Search Results (98)

Background and Objectives: Courier-operated motorcycles and mopeds have become increasingly visible in urban traffic, raising concerns about injuries among both couriers and pedestrians struck by courier-operated vehicles. The study period coincided with the COVID-19 pandemic; however, this study was not designed to evaluate the effect of the pandemic on courier-related injuries. This multicenter retrospective study aimed to describe hospital-based injury patterns, injury severity, treatment requirements, complications, and mortality among selected courier-related casualties, including motorcycle couriers and pedestrians struck by courier-operated motorcycles or mopeds. Materials and Methods: This retrospective multicenter observational study included courier-related traffic casualties identified between 1 March 2020, and 1 June 2022, through nine hospitals in İstanbul and Ankara and, for fatal courier cases, linked emergency medical service and hospital records. The primary clinical cohort consisted of injured couriers and pedestrians evaluated or treated at participating hospitals. Linked prehospital and early fatal courier cases were analyzed separately for mortality-related and mechanism-specific fatality analyses. Injury severity was assessed using the New Injury Severity Score. Treatment was classified as conservative or surgical, including both fracture fixation and soft-tissue procedures. Results: A total of 857 courier-related traffic casualties were identified, including 491 couriers and 366 pedestrians. Among couriers, 111 fatal cases were verified through linked records. Clinical treatment and follow-up analyses were restricted to 380 hospital-treated surviving couriers and 366 pedestrians with available clinical records. In this selected hospital-treated courier cohort, multiple fractures, open fractures, higher injury severity scores, surgical treatment, and complications were more frequent than among pedestrians. All hospital-treated surviving couriers included in the orthopedic trauma cohort underwent surgery, reflecting the orthopedic trauma-based case-identification process, whereas most pedestrians were treated conservatively. Conclusions: Among this selected hospital-based cohort, courier casualties identified through hospital, trauma referral, emergency, forensic, and linked fatal-event records showed a more severe clinical profile than pedestrians evaluated after being struck by courier-operated motorcycles or mopeds. These findings should be interpreted as hospital-based injury-severity patterns rather than population-level estimates of accident incidence, relative injury risk, or public health burden. Full article

Aggressive riding behavior is a key contributing factor to road accidents, particularly in motorcycling, where rider dynamics directly influence vehicle stability and control. Despite growing interest in objective behavioral assessment, validated classification frameworks specific to motorcycles remain scarce in the literature. This pilot study investigated the feasibility of a standard deviation-based method for classifying aggressive riding behavior in a single experienced motorcyclist navigating two distinct environments: an urban route (UR) and a suburban national route (SNR). The participant completed two 20 min rides under real-world conditions. The UR was characterized by frequent accelerations, braking, speed bumps, and traffic lights, whereas the SNR features low traffic density and minimal interruptions. Longitudinal acceleration data were continuously recorded using a Vicon Blue Trident measurement unit mounted on the motorcycle seat. Drawing on the threshold principles established in automotive research, an environment-specific classification framework was developed to categorize riding events into normal, aggressive, and dangerous levels for both acceleration and deceleration maneuvers. The derived thresholds revealed pronounced environmental differences: UR thresholds (acceleration: 2.122 m/s²; deceleration: −2.134 m/s²) were approximately three times lower than those observed in the SNR (acceleration: 6.16 m/s²; deceleration: −7.09 m/s²). From more than four million recorded data points, approximately 88% of the riding behavior was classified as normal in both routes. In the UR, 9.27% of events were identified as aggressive and 4.37% as dangerous, compared with 7.27% aggressive and 5.35% dangerous events in the SNR. These preliminary findings suggest that environment-specific thresholds may be essential for accurately characterizing motorcycle riding behavior, and caution against the direct application of fixed automotive criteria to motorcycle safety analyses. All findings are specific to one rider on two routes and must not be extrapolated to other motorcyclists, vehicle types, or road contexts without replication. Full article

