Vehicle Crashes Research Articles

Left-turn crashes and motorcycle safety

Objective To provide updated statistics on crashes in which another vehicle turns left in front of an oncoming motorcycle and discuss the potential of left turn assist technology. Methods Motorcycle driver involvements in 2-vehicle fatal and police-reported crashes during 2017-2021 were tabulated by crash type, with a focus on crash types involving vehicles turning. Results Crashes in which another vehicle turned left in front of an oncoming motorcycle were, by far, the most frequent type of fatal 2-vehicle motorcycle crash, at 26%. Conclusion There is a large opportunity to reduce harm by specifically addressing crashes in which another vehicle turns left in front of an oncoming motorcycle – ideally using a variety of countermeasures simultaneously.

Injury patterns in patients with severe traumatic brain injuries from motor crashes admitted to Mulago hospital accidents & emergency unit.

The global burden of Road Traffic Crashes (RTC) is increasing. Uganda has one of the highest rates of RTCs in Sub-Sahara. Victims of RTCs sustain varying degrees of injuries depending on factors including the velocity at time of impact, protective gear; and if it was a motorcycle-motorcycle or motorcycle-vehicle crash. High speed collisions can result in severe forms of injuries and polytrauma. Some injuries are undetected. A cross sectional study was carried at Mulago Hospital Accidents & Emergency Unit, between November 2021 and February 2022; on all adult patients (≥18 years) with severe head injury from motor road traffic crashes. The study looked at injury patterns and assessed the relationship of polytrauma in patients with severe head injury to the mechanism of injury (motorcycles versus vehicles). Data were extracted from patient charts using a validated data abstraction tool and complete head to toe physical examination was carried out and injuries recorded. Data were analysed to determine the relationship of polytrauma in patients with severe head injury to the mechanism of injury. The participants were predominantly males with a population median age of 32 (25-39). The commonest modes of transportation of patients to the hospital were Police Pickup trucks (40%) and ambulance (36.1%). Among motorcycle RTCs, (19.2%) wore helmets; 21.2% had protective gear; with injury identified mainly in; the limbs (84.8%), neck (76.8%), chest (39.4%), and abdomen (26.3%). Patients from vehicle RTCs were 19% more likely to have polytrauma compared to patients from motorcycle RTCs. This study showed that patients who sustain severe traumatic brain injuries from vehicle crashes have an increased likelihood of having multiple injuries, compared to patients from motorcycle RTCs. For motorcycle users, injuries mostly affect the limbs. At particular risk are motorcyclists who do not wear helmets and protective coveralls.

Injury, Affirmation, and the Disability Masquerade in Ye’s “Through the Wire”

Ye’s song “Through the Wire” exists in two versions. The first was recorded in late 2002 after a near-fatal car crash and features Ye rapping through a jaw wired shut as he recovered from reconstructive surgery. After he healed, a second version was recorded in 2003 and released as the lead single from his debut album. Although Ye raps unimpeded in this later version, it was still marketed as the authentic product of physical disablement. This study explores Ye’s performance of disability across these two versions of “Through the Wire,” focusing on his engagement with a phenomenon known as the masquerade. Adapted from queer and feminist studies to a disability context by Tobin Siebers, the masquerade encompasses a set of strategies for the public negotiation of disabled identities. Two prominent approaches involve 1) exaggerating a disability through a performative act of disclosure, and 2) disguising one disability behind another. I argue that Ye engages in both strategies throughout “Through the Wire,” and that attending to their roles in the song greatly nuances the straightforward narrative of overcoming that he otherwise projects.

Man With Chest Pain After a Traffic Crash.

