Determination of functional scenarios for intersection collisions.

INTRODUCTION: The National Highway Traffic Safety Administration (NHTSA) estimated that in 2019, intersection crashes accounted for $179 billion of economic damages and $639 billion in societal damages. Intersection advanced driver assist systems (I-ADASs) and automated driving systems (ADS) are designed and have been actively deployed to avoid or mitigate these intersection crash scenarios. Given the indeterminate parameter space for describing collision scenarios, evaluators, and designers are all challenged with condensing the possible intersection crash configurations into digestible, executable conditions for scenario-based simulation testing. The objective of this study is to identify functional intersection crash configurations for I-ADAS and ADS safety evaluation. METHODS: Real-world intersection crash characteristics are important considerations for scenario testing as these features can directly correlate to or influence causality, controllability, and potential injury severity. To identify functional intersection crash types, similar crash scenarios were grouped together by identified critical features using an unsupervised decision tree model. A key advantage of this approach was that the implemented cluster crash scenarios would be understandable and interpretable by users. Unsupervised decision trees work by generating uniformly distributed synthetic data with features from real data and classifying all the data as real or synthetic. Long, non-diverging branches were manually pruned to reduce overfitting and improve model performance. Feature importance values were computed based on how effective a given variable grouped the crashes together. DATA SOURCES: This analysis selected intersection cases that only involved two vehicles from the Crash Investigation Sampling System (CISS) spanning 2017 to 2020. Crash features such as road geometry, intersection signal, and vehicle configuration were important to consider for scenario generation. CISS contained the traffic device, device functionality, vehicle intended pre-event movement, road alignment, road profile, trafficway flow, number of lanes, and crash type for each crash case. Intersection geometry, intersecting road angle, each vehicles' legal moves, and the presence of a two-way-left-turn-lane (TWLTL), channelized roads, bike lanes, crosswalks, street parking, slip lanes, and visual obstructions were manually recorded from the scene diagram. RESULTS: The tree identified 44 functional intersection crash configurations after pruning. These clusters have five main sections: Straight-crossing path (SCP) crashes at 4-legged intersections, Left-Turn-Across-Path/Opposite Direction (LTAP/OD) crashes at 4-legged intersections, other crash types at 4-legged intersections, roundabout and multileg intersections, and 3-legged intersection crashes. The features that best split the data were TWLTL, lane travel direction violation, and traffic control device functionality. The largest cluster was SCP crashes at 4-legged, undivided intersections where the traffic control device was working and both vehicles did not violate the direction of their lane of travel. This cluster was adjacent to 32 vehicles in similar SCP crashes except a vehicle performed an unexpected maneuver based on their lane position. CONCLUSION: These 44 identified crash configurations could be useful in bolstering the robustness of I-ADAS and ADS intersection scenario testing as they are a compact representation of all the police reported intersection crashes where a vehicle was towed. Future studies could generate logical scenarios with distributions of initial conditions and behaviors from these clusters that could be used to evaluate an I-ADAS or ADS.

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 methodology for assessing driver perception-response time during unanticipated cross-centerline events.

OBJECTIVE: The purpose of this study was to present a methodology that utilizes naturalistic driving data to measure the driver response to an unanticipated driving scenario, a cross-centerline event. METHODS: Forward-facing video from naturalistic driving was used to determine when the cross-centerline event occurred. Then, the recorded acceleration and yaw rate data were used to identify the start of braking and steering evasive actions, respectively. A deceleration threshold of -0.1 g was defined as the braking onset, and a yaw rate of 2 deg/s was defined as the steering onset. Perception-response times (PRTs) were derived using these inputs. RESULTS: 17 cross-centerline events were identified from the naturalistic driving database. The drivers in all analyzed events applied the brakes, and 11 of the 17 drivers performed a steering maneuver. However, the average steering PRT (0.39 s) was faster than the average braking PRT (0.84 s). CONCLUSIONS: Based naturalistic data from cross-centerline encroachment scenarios, the average driver steering PRT was faster than the average driver braking PRT. Both the driver's median braking and steering PRT was faster in these real-world scenarios than in similar test track or simulator studies. Future analyses should investigate which action is attempted first and the effect of time to contact on driver response.

Expansion of NASS/CDS for characterizing run-off-road crashes.

