How do bicyclists respond to vehicles with adaptive headlamp systems? A nighttime study in an immersive virtual environment.

INTRODUCTION: The risk of motor vehicle-bicyclist crashes and fatalities is greater during nighttime than daytime lighting conditions, even though there are fewer cyclists on roadways at night. Vehicle Adaptive Headlamp Systems (AHS) aim to increase the visibility of bicyclists for drivers by directing a spotlight to illuminate bicyclists on or near the roadway. AHS technology also serves to alert bicyclists to the approaching vehicle by illuminating the road beneath the rider and by projecting a warning icon on the roadway. METHOD: Here, we examined how bicyclists respond to different AHS designs using a large screen, immersive virtual environment. Participants bicycled along a virtual road during nighttime lighting conditions and were overtaken by vehicles with and without an AHS system. The experiment included five treatment conditions with five different AHS designs. In each design a box of white light was projected beneath the rider; in four of the designs an icon was also projected on the road that varied in color (white or red) and position (to the left of the rider at midline or to the left of the front wheel). Participants in the control condition experienced only non-AHS vehicles. RESULTS: We found that riders in all AHS treatment conditions moved significantly farther away from overtaking vehicles with AHS systems, whereas riders in the control condition did not significantly move away from overtaking vehicles without AHS systems. PRACTICAL APPLICATIONS: The experiment demonstrates that AHS has potential to increase bicycling safety by influencing riders to steer away from overtaking vehicles.

Evaluation of intersection crashes using naturalistic driving data through the lens of future I-ADAS.

OBJECTIVE: Intersection advanced driver assistance systems (I-ADAS) with the capability to detect possible collisions and perform evasive braking have the potential to reduce the number of intersection crashes. However, these systems will encounter many challenges caused by the complexity of real-world driving conditions. The purpose of this study is to use real-world naturalistic driving data to conduct an initial exploration of the potential challenges for future I-ADAS in straight crossing path (SCP), left turn across path/lateral direction (LTAP/LD), and left turn across path/opposite direction (LTAP/OD) crash configurations. METHODS: Intersection crashes were selected from the Second Strategic Highway Research Program (SHRP 2) Naturalistic Driving Study. The SHRP 2 dataset includes front-facing, driver-facing, rear-facing, and a hands/feet-facing video and vehicle speed, steering, accelerator, and brake time-series data. This data was reviewed to understand driver sightline obstructions, driver distractions, and initiation of driver responses. The estimated time to collision (TTC) from the precipitating event, defined as when either vehicle entered the intersection without the right-of-way, was computed based on the distance to the impact point divided by the current velocity of the subject vehicle. RESULTS: The median impact speed was 18.0 km/h for SCP and LTAP/LD crashes and 16.1 km/h for LTAP/OD crashes. The median TTC from the precipitating event was 1.35 s for SCP and LTAP/LD crashes and 1.44 s for LTAP/OD crashes. For SCP crashes, the three main sightline obstruction scenarios were slower vehicles traveling in the same direction waiting to turn right, vehicles in the closer crossing lane, and a parked truck. For LTAP/OD crashes, the sightline obstruction was often oncoming vehicles in a closer lane blocking the view of another vehicle. CONCLUSION: Sightline obstructions could present a challenge for future I-ADAS to activate in SCP, LTAP/LD, and LTAP/OD crashes. This study utilized naturalistic driving data to complete a comprehensive analysis of intersection crashes, including driver distractions, evasive maneuvers, and sightline obstructions that can assist in the development of I-ADAS. This analysis is not possible with police-reported crash data only, which does not contain necessary details on the driver and surrounding environment.

A comparison of daytime and nighttime pedestrian road-crossing behavior using an immersive virtual environment.

OBJECTIVE: Reduced visibility for both drivers and pedestrians is a key factor underlying the higher risk of vehicle-pedestrian collisions in dark conditions. This study investigated the extent to which pedestrians adjust for the higher risk of road crossing at night by comparing daytime and nighttime pedestrian road crossing using an immersive virtual environment. METHOD: Participants physically crossed a single lane of continuous traffic in an immersive pedestrian simulator. Participants were randomly assigned to either the daytime or the nighttime lighting condition. The primary measures were the size of the gap selected for crossing and the timing of crossing motions relative to the gap. RESULTS: The results showed that there were no significant differences in gap selection or movement timing in daytime vs. nighttime lighting conditions. However, there was a marginal increase in the time to spare after crossing the road when crossing in the dark, likely due to an accumulation of small differences in gap choices and movement timing. CONCLUSION: This study suggests that pedestrians do not adjust their road crossing to account for greater risk at night. As such, this study adds to our understanding of the potential risk factors for pedestrian injuries and fatalities in nighttime conditions.

