrails and traffic barriers, which tend to be very close to the road, were more common among the remaining crashes. The study shows that LDW/LDP systems are limited by two factors, driver reaction time and TTC to the roadside object. Thus, earlier driver response and longer TTC may help in these situations.     

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.     

Trends in aggressivity and driver risk for cars,SUVs, and pickups: Vehicle incompatibility from 1989 to 2016

Abstract

Objective: When 2 vehicles of different sizes collide, the occupants of the smaller vehicle are more likely to be injured than the occupants of the larger vehicle. The larger vehicle is both more protective of its own occupants and more aggressive toward occupants of the other vehicle. However, larger, heavier vehicles tend to be designed in ways that amplify their incompatibility with smaller, lighter vehicles (by having a higher ride height, for example). A 2012 study by the Insurance Institute for Highway Safety (IIHS) concluded that fatalities caused by design incompatibility have decreased in recent years. The current study was conducted to update the 2012 IIHS analysis and to explore trends in vehicle incompatibility over time.

Methods: Analyses examined deaths in crashes involving 1- to 4-year-old passenger vehicles from 1989 to 2016 collected from the Fatality Analysis Reporting System (FARS). Trends in driver risk were examined by comparing driver death rates per million registered vehicle years across vehicle type and size. Trends in aggressivity were examined by comparing partner driver death rates across vehicle type and size.

Results: Cars and SUVs have continued their trend toward reduced incompatibility. In 1989–1992, SUVs were 132% more likely to kill the driver in a partner car compared with when a car crashed with another car. By 2013–2016, this value had dropped to 28%. Pickups and cars remain just as incompatible in 2013–2016 as they were in 1989–1992, however (159% vs. 158%). Remaining pickup incompatibility may be largely due to excess curb weight rather than to shape or design features, because light pickups were just 23% more likely to kill the driver in a partner car compared with when a car crashed with another car.

Conclusions: The trend toward reduced fleet incompatibility has continued in the latest crash data, particularly for cars and SUVs. Although pickup–car incompatibility has also decreased over time, pickups remain disproportionately aggressive toward other vehicles, possibly due to their greater average curb weight. Reducing the weight of some of the heaviest vehicles and making crash avoidance technology fitment more widespread may be promising means to reduce remaining fleet incompatibility. Identifying the source of remaining incompatibility will be important for safety improvements going forward.     

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).     

Computational modeling and analysis of thoracolumbar spine fractures in frontal crash reconstruction

Abstract

Objective: This study aimed to reconstruct 11 motor vehicle crashes (6 with thoracolumbar fractures and 5 without thoracolumbar fractures) and analyze the fracture mechanism, fracture predictors, and associated parameters affecting thoracolumbar spine response.

Methods: Eleven frontal crashes were reconstructed with a finite element simplified vehicle model (SVM). The SVM was tuned to each case vehicle and the Total HUman Model for Safety (THUMS) Ver. 4.01 was scaled and positioned in a baseline configuration to mimic the documented precrash driver posture. The event data recorder crash pulse was applied as a boundary condition. For the 6 thoracolumbar fracture cases, 120 simulations to quantify uncertainty and response variation were performed using a Latin hypercube design of experiments (DOE) to vary seat track position, seatback angle, steering column angle, steering column position, and D-ring height. Vertebral loads and bending moments were analyzed, and lumbar spine indices (unadjusted and age-adjusted) were developed to quantify the combined loading effect. Maximum principal strain and stress data were collected in the vertebral cortical and trabecular bone. DOE data were fit to regression models to examine occupant positioning and thoracolumbar response correlations.

Results: Of the 11 cases, both the vertebral compression force and bending moment progressively increased from superior to inferior vertebrae. Two thoracic spine fracture cases had higher average compression force and bending moment across all thoracic vertebral levels, compared to 9 cases without thoracic spine fractures (force: 1,200.6 vs. 640.8 N; moment: 13.7 vs. 9.2?Nm). Though there was no apparent difference in bending moment at the L1–L2 vertebrae, lumbar fracture cases exhibited higher vertebral bending moments in L3–L4 (fracture/nonfracture: 45.7 vs. 33.8?Nm). The unadjusted lumbar spine index correctly predicted thoracolumbar fracture occurrence for 9 of the 11 cases (sensitivity?=?1.0; specificity?=?0.6). The age-adjusted lumbar spine index correctly predicted thoracolumbar fracture occurrence for 10 of the 11 cases (sensitivity?=?1.0; specificity?=?0.8). The age-adjusted principal stress in the trabecular bone was an excellent indicator of fracture occurrence (sensitivity?=?1.0; specificity?=?1.0). A rearward seat track position and reclined seatback increased the thoracic spine bending moment by 111–329%. A more reclined seatback increased the lumbar force and bending moment by 16–165% and 67–172%, respectively.