OBJECTIVE: Run-off-road (ROR) crashes account for one-third of all annual crash fatalities in the US. The National Automotive Sampling System Crashworthiness Data System (NASS/CDS) is a dataset which may be used to understand the nature of ROR crashes. Despite the wealth of coded data available in NASS/CDS, this dataset lacks coded information about the roadside environment and the off-road trajectory of the vehicle. This information would be useful for determining lane departure warning (LDW) benefits, residual safety problems, performance of current safety hardware, lane marking inventory, LDW test procedure development, radius of curvature characterization, and effectiveness of ESC. The purpose of this paper is to demonstrate a methodology for expanding the data available in NASS/CDS to form and validate a specialized road departure database. METHODS: Observed, measured, and reconstructed data elements were extracted from NASS/CDS and compiled into the National Cooperative Highway Research Program (NCHRP) 17-43 database. Observed variables were primarily coded from the scene photographs and included information such as the lane markings, and geometry of the roadside cross-section. Additional variables were measured from the scaled scene diagrams including the path of the vehicle, road dimensions, and roadside object positions. The vehicle impact speed and departure speed were reconstructed using the WinSMASH delta-v, roadside object characteristics, and vehicle path. Two studies were conducted to demonstrate the usefulness of the NCHRP 17-43 database in evaluating both vehicle-based and infrastructure-based ROR countermeasures. RESULTS: The resulting NCHRP 17-43 database includes 1,581 NASS/CDS cases representing 510,154 ROR crashes. Analysis of the database found that drivers which crashed following an overcorrection were younger than drivers which did not overcorrect. This may indicate that inexperienced drivers are more likely to overcorrect when departing the roadway. The 85th percentile impact severity of ROR crashes, which occur on roads with a speed limit greater than 65 mph, is higher than the practical worst-case test conditions for roadside barriers. CONCLUSIONS: The NCHRP 17-43 database contains information extracted from NASS/CDS cases to better understand the nature of ROR crashes, driver behavior in these crashes, and the potential benefits of both vehicle-based and infrastructure-based ROR countermeasures.

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.

Comparison of Artificial Saliva vs Saline Solution on Rate of Suture Degradation in Oropharyngeal Surgery.

Importance: Absorbable sutures are designed to degrade and lose strength over time. Manufacturers warn that exposure to various body fluids can change the estimated degradation rate of these sutures, but few studies have been conducted to quantify the degree of change associated with saliva. Objective: To quantify the association of increased loss of strength of sutures over time after exposure to artificial saliva (hereinafter referred to as "saliva"). Design, Setting, and Participants: This experimental in vitro study was conducted at Bucknell University (Lewisburg, Pennsylvania) from June 19, 2015, to July 4, 2015. No participants were involved. The loss of strength over time of sutures submerged in physiological saline and artificial saliva solutions was compared. Three types of absorbable sutures commonly used in oral surgery were tested: chromic, poliglecaprone 25, and polyglactin 910. Data analysis was conducted from July 15, 2016, to August 16, 2016. Main Outcomes and Measures: The primary outcome measure was 50% strength reduction. To measure breaking strength, 6 knotted sutures of each type were pulled to failure at regular time intervals after immersion in either saline or synthetic saliva at 37°C. Regression analysis was used to interpret strength degradation profiles and to estimate the time to reach 50% of the original breaking strength. Results: Of the 3 suture types submerged in the 2 solutions, all 3 degraded to 50% strength faster (by 2 to 13 days) in saliva than in saline. The differences in the degradation profiles varied by suture type. Poliglecaprone 25 sutures demonstrated a sudden decrease in failure strength between day 5 and day 8 in both solutions, but the decrease was greater in saliva (-10.2 N; 95% CI, -15.5 to -4.9 N) than in saline (-6.1 N; 95% CI, -11.2 to -0.9 N). The polyglactin 910 and chromic sutures share a similar degradation profile when implanted in tissue, but saliva was associated with more degradation of chromic sutures. Differences in degradation rate were seen in polyglactin 910 sutures after day 6 (saline: -0.9 N/d; 95% CI, -1.0 to -0.7 vs saliva: -1.2 N/d; 95% CI, -1.4 to -1.1). After day 2, chromic sutures had a degradation rate of -0.3 N/d (95% CI, -0.5 to -0.2) in saline and -0.5 N/d (95% CI, -0.6 to -0.3) in saliva. Conclusions and Relevance: Knowing the association of saliva with suture degradation rates of various suture types may enable oropharyngeal surgeons to select sutures that retain their strength and degrade at an appropriate rate to allow for the effective healing of the wound.