A 40-year-old man had been involved in a scooter crash and presented to the emergency department with chest pain. His vital signs were blood pressure, 160/84 mmHg; pulse, 109 beats/min; respiratory rate 24 breaths/min, and temperature, 37.5 °C. Physical examination revealed severe local tenderness in the mid-chest region. Plain radiography (Figure 1) and point-of-care ultrasonography of the chest (Figure 2 and Video 1) were performed, and the diagnosis was confirmed by contrast-enhanced computed tomography.Figure 2The point-of-care ultrasound at the site of pain showed a breach in the anterior cortex of the sternal body (arrowhead) and a mass with mixed echogenicity around the fracture indicating hematoma (asterisk).View Large Image Figure ViewerDownload Hi-res image Download (PPT) Sternum fracture. Plain radiography revealed a suspicious mild depression fracture of the sternum. Point-of-care ultrasound imaging, using a high-frequency linear transducer at the site of pain, showed a discontinuous outline of the sternum. A chest computed tomography (Figure 3) image was obtained for confirmation of the diagnosis and to detect possible concomitant associate injuries, such as great vessel disruption, cardiac contusion, and pulmonary contusion. Sternum fracture is characterized by chest pain, which worsens with deep inspiration and shortness of breath. Motor vehicle crashes are the leading cause of sternum fracture, typically due to hitting the steering wheel without an airbag.1Oyetunji T.A. Jackson H.T. Obirieze A.C. et al.Associated injuries in traumatic sternal fractures: a review of the National Trauma Data Bank.Am Surg. 2013; 79: 702-705Crossref PubMed Google Scholar,2Knobloch K. Wagner S. Haasper C. et al.Sternal fractures occur most often in old cars to seat-belted drivers without any airbag often with concomitant spinal injuries: clinical findings and technical collision variables among 42,055 crash victims.Ann Thorac Surg. 2006; 82: 444-450Abstract Full Text Full Text PDF PubMed Scopus (55) Google Scholar Conventional chest radiography has variable diagnosis accuracy, and most sternal fractures may be missed by chest radiography alone.3Perez M.R. Rodriguez R.M. Baumann B.M. et al.Sternal fracture in the age of pan-scan.Injury. 2015; 46: 1324-1327Abstract Full Text Full Text PDF PubMed Scopus (23) Google Scholar The point-of-care ultrasound can be considered a useful technique in identifying sternum fractures.4You J.S. Chung Y.E. Kim D. et al.Role of sonography in the emergency room to diagnose sternal fractures.J Clin Ultrasound. 2010; 38: 135-137PubMed Google Scholar https://www.annemergmed.com/cms/asset/9b3c776c-e7a2-4271-9e98-27acc23ff9ab/mmc1.mp4Loading ... Download .mp4 (3.14 MB) Help with .mp4 files Video 1The point-of-care ultrasound at the site of pain showed a breach in the anterior cortex of the sternal body (arrowhead) and a mass with a mixed echogenicity around the fracture indicating hematoma (asterisk).

Factors associated with driver injury severity of motor vehicle crashes on sealed and unsealed pavements: Random parameter model with heterogeneity in means and variances

The effect of sealed or unsealed road pavements on motorist’s injury severities has not been extensively explored. This study collected a four-year crash dataset (2015–2018) from South Australia to explore this issue. The data shows 3,812 and 1,086 crashes at sealed and unsealed pavement surfaces, respectively, during those years. This study examines the consequence of sealed and unsealed pavements on driver injury severity outcomes of motor vehicle crashes. A mixed logit model was developed by accounting for heterogeneity in means and variances of the random parameters. The variables were distributed among several categories: driver, temporal, spatial, roadway characteristics, crash type, vehicle type, and vehicle movement. Four random parameters were observed in the sealed model, whereas five parameters were in the unsealed one. Moreover, the sealed pavements model showed substantial heterogeneity in means of four of the random parameters, while the unsealed pavements model has some heterogeneity in both means and variances of some of the random parameters. Marginal effect results indicate that two indicator variables have enlarged the likelihood of driver severe injury consequences in sealed, alcohol involvement and posted speed limit > 100 km/hr. Additionally, four other significant variables sustain the probability of severe injury outcomes at unsealed pavement like male drivers, middle-aged drivers, rollover crash types, and crashes at straight roads. Based on these variables, various countermeasures were recommended to enhance the safety of both types of pavements.

