Traffic Accidents In China Research Articles

Does air pollution cause more car accidents? Evidence from auto insurance claims

Using a proprietary data set of auto insurance claims from May 2014 to December 2016, this paper examines the influence of air pollution on the number and severity of traffic accidents in China. Combining an instrumental variable strategy with high-dimensional fixed effects, we find that air pollution significantly increases the occurrence of traffic accidents, with each 1 μg/m3 increase in the particulate matter 2.5 (PM2.5) resulting in a 0.12 % increase in traffic accident probability and a 0.40 % increase in traffic accident number within one day. A different pattern is revealed in our analysis of accident severity, evidenced by a decrease of 1.20 % in the average claim ratio compared to its mean value and a reduction of 26 yuan in the average claim amount made with an increase of 1 μg/m3 in PM2.5. Combining the effect on the number and severity of traffic accidents, for each 1 μg/m3 increase in daily PM2.5, the district daily claim amount decreases by approximately 34 yuan. Further analysis indicates that this may be related to cautious driving behavior resulting from the driver's increased risk aversion. By exercising caution and care on the road, drivers can reduce the negative influence of air pollution on road safety and avoid non-subjective behavioral biases.

Hospitalization information and burden of pediatric inpatients in transport accidents

BackgroundTransport accidents are one of the leading causes of child morbidity and mortality worldwide and represent a significant public health burden. This study aimed to investigate the hospitalization information and burden of pediatric inpatients in transport accidents in China.MethodsIn this study, we collected the cover page of the medical records of pediatric inpatients in transport accidents using the Futang Research Center of Pediatric Development (FRCPD) database from January 1, 2016 to December 31, 2021. Then, we extracted the epidemiological characteristics, including demographic characteristics, cases distribution, disease information, and hospitalization burden.ResultsAmong 36,455 included inpatients, males, aged 1–3 years, East China, July were dominant in different subgroups. In transport accidents, pedestrians were the most frequently type of injury (65.69%). Of all known lesions, craniocerebral/nerve injury was the more common results in pediatric inpatients in transport accidents (33.93%). In addition to pedal cyclists more susceptible to sport system injury, other types of injured person with transport accidents were mainly craniocerebral/nerve injury. In terms of the type of discharge, occupant of heavy transport vehicle or bus and people with craniocerebral/nerve injury had the highest mortality rate after hospitalization in all type and lesion of injured person groups, respectively. The largest hospitalization burden in the type of injured person was occupant of heavy transport vehicle or bus.ConclusionsThis study revealed that epidemiological characteristics and the main factor influencing the hospitalization information and burden of children with traffic accidents in China.

Research on the Testing and Evaluation of Active Safety System for Turning Cars in Two wheeler Traffic Scenarios

China In-depth Traffic Accident Survey (CIDAS) shows that two wheeler has the highest accident fatality rate, more than 38%, which is far more than cars and pedestrians. In this paper, the characteristics of traffic accidents in China, the types of two wheeler, and traffic characteristics of two wheeler are taken into account. There are typical hazardous scenarios in the case of crossing, longitudinal, turning, mixed, etc. In the existing collision scenarios design of cars and two wheeler, the testing methods of crossing and longitudinal have been basically mature. Therefore, combining with the functional testing of the current automobile active safety system, to recurrent the traffic scenarios of two wheeler objectively, the active safety test and evaluation scenarios of turning cars under the two wheeler traffic scenarios are designed. Test paths, test speeds, and impact position are proposed. it complements the test scenarios for active safety function.

Exploring General Personal Tort Issues Between Spouses in China A Perspective on Motor Vehicle Traffic Accidents

With the increasing awareness of individual rights and independence, there is a growing popularity in the concept of citizens personal independence. Consequently, general personal tort disputes between spouses are on the rise, with motor vehicle traffic accidents serving as a typical example. This article explores the general personal tort liability between husbands and wives in China from this perspective. Using the fundamental logic of "problem identification, analysis, and solution finding," it compiles general personal tort cases between spouses in motor vehicle traffic accidents from recent years, examines the current state of domestic and international research, and presents judicial controversies regarding the application of the law, the determination of tort liability, and the realization of damages in such cases. The primary research methods employed are case analysis, literature research, and comparative analysis. Based on the analysis, it is concluded that previous judgments, legal improvements, and traditional views have influenced the application of the law. The determination of tort liability has not yet established a unified standard, and the property system of husbands and wives poses an obstacle to the realization of damages, which is the primary reason for differing judgments in similar cases. Consequently, it is recommended that the application of the law follow the sequence of the Road Traffic Safety Law, Tort Liability section, Personality Rights section, and General Provisions section to determine whether it constitutes general personal tort liability between spouses in motor vehicle traffic accidents in China. Additionally, clarifying the existing legal norms of matrimonial property can eliminate certain obstacles to realizing damages. The objective of this article is to provide practical guidance for judicial practice, ensure that remedies for the rights of the tortfeasor are achievable, and enrich theoretical research outcomes.