Collisions between motorcycles and car doors that are being opened are common, preventable accidents that can result in fatalities. A critical limitation of safety advancements in both cars and motorcycles is high cost associated with the use of radar sensors. In this study, a deep learning model was integrated into an inexpensive and camera-utilizing automatic braking assistance system for motorcycles to enhance braking performance and alert motorcyclists to avoid collisions. This research involved two stages: (1) the training of a deep learning model for detecting car door states and (2) the design of safety mechanisms for selecting appropriate braking intensity and front braking ratio values on the basis of the model’s output, time-to-collision, the rider’s braking action, and the initial braking speed, in order to achieve optimal braking performance. Specifically, the YOLOv12s object detection model showed high performance in predicting the states of car doors, exhibiting precision, recall, and mean average precision values of 90.5%, 80.6%, and 87.8%, respectively. The braking intensity of the system was set to 0%, 25%, 50%, or 100% in scenarios involving opening states of the car door (closed, small, medium, or large opening), time-to-collision values, and the rider’s braking action. The optimal front braking ratio function was determined based on the initial braking speed to achieve the optimal braking performance. At an initial braking speed of 60 km/h, the braking stroke under a front braking ratio of 45% was 35.61% and 13.37% shorter than those under front braking ratios of 20% and 60%, respectively. The proposed braking assistance system can feasibly be deployed in the real world because it can respond within a safe time window under the conditions studied, which is approximately 0.5 s. However, further refinement is required, including improvement of the robustness of the object detection model through the collection of a larger and more diverse dataset, experimental measurement of front braking ratios to determine the optimal braking performance in real scenarios, and design of a physical actuator to control braking intensity and the front braking ratio in real time. Full article

Traffic accidents represent a significant threat to individuals, with motorcycles frequently involved. Despite concerted efforts by organizations like the World Health Organization and governments worldwide, reducing accident rates remains a challenge. Notably, Indonesia has witnessed a surge in traffic accidents, with motorcycles being a prominent mode of transport. This study aims to evaluate situational awareness and motorcycle riders’ behavior among Indonesians, with respect to factors such as riding time and age. This study involves laboratory-based research and uses quantitative primary data collected with the Situation Awareness Global Assessment Technique (SAGAT), the Situation Present Assessment Method (SPAM), and the Motorcycle Rider Behavior Questionnaire (MRBQ). The results indicate that overall situation awareness is low, with the lowest level among young riders. Nighttime situational awareness is also lower than during the daytime. Recommendations to improve situation awareness include periodic training with scenario-based sessions for motorcycle riders, strict adherence to driving regulations, the potential integration of motorcycle simulators, and prioritizing the program to enhance young riders’ situation awareness. These recommendations aim to boost rider safety and reduce motorcycle accidents. Full article

Background: Assessment and treatment of brachial plexus injury in polytrauma patients is often challenging due to concomitant injuries requiring life-saving interventions. Furthermore, the role of immediate nerve exploration in closed postganglionic nerve injuries remains debated. Case presentation: We present the case of a 21-year-old male with an infraclavicular brachial plexus injury, floating shoulder and axillary artery rupture following a motorcycle accident. Early multidisciplinary intervention included vascular repair, bone stabilization and brachial plexus exploration. Nerve reconstruction using grafts and transfers led to significant functional recovery, preventing degenerative changes, and facilitating early rehabilitation. Conclusions: This case highlights the benefits of early exploration and management of complex brachial plexus injuries in polytrauma patients to improve functional outcomes and quality of life. Full article

