Analysis of road traffic accidents and casualties associated with electric bikes and bicycles in Guangzhou, China: A retrospective descriptive analysis.

Introduction: Electric bicycles (e-bikes) and bicycles in large Chinese cities have recently witnessed substantial growth in ridership. According to related accident trends, this study analyzed characteristics and spatial distribution in the period when e-bike-related accidents rapidly increased to propose priority measures to reduce accident casualties. Methods: For e-bike- and bicycle-related accident data from the Guangzhou Public Security Traffic Management Integrated System, linear regression was used to examine the trends in the number of accidents and age-adjusted road traffic casualties from 2011 to 2021. Then, for the period when e-bike-related accidents rapidly increased, descriptive statistics were computed regarding rider characteristics, illegal behaviors, road types, collision objects and their accident liability. One-way analysis of variance (ANOVA) followed by Bonferroni's multiple comparison test. P < 0.05 was considered statistically significant. Finally, the density distribution of accidents was presented, and Moran's I (MI) was used for assessing spatial autocorrelation. Hotspots were identified based on an optimized hotspot analysis tool. Results: Between 2011 and 2021, the number of accidents and casualty rate (per 100,000 population) increased for e-bikes but decreased for bicycles. After 2018, e-bike-related accidents increased rapidly, and bicycle-related accidents plateaued. Accident hotspots were concentrated in central city areas and suburban areas close to the former. Three-quarters of accidents occurred in motorized vehicle lanes. Most occurred on roads without physically segregated nonmotorized vehicle lanes. More than three-fifths of the accidents involved motor vehicles with at least four wheels. The prevalence (per 100 people) of casualties among e-bike rider victims and cyclist victims accounted for 92.0 % and 96.5 %, respectively. A total of 71.6 % of e-bike-related accidents involved migrant workers. Riding in motorized vehicle lanes was the most common illegal behavior. Conclusions: Although e-bike-related and bicycle-related accidents presented similar characteristics, the sharp increase in e-bike-related accidents requires attention. To improve e-bike safety, governments should develop appropriate countermeasures to prevent riders from riding on motorways, such as improving road infrastructure, adjusting the driver's license system and addressing priority control areas.

Two cases of driver death caused by airbag rupture.

OBJECTIVE: This article reports two accidents caused by defective Takata airbags ruptured, which led to the deaths of the drivers. This is the first public report on the deaths caused by Takata airbags in China. METHODS: Determine the relationship between the driver death and airbag rupture through autopsy indings and vehicle inspection. RESULTS: Due to defects in the design of Takata's inflator, moist air was permitted to slowly enter the inflator, resulting the PSAN slowly degraded physically. The damaged propellant burned more rapidly than intended and overpressurized the inflator's steel housing, causing fragmentation and flying debris at high speed, killing or injuring vehicle occupants. CONCLUSIONS: To date, there are still tens of millions of defective Takata airbags that have not been recalled for repair, posing safety risks. This article suggests taking preventive measures to avoid the occurrence of similar accidents.

Overview of road traffic injuries among migrant workers in Guangzhou, China, from 2017 to 2021.

INTRODUCTION: There are many migrant workers in China's first-tier cities, but little is known about road safety. This paper systematically analysed road traffic injuries and risk factors among migrant workers in Guangzhou, China. METHODS: Road traffic crash data from 2017 to 2021 were obtained from the Guangzhou Public Security Traffic Management Integrated System. We plotted the crash network of road users in road traffic crashes and used logistic regression to analyse the risk factors for migrant workers of motorcycle and four-wheeled vehicle crashes. Moreover, the roles of migrant workers and control individuals as perpetrators in road traffic crashes were also analysed. RESULTS: Between 2017 and 2021, 76% of road traffic injuries were migrant workers in Guangzhou. Migrant workers who were motorcyclist drivers most commonly experienced road traffic injuries. Crashes between motorcyclists and car occupants were the most common. The illegal behaviours of migrant worker motorcyclists were closely related to casualties, with driving without a licence only and driving without a licence and drunk driving accounting for the greatest number. Migrant workers were responsible for many injuries of other road users. Motorcycle drivers have a higher proportion of drunk driving. DISCUSSION: Migrant workers play an important role in road traffic safety. They were both the leading source of road traffic injuries and the main perpetrators of road traffic crashes. Measures such as strict requirements for migrant workers to drive motorcycles with licences, prohibit drunk driving, greater publicity of road safety regulations, and combining compulsory education with punishment for illegal behaviours.