EDGE DETECTION TECHNIQUE BASED ON BILATERAL FILTERING AND ITERATIVE THRESHOLD SELECTION ALGORITHM AND TRANSFER LEARNING FOR TRAFFIC SIGN RECOGNITION

The traffic sign identification and recognition system (TSIRS) is an essential component for autonomous vehicles to succeed. The TSIRS helps to collect and provide helpful information for autonomous driving systems. The information may include limits on speed, directions for driving, signs to stop or lower the speed, and many more essential things for safe driving. Recently, incidents have been reported regarding autonomous vehicle crashes due to traffic sign identification and recognition system failures. The TSIRS fails to recognize the traffic signs in challenging conditions such as skewed signboards, scratches on traffic symbols, discontinuous or damaged traffic symbols, etc. These challenging conditions are presented for various reasons, such as accidents, storms, artificial damage, etc. Such traffic signs contain an ample amount of noise, because of which traffic sign identification and recognition become a challenging task for automated TSIRS systems. The proposed method in this paper addresses these challenges. The sign edge is a helpful feature for the recognition of traffic signs. A novel traffic sign edge detection algorithm is introduced based on bilateral filtering with adaptive thresholding and varying aperture size that effectively detects the edges from such noisy images. The proposed edge detection algorithm and transfer learning is used to train the Convolutional Neural Network (CNN) models and recognize the traffic signs. The performance of the proposed method is evaluated and compared with existing edge detection methods. The results show that the proposed algorithm achieves optimal Mean Square Error (MSE) and Root Mean Square Error (RMSE) error rates and has a better Signal to Noise Ratio (SNR) and Peak Signal to Noise Ratio (PSNR) ratio than the traditional edge detection algorithms. Furthermore, the precision rate, recall rate, and F1 scores are evaluated for the CNN models. With the German Traffic Sign Benchmark database (GTSRB), the proposed algorithm and Inception V3 CNN model gives promising results when it receives the edge-detected images for training and testing.

Simultaneous acromioclavicular dislocation, proximal humeral fracture, and reverse Hill–Sachs lesion: a case report

BackgroundIn cases with injuries to the shoulder region, the combination of acromioclavicular joint dislocation, reverse Hill–Sachs lesion, and proximal humeral fracture is a very rare condition.Case presentationThis study described a 38-year-old male Persian patient with simultaneous acromioclavicular joint dislocation, proximal humeral fracture, and reverse Hill–Sachs lesion due to motor vehicle crash injury who underwent arthroscopic acromioclavicular joint fixation using tight rope technique. In the 7-month follow-up period following the surgical fixation, range of motion was approximately normal. Reduction and hardware were intact, no dislocation or apprehension to dislocation was observed. Patient only had minor shoulder pain at the end of range of motion and a dull pain on the site of incision over the clavicle in deep touch. Our findings showed acceptable arthroscopic outcomes in the management of such complex case.ConclusionOur experience on this case showed acceptable outcomes of the arthroscopic treatment of the acromioclavicular joint dislocation in the management of such a complex case with associated injuries to the shoulder region.

Causes of death in children and adolescents: Guns outpace overdoses and car crashes

A letter to the editor of the New England Journal of Medicine picked up on a steady stream of criticism of gun laws – or lack of them – in the United States, focusing on increasing deaths of young people.

Comprehensive Investigation of Commercial Motor Vehicle Crashes at Signalized and Unsignalized Intersections in Kentucky