This research examines the risk factors that influence injury severity in individual motorcycle accidents, utilising a dataset of 5253 incidents. Five machine learning algorithms—multinomial logistic regression, classification trees, random forests, XGBoost, and neural networks—were used to classify the results into three groups: Death (13.48%), Injury (80.14%), and No injury (6.38%). In all models, passenger presence was the most important predictor of injury. Motorcycle accidents involving passengers do not always have more serious consequences for several overlapping reasons. On the one hand, a motorcycle with a passenger has a significantly higher mass, which increases the braking distance and kinetic energy at the moment of collision, hindering quick defensive manoeuvres, cornering, and reactions to sudden hazards. Often, the rider also refrains from sudden movements to prevent the passenger from losing their balance. In the case of single-rider motorcycle accidents on roadways, approximately 5% of those involved with a passenger were fatalities, while approximately 48% were uninjured; in the case of those without a passenger, no one was uninjured. It follows from the above that the presence of a passenger increases the rider’s sense of responsibility. Other factors that significantly increased risk were single-lane carriageways, vehicle overturning, contaminated road surfaces, and collisions with complex objects, e.g., like trees. The multinomial logistic regression model had an overall accuracy of 69.2% on the test set. The Recurrent Neural Network achieved the best overall accuracy of 79.56%. Balanced accuracy, as the average between sensitivity and specificity of the RNN model for the “death” class was 68.15%, for the “injury” class—72.6%, and for the “no injury” class—96.61%. The Area Under the ROC Curve of the Recurrent Neural Networks model for “no injury” was 0.97, indicating it was very good at distinguishing between this class and the other classes. Even though it was easy to tell which cases did not involve injuries, it was still hard to tell the difference between fatal and non-fatal injuries in all models. The results support interventions tailored to specific situations, such as improved road lighting and speed control in rural areas, as well as helmet enforcement and safety measures at intersections in cities. Full article

Road transport across Asia is undergoing rapid motorisation and exemplifies growing road safety challenges, with rising accident rates closely linked to driver behaviour. Recent reports indicate that Vietnamese drivers often perceive risk as manageable and enforcement as inconsistent, contributing to habitual violations such as speeding, signal ignoring, and risky manoeuvres, particularly when traffic is light. Evidence shows that riders, especially young adults, feel confident controlling their vehicles and frequently disregard safety warnings. This study investigates traffic safety awareness among motorcyclists and car drivers in Hanoi, based on a questionnaire survey of 393 respondents. Principal Component Analysis (PCA) was used to group 11 attitudinal statements into key components influencing road safety perceptions, identifying five: non-compliance with traffic regulations (Component 1), aggressive driving behaviour (Component 2), traffic signal issues (Component 3), road quality and infrastructure (Component 4), and preventive measures (Component 5). Multiple Correspondence Analysis (MCA) and two-step cluster analysis (TCA) were then applied to determine user clusters by socio-demographic characteristics, producing three groups: young adults in employment riding motorcycles (Cluster 1), young adults in education riding motorcycles (Cluster 2), and mature adults in employment driving cars (Cluster 3). Finally, Multinomial Logistic Regression (MLR) was applied to assess variations in road safety perceptions across the different groups (clusters). Mature adults driving cars (Cluster 3) identified the first four components as significant, with Components 1 and 2 showing negative associations and Components 3 and 4 positive associations. Full article

Background/Objectives: Motorcycle accidents have grown to become a significant public health thread worldwide. Most of the victims are described to be males of young age, some of lower socioeconomic status. Throughout the literature, head and spinal injuries are described as the most common injuries, while chest injuries and lower extremity fractures are also frequently described. Moreover, driving under the influence of alcohol has been widely described as a major predisposing factor. We conducted a retrospective cohort study to categorize risk factors, including demographic information and alcohol/psychoactive substance consumption, as well as pre-existing medical conditions. Correspondingly, we identified the most common injury patterns and attempted to establish a connection between time to hospital and survival rates. Methods: Cases of motorcycle-related road traffic accidents (RTAs) examined by the authors during 2021–2023 were included in the study sample (94 cases in total). This retrospective cohort study assessed survival time (in days) from accident to death. Kaplan–Meier curves, stratified by key categorical variables, were used to analyze survival probabilities over time. Univariate Cox regression was used to assess each variable’s effect on survival. The association between exposure and mortality was analyzed using hazard ratios (HRs) and 95% confidence intervals (CIs). Results: Head injuries were associated with poorer outcomes. Chest injuries reduced median survival to 1.68 h compared to 5.85 days in cases that had not sustained chest injuries. Abdominal injuries also shortened survival (1.632 h vs. 1.896 h), as did multiple-site injuries (1.584 h vs. 0.2 days for single/double-site). Positive toxicology for psychoactive substances lowered survival to 1.32 h compared to 1.752 h in cases with negative toxicological findings. Multiple-site injuries and head, chest and abdominal injuries appeared to significantly affect the survival of victims. Positive toxicological examination results for psychoactive substances also appeared to heavily impact survival. Full article

