Intersection AEB implementation strategies for left turn across path crashes.

Objective: Left turn across path with traffic from the opposite direction (LTAP/OD) is the second most frequent car-to-car intersection crash type after straight crossing path (SCP) in Germany and the United States. Intersection automated emergency braking (AEB) for passenger cars can address these crashes. This study investigates 2 implementation strategies of intersection AEB addressing LTAP/OD crashes: (1) only the turning car is equipped with an intersection AEB and (2) turning and straight-heading cars are equipped with an intersection AEB. For each strategy, the influence of a safety zone around the vehicles that should not be entered is evaluated in terms of accident avoidance, injury mitigation, and change in velocity (delta-V) of remaining accidents. Results are given as a function of market penetration. Methods: A total of 372 LTAP/OD crashes from the time series precrash matrix (PCM), a subsample of the German In-Depth Accident Study (GIDAS), were resimulated in the PRediction of Accident Evolution by Diversification of Influence factors in COmputer simulation (PRAEDICO) simulation framework. A Kudlich-Slibar rigid-body impact model and an injury risk curve derived from GIDAS were used to predict remaining moderate to fatal (Maximum Abbreviated Injury Scale [MAIS] 2 + F) injuries among car occupants. Results: With a safety zone of 0.2 m, when the turning vehicle only was equipped with an intersection AEB, 59% of the crashes were avoided at a 100% market penetration. With both vehicles equipped the percentage increased to 77%. MAIS 2 + F injured occupants were reduced by 60 and 76%, respectively. Considering both the turning and the straight-heading vehicles, the delta-V decreased strongly with market penetration in remaining left-side impacts but only slightly in remaining frontal and right-side impacts. Eliminating the safety zone substantially decreases effectiveness in all conditions. Conclusions: Implementation strategy and safety zone definition strongly influence the real-life performance of intersection AEB. AEB should be applied not only for the turning vehicle but also for the straight-going vehicle to benefit from the full potential. Situationally appropriate safety zone definitions, in line with human hazard perception, need more attention and are a key to balance true positive and false positive performance. Remaining delta-V does not decrease broadly; hence, there is no evidence that future LTAP/OD crashes will be generally of lower severity. This highlights the need for continuous development of in-crash protection.

Motorcyclist injury risk as a function of real-life crash speed and other contributing factors.

The Vision Zero approach advocates for a road transport system designed with human injury tolerance and human fallibility as its basis. While biomechanical limits and the relationship between speed and injury outcome has been extensively investigated for car occupants and pedestrians, research analyzing this relationship for motorcyclists remains limited. The aim of this study was to address this issue by developing multivariate injury risk models for motorcyclists that estimate the relationship between speed and injury severity. For that purpose, motorcycle injury crashes from the German In-Depth Accident Study (GIDAS) database for the period 1999-2017 (n = 1037) were extracted. Different models were tested using logistic regression and backwards elimination of non-significant variables. The best fitting model in the current study included relative speed, type of crash opponent, impact location on the motorcycle and impact mechanism of the rider during the crash. A strong and significant relationship between relative speed and injury severity in motorcycle crashes was demonstrated. At 70 km/h, the risk for at least serious injuries in collisions with wide objects, crash barriers and narrow objects was 20%, 51%, and 64%, respectively. Further, it was found that head-on collisions between motorcycles and passenger cars, with both vehicles traveling at 60 km/h (a relative speed at 120 km/h), present 55% risk of at least serious injury to the motorcycle rider. More research is needed to fully understand the boundary conditions needed to design a safe road transport system for motorcyclists. However, this study provides important insights into the relationship between speed and injury severity for riders in various crash situations. The results may be useful in the discussion of appropriate speed limits and in determining the benefits of countermeasures which aim to reduce crash speed.

Market penetration of intersection AEB: Characterizing avoided and residual straight crossing path accidents.