This study develops safety performance functions (SPFs) for “fatal and injury” (FI) commercial motor vehicle (CMV) crashes (here, a CMV is defined as a large truck or a bus) at both signalized and unsignalized intersections in Kentucky. Five count-response regression models—negative binomial, Conway–Maxwell–Poisson, heterogeneous Conway–Maxwell–Poisson, zero-inflated Conway–Maxwell–Poisson, and zero-inflated heterogeneous Conway–Maxwell–Poisson (ZI-HTCMP)—were developed and compared at each of the selected signalized and unsignalized intersections. FI CMV intersection-related crash data in Kentucky over a period of five years (2015 to 2019) were used. Information on road-specific characteristics, for example, shoulder width, median width and type, International Roughness Index (IRI) value, and traffic volume (including annual average daily traffic [AADT] and heavy vehicle percentage [HVP]) was collected. Additionally, information on intersection-specific characteristics, for example, number of through lanes and presence of exclusive left- and right-turn lanes on major and minor roads, was collected using Google Maps’ street view time slider back to the crash year. For both signalized and unsignalized intersections, the ZI-HTCMP model (with a varying dispersion parameter) outperformed the other comparative models. With regard to signalized intersections, a speed limit of greater than 45 mph on the major road, a speed limit greater than 45 mph on the minor road, and a median on the major road wider than 3 ft were significantly associated with increased FI CMV crashes. As far as unsignalized intersections were concerned, higher major road AADT, 4-legged configuration, a speed limit greater than 45 mph on the major road, and an IRI value of greater than 100 for the major road were significantly associated with increased FI CMV crashes. The SPF results (for each of the signalized and unsignalized intersections) were then used to identify the top 10 hazardous locations for each intersection type.

Retrospective Review of Antecustodial Deaths Referred for Medicolegal Autopsy at the Medical University of South Carolina.

Deaths occurring in police custody have dominated public discourse over recent years. However, deaths occurring after law enforcement have initiated nonphysical contact but before active restraint or containment lie outside the strict definition of "in custody." These "antecustodial" deaths demonstrate a unique population and interaction with law enforcement. A retrospective analysis of medicolegal cases referred to the Medical University of South Carolina from September 1, 2012, to April 28, 2022 was performed. Deaths during nonphysical interaction with or during evasion of law enforcement occurred in 78 cases and were categorized by demographic data, cause of death, manner of death, the presence of drugs and/or alcohol, and circumstances surrounding the interaction. Antecustodial deaths occurred primarily during law enforcement pursuit and deescalation scenarios. Decedents were predominantly male (92.3%) with a Black-to-White ratio of 1.1:1. The average age of male and female decedents was 35.7 and 32.2 years, respectively. The most common causes of death were gunshot wounds and blunt trauma sustained in motor vehicle crashes. The most common manner of death was homicide (43.6%), followed by suicide (28.2%) and accident (28.2%).

Construction of Collision Equivalent Scaled Model for Locomotive Using Multi-Parameter Nondimensional Method

At present, the research on crashworthiness of locomotive mainly adopts the method of theoretical analysis, numerical simulation and component test, it is too expensive and less repeatable to carry out vehicle crash tests. Therefore, a method to construct the collision equivalent scaled model (SM) for locomotive based on multi-parameter nondimensional is presented in this paper. Firstly, an equivalent method of structural dynamic responses was proposed. The extraction process and analysis method of dynamic responses for thin plate structures widely existing in locomotives were studied. Then, according to the structural characteristics of the locomotive, the partition equivalent design was carried out, and a dimensionless analysis model of impact dynamic responses for SM was established. Finally, the SM crash test was carried out to verify the effectiveness of collision equivalent SM established, it was found that the SM has high reliability, it can achieve equivalence with the locomotive for energy absorption, average impact force, average acceleration of cab and center of gravity of vehicle body. Carrying out the SM crash test can study the reasonable configuration of energy absorption parameters for locomotives and obtain the impact dynamic responses of locomotives under different configurations of energy absorption parameters.

Summertime and the drivin' is easy? Daylight saving time and vehicle accidents.

We investigate how exogenous variation in daylight caused by Daylight Saving Time affects road safety as measured by the count of vehicle crashes. We use administrative daily data from Greece covering the universe of all types of recorded vehicle accidents during the 2006-2016 period. Our regression discontinuity estimates support an ambient light mechanism that reduces the counts of serious vehicle accidents during the Spring transition and increases the count of minor ones during the Fall transition. The effects are driven from the hour intervals that are mostly affected from seasonal clock changes. We then discuss the potential cost implications of those seasonal transitions. In light of the talks about abolishing seasonal clock changes in the European Union (EU), our findings are policy relevant and can inform the public debate as empirical evidence for the block is scarce.