The hybrid systems method integrating STAMP and HFACS for the causal analysis of the road traffic accident

The role of traditional analysis methods in improving complex socio-technical system safety has reached a ceiling, and thus systems theory has been utilised to support the investigations and countermeasures for road traffic accidents. As two widely applied systems accident analysis models, STAMP (systems theoretic accident model and process) and HFACS (human factors analysis and classification system) have their own advantages in accident analysis and safety improvement. Therefore, this study develops a new hybrid systems method integrating STAMP and HFACS for road traffic accident (SH-RTA), which can adopt HFACS to enhance the identification and analysis ability of STAMP for human factors and employ control concepts and elements of STAMP to cement the characteristic of HFACS. To illustrate the applicability of the hybrid method, a case study of ‘9·22’ major road traffic accident in China is thoroughly analysed. Finally, preventive countermeasures and suggestions are presented. Practitioner Summary: This paper proposes a new hybrid systems method integrating STAMP and HFACS for road traffic accident. The new method reveals dysfunctional interactions within the parallel level and across levels, and identifies additional human and organisational factors. The recommendations for preventing road traffic accident are provided from higher levels of system.

Visualizing Temporal and Spatial Distribution Characteristic of Traffic Accidents in China

The interaction among social economy, geography, and environment leads to the occurrence of traffic accidents, which shows the relationship between time and space. Therefore, it is necessary to study the temporal and spatial correlation and provide a theoretical basis for formulating traffic accident safety management policies. This paper aims to explore the traffic accident patterns in 31 provinces of China by using statistical analysis and spatial clustering analysis. The results show that there is a significant spatial autocorrelation among traffic accidents in various provinces and cities in China, which means that in space, the number of traffic accidents and deaths is high with high aggregation and low with low aggregation. Positive spatial autocorrelation is primarily concentrated in the southeast coastal areas, while negative spatial autocorrelation is mainly concentrated in the western areas. Jiangsu, Anhui, Fujian, and Shandong are typical areas of traffic accidents, which deviate from the overall positive spatial autocorrelation trend. Traffic accidents in Sichuan are much more serious than those in neighboring provinces and cities; however, in recent years, this situation has disappeared.

Comparative analysis of AEB effectiveness based on typical and atypical scenarios of electric two-wheeler accidents in China

Electric two-wheeler (ETW) accidents are one of the most important types of traffic accidents in China. Currently, the China New Car Assessment Program (C-NCAP) has proposed test scenarios to evaluate the effectiveness of autonomous emergency braking (AEB) for ETWs, including several common typical crash scenarios, but other atypical scenarios have not been considered. To determine the performance of AEB in real accidents, 16 in-depth accident cases with typical scenarios and 11 cases with atypical scenarios were selected based on a proposed C-NCAP typical scenario set and reconstructed using the virtual simulation tools MADYMO and PC-Crash. The crashes were re-simulated with a car equipped with an AEB system while varying the sensor field of view (FOV), time-to-collision (TTC), sensor delay time (SDT), and lateral trigger width ( W). The results show that for almost all combinations of AEB parameters, the crash avoidance rate was much higher in the typical scenario than that in the atypical scenario. When using an AEB with a FOV of 90° (±45°), all ETW accidents were avoided in typical scenarios, while even with the most efficient AEB system (FOV = ±60°, TTC trigger value = 1.5 s, SDT = 0.1 s), only 82% of crashes were avoided in atypical scenarios. Further considering the effect of lateral width, increasing the width from 2 to 5 m, the maximum avoidance rate of the AEB system increased by 43% in the typical scenarios and 18% in the atypical scenarios. The findings suggest that the typical AEB test scenarios proposed for C-NCAP were useful for other crash scenarios, but that including additional test scenarios may better reflect real world crash scenarios. It is recommended that atypical scenarios should be considered in C-NCAP, particularly perpendicular crash scenarios with the car or ETW turning, to better describe real accidents and improve vehicle safety.