Car occupants account for one third of all junction fatalities in the European Union. Driver warning can reduce intersection accidents by up to 50 percent; adding Autonomous Emergency Braking (AEB) delivers a reduction of up to 70 percent. However, these findings are based on an assumed 100 percent equipment rate, which may take decades to achieve. Our study investigates the relationship between intersection AEB market penetration rates and avoidance of accidents and injuries in order to guide implementation strategies. Additionally, residual accident characteristics (impact configurations and severity) are analyzed to provide a basis for future in-crash protection requirements. We determined which accidents would have been avoided through the use of an Intersection AEB system with different sensor field-of-views (180° and 120°) by means of re-simulating the pre-crash phase of 792 straight crossing path (SCP) car-to-car accidents recorded in the German In-Depth Accident Study (GIDAS) and the associated Pre-Crash Matrix (PCM). Intersection AEB was activated when neither of the conflict opponents could avoid the crash through reasonable braking or steering reactions. For not-avoided accidents, we used the Kudlich-Slibar rigid body impulse model to calculate the change of velocity during the impact as a measure of impact severity and the principal direction of force. Accident avoidance over market penetration is not linear but exponential, with higher gains at low penetration rates and lower gains at higher rates. A wide field-of-view sensor (180°) substantially increased accident avoidance and injury mitigation rates compared to a 120° field-of-view sensor. For a 180° field-of-view sensor at 100 percent market penetration, about 80 percent of the accidents and 90 percent of the MAIS2 + F injuries could be avoided. For the remaining accidents, AEB intervention rarely affected side of impact. The median change of velocity (delta-V) of the remaining crashes reduces only marginally at low penetration rates but this reduction increases with higher penetration rates. With 100 percent market penetration, one quarter of the vehicles still involved in straight crossing path accidents will sustain a delta-V higher than 17 km/h. Intersection AEB is very effective. Enabling a fast initial implementation of systems with wide field-of-view sensor(s) and ensuring a high market penetration over the longer term is essential to achieve high crash avoidance and injury mitigation rates over time. The standards for in-crash protection must be high to mitigate injury in the unavoidable, residual accidents.

Comparing motor-vehicle crash risk of EU and US vehicles.

OBJECTIVE: This study examined the hypotheses that passenger vehicles meeting European Union (EU) safety standards have similar crashworthiness to United States (US) -regulated vehicles in the US driving environment, and vice versa. METHODS: The first step involved identifying appropriate databases of US and EU crashes that include in-depth crash information, such as estimation of crash severity using Delta-V and injury outcome based on medical records. The next step was to harmonize variable definitions and sampling criteria so that the EU data could be combined and compared to the US data using the same or equivalent parameters. Logistic regression models of the risk of a Maximum injury according to the Abbreviated Injury Scale of 3 or greater, or fatality (MAIS3+F) in EU-regulated and US-regulated vehicles were constructed. The injury risk predictions of the EU model and the US model were each applied to both the US and EU standard crash populations. Frontal, near-side, and far-side crashes were analyzed together (termed "front/side crashes") and a separate model was developed for rollover crashes. RESULTS: For the front/side model applied to the US standard population, the mean estimated risk for the US-vehicle model is 0.035 (sd = 0.012), and the mean estimated risk for the EU-vehicle model is 0.023 (sd = 0.016). When applied to the EU front/side population, the US model predicted a 0.065 risk (sd = 0.027), and the EU model predicted a 0.052 risk (sd = 0.025). For the rollover model applied to the US standard population, the US model predicted a risk of 0.071 (sd = 0.024), and the EU model predicted 0.128 risk (sd = 0.057). When applied to the EU rollover standard population, the US model predicted a 0.067 risk (sd = 0.024), and the EU model predicted 0.103 risk (sd = 0.040). CONCLUSIONS: The results based on these methods indicate that EU vehicles most likely have a lower risk of MAIS3+F injury in front/side impacts, while US vehicles most likely have a lower risk of MAIS3+F injury in llroovers. These results should be interpreted with an understanding of the uncertainty of the estimates, the study limitations, and our recommendations for further study detailed in the report.

The potential of clustering methods to define intersection test scenarios: Assessing real-life performance of AEB.