Differential benefit of sensor system field-of-view and range in pedestrian automated emergency braking systems.

OBJECTIVE: Current Pedestrian Automatic Emergency Braking (P-AEB) systems often use a combination of radar and cameras to detect pedestrians and automatically apply braking to prevent or mitigate an impending collision. However, these current sensor systems might have a restricted field-of-view (FOV) which may not detect all pedestrians. Advanced sensors like LiDAR can have a wider FOV that may substantially help improve detection. The objective of this study was to determine the influence of FOV and range on the effectiveness of P-AEB systems to determine the potential benefit of advanced sensors. METHODS: This study utilized vehicle-pedestrian crashes from the Pedestrian Crash Data Study (PCDS) to calculate pre-crash pedestrian and vehicle trajectories. A computational model was then applied to simulate the crash with a hypothetical P-AEB system. The model was designed to be able to vary the system's field-of-view (FOV), range, time-to-collision of activation, and system latency. In this study we estimated how the FOV and range of advanced sensors could affect P-AEB system effectiveness at avoiding crashes and reducing impact speed. Sensor range was varied from 25 - 100 m and sensor FOV was varied from ±10° to ±90°. RESULTS: Sensors simulated with a range of 50 m or greater performed only approximately 1% better than with a 25 m range. Field-of-view had a larger effect on estimated system avoidance capabilities with a ± 10° FOV sensor estimated to avoid 46-47% of collisions compared to 91-92% for a ± 90° FOV sensor. The system was able to avoid a greater percentage of cases in which the vehicle was traveling straight at sensor FOVs of ±30° and below. Among the unavoided crashes with a sensor FOV of ±90°, the average impact velocity using a 100 m range sensor was 7.4 m/s which was 3.1 m/s lower than a 25 m range sensor. CONCLUSIONS: Sensor ranges above 25 m were not found to significantly affect estimated crash avoidance potential, but had a small effect on impact mitigation. Sensor FOV had a larger effect on crash avoidance up to a FOV of ±60° with little additional benefit at larger FOVs.

How do pedestrians respond to adaptive headlamp systems in vehicles? A road-crossing study in an immersive virtual environment.

Three-fourths of pedestrian fatalities in the U.S. occur in the dark (National Center for Statistics and Analysis, 2020). Adaptive Headlight Systems (AHS) offer the potential to address this problem by improving the visibility of pedestrians for drivers and alerting pedestrians to approaching vehicles. The goal of this study was to investigate how pedestrians respond to different types of AHS. We conducted a mixed factor experiment with 106 college-age adults using a large-screen pedestrian simulator. The task for participants was to cross a stream of continuous traffic without colliding with a vehicle. There were four AHS treatment conditions that differed in the color (white or red) and timing of an icon projected on the roadway in front the participant as an AHS vehicle approached. Participants in the treatment conditions encountered a mix of AHS and non-AHS vehicles. There was also a control condition in which participants encountered only non-AHS vehicles. We found that the color and the timing of the icon projected on the roadway influenced the size of the gaps crossed. Participants in the red icon with early onset condition chose the largest gaps for crossing. An unexpected outcome was that participants in the AHS treatment conditions chose larger gaps even when crossing in front of non-AHS vehicles, suggesting that experiences with AHS vehicles generalized to non-AHS vehicles. We conclude that AHS can have a significant, positive impact on pedestrian road-crossing safety.

Video from user-generated content as a source of pre-crash scenario naturalistic driving data.

OBJECTIVE: The objective of this study was to investigate the use of public video from internet user-generated content as a means of collecting naturalistic driving data. METHODS: A convenience sample of 38 videos comprised of 203 events was extracted from publicly available channels on the YouTube™ platform. Each event was manually reviewed and pseudo-coded according to a subset of current CRSS variables. Pre-crash scenarios were coded using categories developed for prior NHTSA analysis. RESULTS: Crashes represented 67% of the reviewed cases. Collisions with motor vehicles accounted for 84% of all crashes in the sample. Pre-crash scenarios were able to be determined for all crashes and near-crashes. The most prevalent pre-crash scenario types in the video data were Crossing Paths (41%), Rear End (21%), and Lane Change (17%). The top pre-crash scenarios from Swanson et al., were Rear End (31%), Crossing Paths (21%), and Lane Change (12%). The most prevalent pre-near crash scenario types in the video data were Crossing Paths (32%), Lane Change (30%), and Pedestrian (12%). CONCLUSIONS: The most prevalent pre-crash scenarios in the video data were similar to those in data from FARS and NASS-GES. Though not nationally representative, this preliminary study demonstrated that user-generated content may be useful as a source of inexpensive naturalistic data and provides sufficient detail to capture important pre-crash, near-crash and crash information.