Analysis of Vehicle-Pedestrian Accident Risk Based on Simulation Experiments

Vehicle-pedestrian accidents are one of the main types of road traffic accidents in China because of their mixed traffic features. By analyzing the characteristics of vehicle-pedestrian accidents, the head injury criterion (HIC) was selected as a quantitative index of pedestrian head injury risk, and vehicle-pedestrian collision simulation tests were carried out using PC-Crash. From the collected test data, the multivariate relationship models between the HIC, vehicle speed, and collision angle were fitted for different vehicle types. A risk assessment method for vehicle-pedestrian accidents based on the HIC was proposed by the Fisher optimal segmentation algorithm. Finally, a new index for evaluating the accuracy of accident risk classification, the degree of error classification, was proposed to verify the validity of the accident risk assessment method. The results show that vehicle speed, collision angle, and vehicle type play a key role in pedestrian injury. Flat-headed vehicles are more likely to cause head injuries to pedestrians than high-headed and low-headed vehicles. Rear-end collisions cause more injuries to pedestrians than side collisions. The research results can provide guidance and a basis for accident liability determination, speed limit management, vehicle safety design, and human injury mechanism analysis.

A Combined Prediction Model Composed of the GM (1,1) Model and the BP Neural Network for Major Road Traffic Accidents in China

This paper compared the expected accuracy of the gray GM (1, 1) model and the combined GMBP model using a data set for major road traffic accidents. A combined GMBP prediction model composed of the very first parameter gray model GM (1, 1) is able to make exact predictions for forecasting dreary type of processes, and BP (back-propagation) neural network for a major traffic accident is proposed to overcome the limitations of a single prediction model for a major traffic accident. The method first obtains predicted data using the gray GM (1, 1) model, then trains the BP neural network using the GM (1, 1) model’s predicted data and the original data as input and output data, respectively, and finally the trained BP neural network can be considered a combined GMBP prediction model. The predicted data of the digit of major traffic accidents, the digit of fatalities, and the digit of damages from 2008 to 2020 were obtained using the combined GMBP prediction model, and it is compared with the expected data of the single gray GM (1, 1) model. The grades showed that the exactitude of the combined GMBP prediction model was significantly higher than that of the single gray GM (1, 1) model. Finally, from 2021 to 2033, the combined GMBP prediction model is used to forecast the number of significant road traffic incidents, mortalities, and damages. The prediction results show that the number of accidents, faculties, and injuries is on the decline in the future years.

Adaptation and validity of the Sleep Quality Scale among Chinese drivers.

PurposePoor sleep quality is closed related with driving accidents. However, due to the lack of a valid instrument for assessing drivers’ sleep quality, few studies have examined drivers’ sleep quality and its associations with driving behaviours and traffic accidents in China. The aim of this paper is to revise the Sleep Quality Scale (SQS) and assess its reliability and validity in Chinese drivers.Methods522 Chinese drivers aged from 18 to 56 years old agreed to complete the SQS, Daytime Sleepiness Perception Scale version 4 (DSPS-4), Self-report of Risky Driving Behavior (RD-SR) and Self-assessment of the Likelihood of Being Involved in a Risky Driving Situation (RD-SA).ResultsThe final Chinese version of the SQS contained 23 items across four factors: difficulty in getting up, difficulty in falling asleep, sleep recovery and daytime dysfunction. Second, man scored lower on the difficulty in falling asleep factor but higher on the sleep recovery factor than women. Third, low to moderate correlations were found between the SQS factors and the DSPS-4, RD-SA and RD-SR, indicating that the validity of the revised scale was satisfactory. More importantly, daytime dysfunction factor is an effective predictor of violation involvement and accident involvement.ConclusionThe revised SQS has acceptable reliability and validity and can be used as a tool to measure the sleep quality of Chinese drivers.

5G-V2X Based Traffic Safety Warning System through Mobile Sensor and Wireless Communication

This project designs a traffic safety early warning system based on 5G-V2X for the current situation of increasing traffic accidents in China, which concentrates on two modules of V2V (vehicle-to-vehicle), V2I (vehicle-to-road) for early warning system design, with OBU (vehicle communication unit) and RSU (roadside communication unit) based on 5G-V2X communication technology to establish vehicle-to-vehicle and vehicle-to-road interactive communication, and realize V2V collision warning and V2I traffic light emergency event warning at intersections through collision risk warning algorithm and intersection passage assistance algorithm, thus alerting drivers to avoid dangerous situations and reducing the incidence of traffic accidents.