This paper presents an active safety warning system for two-wheeled motorcycles that integrates YOLO v4 image recognition technology with a heuristic weighting mechanism (HWM) model to calculate risk scores and thus alert riders. The system’s analytical core is based on the NVIDIA Jetson TX2 module, with a camera mounted on the left-side rearview mirror of the motorcycle. YOLO is used to identify the type of approaching vehicle and measure the distance between the vehicle and the motorcycle. Moreover, the HWM model takes inputs such as vehicle type, spacing between the motorcycle and the vehicle, motorcycle speed, and distance from the intersection to generate potential risk scores. After training, the YOLO model for vehicle recognition achieved a mean Average Precision (mAP) of 92.78% at an Intersection over Union (IoU) threshold of 0.5. Additionally, the camera mounted at a 30° angle could clearly capture vehicles approaching from the left rear side of the motorcycle, achieving the highest vehicle recognition rate. Moreover, the HWM model generates a reasonable risk score to advise the rider to decelerate when the motorcycle is traveling at high speed with a vehicle approaching from behind, thereby reducing the risk of an accident and enhancing the safety of the motorcyclist. Full article

In recent years, the issue of drivers under the influence of medications and psychoactive substances as a cause of road accidents has gained increasing importance. This study aimed to assess the prevalence and blood concentration ranges of alcohol and psychoactive substances among drivers in northeastern Poland between 2013 and 2024. To determine the prevalence of medications and psychoactive substances in drivers’ blood, data were collected from 266 blood samples obtained from drivers (251 men and 15 women). Among these, 79 drivers died immediately, 61 drivers survived the accident, and 126 drivers were stopped for roadside checks. The presence of the studied substances was confirmed using gas chromatography combined with mass spectrometry detection (GC-MS) and liquid chromatography combined with mass spectrometry detection (LC-MS). Blood alcohol content was measured using headspace gas chromatography with a flame ionisation detector (HS-GC-FID). Psychoactive substances were detected in 152 of the 266 samples. Drivers testing positive for medications and psychoactive substances were most frequently stopped during roadside controls—67.46%. Among the total positive cases, psychoactive substances used alone or in combination included THC—46.3% (range 0.2–20 ng/mL), alcohol—26.8% (range 0.1–4.1‰), amphetamines—20.7% (range 15–2997 ng/mL), opiates—4.3% (morphine 66.0 ng/mL; methadone 174.0 ng/mL; ranges: tramadol 15.0–600.0 ng/mL; fentanyl 45.0–100.0 ng/mL), benzodiazepines—9.8% (ranges: diazepam 55.0–480.0 ng/mL; midazolam 17.0–1200.0 ng/mL; clonazepam 21.0–36.0 ng/mL), stimulants—6.10% (ranges: amphetamine 15.0–2997.0 ng/mL; cocaine 4.0–30.0 ng/mL; benzoylecgonine 38.0–602.0 ng/mL; PMMA 45.0–360.0 ng/mL; MDMA 20.0–75.0 ng/mL; mephedrone 37.5 ng/mL; alfa-PVP 120 ng/mL), psychotropic drugs—3.1% (carbamazepine 8.0–2100.0 ng/mL; zolpidem 233.0 ng/mL; citalopram 320.0 ng/mL; opipramol 220 ng/mL). The most commonly used substance among car and motorcycle drivers was THC (37.7% of car drivers and 60% of motorcyclists). Among operators of other types of vehicles, alcohol was the most frequently detected substance, present in 35% of cases. The majority of drivers (81.1%) were under the influence of a single substance. Among the drivers, 7.3% consumed alcohol in combination with at least one other substance, and 11.6% used two or more substances excluding alcohol. Among the psychoactive substances most frequently used alone or in combination with others, THC was predominant. Roadside testing, based on effects similar to alcohol intoxication, was mainly conducted on male drivers. Full article