Considering real-world sightline obstructions in crash and injury prevention estimates for left turn across path/opposite direction intersection active safety systems.

OBJECTIVE: Previous analyses of active safety systems in left turn across path/opposite direction (LTAP/OD) crashes have shown that sensor sightline obstructions might affect the performance of these systems. National retrospective crash databases provide little information about the proportion of cases which have sightline obstructions. One promising alternative are naturalistic driving studies (NDS). The objective of this study was to estimate the proportion of LTAP/OD crashes and near-crashes which have sightline obstructions using a large-scale NDS and update previous estimates of intersection active safety system effectiveness using this information. METHODS: LTAP/OD crash and near-crash cases were identified from the Second Strategic Highway Research Program (SHRP 2) dataset. Each case was reviewed for the presence of obstructing vehicles when the left turning vehicle began turning. This study considered 241 crash and near-crash LTAP/OD events selected from SHRP 2. SHRP 2 was an NDS which collected 80 million kilometers of driving from approximately 2,500 participants over a 2.5 year period. The sightline obstruction ratio was defined as the proportion of cases which had sightline obstructions when the turning vehicle began turning. A logistic regression model was used to determine the statistical significance of factors which affected the sightline obstruction ratio, which included event severity, traffic control device, subject vehicle crash configuration, and turning lane presence. LTAP/OD active safety system effectiveness was quantified in a prior study for cases with and without sightline obstructions separately. System effectiveness was re-computed by weighting the results according to the worst-case sightline ratio computed in this study. RESULTS: Traffic control device, subject vehicle crash type (turning or traveling through), and turning lane presence were not found to affect sightline obstruction ratio. In crash cases, the sightline obstruction ratio was 40%. In near-crash cases, the sightline obstruction ratio was 18%. Finally, the effectiveness of an intersection active safety system was evaluated using this sightline obstruction ratio. CONCLUSIONS: This study quantified the sightline obstruction ratio, an important parameter needed to evaluate intersection active safety systems. This study also establishes a baseline for evaluating the presence of sightline obstructions in a future naturalistic driving study when road infrastructure has changed.

Age Differences in Occupant Motion during Simulated In-Vehicle Swerving Maneuvers.

BACKGROUND: With active safety and automated vehicle features becoming more available, unanticipated pre-crash vehicle maneuvers, such as evasive swerving, may become more common, and they may influence the resulting effectiveness of occupant restraints, and consequently may affect injury risks associated with crashes. Therefore, the objective of this study was to quantify the influence of age on key occupant kinematic, kinetic, and muscular responses during evasive swerving in on-road testing. METHODS: Seat belt-restrained children (10-12 years old), teens (13-17 years old), and adults (21-33 years old) experienced two evasive swerving maneuvers in a recent model sedan on a test track. Kinematics, muscle activity, and seat belt load distribution were determined and analyzed. RESULTS: Compared to teens and adults, children showed greater head and trunk motion (p < 0.03), but similar muscle activation in the into-the-belt direction of swerving. In the out-of-the-belt direction, children showed head and trunk motion more similar to teens and adults (p < 0.02), but with greater muscle activation. CONCLUSIONS: Children showed different neuromuscular control of head and trunk motion compared to older occupants. This study highlights differences in the relationship between kinematics and muscle activation across age groups, and provides new validation data for active human body models across the age range.

Characterization of the motion of booster-seated children during simulated in-vehicle precrash maneuvers.