Research on Control Strategy and Central Control System of Intelligent Electric Vehicle

With the continuous improvement of world science and technology, vehicle technology has also been greatly developed. Cars bring convenience to people’s travel, and occupy an increasingly high proportion in social life. Automobile plays an important role in the continuous progress of contemporary society and the change of human travel conditions. At the same time, the increasing number of cars also brings many problems: energy consumption and environmental pollution are worsening, traffic accidents are increasing year by year. According to the who survey, the number of casualties caused by traffic accidents in China is gradually increasing. High traffic accidents have caused irreversible losses to social development, people’s lives and property. It has become the development goal to improve the vehicle active safety, control the vehicle to automatically identify the road, drive according to the planned route and reduce the frequency of traffic accidents. In the traditional driving environment, people occupy a dominant position. In the face of complex and changeable traffic environment and a large number of traffic information, it is easy to make mistakes in driving and cause serious traffic accidents. Therefore, it is very important to extricate the driver from the complex and changeable traffic environment and make driving safer. The intelligent vehicle collects the information about the road and the vehicle itself through the sensor, and sends it to the central controller which controls the transverse and longitudinal movement of the electric vehicle. The central controller sends out corresponding instructions to control the horizontal and longitudinal operation of the vehicle according to the control strategy, so as to realize the control of the driving behavior of the vehicle, so that the vehicle can drive safely on the desired track at the expected speed, It can avoid driver fatigue driving behavior and traffic accidents caused by driving technology. Various sensors in the intelligent vehicle can obtain more vehicle information at the same time, and control the vehicle through the controller processing.

Empirical Analysis on Influencing Factors of Traffic Casualties in China

In order to further explore the complex correlation between the influencing factors of road traffic accidents in China, this paper takes the road traffic safety-related data of 31 provinces from 2004 to 2018 as the sample data, selects five index data that may affect the occurrence of traffic accidents in various regions of the country, i.e. resident population, urban population, population density, GDP and number of car drivers, and uses Eviews software for stepwise regression analysis to establish a fixed effect model of the influencing factors of traffic accidents and analyze the macro and micro factors that affect the death toll of traffic accidents in China. The model shows that each index has a significant impact on the number of road traffic casualties. Urban population, population density and number of car drivers are positively correlated with the number of road traffic casualties. The resident population and GDP are negatively correlated with the number of road traffic casualties. According to the research conclusions, this paper puts forward some suggestions, such as optimizing the management technology of road traffic construction, strengthening the education system of traffic safety awareness of residents in the new urbanization, increasing the investment in traffic construction, and establishing an institution for differentiated training and management of drivers based on driving experience.

Modeling drivers’ scrambling behavior in China: An application of theory of planned behavior

Scrambling behavior is one of the main causes of road traffic accidents in China. This study aimed to investigate the characteristics of drivers’ scrambling behavior and its influencing factors based on the theory of planned behavior. A total of 388 drivers answered the questionnaire and 359 provided valid data. The structure equation model of scrambling behavior showed that positive attitudes towards scrambling behavior, subjective norms and perceived behavior control increased the intention of scrambling behavior. Furthermore, the path coefficient of the structural equation model for the scrambling behavior revealed that attitude was the most important factor influencing scrambling behavior. Thus, to prevent drivers from scrambling, traffic regulators should focus on improving drivers’ attitude towards this behavior, while auxiliary measures should be enacted to regulate drivers' subjective norms and perceptual behavior control. Implications on intervention strategy and policy to reduce scrambling behavior are discussed.

Non-motorized Vehicle Traffic Accidents in China: Analysing Road Users’ Precrash Behaviors and Implications for Road Safety

The paper aims to explore underlying patterns of non-motorized vehicle (NM, including both regular bicycles and e-bikes) traffic accident occurrences based on precrash behaviors. A quarter-year data of NM accidents was collected by Yinzhou Traffic Police Department of Ningbo, China. Descriptive statistics and Rough Set theory were used to examine rules within different types of NM accidents from temporal, spatial, and behavioral aspects. Some main findings include: behavior patterns of different parties involved vary across different accident types, levels of roads, and intersections; motorized vehicle’s illegal turning as well as NM’s reverse riding are the two key behaviors that deserve concern across all levels of roads and intersection; in addition, for higher level urban roads more attention should be focused on lane violations of motorized vehicles, and for branch roads and intersections prevention efforts could be directed to motorized vehicles’ illegal turning around and NM’s red-light running respectively. Results from this paper could facilitate related staff formulating more targeted policies to make roadways safer.