Conclusions: This study provided a computational framework for assessing thoracolumbar fractures and also quantified the effect of precrash driver posture on thoracolumbar response. Results aid in the evaluation of motor vehicle crash–induced vertebral fractures and the understanding of factors contributing to fracture risk.     

自适应滑模控制器的EPS侧风反向控制研究

为了研究在侧风影响下汽车正向助力转向偏移过大而威胁驾驶员行车安全的问题,提出一种将反向助力和自适应滑模控制器相结合的控制方法。该方法通过驾驶员转矩和汽车车速的配比设计反向助力特性曲线,并利用自适应滑模电机控制器控制电机输出助力转矩,使汽车在转向过程中,增加了驾驶员转向的阻尼感,也同时提高了驾驶员对转向电机的实时操纵性。将其应用到汽车EPS系统中,仿真结果表明,在不同的车速、风速下,采用反向控制策略不仅减小了方向盘角度、齿条位移,还减小了汽车横摆角速度,可以显著地改善汽车行驶的稳定性和安全性。     

The detection of drowsiness using a driver monitoring system

Abstract

Objective: Drowsiness is a major cause of driver impairment leading to crashes and fatalities. Research has established the ability to detect drowsiness with various kinds of sensors. We studied drowsy driving in a high-fidelity driving simulator and evaluated the ability of an automotive production-ready driver monitoring system (DMS) to detect drowsy driving. Additionally, this feature was compared to and combined with signals from vehicle-based sensors.

Methods: The National Advanced Driving Simulator was used to expose drivers to long, monotonous drives. Twenty participants drove for about 4?h in the simulator between 10 p.m. and 2 a.m. They were allowed to use cruise control and traffic was sparse and semirandom, with both slower- and faster-moving vehicles. Observational ratings of drowsiness (ORDs) were used as the ground truth for drowsiness, and several dependent measures were calculated from vehicle and DMS signals. Drowsiness classification models were created that used only vehicle signals, only driver monitoring signals, and a combination of the 2 sources.

Results: The model that used DMS signals performed better than the one that used only vehicle signals; however, the combination of the two performed the best. The models were effective at discriminating low levels of drowsiness from moderate to severe drowsiness; however, they were not effective at telling the difference between moderate and severe levels. A binary model that lumped drowsiness into 2 classes had an area under the receiver operating characteristic (ROC) curve of 0.897.

Conclusions: Blinks and saccades have been shown to be predictive of microsleeps; however, it may be that detection of microsleeps and lane departures occurs too late. Therefore, it is encouraging that the model was able to distinguish mild from moderate drowsy driving. The use of automation may make vehicle-based signals useless for characterizing driver states, providing further motivation for a DMS. Future improvements in impairment detection systems may be expected through a combination of improved hardware, physiological measures from unobtrusive sensors and wearables, and the intelligent integration of environmental variables like time of day and time on task.     

Medical investigation after a motorcoach strikes the rear of a tractor semitrailer parked on the highway; 13 fatal

Abstract

Objective: The objective of this study was to examine the medical conditions of 2 commercial drivers and the effects of physical barriers to occupant egress in a crash involving a tractor trailer and a motorcoach in order to assess and identify the factors that caused the crash and had a significant effect on occupant extrication.

Methods: Physical evidence from the scene, video evidence, commercial driver information, phone records, toxicology findings, autopsy results, and personal medical information were reviewed.

Results: On October 23, 2016, at 5:16 a.m., a motorcoach carrying a driver and 42 passengers struck the rear of a stopped semitrailer occupied by its driver in the center-right lane of Interstate 10 at highway speed outside Palm Springs, California. The motorcoach driver and 12 passengers died; 11 passengers were seriously injured.

All traffic had been stopped on I-10 early that morning to allow electrical lines to be strung over the highway. Security camera footage showed that the truck arrived at the end of a traffic queue 2?min before traffic flow resumed. Physical evidence indicated that the truck’s parking brake was still engaged at the time of the collision about 2?min later. The truck driver had a body mass index (BMI) between 45.6 and 50?kg/m², which placed him at very high risk of moderate to severe obstructive sleep apnea; he also inaccurately recalled that he had been stopped for 20–25?min and had placed the vehicle in gear just before the collision.