Objective: Precrash occupant motion may affect head and trunk position and restraint performance in a subsequent crash, particularly for young children. Others have studied seat belt-restrained adult drivers and adult and adolescent passengers in precrash maneuvers. For younger children, optimal restraint includes a belt-positioning booster seat, which in precrash maneuvers may contribute in unique ways to the overall body motion. Therefore, the objective of this study was to quantify booster-seated child occupant kinematic, kinetic, and muscle responses during precrash maneuvers and characterize booster movement with respect to the overall occupant kinematics.Methods: Vehicle maneuver tests were conducted with a recent model year sedan at the Transportation Research Center Inc. (TRC, Marysville, Ohio). Three precrash vehicle maneuvers were simulated: Automated and manual emergency braking (AEB and MEB) and oscillatory swerving or slalom (SLA). Each maneuver was repeated twice for each participant. Seven 6- to 8-year-old booster-seated children participated in the study and all subjects were seated in the right rear seat. Vehicle dynamics (i.e., motion, position, and orientation) were measured with an inertial and Global Positioning System navigation system (Oxford RT 3003). Kinematic data from human volunteers were collected with an 8-camera 3D motion capture system (Optitrack Prime 13 200 Hz, NaturalPoint, Inc.). Photoreflective markers were placed on participants' head and trunk. Electromyography (EMG; Trigno EMG Wireless Delsys, Inc., 2,000 Hz) sensors were placed on bilateral muscles predicted to be most likely involved in bracing behaviors.Results: Children demonstrated greater head and trunk velocity in MEB (head 123.7 ± 13.1 cm/s, trunk 77.6 ± 14.1 cm/s) compared to AEB (head 45.31 ± 11.5 cm/s, trunk 27.1 ± 5.5 cm/s; P < .001). Participants also showed greater head motion in MEB (18.9 ± 1.4 cm) vs. AEB (15.1 ± 4.8 cm) but the differences were not statistically significant (P < .1). Overall, the booster seats themselves did not move substantially (<3 cm) in the braking maneuvers. During the SLA, however, the booster seat moved laterally up to 5 cm in several subjects, contributing substantially to peak trunk (6.5-14.0 cm) and head (9.9-21.4 cm) excursion during the maneuver. Booster-seated children also exhibited a greater activation of biceps and deltoid muscles and abdominal and middle trapezii muscles than the sternocleidomastoids during these maneuvers.Conclusions: The quantification of booster seat motion and neuromuscular control and the relationship between kinematics and muscle activation in booster-seated children in precrash maneuvers provides important data on the transition between the precrash and crash phases for this young age group and may help identify opportunities for interventions that integrate active and passive safety.

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

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.

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

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.

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

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.

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

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.

Passenger head kinematics in abrupt braking and lane change events.

OBJECTIVE: A test track study was conducted to quantify patterns of adult front seat passenger head motion during abrupt vehicle maneuvers. METHOD: Eighty-seven men and women with a wide range of body sizes and ages participated in data collection on a closed test track in a passenger sedan under manual control by a test driver. Because a primary goal of the study was to gather "unaware" data, the participants were instructed that the study was concerned with vehicle dynamics and they were required to read from a questionnaire taped to the top of their thighs as the drive began. The first event was a hard brake (approximately 1 g) to a stop from 35 mph (56 kph). Within the space of approximately 5 min the participants also experienced an aggressive lane change, a sharp right turn with simultaneous hard braking, and a second hard braking event. A Microsoft Kinect v2 sensor was positioned to view the area around the front passenger seat. Head location was tracked using the Kinect data with a novel methodology that fit 3D head scan data to the depth data acquired in the vehicle. RESULT: The mean (standard deviation) forward excursion of the estimated head center of gravity (CG) location in the first braking event was 135 (62) mm. The forward head CG excursion in the second braking event of 115 (51) mm was significantly less than that in the first, but the difference was small relative to the within-condition variance. Head excursion on the second braking trial was less than that on the first trial for 69% of participants. The mean maximum inboard head excursion in lane-change maneuvers was 118 (40) mm. Forward head excursions in braking were significantly smaller for older passengers and those with higher body mass index, but the combined factors accounted for less than 25% of the variance. Inboard head excursion in the lane-change event was significantly related to stature, but only about 7% of variance was related to body size. Head excursions for men and women did not differ significantly after accounting for body size. DISCUSSION: This is the first quantitative occupant dynamics study to use a large, diverse sample of passengers, enabling the exploration of the effects of covariates such as age and body size. CONCLUSIONS: The data demonstrate that a relatively large range of head positions can be expected to result from abrupt vehicle maneuvers. The data do not support simple scaling of excursions based on body size.

Injury mitigation estimates for an intersection driver assistance system in straight crossing path crashes in the United States.