Characteristics of road traffic accident types and casualties in Guangzhou, China, from 2007 to 2020: A retrospective cohort study based on the general population.

Introduction: This study aimed to explore the trend and main influencing factors of road traffic accidents in Guangzhou, China, from 2007 to 2020 and to provide a reference and guidance for government decision-making. Methods: A retrospective cohort study was used to describe road traffic accidents in Guangzhou. According to the population types, all people with road traffic accidents were divided into migrant workers and the control population. We divided road users, administrative districts, motorcycle types and injury levels into subgroups to investigate the characteristics of road traffic accidents in Guangzhou. The road traffic accident data were derived from the Guangzhou Public Security Traffic Management Integrated System. Results: The incidence rate of road traffic accidents per 10,000 vehicles in Guangzhou decreased from 36.55 in 2007 to 10.07 in 2012, remained relatively stable at 9.47 in 2017, and finally rose to 11.12 in 2020. The injury rate showed the same trend as the incidence rate, while the mortality rate gradually decreased from 14.21 in 2007 to 5.19 in 2020. Vulnerable road users such as motorized two-to-three-wheeler drivers and migrant workers were casualties in more than 80% of the cases. The proportion of casualties involving mopeds and electric bicycles increased rapidly after 2018. Motor vehicle drivers frequently caused road traffic accidents and were most often uninjured. Conclusion: Road safety in Guangzhou has shown a clear trend of improvement, but casualties are uneven across administrative districts. More attention should be given to motorized two-to-three-wheelers, migrant workers, and road traffic violations by uninjured individuals.

Human thermal sensation and its algorithmic modelization under dynamic environmental thermal characteristics of vehicle cabin.

Thermal conditions are strongly changeable in a vehicle cabin, where passengers could suffer consecutive self-thermoregulation to such dynamic changing thermal stresses, though its HVAC system works well. To observe human overall and local thermal sensations in dynamic thermal conditions, a series of experiments under various conditions were carried out in a cabin-like climate chamber. The results showed that the head, chest, back, and hands during hot exposure are warmer leading to the overall thermal sensation being hot. The thermal sensation of the head was warmer than the overall thermal sensation. During cold exposure, arms, hands, legs, and feet were the main areas causing coldness. In a dynamic thermal environment, the previous skin temperature state and thermal sensation form a thermal sensation overshoot, causing a shift in the body's neutral temperature point. This study proposes a thermal sensation model for the prediction of human thermal sensation local and overall based on skin temperature changes in a dynamic environment. Considering the airflow characteristics in the cabin, the human body is set into seven local parts in the local thermal sensation model. To compensate for sensation overshoot from this, defining recovery points rp for local parts differentiate temperature setpoints according to the experienced thermal state so that the effect resulting from the dynamic condition is integrated into the model algorithm. The model provides a scientific basis for guiding design optimization and intelligent regulation in the dynamic environment of the vehicle cabin, so as to achieve efficient energy utilization.

Human thermal sensation algorithm modelization via physiological thermoregulatory responses based on dynamic thermal environment tests on males.

BACKGROUND AND OBJECTIVES: Thermal conditions are changeable in cabin space, where occupants could suffer consecutive self-thermoregulation to such changing thermal stresses. Thermal environment management is expected to be purposefully auto-adjustable for the environment by recognizing individual real-time thermal sensations. Current thermal sensation evaluation models are developed for virtual simulations rather than for realistic scenarios, challenging to evaluate human thermal sensation in the field surveys. METHODS: The study constructs a human thermal sensation model via human physiological responses to evaluate the human thermal sensation in the actual vehicle environment. The thermal sensation model forms with exponential functions to clarify the relationship between thermal sensation and pulse rate and blood pressure, which successfully expresses the approximately linear trend around neutral sensation and compensates for the end-points bias. The study set up experimental cases to determine the parameter states in the thermal sensation model. Firstly, subjective thermal sensation scoring was performed by combing with an established seven-point-scale questionnaire survey system for human thermal sensation. Wearable sensors are then applied to measure the human physiological response, including blood pressure BP, pulse rate PR and blood oxygen saturation SpO2. RESULTS: The subjects revealed significantly higher pulse rates (positively correlated) and lower blood pressure (negatively correlated) in the warm chamber than in the cool chamber. The defined parameter change rate effectively reveals the trend of human thermal sensation and avoids the inconsistency of raw physiological response levels. The change rate in PR and MAP between the thermal sensation in cold -3 and hot +3 is about a 10% difference. CONCLUSIONS: Based on the thermal sensation model algorithm, model parameters were fitted by the subjects' thermal sensation voting and the change rate of their physiological responses. With the coefficient of determination (R2) of the regression over 0.8, the proposed thermal sensation model can be employed for human thermal sensation evaluation. The physiological thermoregulatory responses effectively indicate the thermal state of the human body and can be used in thermal environments in conjunction with human smart wearable devices.