Background/Objectives: Traumatic brain injuries (TBI) account for over a third of all injury-related deaths, predominantly due to motor vehicle collisions (MVC). This study provides a comprehensive analysis of TBI trends in Eastern Massachusetts, focusing on injuries resulting from motorcycle MVCs (mMVC), non-motorcycle MVCs (nmMVC), and pedestrian-vehicle strikes (PVS). Methods: A retrospective analysis was conducted on TBI patients admitted between 2010 and 2020 to Boston Medical Center. TBI severity was assessed using the Glasgow Coma Scale (GCS) on admission (mild: 13–15, moderate: 9–12, severe: 3–8), and outcomes were determined by discharge disability scales. Descriptive and inferential statistics evaluated patient profiles, TBI severity, and group differences. Results: Among the 2901 identified TBI cases from MVCs, 14.1% were mMVCs, 55.1% nmMVCs, and 30.8% PVS. Mortality rates were 3.7% for mMVCs, 2.1% for nmMVCs, and 8.9% for PVS. In 2017, nmMVC-related TBIs decreased by 50% and PVS-related TBIs by 35% (p < 0.01). The PVS group tended to be older (mean age 41.0 years) and more racially diverse, with Asian patients overrepresented. The mMVC group had a significantly skewed gender distribution, with 91% male. TBI severity also varied significantly, with the mMVC and PVS groups experiencing more severe TBIs compared to the nmMVC group (p < 0.001). Discharge outcomes, as assessed by the Cerebral Performance Category (CPC) scale, differed across cohorts (p = 0.0005), with the PVS group showing the most severe outcomes and the nmMVC group demonstrating the highest rate of return to previous function (CPC 0: 5.6%). Conclusions: Our study revealed significant differences in injury severity and outcomes based on the type of vehicular collision. Notably, Asian patients were disproportionately affected by PVS. Older PVS patients exhibited higher mortality rates, while severe TBIs were more common among male mMVC patients. In contrast, nmMVC patients showed better recovery outcomes. Coinciding with the implementation of Boston’s Vision Zero initiative in 2017, decreases in both nmMVC-related and PVS-related TBIs were observed; however, other contributing factors may have also influenced this decline. These findings highlight the urgent need for targeted public health strategies to mitigate TBI risks across diverse populations. Full article

In recent years, novel Personal Mobility Vehicles (PMVs) with a narrow width and an inward tilting mechanism, similar to motorcycles (MCs), have been proposed to prevent overturning during turns. Due to their compact size, these vehicles have inherent limitations in collision safety, making their dynamic safety and accident avoidance capabilities particularly crucial. In this study, a comparative analysis was conducted using a simulated single lane change course to evaluate obstacle avoidance performance. The results reveal that PMVs equipped with an active inward tilting mechanism exhibit superior obstacle avoidance capabilities. Based on the roll moment equilibrium conditions of these vehicles, an investigation of vehicle states during avoidance maneuvers revealed that both actual and virtual tilt angles coexist in PMVs, and their combined equivalent tilt angle effectively balances the roll moment during turning. This unique mechanism, which integrates the responsiveness of passenger cars with motorcycle-like tire lateral force characteristics, underpins the exceptional obstacle avoidance capabilities of actively inward tilting PMVs. Full article

