The effects of airbags and seatbelts on occupant injury in longitudinal barrier crashes

Introduction

Longitudinal barriers, such as guardrails, are designed to prevent a vehicle that leaves the roadway from impacting a more dangerous object while minimizing the risk of injury to the vehicle occupants. Current full-scale test procedures for these devices do not consider the effect of occupant restraints such as seatbelts and airbags. The purpose of this study was to determine the extent to which restraints are used or deployed in longitudinal barrier collisions and their subsequent effect on occupant injury.

Methods

Binary logistic regression models were generated to predict occupant injury risk using data from the National Automotive Sampling System / Crashworthiness Data System from 1997 through 2007.

Results

In tow-away longitudinal barrier crashes, airbag deployment rates were 70% for airbag-equipped vehicles. Compared with unbelted occupants without an airbag available, seat belt restrained occupants with an airbag available had a dramatically decreased risk of receiving a serious (MAIS 3+) injury (odds-ratio (OR) = 0.03; 95% CI: 0.004-0.24). A similar decrease was observed among those restrained by seat belts, but without an airbag available (OR = 0.03; 95% CI: 0.001- 0.79). No significant differences in risk of serious injuries were observed between unbelted occupants with an airbag available compared with unbelted occupants without an airbag available (OR = 0.53; 95% CI = 0.10-2.68).

Impact on Industry

This study refutes the perception in the roadside safety community that airbags rarely deploy in frontal barrier crashes, and suggests that current longitudinal barrier occupant risk criteria may over-estimate injury potential for restrained occupants involved in a longitudinal barrier crash.     

铁钙复合絮凝剂HC211用于钻井废水处理性能研究

探讨了在不同PH值、温度、剂量及酸化预处理条件下，铁钙复合絮凝剂HC211絮凝特性和絮凝效果的好坏。研究表明铁钙复合絮凝剂HC211在PH值为8－10，温度为15℃，剂量在4‰左右有好的絮凝效果。尤其在酸化预处理后，铁钙复合絮凝剂HC211絮凝效果更佳。     

Community‐based water supplies in Cikarang,Indonesia: are they sustainable?

Community‐based water supply (CBWS) is an example of how a community manages common pool resources (CPR). This results in an alternative approach to solve water supply problems in developing countries by enhancing community participation in managing water supply. This research evaluates the sustainability of five CBWS projects in Cikarang, Indonesia by using Ostrom's design principles, with additional sustainability factors found in the Sustainable Development Goal (SDG) on drinking water and groundwater sustainability. Quinn et al. (2007) criteria were used in the analysis, and the results show that the management of four CBWS institutions were absent and one CBWS institution was weak. With regards to the SDG's drinking water target, the CBWS institutions were unable to comply with safe water standards, and in terms of groundwater sustainability, efforts to monitor and sustain groundwater tables were absent. Results from this research suggest that more focus must be placed on water quality and groundwater sustainability for CBWS projects.     

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.     

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.     

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.     

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.     

Evaluation of Vehicle-Based Crash Severity Metrics

Objective: Vehicle change in velocity (delta-v) is a widely used crash severity metric used to estimate occupant injury risk. Despite its widespread use, delta-v has several limitations. Of most concern, delta-v is a vehicle-based metric which does not consider the crash pulse or the performance of occupant restraints, e.g. seatbelts and airbags. Such criticisms have prompted the search for alternative impact severity metrics based upon vehicle kinematics. The purpose of this study was to assess the ability of the occupant impact velocity (OIV), acceleration severity index (ASI), vehicle pulse index (VPI), and maximum delta-v (delta-v) to predict serious injury in real world crashes.

Methods: The study was based on the analysis of event data recorders (EDRs) downloaded from the National Automotive Sampling System / Crashworthiness Data System (NASS-CDS) 2000–2013 cases. All vehicles in the sample were GM passenger cars and light trucks involved in a frontal collision. Rollover crashes were excluded. Vehicles were restricted to single-event crashes that caused an airbag deployment. All EDR data were checked for a successful, completed recording of the event and that the crash pulse was complete. The maximum abbreviated injury scale (MAIS) was used to describe occupant injury outcome. Drivers were categorized into either non-seriously injured group (MAIS2?) or seriously injured group (MAIS3+), based on the severity of any injuries to the thorax, abdomen, and spine. ASI and OIV were calculated according to the Manual for Assessing Safety Hardware. VPI was calculated according to ISO/TR 12353-3, with vehicle-specific parameters determined from U.S. New Car Assessment Program crash tests. Using binary logistic regression, the cumulative probability of injury risk was determined for each metric and assessed for statistical significance, goodness-of-fit, and prediction accuracy.

Results: The dataset included 102,744 vehicles. A Wald chi-square test showed each vehicle-based crash severity metric estimate to be a significant predictor in the model (p < 0.05). For the belted drivers, both OIV and VPI were significantly better predictors of serious injury than delta-v (p < 0.05). For the unbelted drivers, there was no statistically significant difference between delta-v, OIV, VPI, and ASI.

Conclusions: The broad findings of this study suggest it is feasible to improve injury prediction if we consider adding restraint performance to classic measures, e.g. delta-v. Applications, such as advanced automatic crash notification, should consider the use of different metrics for belted versus unbelted occupants.