Environmental conditions driven method for automobile cabin pre-conditioning with multi-satisfaction objectives.

The optimal initial pre-conditioning parameter is essential to properly adjust the temperature within the cabin in an effective and accurate way, especially while passengers' thermal comfort and energy-saving properties are both considered. Under the various environmental thermal loads, the pre-conditioning solutions resulting from those pre-fixed cooling parameters are unfeasible for achieving accurately passengers' comfort temperature. In addition, it is also difficult in such a narrow car space to identify a lot of local attributes due to the different material properties and sizes of a variety of structural parts that have various thermal responses to environmental conditions. This paper presents a data-driven decision model to numerically identify the degrees of the cabin thermal characteristic to determine satisfactory pre-conditioning parameter schemes. Initially, based on the thermal data within a vehicle recorded through the whole year at a selected hot climate region of the Middle East, the study levels multiple climate scenes corresponding to change in the cabin air temperature. Then three classification algorithms (Support Vector Machines, Decision Tree, and K-nearest neighbor model) are used to comparatively identify climate levels according to the input conditions. Based on the identified climate level, an appropriate parameters scheme for this level is applied. A comprehensive evaluation index (CEI) is proposed to characterize the passengers' satisfaction in numerical computation, on considering multi-satisfaction objectives including Predicted Mean Vote (PMV), local temperature, air quality, and energy efficiency; and it formulates the pre-conditioning parameter scheme for each climate scene with CEI. Several scene cases are carried out to verify the effectiveness of the proposed models. The result shows that the pre-conditioning schemes of the model can effectively satisfy passengers in multi-satisfaction objectives.

Analysis of Pedestrian Fractures in Collisions Between Small Cars and Pedestrians Based on Surveillance Videos.

OBJECTIVE: To discuss the collision relationship and the cause of the fracture caused by traffic accidents in which the front of a small car collides with the side of a pedestrian while braking. METHODS: The surveillance videos of 42 traffic accidents involving the front of a small car colliding with the side of a pedestrian while braking were collected. By analyzing the surveillance videos and the paths, the speed of the collision, the relationship between the vehicle and the pedestrian upon collision, and the movement trajectory of the human body were clearly identified. The type and severity of the injuries were also determined through autopsy. The characteristics of the human injuries and vehicle paths were analyzed according to the collision speed (<40 km/h, 40-60 km/h, 60-90 km/h), and the correlations between the fracture and the height of the pedestrian, the height of the hood and the length of the hood were discussed. RESULTS: When a small car hits the side of a pedestrian, the front bumper first hits the lower limbs of the pedestrian, and then, the human body falls to the side of the vehicle, causing a secondary collision with the hood and front windshield; thus, the pedestrian is thrown at a speed similar to the speed of the vehicle, finally falling to the ground and sliding forward a certain distance. (1) When V is less than 40 km/h (n = 10), the pedestrian's head did not collide with the windshield, and the fatal injuries were caused by the individual striking the ground. (2) When V is greater than 40 km/h (n = 32), the majority (97%) of cases showed collision with the windshield. (3) When 40 to 60 km/h (n = 16), the pedestrian's head collided with the windshield, which can cause fatal injuries, and pelvic fractures and rib fractures occurred in 56.25% of patients. (4) When V is less than 60 km/h (n = 26), the ratio of the height of the pedestrian to the height of the hood was significantly smaller in the pelvic fracture group than in the nonpelvic fracture group (P < 0.01). (5) When 60 to 90 km/h (n = 16), there were holes in the windshield, and the pedestrians experienced severe head injuries, with cervical spine fracture occurring in 37.5% of patients, pelvic fractures occurring in 43.75% of patients, and rib fractures occurring in 31.25% of patients. CONCLUSIONS: When V is less than 40 km/h, the vehicle does not cause severe injuries in pedestrians; when V is greater than 40 km/h, the collisions of the pedestrian's head with the windshield lead to severe head injuries and the accident can cause severe pelvic and rib fractures; when V is greater than 60 km/h, the collisions of the pedestrian's head with the windshield can cause cervical spine fracture in addition to head injuries. The occurrence of human injuries is related to not only the vehicle speed but also factors such as the height of the pedestrian, the height of the hood and the length of the hood.