The motorcoach driver was on the return leg of an overnight trip to a casino. Based on his phone records, known driving time, and security camera footage, at the time of the collision he had had 4?h of sleep opportunity in the preceding 35?h. There was no evidence that the motorcoach driver attempted any evasive action before the collision. In addition, postmortem testing revealed a hemoglobin A1C of 11.4%, indicating poorly controlled diabetes; this was apparently undiagnosed prior to the crash.

The motorcoach was equipped with a single loading door at the front of the vehicle; it was rendered inoperable by the collision. Emergency egress was initially carried out through the emergency exit windows, but they repeatedly swung shut, impeding passengers’ efforts to exit. Emergency responders eventually cut open the bus wall to create a larger means of egress. Overall, it took almost 3?h to extricate the occupants from the vehicle.

Conclusions: The National Transportation Safety Board (NTSB) determined that the probable cause of the accident was the truck driver’s falling asleep, most likely due to undiagnosed moderate-to-severe obstructive sleep apnea, and the motorcoach driver’s failure to identify the stopped truck as a hazard requiring evasive action, most likely as the result of fatigue. Additional easy-to-use emergency exits would have decreased the time to extricate the occupants.     

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.     

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.     

Exploratory multinomial logit model–based driver injury severity analyses for teenage and adult drivers in intersection-related crashes

Objective: Teenage drivers are more likely to be involved in severely incapacitating and fatal crashes compared to adult drivers. Moreover, because two thirds of urban vehicle miles traveled are on signal-controlled roadways, significant research efforts are needed to investigate intersection-related teenage driver injury severities and their contributing factors in terms of driver behavior, vehicle–infrastructure interactions, environmental characteristics, roadway geometric features, and traffic compositions. Therefore, this study aims to explore the characteristic differences between teenage and adult drivers in intersection-related crashes, identify the significant contributing attributes, and analyze their impacts on driver injury severities.

Methods: Using crash data collected in New Mexico from 2010 to 2011, 2 multinomial logit regression models were developed to analyze injury severities for teenage and adult drivers, respectively. Elasticity analyses and transferability tests were conducted to better understand the quantitative impacts of these factors and the teenage driver injury severity model's generality.

Results: The results showed that although many of the same contributing factors were found to be significant in the both teenage and adult driver models, certain different attributes must be distinguished to specifically develop effective safety solutions for the 2 driver groups.

Conclusions: The research findings are helpful to better understand teenage crash uniqueness and develop cost-effective solutions to reduce intersection-related teenage injury severities and facilitate driver injury mitigation research.     

Crash and injury prevention estimates for intersection driver assistance systems in left turn across path/opposite direction crashes in the United States

Abstract

Objective: The objective of this research study was to estimate the number of left turn across path/opposite direction (LTAP/OD) crashes and injuries that could be prevented in the United States if vehicles were equipped with an intersection advanced driver assistance system (I-ADAS).

Methods: This study reconstructed 501 vehicle-to-vehicle LTAP/OD crashes in the United States that were investigated in the NHTSA National Motor Vehicle Crash Causation Survey (NMVCCS). The performance of 30 different I-ADAS system variations was evaluated for each crash. These variations were the combinations of 5 time-to-collision (TTC) activation thresholds, 3 latency times, and 2 different response types (automated braking and driver warning). In addition, 2 sightline assumptions were modeled for each crash: One where the turning vehicle was visible long before the intersection and one where the turning vehicle was only visible within the intersection. For resimulated crashes that were not avoided by I-ADAS, a new crash delta-V was computed for each vehicle. The probability of Abbreviated Injury Scale 2 or higher injury in any body region (Maximum Abbreviated Injury Scale [MAIS] 2+F) to each front-row occupant was computed.

Results: Depending on the system design, sightline assumption, I-ADAS variation, and fleet penetration, an I-ADAS system that automatically applies emergency braking could avoid 18–84% of all LTAP/OD crashes. Only 0–32% of all LTAP/OD crashes could have been avoided using an I-ADAS system that only warns the driver. An I-ADAS system that applies emergency braking could prevent 47–93% of front-row occupants from receiving MAIS 2?+?F injuries. A system that warns the driver in LTAP/OD crashes was able to prevent 0–37% of front-row occupants from receiving MAIS 2?+?F injuries. The effectiveness of I-ADAS in reducing crashes and number of injured persons was higher when both vehicles were equipped with I-ADAS.