Intersection accidents are frequent and harmful. The accident types 'straight crossing path' (SCP), 'left turn across path - oncoming direction' (LTAP/OD), and 'left-turn across path - lateral direction' (LTAP/LD) represent around 95% of all intersection accidents and one-third of all police-reported car-to-car accidents in Germany. The European New Car Assessment Program (Euro NCAP) have announced that intersection scenarios will be included in their rating from 2020; however, how these scenarios are to be tested has not been defined. This study investigates whether clustering methods can be used to identify a small number of test scenarios sufficiently representative of the accident dataset to evaluate Intersection Automated Emergency Braking (AEB). Data from the German In-Depth Accident Study (GIDAS) and the GIDAS-based Pre-Crash Matrix (PCM) from 1999 to 2016, containing 784 SCP and 453 LTAP/OD accidents, were analyzed with principal component methods to identify variables that account for the relevant total variances of the sample. Three different methods for data clustering were applied to each of the accident types, two similarity-based approaches, namely Hierarchical Clustering (HC) and Partitioning Around Medoids (PAM), and the probability-based Latent Class Clustering (LCC). The optimum number of clusters was derived for HC and PAM with the silhouette method. The PAM algorithm was both initiated with random start medoid selection and medoids from HC. For LCC, the Bayesian Information Criterion (BIC) was used to determine the optimal number of clusters. Test scenarios were defined from optimal cluster medoids weighted by their real-life representation in GIDAS. The set of variables for clustering was further varied to investigate the influence of variable type and character. We quantified how accurately each cluster variation represents real-life AEB performance using pre-crash simulations with PCM data and a generic algorithm for AEB intervention. The usage of different sets of clustering variables resulted in substantially different numbers of clusters. The stability of the resulting clusters increased with prioritization of categorical over continuous variables. For each different set of cluster variables, a strong in-cluster variance of avoided versus non-avoided accidents for the specified Intersection AEB was present. The medoids did not predict the most common Intersection AEB behavior in each cluster. Despite thorough analysis using various cluster methods and variable sets, it was impossible to reduce the diversity of intersection accidents into a set of test scenarios without compromising the ability to predict real-life performance of Intersection AEB. Although this does not imply that other methods cannot succeed, it was observed that small changes in the definition of a scenario resulted in a different avoidance outcome. Therefore, we suggest using limited physical testing to validate more extensive virtual simulations to evaluate vehicle safety.

Opportunities and limitations for intersection collision intervention-A study of real world 'left turn across path' accidents.

Turning across the path of oncoming vehicle accidents are frequent and dangerous. To date not many car manufacturers have introduced Automated Emergency Braking (AEB) systems addressing this type of conflict situation, but it is foreseeable that these scenarios will be part of the Euro NCAP 2020 rating. Nine out of ten collisions are caused by the driver of the turning vehicle. An AEB system evaluating the ego and conflict vehicle driver's possibilities to avoid a pending crash by either braking or steering was specified for application in various constellations of vehicle collisions. In virtual simulation, AEB system parameters were varied, covering parameters that are relevant for driver comfort such as longitudinal and lateral acceleration (to define avoidance possibilities), expected steering maneuvers to avoid conflict, and intervention response characteristics (brake delay and ramp up) to assess the safety benefit. The reference simulation showed a potential of the AEB system in the turning vehicle to avoid approximately half of the collisions. An AEB system of the straight going vehicle was less effective. The effectiveness of the turning vehicle's AEB system increases if spatial limitations for the collision-avoidance steering maneuver are known. Such information could be provided by sensors detecting free space in or around the road environment or geographical information shared via vehicle to cloud communication. AEB interventions rarely result in collision avoidance for turning vehicles with speeds above 40km/h or for straight going vehicles with speeds above 60km/h. State of the art field-of-views of forward looking sensing systems designed for AEB rear-end interventions are capable of addressing turning across path situations.

Literature review of pedestrian fatality risk as a function of car impact speed.

The aim of this review was to evaluate all studies of pedestrian fatality risk as a function of car impact speed. Relevant papers were primarily investigated with respect to data sampling procedures and methods for statistical analysis. It was uniformly reported that fatality risk increased monotonically with car impact speed. However, the absolute risk estimates varied considerably. Without exceptions, papers written before 2000 were based on direct analyses of data that had a large bias towards severe and fatal injuries. The consequence was to overestimate the fatality risks. We also found more recent research based on less biased data or adjusted for bias. While still showing a steep increase of risk with impact speed, these later papers provided substantially lower risk estimates than had been previously reported.

Pedestrian fatality risk as a function of car impact speed.

Knowledge of the amount of violence tolerated by the human body is essential when developing and implementing pedestrian safety strategies. When estimating the potential benefits of new countermeasures, the pedestrian fatality risk as a function of impact speed is of particular importance. Although this function has been analysed previously, we state that a proper understanding does not exist. Based on the largest in-depth, pedestrian accident study undertaken to date, we derive an improved risk function for adult pedestrians hit by the front of passenger cars. Our results show far lower fatality risks than generally reported in the traffic safety literature. This discrepancy is primarily explained by sample bias towards severe injury accidents in earlier studies. Nevertheless, a strong dependence on impact speed is found, with the fatality risk at 50 km/h being more than twice as high as the risk at 40 km/h and more than five times higher than the risk at 30 km/h. Our findings should have important implications for the development of pedestrian accident countermeasures worldwide. In particular, the scope of future pedestrian safety policies and research should be broadened to include accidents with impact speeds exceeding 50 km/h.