Finite element study of human pelvis model in side impact for Chinese adult occupants.

OBJECTIVE: The occupant's pelvis is very vulnerable to side collision in road accidents. Finite element (FE) studies on pelvic injury help to design occupant protection devices to improve vehicle safety. This study was aimed to develop a highly biofidelic pelvis model of Chinese adults and assess its sensitivity to variations in pelvis cortical bone thickness, bone material properties, and loading conditions. METHODS: In this study, 4 different FE models of the pelvis were developed from the computed tomography (CT) data of a volunteer representing the 50th percentile Chinese male. Two of them were meshed using entirely hexahedral elements with variable and constant cortical thickness distribution (the V-Hex and C-Hex models), and the others were modeled with hexahedral elements for cancellous bone and variable or constant thickness shell elements for cortical bone (the V-HS and C-HS models). In model developments, the semi-automatic multiblock meshing approach was employed to maintain the pelvis geometric curvature and generate a high-quality hexahedral mesh. Then, several simulations with postmortem human subjects (PMHS) tests were performed to obtain the most accurate model in predicting pelvic injury. Based on the most accurate model, sensitivity studies were conducted to analyze the effects of the cortex thickness, Young's modulus of the cortical and cancellous bone, impactor velocity, and impactor with or without padding on the biomechanical responses and injuries of pelvis. RESULTS: The results indicate that the models with variable cortical bone thickness can give more accurate predictions than those with constant cortical thickness. Both the V-Hex and V-HS models are favorable for simulating pelvic response and injury, but the simulation results of the V-Hex model agree with the tests better. The sensitivity study shows that pelvic response is more sensitive to alterations in the Young's modulus of cortical bone than cancellous bone. Compared to failure displacement, peak force is more sensitive to the cortical bone thickness. However, displacement is more sensitive to the Young's modulus of cancellous bone than peak force. The padding attached on the impactor plays a significant role in absorbing the impact energy and alleviating pelvic injury. CONCLUSIONS: The all-hex meshing method with variable cortical bone thickness has the highest accuracy but is time-consuming. The cortical bone plays a determining role in resisting pelvic fracture. Peak impact force appears to be a reasonable injury predictor for pelvic injury assessment. Some appropriate energy absorbers installed in the car door can significantly reduce pelvic injury and will be beneficial for occupant protection.

Development and validation of a human biomechanical model for rib fracture and thorax injuries in blunt impact.

From 1990 to approximately 50,000-120,000 people die annually of road traffic accidents in China. Traffic accidents are the main cause of death of Chinese adults aged 15-45 years. This study aimed to determine the biomechanical response and injury tolerance of the human body in traffic accidents. The subject was a 35-year-old male with a height of 170 cm, weight of 70 kg and Chinese characteristics at the 50th percentile. Geometry was generated by computed tomography and magnetic resonance imaging. A human-body biomechanical model was then developed. The model featured in great detail the main anatomical characteristics of skeletal tissues, soft tissues and internal organs, including the head, neck, shoulder, thoracic cage, abdomen, spine, pelvis, pleurae and lungs, heart, aorta, arms, legs, and other muscle tissues and skeletons. The material properties of all tissues in the human body model were obtained from the literature. Material properties were developed in the LS-DYNA code to simulate the mechanical behaviour of the biological tissues in the human body. The model was validated against cadaver responses to frontal and side impact. The predicted model response reasonably agreed with the experimental data, and the model can further be used to evaluate thoracic injury in real-world crashes. We believe that the transportation industry can use numerical models in the future to simultaneously reduce physical testing and improve automotive safety.