System Analysis of Potential Accidents on Mountain Road Based on Rough Set and Quantitative Theory

Although the number of traffic accidents in China has been declining year by year, the proportion of major traffic accidents in mountainous areas has continued to rise, reaching 60% in recent years. This shows that a mountain road safety system has not been effectively established. The majority of the methods used in mountain road safety assessments are statistical analysis methods based on accident causation theory. However, these expert methods greatly depend on massive amounts of traffic environmental data, which are very difficult and time-consuming to obtain. This study had the goal of reducing the environmental monitoring data required for this assessment and increasing analysis efficiency. Based on the research of road traffic accident data and traffic flow characteristics in mountainous areas, an attribute reduction algorithm was developed to weigh the significance of the data and construct a systemic analysis mothed. The proposed risk analysis model, which considers the accidents, roadside environment, and traffic safety facilities, is based on Shaanxi province data. The results from the actual implementation of this model indicate that the approach has good operability and holds great promise for mountain road safety assessment.

Research on Characteristics of Perpetrators and casualties in Road Traffic Accidents in China——Based on the panel data analysis of national traffic accidents from 2006 to 2019

Under the background of the rapid development of Internet technology, the emergence of Internet platform accelerates the industrial agglomeration. As a chain connecting the material circulation between industries, the rise of logistics industry is inevitable. As a key link of logistics industry, transportation, along with the rise of logistics industry, has led to an increase in traffic accidents year by year. Therefore, based on the national road traffic accident data from 2006 to 2019, this paper uses SPSS 26.0 to analyse the accident incidence, casualties and direct property loss indicators of different regions and occupation, and study the characteristics of perpetrators and casualties. The results show that the traffic accidents in the whole country show a downward trend, but they are unbalanced. Workers and farmers accounted for the largest proportion, but the death and injury rate showed a downward trend. Other showed an upward trend in the past five years, especially in the delivery industry. Future road traffic safety management should take corresponding measures to reduce the accident rate from the perspective of the development of related industries.

Spatiotemporal Characteristics of Traffic Accidents in China, 2016–2019

Spatiotemporal Characteristics of Traffic Accidents in China, 2016–2019

Critical Factors Analysis of Severe Traffic Accidents Based on Bayesian Network in China

The purpose of this study is to minimize the negative influences of the severe traffic accidents in China by profoundly analyzing the complex coupling relations among accident factors contributing to the single-vehicle and multivehicle traffic accidents with the Bayesian network (BN) crash severity model. The BN model was established by taking the critical factors identified with the improved grey correlation analysis method as node variables. The severe traffic accident data collected from accident reports published in China were used to validate this model. The model’s efficiency was validated objectively by comparing the conditional probability obtained by this model with the actual value. The result shows that the BN model can reflect the real relations among factors and can be seen as the target network for the severe traffic accidents in China. Besides, based on BN’s junction tree engine, five-factor combination sequences for the number of deaths and three-factor combination sequences for the number of injuries were ranked according to the severity degree to reveal the critical reasons and reduce the massive traffic accidents damage.

Head kinematics study of E-bicycle rider in car to E-bicycle side collisions

In recent years, car to bicycle collisions take place more and more frequently, which have attracted the attention of some organizations and engineers. They are trying to make some rules for cars to realize better bicyclist protection, including defining new head impact location area and head impact velocity in pedestrian protection tests. However, car to E-bicycle collisions occur more than car to bicycle collisions in China. Therefore, vehicle to E-bicycle collisions should be researched to define appropriate head impact location area and head impact velocity in pedestrian protection tests for cars in Chinese market. In this article, the head kinematics of E-bicycle riders in car to E-bicycle side collisions are studied. First, through analyzing data from China In-Depth Accident Study Database (which conducts field investigation, analysis, and research on traffic accidents in China), some representative conditions and key parameters in car to E-bicycle collisions are extracted. Second, a condition of car to E-bicycle side collision from above analysis is simulated. Third, an experiment according to the above condition is performed and the finite element models in the above simulation are validated. Then, a series of conditions are simulated by using the validated models, and some factors affecting head impact locations and head impact velocities in car to E-bicycle side collisions are studied. Finally, some factors that affect the head kinematics of E-bicycle riders in car to E-bicycle collisions are identified and some results of head movement in these collisions are concluded, such as head impact locations and head impact velocities.