OBJECTIVE: Accounting for one fifth of all crashes and one sixth of all fatal crashes in the United States, intersection crashes are among the most frequent and fatal crash modes. Intersection advanced driver assistance systems (I-ADAS) are emerging vehicle-based active safety systems that aim to help drivers safely navigate intersections. The objective of this study was to estimate the number of crashes and number of vehicles with a seriously injured driver (Maximum Abbreviated Injury Scale [MAIS] 3+) that could be prevented or reduced if, for every straight crossing path (SCP) intersection crash, one of the vehicles had been equipped with an I-ADAS. METHODS: This study retrospectively simulated 448 U.S. SCP crashes as if one of the vehicles had been equipped with I-ADAS. Crashes were reconstructed to determine the path and speeds traveled by the vehicles. Cases were then simulated with I-ADAS. A total of 30 variations of I-ADAS were considered in this study. These variations consisted of 5 separate activation timing thresholds, 3 separate computational latency times, and 2 different I-ADAS response modalities (i.e., a warning or autonomous braking). The likelihood of a serious driver injury was computed for every vehicle in every crash using impact delta-V. The results were then compiled across all crashes in order to estimate system effectiveness. RESULTS: The model predicted that an I-ADAS that delivers an alert to the driver has the potential to prevent 0-23% of SCP crashes and 0-25% of vehicles with a seriously injured driver. Conversely, an I-ADAS that autonomously brakes was found to have the potential to prevent 25-59% of crashes and 38-79% of vehicles with a seriously injured driver. I-ADAS effectiveness is a strong function of design. Increasing computational latency time from 0 to 0.5 s was found to reduce crash and injury prevention estimates by approximately one third. For an I-ADAS that delivers an alert, crash/injury prevention effectiveness was found to be very sensitive to changes in activation timing (warning delivered 1.0 to 3.0 s prior to impact). If autonomous braking was used, system effectiveness was found to largely plateau for activation timings greater than 1.5 s prior to impact. In general, the results of this study suggest that I-ADAS will be 2-3 times more effective if an autonomous braking system is utilized over a warning-based system. CONCLUSIONS: This study highlights the potential effectiveness of I-ADAS in the U.S. vehicle fleet, while also indicating the sensitivity of system effectiveness to design specifications. The results of this study should be considered by designers of I-ADAS and evaluators of this technology considering a future I-ADAS safety test.

Predicting crash-relevant violations at stop sign-controlled intersections for the development of an intersection driver assistance system.

OBJECTIVE: Intersection crashes resulted in over 5,000 fatalities in the United States in 2014. Intersection Advanced Driver Assistance Systems (I-ADAS) are active safety systems that seek to help drivers safely traverse intersections. I-ADAS uses onboard sensors to detect oncoming vehicles and, in the event of an imminent crash, can either alert the driver or take autonomous evasive action. The objective of this study was to develop and evaluate a predictive model for detecting whether a stop sign violation was imminent. METHODS: Passenger vehicle intersection approaches were extracted from a data set of typical driver behavior (100-Car Naturalistic Driving Study) and violations (event data recorders downloaded from real-world crashes) and were assigned weighting factors based on real-world frequency. A k-fold cross-validation procedure was then used to develop and evaluate 3 hypothetical stop sign warning algorithms (i.e., early, intermediate, and delayed) for detecting an impending violation during the intersection approach. Violation detection models were developed using logistic regression models that evaluate likelihood of a violation at various locations along the intersection approach. Two potential indicators of driver intent to stop-that is, required deceleration parameter (RDP) and brake application-were used to develop the predictive models. The earliest violation detection opportunity was then evaluated for each detection algorithm in order to (1) evaluate the violation detection accuracy and (2) compare braking demand versus maximum braking capabilities. RESULTS: A total of 38 violating and 658 nonviolating approaches were used in the analysis. All 3 algorithms were able to detect a violation at some point during the intersection approach. The early detection algorithm, as designed, was able to detect violations earlier than all other algorithms during the intersection approach but gave false alarms for 22.3% of approaches. In contrast, the delayed detection algorithm sacrificed some time for detecting violations but was able to substantially reduce false alarms to only 3.3% of all nonviolating approaches. Given good surface conditions (maximum braking capabilities = 0.8 g) and maximum effort, most drivers (55.3-71.1%) would be able to stop the vehicle regardless of the detection algorithm. However, given poor surface conditions (maximum braking capabilities = 0.4 g), few drivers (10.5-26.3%) would be able to stop the vehicle. Automatic emergency braking (AEB) would allow for early braking prior to driver reaction. If equipped with an AEB system, the results suggest that, even for the poor surface conditions scenario, over one half (55.3-65.8%) of the vehicles could have been stopped. CONCLUSIONS: This study demonstrates the potential of I-ADAS to incorporate a stop sign violation detection algorithm. Repeating the analysis on a larger, more extensive data set will allow for the development of a more comprehensive algorithm to further validate the findings.