In this research work, the authors propose an approach for analyzing a traffic accident involving a motorcycle and a pedestrian. The study was conducted under the condition that there are objects in the accident area that limit the visibility of the participants. For this purpose, a three-dimensional simulation model was developed to determine the relative positions of the pedestrian and the motorcycle-driver system at discrete moments, examining the period of time from the moment the pedestrian steps onto the roadway to the moment of contact between the participants. Data from a real traffic accident were used. Full article

Background: Trauma-related injuries are among the most common reasons for paediatric hospital presentations and represent a substantial component of orthopaedic care. Their management poses unique challenges due to ongoing skeletal development in children. While most reported fractures occur at home or during sports, prior studies have primarily used data from urban European populations, limiting the relevance of their findings for rural and regional settings. Urban-centred research often informs public healthcare guidelines, treatment algorithms, and infrastructure planning, introducing a bias when findings are generalised outside of metropolitan populations. This study addresses that gap by analysing fracture data from two rural trauma centres in New South Wales, Australia. This study assesses paediatric fractures resulting from severe injury mechanisms in rural areas, identifying common fracture types, underlying mechanisms, and treatment approaches to highlight differences in demographics. These findings aim to cast a light on healthcare challenges that regional areas face and to improve the overall cultural safety of children who live and grow up outside of the metropolitan trauma networks. Methods: We analysed data from two major rural referral hospitals in New South Wales (NSW) for paediatric injuries presenting between 1 January 2018 and 31 December 2022. This study included 150 patients presenting with fractures following severe mechanisms of injury, triaged into Australasian Triage Scale (ATS) categories 1 and 2 upon initial presentation. Results: A total of 150 severe fractures were identified, primarily affecting the upper and lower limbs. Males presented more frequently than females, and children aged 10–14 years old were most commonly affected. High-energy trauma from motorcycle (dirt bike) accidents was the leading mechanism of injury among all patients, and accounted for >50% of injuries among 10–14-year-old patients. The most common fractures sustained in these events were upper limb fractures, notably of the clavicle (n = 26, 17.3%) and combined radius/ulna fractures (n = 26, 17.3%). Conclusions: Paediatric trauma in regional Australia presents a unique and under-reported challenge, with high-energy injuries frequently linked to unregulated underage dirt bike use. Unlike urban centres where low-energy mechanisms dominate, rural areas require targeted prevention strategies. While most cases were appropriately managed locally, some were transferred to tertiary centres. These findings lay the groundwork for multi-centre research, and support the need for region-specific policy reform in the form of improved formal injury surveillance, injury prevention initiatives, and the regulation of under-aged off-road vehicular usage. Full article

Helmets are crucial for protecting motorcycle riders from head injuries in accidents. This study proposes a helmet pad design based on a negative-Poisson’s-ratio (NPR) structure and comprehensively evaluates its protective effect on head injuries. A concave hexagonal honeycomb structure was embedded into the energy-absorbing lining of a motorcycle helmet, and finite element collision simulations were conducted according to the ECE R22.05 standard. These simulations compared and analyzed the differences in protective performance between concave hexagonal honeycomb helmets with different parameter configurations and traditional expanded polystyrene (EPS) helmets under flat anvil impact scenarios. Using biomechanical parameters, including peak linear acceleration (PLA), head injury criterion (HIC), intracranial pressure (ICP), maximum principal strain (MPS), and the probability of AIS2+ traumatic brain injury, the protective effect of the helmets on traumatic brain injury was evaluated. The results showed that when the wall angle of the honeycomb structure was 60°, honeycomb helmets with wall thicknesses of 0.8 mm and 1.0 mm significantly reduced PLA and HIC values. In particular, the honeycomb helmet with a wall thickness of 1.0 mm reduced ICP by 25.7%, while the honeycomb helmet with a wall thickness of 1.2 mm exhibited the lowest maximum principal strain in the skull compared to EPS helmets and reduced the probability of AIS2+ brain injury by 7.2%. Concave hexagonal honeycomb helmets demonstrated an excellent protective performance in reducing the risk of traumatic brain injury. These findings provide important theoretical foundations and engineering references for the design and optimization of new protective helmets. Full article