The association between childhood opportunity index and pediatric hospitalization for firearm injury or motor vehicle crash

BackgroundCommunity-level factors can profoundly impact children’s health, including the risk of violent injury. This study’s objective was to understand the relationship between the Childhood Opportunity Index and pediatric firearm injury owing to interpersonal violence compared with a motor vehicle crash. MethodsAll pediatric patients (<18 years) who presented with an initial encounter with a firearm injury or motor vehicle crash between 2016 to 2021 were identified from 35 children’s hospitals included in the Pediatric Health Information System database. The child-specific community-level vulnerability was determined by the Childhood Opportunity Index, a composite score of neighborhood opportunity level data specific to pediatric populations. ResultsWe identified 67,407 patients treated for injuries related to motor vehicle crashes (n = 61,527) or firearms (n = 5,880). The overall cohort had a mean age of 9.3 (standard deviation 5.4) years; 50.0% were male patients, 44.0% non-Hispanic Black, and were 60.8% publicly insured. Compared with motor vehicle crash injuries, patients with firearm-related injuries were older (12.2 vs 9.0 years), more likely to be male patients (77.7% vs 47.4%), non-Hispanic Black (63.5% vs 42.1%), and had public insurance (76.4 vs 59.3%; all P < .001). In multivariable analysis, children living in communities with lower Childhood Opportunity Index levels were more likely to present with firearm injury than those living in communities with a very high Childhood Opportunity Index. The odds increased as the Childhood Opportunity Index level decreased (odds ratio 1.33, 1.60, 1.73, 2.00 for high, moderate, low, and very low Childhood Opportunity Index, respectively; all P ≤ .001). ConclusionChildren from lower-Childhood Opportunity Index communities are disproportionately impacted by firearm violence, and these findings have important implications for both clinical care and public health policy.

Effects of Concrete Conceptual Metaphor on Peoples Reasoning

In this work, the effect of metaphorical language on people's cognition about concrete events will be tested. In order to do so, the study will exploit the difference in metaphor use in describing the extent of a car crash to evaluate the framing effect of the word choice on people's perception of a concrete physical accident. In the experiment, participants will be randomly assigned to read two versions of texts about a car accident with only different metaphor usages to describe the extent of the car's windshield breakage. Then participants will be asked to answer three multiple-choice questions that can reflect participants reasoning towards the severity of the car accident they have read. This study predicts that participants who read the "milder" metaphor version will perceive the car accident less severely than those who read the "severer" metaphor version, which can prove the influence of metaphorical language on people's perception of concrete events.

A predictive model to analyze the factors affecting the presence of serious chest injury in the occupants on motor vehicle crashes: Logistic regression approach

Objective Chest injuries that occur in motor vehicle crashes (MVCs) include rib fractures, pneumothorax, hemothorax, and hemothorax depending on the injury mechanism. Many risk factors are associated with serious chest injuries from MVCs. The Korean In-Depth Accident Study database was analyzed to identify risk factors associated with motor vehicle occupants’ serious chest injury. Methods Among 3,697 patients who visited the emergency room in regional emergency medical centers after MVCs between 2011 and 2018, we analyzed data from 1,226 patients with chest injuries. Vehicle damage was assessed using the Collision Deformation Classification (CDC) code and images of the damaged vehicle, and trauma scores were used to determine injury severity. Serious chest injury was defined as an Abbreviated Injury Scale (AIS) score for the chest code was more than 3. The patients were divided into two groups: serious chest injury patients with MAIS ≥ 3 and those with non-serious chest injury with MAIS < 3. A predictive model to analyze the factors affecting the presence of serious chest injury in the occupants on MVCs was constructed by a logistic regression analysis. Results Among the 1,226 patients with chest injuries, 484 (39.5%) had serious chest injuries. Patients in the serious group were older than those in the non-serious group (p=.001). In analyses based on vehicle type, the proportion of light truck occupants was higher in the serious group than in the non-serious group (p=.026). The rate of seatbelt use was lower in the serious group than in the non-serious group (p=.008). The median crush extent (seventh column of the CDC code) was higher in the serious group than in the non-serious group (p<.001). Emergency room data showed that the rates of intensive care unit (ICU) admission and death were higher among patients with serious injuries (p<.001). Similarly, the general ward/ICU admission data showed that the transfer and death rates were higher in patients with serious injuries (p<.001). The median ISS was higher in the serious group than in the non-serious group (p<.001). A predictive model was derived based on sex, age, vehicle type, seating row, belt status, collision type, and crush extent. This predictive model had an explanatory power of 67.2% for serious chest injuries. The model was estimated for external validation using the confusion matrix by applying the predictive model to the 2019 and 2020 data of the same structure as the data at the time of model development in the KIDAS database. Conclusions Although this study had a major limitation in that the explanatory power of the predictive model was weak due to the small number of samples and many exclusion conditions, it was meaningful in that it suggested a model that could predict serious chest injuries in motor vehicle occupants (MVOs) based on actual accident investigation data in Korea. Future studies should yield more meaningful results, for example, if the chest compression depth value is derived through the reconstruction of MVCs using accurate collision speed values, and better models can be developed to predict the relationship between these values and the occurrence of serious chest injury.