Conclusions: This study presents the simulated effectiveness of a hypothetical intersection active safety system on real crashes that occurred in the United States. This work shows that there is a strong potential to reduce crashes and injuries in the United States.     

Prevalence of alcohol impairment and odds of a driver injury or fatality in on-road farm equipment crashes

Objective: The objective of this article was to estimate the prevalence of alcohol impairment in crashes involving farm equipment on public roadways and the effect of alcohol impairment on the odds of crash injury or fatality.

Methods: On-road farm equipment crashes were collected from 4 Great Plains state departments of transportation during 2005–2010. Alcohol impairment was defined as an involved driver having blood alcohol content of ≥0.08 g/100 ml or a finding of alcohol impairment as a driver contributing circumstance recorded on the police crash report. Injury or fatality was categorized as (a) no injury (no and possible injury combined), (b) injury (nonincapacitating or incapacitating injury), and (c) fatality. Hierarchical multivariable logistic regression modeling, clustered on crash, was used to estimate the odds of an injury/fatality in crashes involving an alcohol-impaired driver.

Results: During the 5 years under study, 3.1% (61 of 1971) of on-road farm equipment crashes involved an alcohol-impaired driver. One in 20 (5.6%) injury crashes and 1 in 6 (17.8%) fatality crashes involved an alcohol-impaired driver. The non-farm equipment driver was significantly more likely to be alcohol impaired than the farm equipment driver (2.4% versus 1.1% respectively, P = .0012). After controlling for covariates, crashes involving an alcohol-impaired driver had 4.10 (95% confidence interval [CI], 2.30–7.28) times the odds of an injury or fatality. In addition, the non-farm vehicle driver was at 2.28 (95% CI, 1.92–2.71) times higher odds of an injury or fatality than the farm vehicle driver. No differences in rurality of the crash site were found in the multivariable model.

Conclusion: On-road farm equipment crashes involving alcohol result in greater odds of an injury or fatality. The risk of injury or fatality is higher among the non-farm equipment vehicle drivers who are also more likely to be alcohol impaired. Further studies are needed to measure the impact of alcohol impairment in on-road farm equipment crashes.     

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.     

Improving the Chest Protection of Elderly Occupants in Frontal Crashes Using SMART Load Limiters

Objective: To determine whether varying the seat belt load limiter (SBL) according to crash and occupant characteristics could have real-world injury reduction benefits in frontal impacts and, if so, to quantify those benefits.

Methods: Real-world UK accident data were used to identify the target population of vehicle occupants and frontal crash scenarios where improved chest protection could be most beneficial. Generic baseline driver and front passenger numerical models using a 50th percentile dummy were developed with MADYMO software. Simulations were performed where the load limiter threshold was varied in selected frontal impact scenarios. For each SBL setting, restraint performance, dummy kinematics, and injury outcome were studied in 5 different frontal impact types. Thoracic injury predictions were converted into injury probability values using Abbreviated Injury Scale (AIS) 2+ age-dependent thoracic risk curves developed and validated based on a methodology proposed by Laituri et al. (2005). Real-world benefit was quantified using the predicted AIS 2+ risk and assuming that an appropriate adaptive system was fitted to all the cars in a real-world sample of recent frontal crashes involving European passenger cars.

Results: From the accident data sample the chest was the most frequently injured body region at an AIS 2+ level in frontal impacts (7% of front seat occupants). The proportion of older vehicle front seat occupants (>64 years) with AIS 2+ injury was also greater than the proportion of younger occupants. Additionally, older occupants were more likely to sustain seat belt–induced serious chest injury in low- and moderate-speed frontal crashes. In both front seating positions, the low SBL provided the best chest injury protection, without increasing the risk to other body regions. In severe impacts, the low SBL allowed the driver to move dangerously close to the steering wheel. Compared to the driver side, greater ride-down space on the passenger side gave a higher potential for using the low SBLs. When applying the AIS 2+ risk reduction findings to the weighted accident data sample, the risk of sustaining an AIS 2+ seat belt injury changed to 0.9, 4.9, and 8.1% for young, mid, and older occupants, respectively, from their actual injury risk of 1.3, 7.6, and 13.1%.

Conclusions: These results suggest the potential for improving the safety of older occupants with the development of smarter restraint systems. This is an important finding because the number of older users is expected to increase rapidly over the next 20 years. The greatest benefits were seen at lower crash severities. This is also important because most real-world crashes occur at lower speeds.