Potential occupant injury reduction in the U.S. vehicle fleet for lane departure warning-equipped vehicles in single-vehicle crashes.

OBJECTIVE: Single-vehicle collisions involve only 10 percent of all occupants in crashes in the United States, yet these same crashes account for 31 percent of all fatalities. Along with other vehicle safety advancements, lane departure warning (LDW) systems are being introduced to mitigate the harmful effects of single-vehicle collisions. The objective of this study is to quantify the number of crashes and seriously injured drivers that could have been prevented in the United States in 2012 had all vehicles been equipped with LDW. METHODS: In order to estimate the potential injury reduction benefits of LDW in the vehicle fleet, a comprehensive crash and injury simulation model was developed. The model's basis was 481 single-vehicle collisions extracted from the NASS-CDS for year 2012. Each crash was simulated in 2 conditions: (1) as it occurred and (2) as if the driver had an LDW system. By comparing the simulated vehicle's off-road trajectory before and after LDW, the reduction in the probability of a crash was determined. The probability of a seriously injured occupant (Maximum Abbreviated Injury Score [MAIS] 3+) given a crash was computed using injury risk curves with departure velocity and seat belt use as predictors. Each crash was simulated between 18 and 216 times to account for variable driver reaction, road, and vehicle conditions. Finally, the probability of a crash and seriously injured driver was summed over all simulations to determine the benefit of LDW. RESULTS AND CONCLUSIONS: A majority of roads where departure crashes occurred had 2 lanes and were undivided. As a result, 58 percent of crashes had no shoulder. LDW will not be as effective on roads with no shoulder as on roads with large shoulders. LDW could potentially prevent 28.9 percent of all road departure crashes caused by the driver drifting out of his or her lane, resulting in a 24.3 percent reduction in the number of seriously injured drivers. The results of this study show that LDW, if widely adopted, could significantly mitigate a harmful crash type. Larger shoulder width and the presence of lane markings, determined by manual examination of scene photographs, increased the effectiveness of LDW. This result suggests that highway systems should be modified to maximize LDW effectiveness by expanding shoulders and regularly painting lane lines.

Methodology for using advanced event data recorders to reconstruct vehicle trajectories for use in safety impact methodologies (SIM).

OBJECTIVE: Safety impact methodologies (SIMs) have the goal of estimating safety benefits for proposed active safety systems. Because the precrash movements of vehicles involved in real-world crashes are often unknown, previous SIMs have taken the approach to reconstruct collisions from incomplete information sources, such as scaled scene diagrams and photographic evidence. The objective of this study is to introduce a novel methodology for reconstructing the precrash vehicle trajectories using data from advanced event data recorders (EDRs). METHODS: Some EDRs from model year 2009 and newer Ford vehicles can record steering wheel angle in addition to precrash vehicle speed, accelerator pedal, and throttle input prior to the crash. A model was constructed using these precrash records and a vehicle model developed in the simulation software PreScan. The model was validated using the yaw rate and longitudinal and lateral accelerations also recorded by this type of Ford EDR but not used to develop the models. RESULTS: In general, the model was able to approximate the dynamics recorded on the EDR. The model did not match the observed dynamics when either the vehicle departed the paved surface or when electronic stability control was active. Modifying the surface friction at the estimated point at which the vehicle departed the road produced better simulation results. The developed trajectories were used to simulate 2 road departure crashes, one into a fixed object and one into a vehicle traveling in the opposite direction, as if the departing vehicle were equipped with a lane departure warning (LDW) system. This example application demonstrates the utility of this method and its potential application to a SIM. CONCLUSIONS: This study demonstrated a novel method for crash reconstruction that can be applied to a SIM for active safety systems. Benefits of this method are that the driver inputs do not need to be inferred from other reconstructions because they are recorded directly by the EDR. Currently, there are too few cases with the advanced EDR data to estimate fleet-wide benefits of a system. Because of recent regulation (49 CFR Part 563), EDRs are likely to be downloaded in more real-world crashes, making this method a potentially valuable and low-cost method for developing SIMs in the future.