Improving elementary students' knowledge and behavior to prevent traumatic injury: the impact of a behavioral skills training model delivered by aspirational role models.

Trauma is the leading cause of childhood morbidity and mortality annually in the USA, accounting for 11% of deaths, most commonly due to car crashes, suffocation, drowning, and falls. Prevention is paramount for reducing the incidence of these injuries. As an adult level 1 and pediatric level 2 trauma center, there is a commitment to injury prevention through outreach and education. The Safety Ambassadors Program (SAP) was developed as part of this aim. Safety Ambassadors (SA) are high schoolers who teach elementary school students about safety/injury prevention. The curriculum addresses prevalent areas of injury risk: car/pedestrian safety, wheeled sports/helmets, and fall prevention. The study group hypothesized that participation in SAP leads to improved safety knowledge and behaviors and ultimately reduces childhood preventable injuries. Educational material was delivered by high school students (ages 16-18years old). First and second-grade participants (ages 6-8years old) completed pre- and post-course exams to assess knowledge (12 questions) and behavior (4 questions). Results were retrospectively reviewed, and pre/post training mean scores were calculated. Scores were calculated based on number of correct answers on pre/post exam. Comparisons were made using the Student t-test. All tests were 2-tailed with significance set at 0.05. Pre- and post-training results were assessed for 2016-2019. Twenty-eight high schools and 37 elementary schools were enrolled in the program with 8832 student participants in SAP. First graders demonstrated significant improvement in safety knowledge (pre 9 (95% CI 8.9-9.2) vs post 9.8 (95%CI 9.6-9.9), (p < 0.01)) and behavior modification (pre 3.2 (95%CI 3.1-3.2) vs post 3.6 (95% CI 3.5-3.6), (p < 0.01)). Similar findings were seen in 2nd graders: safety knowledge (pre 9.6 (95% CI 9.4-9.9) vs post 10.1 (95% CI 9.9-10.2), (p < 0.01)) and behavior (pre 3.3 (95% CI 3.1-3.4) vs post 3.5 (95%CI 3.4-3.6), (p < 0.01)). Conclusion: SAP is a novel evidence-based educational program delivered to elementary school students by aspirational role models. This model is impactful, relatable, and engaging when provided by participants' older peer mentors. On a local level, it has demonstrated improved safety knowledge and behavior in elementary school students. As trauma is the leading cause of pediatric death and disability, enhanced education may lead to life-saving injury prevention in this vulnerable population. What is Known: • Preventable trauma is the leading cause of pediatric death in the USA and education has contributed to improvements in both safety knowledge and behavior. • The ideal delivery method for injury prevention education in children continues to be under investigation. What is New: • Our data suggest that a peer-based injury prevention model is both an effective education delivery method and easily instituted within existing school systems. • This study supports implementation of peer-based injury prevention programs to improve safety knowledge and practices. • With more widespread institution and research, we hope to ultimately reduce preventable childhood injury.

Direct medical charges of all parties in teen-involved vehicle crashes by culpability

BackgroundMotor vehicle crashes among teen drivers often involve passengers in the teen’s vehicle and occupants of other vehicles, and the full cost burden for all individuals is largely unknown. This...

Scientometric and Bibliographic Analysis of Pedestrian Safety Research

The vulnerability of pedestrians means that pedestrian and vehicle crashes often have severe consequences. Pedestrian safety related research has attracted researchers’ attention since the 1970s and has become increasingly popular in recent years. There were about 250 papers published in 2021 alone on this research domain. However, scientometric studies on a specific safety area are rarely conducted. Scientometric and bibliographic analyses provide researchers with a thorough understanding of research topics and historical knowledge on authorship, publishers, keywords (thematic topics), and collaborations that occurred in the research community on the specific research domain. This study bridges this gap by collecting 2,689 pedestrian safety-related papers from the Web of Science (WoS) Core Collection database and conducting a scientometric and bibliographic analysis. The results show the increasing popularity of pedestrian safety-related studies, and the number of papers has increased significantly each year since 2000. This study also investigated the changes in the research interests in pedestrian safety-related studies temporally. The results show research interests changed from investigating the built environment, theoretical modeling, behavioral studies, and advanced modeling techniques over time. Moreover, the findings suggest that child pedestrian safety interests started to gain popularity in 2008, soon after the Safe Routes to School (SRTS) program was initiated in 2005, which shows the positive interactions between this research domain and policy-making progress.

Human and machine drivers: Sharing control, sharing responsibility

Machines are empowered with ever-increasing agency and decision-making authority to augment or even replace humans in various settings, making responsibility attribution less straightforward when they cause harm. Focusing on their applications in transportation, we consider human judgments of responsibility for automated vehicle crashes through a cross-national survey (N = 1657) and design hypothetical crashes after the 2018 Uber automated vehicle crash reportedly caused by a distracted human driver and an inaccurate machine driver. We examine the association between automation level—the human and machine drivers have different levels of agency (i.e., the human as a supervisor, backup driver, and mere passenger, respectively)—and human responsibility through the lens of perceived human controllability. We show the negative association between automation level and human responsibility, partly mediated by perceived human controllability, regardless of the involved responsibility metric (rating and allocation), the nationality of the involved participant (China and South Korea), and crash severity (injury and fatality). When the human and machine drivers in a conditionally automated vehicle jointly cause a crash (e.g., the 2018 Uber crash), the human driver and car manufacturer are asked to share responsibility. Our findings imply that the driver-centric tort law needs to be control-centric. They offer insights for attributing human responsibility for crashes involving automated vehicles.

Kinematics Bionic Concept Structure Design and Optimization of Vehicle Crash Dummy’s Knee Joint: Bionics and Biomechanics Applied in Collision Safety of Cars

The structural bionicism of the knee joint of an automobile crash dummy is an important factor affecting the accuracy of the dummy’s knee displacement and knee flexion angle measurements in automobile crash tests. This study focused mainly on the optimization of the bionic structure of the knee joint of an automobile crash dummy to ensure that the dummy has a kinematic response closer to that of the knee joint of a real human. Forty sets of high-speed photographic images of the sphyrion were acquired by performing a trajectory-measurement test at the lower tibial point. Subsequently, the high-flexion motion trajectory of the knee joint was obtained by solving vector equations and by multicurve fitting. This trajectory, combined with the bionic structure design method, optimized the structure of the existing dummy’s knee joint. Thereby, its motion can be altered from a fixed-axis rotation to a non-fixed-axis curve motion close to how the human tibial plateau rotates around the femoral condyle. This increases the degrees of freedom of the dummy’s knee joint from two to three. The knee joint structures before and after the optimization were simulated kinematically using a multibody dynamics method. The results showed that the peak of the motion trajectory deviation of the optimized sphyrion decreased from 3.7% to 1.9%, and the average deviation decreased from 2.0% to 0.2%. This indicates that the structural optimization scheme improved the motion bionics of the crash dummy’s knee joint.